Happiness, Economics and Politics: Towards a Multi-Disciplinary Approach

Happiness, Economics and Politics

Happiness, Economics and Politics Towards a Multi-Disciplinary Approach

Edited by

Amitava Krishna Dutt and Benjamin Radcliff University of Notre Dame, USA

Edward Elgar Cheltenham, UK • Northampton, MA, USA

© Amitava Krishna Dutt and Benjamin Radcliff 2009 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical or photocopying, recording, or otherwise without the prior permission of the publisher. Published by Edward Elgar Publishing Limited The Lypiatts 15 Lansdown Road Cheltenham Glos GL50 2JA UK Edward Elgar Publishing, Inc. William Pratt House 9 Dewey Court Northampton Massachusetts 01060 USA

A catalogue record for this book is available from the British Library Library of Congress Control Number: 2009936225

ISBN 978 1 84844 093 7 Printed and bound by MPG Books Group, UK

Contents List of contributors Preface

vii ix

Introduction: happiness, economics and politics Amitava Krishna Dutt and Benjamin Radcliff PART I

HAPPINESS

1 The history of happiness and contemporary happiness studies Darrin M. McMahon 2 On the measurement and mismeasurement of happiness: contemporary theories and methodological directions Anthony D. Ong 3 How do we assess how happy we are? Tenets, implications and tenability of three theories Ruut Veenhoven 4 Happiness and domain satisfaction: new directions for the economics of happiness Richard A. Easterlin and Onnicha Sawangfa PART II

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25

33

45

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HAPPINESS AND ECONOMICS

5 Happiness when temptation overwhelms willpower Alois Stutzer 6 Happiness and the relative consumption hypothesis Amitava Krishna Dutt 7 The Easterlin Paradox revisited Robert H. Frank 8 Does inequality matter to individual welfare? An initial exploration based on happiness surveys from Latin America Carol Graham and Andrew Felton 9 Perceptions of discrimination, effort to obtain psychological balance and relative wages: can we infer a happiness gradient? Arthur Goldsmith

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97 127 151

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PART III

Happiness, economics and politics

HAPPINESS AND POLITICS

10 Politics and happiness: an empirical ledger Alexander C. Pacek 11 Democracy and happiness: what causes what? Ronald Inglehart 12 The causal link between happiness and democratic welfare regimes Charlotte Ridge, Tom Rice and Matthew Cherry 13 Labor organization and the quality of life in the American states Suzanne M. Coshow and Benjamin Radcliff PART IV

231 256

271

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WHAT IS TO BE DONE?

14 Should national happiness be maximized? Bruno S. Frey and Alois Stutzer 15 Change your actions, not your circumstances: an experimental test of the Sustainable Happiness Model Kennon M. Sheldon and Sonja Lyubomirsky 16 What is to be done? Toward a ‘happier’ world Amitava Krishna Dutt and Benjamin Radcliff

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Index

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324 343

Contributors Matthew Cherry, Department of Political Science, University of Iowa, Iowa City, Iowa, USA. Suzanne M. Coshow, Department of Sociology, Indiana University-South Bend, South Bend, Indiana, USA. Amitava Krishna Dutt, Department of Economics and Policy Studies, University of Notre Dame, Indiana, USA. Richard A. Easterlin, Department of Economics, University of Southern California, Los Angeles, California, USA. Andrew Felton, Federal Deposit Insurance Corporation, Washington, DC, USA. Robert H. Frank, Johnson Graduate School of Management, Cornell University, Ithaca, New York, USA. Bruno S. Frey, Department of Economics, University of Zurich, Switzerland. Arthur Goldsmith, Department of Economics, Washington, DC and Lee University, Lexington, Virginia, USA. Carol Graham, The Brookings Institution, Washington, DC and School of Public Policy, University of Maryland, College Park, Maryland, USA. Ronald Inglehart, Department of Political Science, University of Michigan, Ann Arbor, Michigan, USA. Sonja Lyubomirsky, Department of Psychology, University of CaliforniaRiverside, California, USA. Darrin M. McMahon, Department of History, Florida State University, Tallahassee, Florida, USA. Anthony D. Ong, Department of Human Development, Cornell University, Ithaca, New York, USA. Alexander C. Pacek, Department of Political Science, Texas A&M University, College Station, Texas, USA. vii

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Benjamin Radcliff, Department of Political Science, University of Notre Dame, Indiana, USA. Tom Rice, Department of Political Science, University of Iowa, Iowa City, Iowa, USA. Charlotte Ridge, Department of Political Science, University of Iowa, Iowa City, Iowa, USA. Onnicha Sawangfa, Department of Economics, University of Southern California, Los Angeles, California, USA. Kennon M. Sheldon, Department of Psychology, University of MissouriColumbia, Columbia, Missouri, USA. Alois Stutzer, Department of Business and Economics, University of Basel, Basel, Switzerland. Ruut Veenhoven, Department of Sociology, Erasmus University, Rotterdam, the Netherlands.

Preface This volume grew out of a conference entitled ‘New Directions in the Study of Happiness: US and International Perspectives’, held at the University of Notre Dame on 22–24 October 2006. Earlier drafts of most of the chapters in this volume were presented at this conference. We are very grateful to the participants of the conference, especially those whose work is included in this volume, for their contribution, patience and encouragement. We are also deeply indebted to the Department of Economics and Policy Studies and the College of Arts and Letters, and to the Program in American Democracy, at the University of Notre Dame, for their generous financial and logistic support. We would especially like to thank Harriet Baldwin for her help with the organization of the conference. We also gratefully acknowledge the help we received from the staff at Edward Elgar, especially from Joanne Betteridge and Kate Pearce. The conference, especially because of its multidisciplinary nature, was very stimulating and enjoyable to us (and, as we could gather from their comments, the other participants), and we are very pleased to be able to prepare this volume for wider dissemination. This is doubly so since we like to believe, as our introduction makes clear, that the individual chapters add up to rather more than the sum of their parts, providing as they do a good summary of the state of the emerging field of the scientific study of happiness. We hope that this volume will also be stimulating and enjoyable – and, dare we say, increase the happiness – of a wider audience. Amitava Krishna Dutt and Benjamin Radcliff

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Introduction: happiness, economics and politics Amitava Krishna Dutt and Benjamin Radcliff The nature and meaning of happiness has been discussed over the centuries by religious figures, philosophers and, more recently, by social scientists. Moreover, it seems indisputable that happiness has always been the (or at least, a) goal of, or driving force for, most human beings. In recent years a new field of inquiry, the so-called ‘science of happiness’, has emerged. This field tries to examine the idea of happiness using quantifiable and measurable concepts and to analyse its determinants using the empirical and theoretical tools of the social and biological sciences. The ‘scientific’ study of happiness, however, has been conducted by scholars from different disciplines in different and largely separate ways. Psychologists have turned from an emphasis on problems such as depression to a consideration of positive affect, and attempted to measure a number of notions of happiness using survey and experimental data, as well as brain signals, and have focused on different kinds of mental processes, personality traits and environmental factors to understand the determinants of happiness. Economists have focused on the effects of income and consumption on happiness and well-being, debating, essentially, whether money buys happiness. They have also approached the study of economic development using the concepts of economic growth and improvements in well-being. Sociologists have emphasized interactions within communities, families and groups as well as the broader effects of culture on happiness. Political scientists have focused on how different systems of government – such as democracies – and different types of governmental policies, such as the size of the welfare state, affect happiness. Philosophers have speculated on the meaning of happiness – for instance, whether it involves the maximization of pleasure, the minimization of pain, or maximization of the difference between pleasure and pain, or whether it refers to human flourishing. There have, of course, been scholars who have crossed the normal boundaries of their own disciplines to incorporate factors from outside. For instance, some economists – such as Veblen (1899) and, more recently, Schor (1998) and Frank (1999) – have incorporated ideas about 1

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Happiness, economics and politics

status, more traditionally studied by sociologists, in analysing the relation between consumption and happiness, while some political scientists – such as Lane (2000) and Putnam (2000) – have addressed issues related to friendship and community in understanding the determinants of happiness. But the general tendency, given the disciplinary structure of the academy, has been to remain largely within a particular discipline. As students of happiness and well-being, we believe that the study of happiness is best done from a multidisciplinary perspective, and that to make progress in the subject we need greater communication and interaction among different disciplines. We therefore decided to organize a conference with scholars from different disciplines, including history, psychology, philosophy, sociology, economics and political science. Coming ourselves from economics and from political science, we are especially interested in how concepts and issues in economics and political science can be combined and cross-fertilized to deepen our understanding of happiness. Therefore, although we sought representation from a variety of disciplines, we invited more scholars from our two disciplines than from the others. This book contains versions of most of the papers presented at the conference, as well as our own reflections based on our own work and the proceedings of the conference. The book is divided into four parts, the first on happiness in general, the second on economics and happiness, the third on politics and happiness, and a final one on what is to be done. The following sections of this introduction discuss some of the key questions related to each part and how the chapters in this volume relate to these questions. Thus, the next section provides a general introduction to the history, conceptualization, theories and empirics of happiness. The following two sections then examine, in turn, the relationships between happiness, and economics, and politics. The subsequent section argues that an interdisciplinary perspective is necessary for obtaining a better understanding of happiness and its determinants, and focuses on the interaction between economic and political factors in explaining happiness. The final section discusses some implications of the analysis for what can and should be done, individually and collectively, for improving human well-being and making people happier.

I.1

HAPPINESS

Like most genuinely great ideas, happiness has successfully resisted attempts to be reduced to any single meaning or definition. We begin, thus, with an appraisal of what happiness is, and how best we might conceive of

Introduction

3

it not merely as philosophers, but also as scholars of the empirical, observable world. The volume thus begins with Darrin McMahon’s insightful discussion of Western attitudes to the meaning of happiness and the possibility of its attainment, a discussion which he has carried out at much greater length in his book on the history of happiness (McMahon, 2006). Early on, happiness was considered a matter of luck, or something that was not achievable in the here and now, at least by more than a handful of people. He argues that the notion of happiness being our being’s ends and goal is an Enlightenment creed which has crowded out other ways of looking at the world and human purpose in it. McMahon sees the triumph of this Enlightenment creed as a larger dynamic which explains the wide contemporary appeal of happiness studies. But, he argues, happiness studies would do well to be cognizant of this history of happiness. Thus, McMahon ‘enter[s] a humble plea as a historian and scholar of the humanities for a certain humility as we approach our subject, pointing out the un-nerving tendency of happiness to frustrate and circumvent those who would try to grasp it in pursuit’. The need for that humility is readily seen in any survey of the meaning of happiness. We see a concern with happiness in the earliest philosophers and religions in both the East and the West. For instance, the ancient belief systems of India, which are now collectively referred to as Hinduism, took the view that ‘true’ happiness requires the realization of a person’s oneness with Brahman, the universal soul, and the liberation from worldly desires. Buddhism also stressed the importance of overcoming desire and of avoiding extremes of pleasure and austerity, of following ‘the middle path’. The major Greek philosophers did not especially value everyday sensual pleasures, with Plato favoring the controlling of appetites rather than being enslaved by them, and Aristotle valuing fulfilling activities which led to eudaimonia or flourishing, exemplified at the highest level by intellectual contemplation. Christianity, Judaism and Islam regard happiness as the goal of religious life and beliefs to be attempted through knowing and serving God. However, true happiness, they imply, can only be achieved in afterlife, in the form of union with God. Later Christian philosophers, like St Thomas Aquinas, tried to synthesize the Aristotelian view about happiness in this world and the early Christian view that true happiness can only be achieved in afterlife by suggesting that happiness in this life, while imperfect, can approximate the true happiness of afterlife through virtuous living. With the weakening of the hold of religion in everyday life and general secularization that accompanied the Enlightenment and the Industrial Revolution, it came to be increasingly accepted that happiness is something that all people could at least aspire to in their lives on earth. However, a

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Happiness, economics and politics

variety of meanings was attached to happiness by philosophers. Some, such as the Utilitarians, emphasized that increasing happiness entailed that we take seriously the seemingly mundane observation that we should increase pleasure and decrease pain. Others, such as Schopenhauer, were closer to Eastern traditions by focusing mostly on minimizing pain, while still others, such as Nietzsche – and creative writers such as Joyce – emphasized the maximization of pleasure, the pursuit of ‘passionate joy’, whatever the potential price to be paid. Many social scientists, instead of trying to define happiness in these ways, rely on asking people how happy they actually feel. There is a large amount of survey data now available which asks people to report on, say, on a 10-point scale, how happy or satisfied they are with their lives, all things considered. This approach in effect allows subjects to decide what they mean by happiness, and lets them decide how happy they are given their own definition. This approach to happiness is often referred to as subjective well-being, in an effort to apply a more precise and less emotionally laden term than happiness. While some have argued that such measures are valid and reliable, and that levels of subjective well-being and how they change over time and place can tell us about the objective conditions that make people better off, others remain skeptical, because of cultural differences across people and because people are known to adapt to their environments. Thus, different cultures can interpret happiness and its desirability differently, and the poor can get used to their destitution and feel reasonably happy. Despite the growing popularity of measures of subjective well-being, social scientists have continued using less subjective measures of happiness and well-being. Thus, psychologists distinguish between different levels of happiness, a first referring to (transient) emotions and feelings of joy and pleasure, a second to people’s judgments about their feelings over a long period of time (that is, subjective well-being), and a third to whether one fulfills one’s true potential, or whether one flourishes, and is closer to the Greek notion of the good life or eudaimonia (see, for instance, Nettles, 2005). In his contribution to this volume, Anthony Ong argues that developments in the psychology of happiness and well-being suggest that wellbeing cannot be well represented by a single dimension, so that researchers have to examine both eudaimonic and hedonic aspects of happiness and well-being to obtain a more complete understanding of positive human health. Ong points out that current psychological research measuring wellbeing takes two major alternative paths. One measures subjective wellbeing, which involves a person’s cognitive judgment of life satisfaction, and an emotional aspect consisting of independent positive and negative affect components. The other derives from eudaimonic expressions of

Introduction

5

virtue, and the striving for the realization of one’s true potential, and is measured by the concept of psychological well-being, involving different aspects of human actualization, such as autonomy, personal growth, life purpose and social connectedness. Ong then discusses methods with which it is possible to examine the relationship between these two aspects of well-being, and how this varies within persons (with most of the current research examining variations across persons for a single aspect). He examines methods involving longitudinal panel designs and intensive bursts designs, as well as less widely used growth curve modeling and dynamic systems analysis using differential equations, and explores how these methods can deal with rounded and irregular structures (rather than rectilinear systems) necessary for understanding the complexity of the human brain. While this work, like McMahon’s, tells a cautionary tale in how readily we are willing to accept the conventional, mainstream use of survey-based indicators of happiness or life satisfaction, much of the rest of the chapters in this volume, reflecting the norms of the literature, do rely upon fairly straightforward measures of well-being. Economists, while strongly wedded to the notion of utility and its maximization by economic agents as the method of explanation behavior and evaluating states in terms of individual utility (which may be measured with subjective well-being surveys), often rely more heavily on real income and production as measured by the national accounts because of their relative ease of measurement, assuming that more (in terms of products and income) is better (in terms of utility or happiness). Moreover, recognizing that people adapt to their states in terms of subjective feelings (like the poor person getting used to poverty), some economists (see especially Sen, 1999) favor less subjective concepts such as functionings (whether people are able to achieve particular good results in terms of things – such as good health, adequate nutrition and even adequate self respect – that are considered valuable) or capabilities (whether people have the opportunity to achieve these functions, rather than whether they actually achieve them). Turning from the meaning of happiness to theories of happiness, in the social scientific literature on subjective well-being, three broad kinds of theories have emerged for predicting how happiness varies across countries or individuals. Using the terminology suggested by Veenhoven and Ehrhardt (1995), and further elaborated by Ruut Veenhoven in his contribution to this volume, one can think of theories focusing on (1) traits, (2) social comparisons or (3) satisfaction of needs. Trait theories contend that happiness is a relatively fixed personality trait, similar to other aspects of personality, resulting from a combination of genetic inheritance, cultural socialization and other early life experiences. Individuals, then, tend toward a basic level of happiness,

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Happiness, economics and politics

in the same way that they tend toward a certain level of extroversion or optimism. Psychologists often think thus in terms of ‘set-points’ to which individuals are prone. Life events may move them to either more or less happiness, but such changes tend to be temporary, with individuals eventually returning to something like their original set points over time. The same logic applied to the national level suggests that people in some countries just naturally tend to be happier than those in others, as a part of the national character – that is, a national set-point, reflecting a kind of national personality. Comparison theories, often favored by economists such as Easterlin (1974), are predicated upon the notion that individuals appraise the quality of their lives in relative rather than absolute terms. In it simplest incarnation, people look to society’s ‘consumption norm’, and evaluate their lives relative to that norm, such that those with a higher level of consumption view themselves as more satisfied, and those below, less so. The obvious conclusion is that, presuming the consumption norm is society’s median, the mean level of happiness will everywhere be the same, and will not change significantly over time (since, of course, raising the social median level of consumption cannot change the fact that there are always as many people above it as below it). There are more complicated and sophisticated notions of relativity (as reviewed by Diener et al., 1999), but all depend upon the fundamental notion of comparing one’s position (typically in terms of income, social status or other measures of consumption) against some external standard. Both trait and comparison theory, then, stand in contrast to what Veenhoven has rightly characterized as the ‘common sense’ view that satisfaction with life is determined by the amount of needs that one’s life circumstances allow to be meet. Thus, following the conventional idea of a hierarchy of needs (Maslow, 1954), the more needs that are met, the more rewarding and fulfilling one is likely to find life. Veenhoven’s contribution to this volume continues his work in evaluating trait and comparison theories, and in articulating and defending the needs-based theory. As his chapter notes, the stakes involved in which theory we find most compelling are enormous, in that trait and comparison-based theories tend toward the view that national levels of happiness simply cannot be lastingly improved, since if happiness is a trait, levels will return to their set-points whatever interventions we make in the world to make life more secure or otherwise enjoyable, and if happiness is relative, these same kind of changes will merely raise the consumption norm, and thus leave the overall level of happiness unchanged. In sum, how we theorize about happiness determines whether it is sensible to even try to improve living conditions across the world, given that both trait and comparison theory suggest that doing

Introduction

7

so will not increase the amount of actual happiness in the world. We return to this issue in the conclusion of this book. The set-point notion of happiness, of course, need not lend itself to the conclusions Veenhoven sees when applied at the purely individual level (and hence even over aggregates). Thus, one can posit that people do have set-points, perhaps even as a hardwired, genetic aspect of a personality, while admitting that individuals might be able to reprogram themselves for greater happiness by using their power of agency to play against a reversion to set-point (that is, ‘adaptation’). This may be of scant comfort to those of us, like Veenhoven, concerned with the possibility of using public policy to improve objective living conditions, and thus, subjective appraisal of life (given that a country’s ‘national character’ as expressed by its cultural norms can hardly be consciously reprogrammed), but it does open the door to specific strategies individuals may use in their day-to-day lives to make life more satisfying. It is this very possibility that has given rise to the ‘positive psychology’ movement. In their contribution to this volume, Kennon Sheldon and Sonja Lyubomirsky provide an overview of one of the most promising developments in that field in the form of the ‘Sustainable Happiness Model’. They grant that one’s happiness is largely determined by genetics and other circumstantial factors beyond the individual’s control, but also argue that one’s activities also play a role, such that the set-point should be construed ‘as a range’ so that it is possible ‘to construct one’s life in such a way that one stays in the upper half of one’s set range, finding ways to remain at a level of happiness that is higher than one’s genetics alone would dictate’. Proponents of the comparison theory, also, do not argue that happiness levels cannot change over time and space. Even if for some things, like income and consumption, people obtain happiness mainly from what they have in comparison to others, rather than from their absolute levels, it does not follow that all things on which individual happiness depends involve such comparisons. For instance, individual happiness may depend strongly on absolute levels of leisure, time spent with family and friends, good health and a clean environment. Indeed, as we shall discuss later, they argue that individuals actually devote too much effort in obtaining things involving comparisons (to get ahead of others) and too little on things that do not involve comparisons. A final theoretical distinction in the study of happiness relevant to our concerns is the distinction between global evaluations of life in general, which is the principal focus of most research, and the evaluations of happiness with particular aspects, or ‘domains’, of life. In this latter interpretation happiness may be defined as the feeling one gets by being with one’s family, having better health, having a rewarding job or having more

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Happiness, economics and politics

money. This observation also suggests empirical analysis of what actual conditions determine overall happiness. There is considerable literature examining the determinants of happiness, more specifically, exploring how happiness depends on personal factors such as income, health conditions, whether one is employed, conditions of work, time spent with family and friends, status, religiosity, personality traits, age, marital status, gender and race, overall economic conditions such as inflation, unemployment and income distribution, overall political conditions such as nature of the government, trust in government and political instability, and other general factors like the weather (see, for instance, Argyle, 1987, 1999; Frey and Stutzer, 2002; Layard, 2005). In their contribution to this volume, Richard Easterlin and Onnichi Sawangfa bring these two strands of the literature together, and examine how trends in overall indicators of happiness relate to satisfaction people report from the widely discussed domains of finance, family life, work and health. They find that the importance of any given domain depends on actual life circumstances regarding socioeconomic status (as measured by years of schooling), time (year dummies), age or birth cohort, and that no individual domain is invariably the key determinant of overall happiness. This analysis also enables them to explain a number of empirical trends that have been found in the happiness data for the USA, that is, the positive cross-sectional relation between happiness and socio-economic status, the horizontal time series trend in happiness, the hill pattern of life cycle happiness and decline in happiness across generations.

I.2

HAPPINESS AND ECONOMICS

Of obvious relevance to economists is the question whether happiness increases when people consume more goods and services. It is widely believed by people that more is better and that money buys happiness. This belief is reflected in the theory used by mainstream economists, which assumes that individuals maximize utility, and that utility increases with the individual’s consumption or income without bound (although there may be diminishing marginal utility). It is also reflected in the way mainstream economists usually evaluate states of the economy using the notion of efficiency. Although efficiency is formally described as a situation in which no one can be made better off without making someone else worse off, in actual applications the concept is usually taken to require that there is production efficiency, that is, the economy cannot produce any more of any good or service without reducing the production of something else: everything has an opportunity cost. Economists also typically equate economic development

Introduction

9

with the growth of per capita income or product, and even when they take equity or distributional issues into account, they usually measure inequality and poverty in terms of real income or consumption. But is more really better as judged by the people who have more? Starting with Easterlin’s (1973) pioneering contribution, some economists have found that happiness in the sense of subjective well-being doesn’t seem to rise systematically with income (see Easterlin, 2001; Frey and Stutzer, 2002; Layard, 2005). Across countries most studies find that, at least beyond a certain level of income, happiness does not rise significantly with income. Time series data for rich countries, such as the USA and Japan, suggest that happiness does not increase over time despite significant increases in income. Individuals in rich countries who experience significant increases in time do not report significant increases in happiness. The only kind of empirical analysis that unequivocally supports the notion that more is better is cross-sectional analysis of individual countries: people with higher levels of income tend to be happier than those who are poorer. What explains these empirical findings, which contradict some of the basic assumptions of many economists? Suitable answers have to explain both why people increase their income and consumption and why they are not happier as a result, a phenomenon that has been called the Easterlin Paradox. Economists have come up with a number of plausible explanations which can be classified into two groups. One group focuses on the individual decision maker and argues that for a variety of reasons individuals make poor decisions which make them consume more without becoming happier as a result. The other group examines the individual decision maker in a social context where, although in isolation they could make decisions which make them happier, such decisions are influenced by the behavior of others, and the actions of all individuals taken together result in conditions which make individuals not happier. In the first group are explanations which focus on psychological processes involved in decision making and the feelings individuals experience after they make their decisions. Individuals make decisions to do certain things – like consuming more – but they make decisions which make them no happier because they either do not know what makes them happier, or because they do not have the willpower to do what makes them happier. In his contribution to this volume, Alois Stutzer uses the tools of happiness studies to examine whether individuals act ‘rationally’ in their self-interest, or whether they sometimes yield to temptation which overwhelms their willpower, resulting in outcomes that are not optimal for them. He examines this question by reviewing analysis and evidence on smoking and television viewing, and discusses his own recent work on obesity. He finds that

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Happiness, economics and politics

individuals frequently report to being unhappy with their decisions about smoking, television viewing and eating, and their consequences, and this loss in happiness is positively related to their own judgments about their lack of self-control. Thus, when doing something leads to immediate (even minor) gratification, and the costs – even if well understood and significant – come later, individuals perform these activities. These findings go against one of the standard assumptions of neoclassical economics – that what people choose is the best for them because they choose ‘rationally’. In the second group are explanations which state that people, when interacting with others, make decisions which do not make them happier because they are influenced by the behavior of others, and because the feelings they experience after making their decisions are affected by what others do. For instance, following the work of Veblen (1899), Schor (1998) and Frank (1999) many others have argued that individuals try to consume more to increase their status in society, but if all of them do so, no one is better off. In fact, they may be worse off if their attempts to increase consumption result in their working more hours at the expense of leisure and time spent with friends and family, and their incurring more debt which makes them financially insecure. Increases in consumption over time can also result in higher levels of aspirations and social conventions about needs, so that there may be no increases in happiness (see Easterlin, 2001). Moreover, by increasing sales promoting expenditures, firms may influence consumers into buying goods which ultimately raise their expectations and do not make them happier. Such explanations are examples of what, following Veenhoven, was earlier referred to as comparison theory. However, this approach does not imply that happiness or well-being cannot depend on specific circumstances. Several of these arguments are closely related to the relative consumption hypothesis which states efforts by all to increase their consumption will lead to no significant changes in happiness since their relative consumption does not change. The chapter by Amitava Dutt reviews different explanations about why people increase their consumption without experiencing increases in their happiness, and argues that the relative consumption effect, especially those operating through status-seeking and norm-based consumption, seem to have the widest applicability. This chapter also discusses a simple theoretical formulation of the relative consumption hypothesis and examines some implications of it, such as the role of religiosity in promoting happiness, to show that they are consistent with the empirical evidence. The analysis implies that, at least after a point, more need not be better. It may be noted that, in addition to explaining why consumption may increase without increasing happiness, both of these groups of explanations have important and wide-ranging implications for the methodological

Introduction

11

underpinnings of mainstream or neoclassical economics. The first group questions a basic axiom of neoclassical economics, that is, economic actors are ‘rational’ optimizers. The second group questions the entire notion of efficiency, that is, the idea that more (goods and services) is better. Beyond their interest in whether money buys happiness for individuals, economists are also concerned with how happiness and well-being depend on other macroeconomic factors, such as unemployment, inflation, income distribution and fairness, economic growth and the state of the environment. These relations are not only important in themselves for understanding what conditions make people better off, but also affect the relation between consumption and income, on the one hand, and happiness and well-being on the other. For instance, higher levels of individual consumption can collectively damage the environment which in turn may have a negative effect on happiness. Also, efforts by people to increase their consumption can lead them to support policies – such as less support for worker rights – that may worsen the distribution of income which may in turn reduce happiness. It is also possible that higher levels of consumption boost aggregate demand, increase output and reduce unemployment, thereby making people happier. Two chapters in this book examine the relation between happiness and well-being and such aggregate conditions. Robert Frank examines whether, in light of the Easterlin Paradox which states that increases in income (at least beyond a certain point) do not increase happiness, economic growth is a desirable goal. He first points out that the incomehappiness relation remains a controversial one, as the recent debate between Stevenson and Wolfers (2008) and Easterlin suggests. However, the debate about the income-happiness relationship does not resolve the question about the desirability of growth. While self-reported happiness is good, so are other things, such as autonomy, good health and safe neighborhoods. Frank argues that economic growth does, in fact, improve the human lot, because it reduces child mortality and hunger, and because it produces preconditions for political and social progress, including environmental improvements, reduction of discrimination against minorities and policies which help the poor. Evolutionary selection rewards organisms which have a high probability of survival and therefore are better able to adapt to their environments, but not necessarily happier people. People therefore adapt to the good and the bad, but that is not to say that growth is not good. Carol Graham and Andrew Felton provide a brief review of the empirical literature on the effect of inequality on subjective well-being and then analyse in detail data from a large survey for Latin America. While some earlier studies – including Alesina et al. (2004) – suggest that inequality

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Happiness, economics and politics

has a negative effect on happiness in the USA and Europe, not all studies confirm this. Graham and Felton find that the effect of inequality on happiness in Latin America depends on the concept of inequality used (that is, overall inequality in the country, the relative income or wealth to different reference groups and perceived status of a person, or perceptions about overall inequality or social mobility). Their results show that relative income and wealth have a positive, significant effect on happiness, supporting the relative consumption hypothesis and implying that the poor are made less happy by increasing inequality and the rich made happier. They also find that perceptions about inequality, rank and opportunity are at least as important as differences in relative income and wealth, and that inequality in Latin America is perceived as a sign of persistent advantage for the rich and disadvantage for the poor, rather than future opportunities. An important mechanism by which income inequality can arise is discrimination. The effect of discrimination on subjective well-being and happiness, and its consequences on behavior, are examined by Arthur Goldsmith in his examination of the issue of wage discrimination by race. Their analysis starts from the fact that black workers in the USA have a lower wage than white workers of comparable background and characteristics, and from the idea that relative income is an important determinant of happiness and well-being. Using data on perceptions of discrimination they examine how workers who feel that they are discriminated against (in terms of hiring, advancement and general workplace discrimination) react to this – either by waiting to allow employers to learn about their productivity and end statistical discrimination, or by reducing their effort, or by increasing their effort. They do so by examining the impact of these reactions to wage differences between black workers who perceive discrimination, on the one hand, and black workers who do not and white workers, on the other. They find that the data are consistent with the hypothesis that black workers who are discriminated against at hiring attempt to overcome the problem by increasing effort, while those who are discriminated against in the workplace or for advancement reduce their effort.

I.3

HAPPINESS AND POLITICS

Political scientists are latecomers to the study of happiness and subjective well-being. It is one of the goals of this book to bring specifically political concerns, and more specifically still, the concerns of political science as a scholarly discipline, into the academic study of happiness.

Introduction

13

Thus, the contribution by Alexander Pacek provides a general summary of the extant work on the role of the political, broadly construed, as a factor determining the quality of life that citizens experience. Pacek provides a nearly encyclopedic review, cataloguing and critically evaluating the research in a way never previously attempted. As he discusses in more detail, the central areas of political inquiry relate to the role of democracy, social capital (and the governmental mechanisms thought to inhibit or promote it), the role of organized labor as an interest group capable of articulating the interests of the broad class of wage-earners in capitalist society, the size and qualitative characteristics of the welfare state (in conjunction with the social democratic, labor and other progressive parties conventionally understood as agents supportive of state efforts at income maintenance and redistribution), and, finally, the overall taxing and spending policies of governments. Three of these topics are further addressed by contributions to this volume. Ronald Inglehart addresses what is surely the single most basic and compelling question that a political scientist might ask about wellbeing: does the institutionalization of the democratic process, and with it the concomitant civil and political liberties democracy implies, contribute to greater happiness? Perhaps surprisingly to those outside the field, this question may not have the easy answer we might expect. First, there are good reasons to wonder if democracy, so often thought of as a panacea for social problems, really lives up to the hopes we reflexively tend to invest in it. To be sure, democracy might well be valued intrinsically, as the protection against tyranny and exploitation it is synonymous with, but it does not automatically follow that democracy per se makes people’s lives more rewarding. Thus Robert Lane (2000) argues that democracy increases the costs that citizens face, in both the literal and the psychological senses. Simplifying somewhat, Lane suggests that democracy may induce the same kind of anxiety and frustration that existentialists see in modern life: the individual appears, via the existence of representative institutions, to share in the responsibility for events, but at the same time feels powerless as an individual in the face of the collective outcomes over which one has no control. There is, too, the possibility that citizens may collectively make poor choices at the ballot box, politicizing decisions that are better left to the market or technocrats, with deleterious consequences for social life. Another line of argumentation, which is the immediate focus of Inglehart’s work, is the direction of causality between the evidence that we do have linking democracy to greater well-being. In essence, Inglehart asks, does democracy promote satisfaction, or are satisfied citizens a necessary condition for the successful operation of democratic processes?

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Strikingly, the other political factors that appear in the list of the ‘usual suspects’ in happiness studies all relate to questions of political economy. That receiving the most attention has been the controversial work by Benjamin Radcliff (for example, Radcliff, 2001), suggesting that an expansive welfare state is strongly associated with higher levels of subjective appreciation of life. The fundamental argument at hand is the perennial one between, in the argot that political scientists have come to accept, that of ‘markets vs politics’. We face here the two basic schools of thought in political economy: should human welfare be left primarily to a self-regulating market, with a minimalist state providing the least possible ‘safety net’ and the lowest possible level of government regulation of the economy in general and the labor market in particular, or should the state intervene in the market, through a program of what Radcliff (2001) calls ‘emancipation’ from the market through the joint mechanisms of greater regulation and a greater commitment to income maintenance? Generalizing, the debate becomes one of the overall public policy regimes that governments pursue, with the basic options remaining those available since the advent of the modern industrial economy, viz. the conventional programs of left and right. In his chapter in this volume Pacek reviews at some length the considerable evidence in favor of the contention of Radcliff’s (2001) and others that it is the program of the left that, empirically, appears to offer the surest path to the greatest good for the greatest number. The chapter by Charlotte Ridge, Tom Rice and Matthew Cherry offers a contrary view, suggesting that the apparent statistical relationship between social democratic policy regimes and happiness may neither be as theoretically coherent or as empirically robust as it may appear. As they note, arguments of the sort offered by Radcliff demand a certain amount of skepticism, given the stakes involved. As they write: ‘Not only does [Radcliff] claim that life is better under one type of government than others, it makes the claim with respect to human happiness, perhaps the most meaningful measure of a good society.’ The same tension between market and politics also animates the research on the role of labor organization as an agent of human wellbeing. Political scientists rightly focus on labor unions as political institutions in a variety of respects. Unions are, first, political actors in the electoral and policy making processes, being important elements in the coalition of left and center-left parties throughout the Western world. Capitalist societies are by their very nature class societies, such that organized labor emerges as the only interest group with either the resources or the inclination to represent the interests of working-class citizens. Thus, how countries (or, in the USA, states) differ in the extent to which workers

Introduction

15

are organized is frequently argued to be one of the most salient features in determining their political make-ups. The strength of the labor movement is also commonly viewed as the result of the political process, in that the level of organization is largely (though by no means exclusively) determined by the legal structures that determine how readily workers can form unions. Finally, the workplace itself is an inherently political institution, and the one in which workers spend more waking hours of their lives than any other single activity. Given that the work experience affects not only one’s economic well-being, but one’s sense of dignity and self-respect, the institution of the labor union, as the advocate and agent of the worker in obtaining both income and dignity, has an obvious potential for affecting an individual’s sense of satisfaction with life. Pacek’s chapter reviews the cross-national evidence on the role of unions in fostering well-being, whereas the chapter by Suzanne Coshow and Benjamin Radcliff explores this issue further by focusing on the role of organized labor in the USA per se. They attempt to determine if the relatively modest differences in the power of organized labor across the US states appear to have equally strong effects on well-being as the larger differences across countries do. This question is especially compelling given that the national political context in the contemporary USA is one in which labor is universally regarded as a weak (and ever more progressively weak) political actor.

I.4

HAPPINESS, ECONOMICS AND POLITICS

As noted earlier, the central theme of this book is that the study of happiness is best conducted from a consciously multidisciplinary perspective. To illustrate this, the book has focused on the interaction between economics and politics in understanding happiness. In general, there are several reasons why a multidisciplinary approach is useful. First, different disciplines have evolved in specific ways because of accidents in the development of these disciplines. Some issues have been given the label ‘economic’ and others the label ‘political’ not because they are intrinsically unrelated, but because dominant traditions within them happened to focus on them while excluding others. Second, the way that dominant traditions have separated different disciplines can also be argued to be flawed. For instance, in some popular interpretations ‘economics’ has focused on the operation of ‘markets’ and ‘politics’ on the operation of ‘the state’. The problem with such dichotomies is that they overlook the fact that what are called ‘markets’ and ‘the state’ are intrinsically interrelated. Thus, markets do not exist in a vacuum, but are regulated by social norms and political processes, without which they

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simply cannot exist, let alone operate smoothly. Moreover, the state is deeply influenced by market processes through, for instance, their effects on income distribution, to say nothing of the dependency of the government on the ‘economy’ to maintain employment, its own tax revenues and, thus ultimately, the maintenance of public order. Of course, as the stock of knowledge continues expanding, specialization in areas of knowledge becomes necessary. However, it is not clear that such specialization is best done in terms of disciplines and sub-disciplines, rather than in terms of issues. Thus, we argue that it is preferable for scholars to focus on the issue of happiness, rather than simply applying the ideas of particular disciplines to the study of happiness. But given our disciplinary backgrounds, this is easier said than done. Indeed, the book is divided into separate parts which deal with economics and happiness, and with politics and happiness. However, while we are at least to some extent prisoners of our disciplines, we realized from our conference that we have much to gain in our study by struggling to break free of our disciplinary moorings. We can illustrate this through four examples of what the chapters in the book suggest can be gained by combining the insights of economics and politics to the study of happiness. The first example concerns the concept and measurement of happiness. Economics has a long history of conceiving of happiness in terms of subjective well-being. The Utilitarians mostly thought of well-being in terms of how people evaluated their circumstances, and Easterlin’s early work used evidence from happiness surveys to quantify the ‘human lot’. As noted earlier, some economists, such as Sen (1999) have discussed serious problems with overemphasis on utility or subjective well-being, and advocated the use of other indicators, such as people’s ability to achieve valued ‘goods’. Political scientists, who seem to be overly wedded to measuring happiness using the notion of subjective well-being by using happiness surveys can do worse than take into account the warnings posed by these economists. The second example relates to whether happiness depends on some outcomes or of some processes. Most economists entertain a consequentialist bias, evaluating well-being in terms of actual outcomes. Political scientists, however, have frequently been more interested in processes, such as whether governments are democratic, and to what extent individuals participate. To be sure, there are some economists who seem to be interested in processes – such as, for instance, those promoting the freedom of choice and the equality of opportunity and reducing economic insecurity – while, as discussed in some of the chapters in this book, some political scientists are interested in the outcomes – such as the election of left parties – on happiness. Happiness and well-being, of course, can be said to depend on both outcomes and processes, and an approach that is informed by the

Introduction

17

work of both economists and political scientists is more likely to recognize this. While these two examples related to the concept and broad approach to the study of happiness, our remaining examples relate to how multidisciplinary study involving both economics and politics can improve our understanding of the determinants of happiness. The third example concerns efforts by economists to understand the determinants of happiness. If increases in income and consumption do not make people significantly happier, at least beyond a certain level, what economic choices and conditions do? Economists and other social scientists have examined the evidence to find that higher socio-economic status, lower unemployment rates, lower inflation, more economic equality (although this is somewhat controversial), the kind (that is, their intrinsic nature) of work people do, more time not spent at work and lower levels of consumer debt contribute to happiness. These findings also suggest that greater economic insecurity – the possibility of losing jobs, for instance – affect subjective well-being. Economic well-being – in terms of functioning and capabilities – is also positively affected by greater access to good health and education. Some of these determinants of happiness can be chosen by individuals, but many of these can be affected by economic conditions. Other determinants, like income distribution and unemployment, are beyond individual control. If there is some validity to these empirical findings, the question then arises: what kinds of overall economic conditions and policies are more likely to increase happiness and well-being? This, in turn, raises the question: what political factors make it more likely that these policies will actually be adopted? For instance, given that the public policies that protect workers from insecurity (through, say, unemployment insurance), or the structure of laws that make union organizing easier or more difficult, are simultaneously economic in their impact on individuals, but also the result of a political process. It is thus necessary to understand economic and political factors and their interaction to answer these questions. As the labor union example illustrates most strikingly, seemingly economic factors are often inherently political, and can only be adequately understood as political phenomena. Fourth, and this time starting from the work done by political scientists (as Pacek’s chapter reviews) suggests that the election of parties on the political left (as compared to those on the political right) increases subjective well-being. These contributions argue that this finding can be explained in terms of the economic security and social safety nets provided by such left-leaning governments However, left-leaning governments are not all the same and there is a great deal of heterogeneity about what policies they pursue. It is worthwhile for political scientists to draw on the

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work of economists to examine what specific types of policies promote economic security in any given context. We end this section with two comments. First, although we argue that there needs to be a greater recognition of the interaction between the economic and political, and more collaborative work between economists and political scientists, we do not endorse any particular type of what has been called political economy. In particular, we do not endorse that all of this interdisciplinary work needs to follow what is called ‘rational choice’ approach of self-interested, optimizing agents. This approach can illuminate some issues, but we find – for instance, because of what was argued earlier about ‘rationality’ – that for many questions this approach can be extremely misleading. Second, although we have concentrated here on economics and politics, this argument applies to other disciplines – such as psychology, sociology, philosophy and theology – as well, as implied by several chapters in the book.

I.5

TOWARD A HAPPIER WORLD?

A final concern that must animate any study of human happiness is the obvious one of what should be done by people and societies to improve their lives, individually and collectively. The first question is whether happiness itself is a goal that should be pursued. Despite the fact that for so many people happiness is the goal of life and the motivation for living, and the widespread acceptance of the legitimacy of this goal (as ensconced, for instance, in the US Declaration of Independence’s statement that ‘the life, liberty and the pursuit of happiness’ are the ‘inalienable rights’ of people), some have questioned whether the goal is worth pursuing. Wilson (2008), for example, argues that ‘happiness as immediate gratification, happiness as superficial comfort, happiness as static contentment’ could well be a ‘dystopia of flaccid grins’ (pp. 8–9). He argues that the search for happiness is delusional and inauthentic in a world full of insecurity, and that it can lead to the destruction of a thriving culture, by removing the muse of great literature, painting, music and innovation. While Wilson’s admonitions need to be taken seriously, and are closely related to Alasdair MacIntyre’s insightful remarks at the conference, they do not negate the fact that it may be desirable to reduce insecurity of certain kinds for many people in an insecure world in ways that do not provide only immediate gratification through the mere accumulation of ‘stuff’. Moreover, as Wilson is careful to point out, he is ‘thinking only of . . . [the] specific American type of happiness. I am not questioning joy in general . . . [For instance,] I am not criticizing that slow-burning

Introduction

19

bliss that issues from a life spent helping those that hurt. . . . Likewise, . . . I don’t want to romanticize clinical depression’ (Wilson, 2008, p. 7). Even if happiness, appropriately defined, is accepted as a legitimate goal, it can be asked whether we should try to maximize happiness as a matter of public policy. In their chapter in this volume Bruno Frey and Alois Stutzer discuss whether recent advances in the measurement of happiness, especially using data from surveys which ask people to evaluate the quality of their own lives, should make societies try to maximize aggregate national happiness. Although they find that these measures improve on standard measures of evaluation like GDP, they argue that governments should not try to maximize total happiness because doing so fails to take into account the complexities of the political process, fails to take into account the fact that people adapt to their situations (perhaps being on a kind of aspirations treadmill), results in governments trying to manipulate happiness measures to suit their purposes, and induces people to misrepresent their happiness levels strategically to make policies favor them. But even if pursing the formal maximization of happiness is problematic, in Frey and Stutzer’s view happiness research is valuable because it can help people make informed choices on how to best pursue their happiness (broadened to include other goods such as loyalty, self-respect, freedom and personal development) privately and collectively, and to identify institutions which help to achieve these goals. The brief concluding chapter by Dutt and Radcliff addresses the issue of what can be done to help people lead happier and more fulfilling lives? They argue that it is necessary to take not only a multidisciplinary approach to what can be done to increase happiness and well-being, but that it is appropriate to approach this question at different levels: at the level of the individual, of groups, of nations and of the world as a whole. Individuals can do many things to make appropriate decisions. As we have previously noted, the chapter by Sheldon and Lyubomirsky examines directly how, and to what extent, individuals can act to improve the degree to which they find life rewarding. The chapter by Dutt suggests people can be happier by consuming those things which provide gains that endure rather than those things which increase their status or those things to which they quickly get habituated. However, in some cases individuals may lack the incentive to do things on their own, because the happiness they will get from their actions depends not only on what they do, but what others do. For instance, it is possible that if individuals try to work fewer hours to spend more time with family or friends, they may create the impression that they are not dependable and committed employees and possibly lose their jobs. Thus groups of workers can collectively try to reduce their working hours, and governments can impose laws to limit

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working hours which could increase happiness. But here, too, individuals with a better understanding of the determinants of happiness can make more informed choices about which policies to support. Finally, especially in an increasingly globalized world, the consequences of individual decisions for happiness and well-being may well depend on what people around the world do – the issue of global warming is an obvious example – such that achieving happiness can be seen as a truly human undertaking, not merely a personal or national one.

REFERENCES Alesina, Alberto, Rafael Di Tella and Robert MacCulloch (2004), ‘Inequality and happiness: are Europeans and Americans different?’, Journal of Public Economics, 88, 2009–42. Argyle, Michael (1987), The Psychology of Happiness, 2nd edn, 2001, London: Routledge. Argyle, Michael (1999), ‘Causes and correlates of happiness’, in D. Kahneman, E. Diener and N. Schwarz (eds), Well-Being: The Foundations of Hedonic Psychology, New York: Russel Sage Foundation, pp. 353–73. Diener. E., E.M. Suh, R.E. Lucas and H.L. Smith (1999), ‘Subjective well-being three decades of progress’, Psychological Bulletin, 125, 276–302. Easterlin, Richard (1974), ‘Does economic growth improve the human lot? Some empirical evidence’, in Paul David and Melvin Reder (eds), Nations and Households in Economic Growth: Essays in Honor of Moses Abramovitz, Palo Alto, CA: Stanford University Press, pp. 98–125, reprinted in Easterlin (2002). Easterlin, Richard (2001), ‘Income and happiness: towards a unified theory’, Economic Journal, 111, July, 465–84, reprinted in Richard Easterlin (ed.) (2002), Happiness and Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar Publishing. Easterlin, Richard (ed.) (2002), Happiness in Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar Publishing. Frank, Robert (1999), Luxury Fever. Why Money Fails to Satisfy in an Era of Excess, New York: The Free Press. Frey, Bruno S. and Alois Stutzer (2002), Happiness and Economics, Princeton, NJ: Princeton University Press. Lane, Robert E. (2000), The Loss of Happiness in Market Democracies, New Haven, CN: Yale University Press. Layard, Richard (2005), Happiness. Lessons from a New Science, London: Penguin Press. Maslow, Abraham (1954), Motivation and Personality, New York: Harper. McMahon, Darrin M. (2006), Happiness. A History, New York: Atlantic Monthly Press. Nettles, Daniel (2005), Happiness. The Science Behind Your Smile, Oxford: Oxford University Press. Putnam, Robert (2000), Bowling Alone. The Collapse and Revival of American Community, New York: Touchstone Books.

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Radcliff, Benjamin. (2001), ‘Politics, markets, and life satisfaction: on the political economy of human happiness’, American Political Science Review, 95 (4), 939–52. Schor, Juliet (1998), The Overspent American. Upscaling, Downshifting and the New Consumer, New York: Basic Books. Sen, Amartya (1999), Development as Freedom, New York: Anchor Books. Stevenson, Betsey and Justin Wolfers (2008), ‘Economic growth and subjective well-being: reassessing the Easterlin Paradox’, Brookings Papers on Economic Activity, 1, 1–87. Veblen, Thorstein (1899), The Theory of the Leisure Class. An Economic Study of Institutions, New York and London: Macmillan. Veenhoven, R. and J. Ehrhardt (1995), ‘The cross-national pattern of happiness: test of predictions implied in three theories of happiness’, Social Indicators Research, 43, 33–86. Wilson, Eric (2008), Against Happiness, New York: Farrar, Straus and Giroux.

PART I

Happiness

1.

The history of happiness and contemporary happiness studies Darrin M. McMahon

I feel that I am singularly unfit to answer the question: ‘what is happiness?’ in large part because of my training as a historian, which makes me, I fear, unduly attentive to the way in which words and concepts change their meanings over time. To be perfectly frank, I’m partial to Immanuel Kant’s observation that ‘the concept of happiness is such an indeterminate one that even though everyone wishes to attain happiness, yet he can never say definitely and consistently what it is what he really wishes and wills.’ But clearly that is not really going to be good enough for this chapter. So how to answer the question ‘what is happiness?’ I might point out, as I do in my book, the strong and stubborn etymological link between happiness and luck in every Indo-European language (see McMahon, 2006). The old Norse and Old English root ‘hap’, like the old French heur or the Mittelhockdeutsch ‘Glück’ simply means luck or fortune. We have mishaps when bad things happen to us. And when good things happen to us – when we are lucky – we are happy, Glücklich, filled with bon-heur. I might, to take another tack, note the equally long and stubborn connection relating happiness and good fortune to fortune itself – to wealth, prosperity, fertility and abundance. It is not coincidental that the early Greeks spoke of the gods as olbios or makarios – as blessed or happy – not least because of their material prosperity. Thus the Homeric ‘Hymn to Hermes’ uses a form of makarios to describe the cave dwelling of the god Hermes and his mother, which is full of ‘nectar and lovely ambrosia’, with much ‘silver and gold’, fine clothing, and other things ‘such as are kept in the sacred houses of the happy’. Nor is it coincidental that the Romans placed the goddess Felicitas on the back of coins, with a horn of plenty in one hand, symbolizing abundance, fecundity and bounty. Nor is it coincidental that they referred to the destitute as ‘miser’ – wretched, unfortunate, poor – the root, of course, of our modern English term miserable. Still another tack – less historical and more analytical would be to borrow from the positive psychologists and social scientists – to note the various dimensions of happiness on a synchronic as opposed to a 25

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diachronic plane. And here we might, following say Marty Seligman, or the English psychologist Daniel Nettle, among others, point to a first level set of associations linking happiness to positive emotion and good feeling – feelings of pleasure and joy. A second level order of happiness having to do with the longer term, encompassing a sense of satisfaction and well being, a set of judgments about one’s condition or state. I am happy with my marriage, with my work and so forth. Finally, we might distinguish a third level of happiness – the broadest of all – having do with quality of life as a whole, with human flourishing, with fulfilling one’s potential, with human excellence and the good life. In short, use a definition that accounts for some of the distinctions between hedonic and eudemonic conceptions of happiness discussed in Ong’s chapter in this volume. Now there is much to recommend this latter approach – and for practical purposes it may well be among the most satisfactory. But historians have the luxury of not being practical, as my wife – a practical woman – constantly reminds me. And so let me be myself – impractical, perhaps even something of an annoyance – by taking a page from Wittgenstein to note, as a historian, that no matter how hard we try to pin down happiness, its meaning, or meanings, will always be pregnant with the past and with its past uses. Happiness, like all of us, cannot entirely escape the past. And so it strikes me that it is worthwhile thinking seriously about those past uses before we, in the present, make use of happiness ourselves. What I’d like to do, in effect, is to repay a debt. I have benefited a great deal from the work that is done in contemporary happiness studies, and so it is clear to me at least what it can do for history. But what, it may be asked, can history do for happiness studies? And here I would hope not just to reiterate some of the past uses of happiness that inevitably bear on those in the present, but also to try to place contemporary happiness studies in a somewhat broader context, to help situate the present moment vis-à-vis the past. For though it may be true, as William James observed in the Varieties of Religious Experience that ‘How to gain, how to keep, how to recover happiness, is in fact for most men at all times the secret motive of all they do, and of all they are willing to endure’, human beings have never been as preoccupied, never been as obsessed, I would argue, with happiness as they are right now. Indeed, it is really only in the eighteenth century that considerable numbers of people began to think of happiness as a this-worldly possibility. Hitherto, happiness, at least in Western societies, had been considered by and large either as a condition of the future (of the millennium, say, or the second coming, or when the children of Israel are fully redeemed in the promised land – next year in Jerusalem), or in the past (in the Garden of Eden, in a primordial golden age, a Prelapsarian time of innocence). Or,

The history of happiness and contemporary happiness studies

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alternatively, in another dimension of space and time altogether (heaven, or those ‘blessed or happy isles’ of the Greeks). Happiness in the here and now –in the normal conditions of life – wasn’t really considered an earthly prospect, or at least wasn’t considered by most as such. Now of course it is certainly true that one has the tradition of classical philosophy initiated by Socrates towards the end of the fifth century bce – a tradition that presented happiness or human flourishing (eudaimonia) as a function of human virtue. This is tradition that is developed by a great many Greek and Roman moralists, though none so centrally as Aristotle, for whom eudaimonia, as you know, was the goal or end, the telos of human activity. But the point I want to stress here is that for Aristotle – and in this respect he is perfectly in keeping with virtually every prominent Classical moralist after Socrates – happiness, though yes an earthly prospect, was not a habitual reward. On the contrary, happiness was a prize to be won over the course of a lifetime only by the virtuous – the happy few – those whose excellence of conduct and character allowed them to rise above normal human conditions, to live what Aristotle describes in the Nichomachean Ethics, as a ‘god-like’ life. To be happy might be within human power, but it was a power that would only ever be realized by a very small percentage of the human population. How radically different this is from that goal, first stated in the eighteenth century, to pursue the greatest happiness for the greatest number, to seek to attain, what the French Constitution of Year 3 during the French Revolution described, in its very first article, as ‘common happiness’, the happiness of all. ‘Does not every man have a right to happiness’, asks the author of the article on happiness in Diderot and D’Alembert’s great Encyclopédie, the Bible as it were of the European Enlightenment. A right to happiness! Think about it: this is revolutionary talk! And in that respect, the French revolutionary St Just was perfectly right to announce, as he did in the National Convention in 1794, that ‘happiness is a new idea in Europe’. In some real ways it was. But what was a revolutionary pronouncement in the age of Enlightenment – a right à la Jefferson to the pursuit of happiness, or a right à la St Just and the French revolutionaries to its attainment – has steadily become less and less revolutionary and more and more a part of our received assumptions about the way human life should be. Far from thinking about happiness as a miracle of the universe – or as the attainment of a god-like few – people in the developed world tend to think of happiness, today, I would argue (however they define it) as the natural human state, the way men and women ought to be if they are not abused, or prone to depressive illness, or unjustly deprived of their natural human endowments.

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It is worth stressing that this conviction involves an assumption about human nature and human experience – about the purpose of human lives – about the way we are intended to be here on earth. It is something of a teleological assumption – one that is nice to believe, one that is comforting, one that is humane and which may in fact be true. It is an assumption, nevertheless, that can’t really be proved. The assumption rests, to some degree, on an article of faith. I talk quite a bit about this in my book – about the way in which the belief in happiness as what Alexander Pope called in the eighteenth century human ‘being’s end and aim’ not only constituted an article of faith in its own right, but an article of faith that steadily challenged, and gradually replaced, however fitfully and imperfectly, that of the reigning Judeo-Christian belief in individual salvation by God. To be sure, not all bowed either immediately or easily to the new faith in earthly happiness. I’m fond of quoting Thomas Carlyle as an example of one such apostate. That cranky, irascible Scot could write in the mid nineteenth century: Every pitifulest whipster that walks within a skin has had his head filled with the notion that he is, shall be, or by all human and divine laws ought to be, ‘happy.’ His wishes, the pitifulest whipster’s, are to be fulfilled for him; his days, the pitifulest whipster’s, are to flow on in ever-gentle current of enjoyment, impossible even for the gods. The prophets preach to us, Thou shalt be happy; thou shalt love pleasant things, and find them. The people clamour, Why have we not found pleasant things?

Carlyle was perhaps something of an exception in his blunt refusal to countenance the new faith. But others who shared it were at least prepared to acknowledge that it was in part just that, an article of faith. Darwin is interesting on this score, as is John Stuart Mill, as is Freud, who of course was ultimately a skeptic. In his Das Unbehagen in der Kultur, Civilization and its Discontents, a work, revealingly, which was originally titled Das Unglück in der Kultur, Unhappiness in Civilization, Freud, after parsing the pleasure principle which in his view ‘decides the purpose of life’, concluded that the pleasure principle was ‘at loggerheads with the whole world, with the macrocosm as much as with the microcosm. There is no possibility at all of its being carried through,’ he declared, ‘all the regulations of the universe run counter to it’. Threatened always by the suffering of our own bodies which are doomed to decay and dissolution and which cannot even do without pain and anxiety as warning signals; from the external world, which may rage against us with overwhelming and merciless forces of destruction; and finally from our relations to other men, Freud concluded that the barriers to sustained happiness were insuperable. Human beings

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29

might take happiness to be the ‘purpose and intention of their lives’. ‘They strive after happiness; they want to become happy and to remain so.’ But they were, according to Freud, mistaken or deceived. ‘One feels inclined to say,’ he concluded, ‘that the intention that man should be “happy” is not in the plan of “Creation.”’ Freud was writing in the aftermath of the First World War and on the brink of the Second, not long before Hitler came to power, and so we might forgive him his pessimism. But it is, I think, an index of how far we have moved since that time that Freud’s tragic view of the inevitable frustrations, conflicts and irresolvable tensions of the human condition has long been out of favor. The Enlightenment belief in happiness – the Enlightenment faith in happiness – has totally triumphed in the developed world in the second half of the twentieth century, commensurate with – it is surely not irrelevant to note – the greatest cumulative economic expansion in human history. If, as we know from our sociologist colleagues’ work on reported subjective well-being, men and women in the USA and Europe have not, it seems, gotten appreciably happier since the 1950s, despite the massive gains in cumulative GNP. It is the case, I would argue, that men and women’s sense that they should be happy has in fact increased a great deal. Paradoxically this increase in expectations may actually decrease happiness by increasing disappointment. What I call the unhappiness of not being happy is a phenomenon one can detect in Western culture since the eighteenth century, but it has probably never been as acute as it is today. So happiness as our being’s end and aim – this Enlightenment creed has triumphed, and in the process it has tended to crowd out, discredit or co-opt other ways of looking at the world and the human purpose in it. Religion provides an interesting case in point. You would be hard-pressed to find in, say, the early part of the seventeenth century, a Christian religious apologist arguing that religion was a means to happiness (at least a means to happiness in this life). Religion – and the salvation that it offered – were considered, rather, ends in themselves. And yet increasingly, beginning in the latter part of the seventeenth century, religious apologists themselves have tended to genuflect before the new god of human happiness on earth. True Pleasure, Chearfulness, and Happiness, The Immediate Consequence of Religion was the way one American author in the 1760s titled his book on the merits of Christianity, while reminding his readers that Christ’s first miracle was to create more wine to keep the party going – and there are many Catholic analogues for this too. By the early nineteenth century, this tendency was considerably developed, prompting Alexis de Tocqueville to observe in Democracy in America that whereas Old World priests had once spoken ‘of nothing but the other life,’ and ‘hardly took any trouble

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to prove that a sincere Christian might be happy here below,’ preachers in America were ‘continually coming down to earth’ Indeed they find it difficult to take their eyes off it. The better to touch their hearers, they are forever pointing out how religious beliefs favor freedom and public order, and it is often difficult to be sure when listening to them whether the main object of religion is to procure eternal felicity in the next world or prosperity in this.

Living, as I now do in the South, a transplant from New York City, I can affirm that this form of exhortation is very much alive. Get religion, get happy. When the latest Pew Foundation findings linking evangelical Protestantism to subjective well-being were released recently, people in my neck of the woods were doubly elated. So even among those who might be expected to be preaching fire and brimstone, earthly happiness today in effect is the highest good. The French philosopher Pascal Bruckner goes so far as to observe that it (happiness) has become ‘the sole horizon of our democracies’. Taking into account that general Enlightenment triumphs, I think, may help us to situate contemporary happiness studies in a somewhat broader context than you might get simply from studying its place in the history of psychology, say, or economics or sociology. And that is a reflection that I hope will give you a slightly better understanding of the extraordinary contemporary appeal of work on happiness in a number of fields, for that work is in many respects the culmination and perfect expression of precisely the dynamic I have traced briefly here. Happiness, we might say, is all that many have left, and so it is only natural to conclude that we should do everything in our power to figure out how to secure it. Notwithstanding the creativity and insight of many of those who study happiness today, this broader dynamic, I think, helps to account even more than their own labour for the tremendous popularity of their work. Let me make one more reflection – or series of reflections – based on my observation about the uses to which happiness has been put in the past and how that bears on the present. I think one needs to recognize that when happiness began to occupy the space formerly occupied by religion – when it became, to quote a letter from Voltaire in 1726, ‘the great and only concern’, there was born a concept of extraordinary power and allure. For what had for so long resided on the horizon of human experience, outside our temporal bounds, the source and repository of all our hopes and longings and dreams, had now been pulled down from heaven to earth, and dangled before us, every one of us, as a legitimate prospect in the here and now. With the result that those who could marshal those hopes, who could claim to lead us towards the coveted promised land of happiness on earth

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were necessarily vested with extraordinary power. At the very time that St Just was proclaiming happiness as a new idea in Europe, his Jacobin colleagues were preaching secular sermons in former Catholic churches about happiness on earth – ‘real’ happiness, as opposed, they claimed, to the false kind that came surrounded by angels – real happiness, while the guillotine did its work. ‘The overcoming of religion as the illusory happiness of the people is the demand for their real happiness’, Marx would later write in his Contribution to the Critique of Hegel’s Philosophy of the Right. It is one of those terrible ironies of history that in taking up this injunction, Stalin liked to describe himself as the Constructor of Happiness. So what am I implying with these ominous allusions? That authorities on happiness are somehow dangerous, despite their best intentions? That the search for earthly happiness must end in blood? Of course not. And yet I would enter a humble plea as a historian and scholar of the humanities for a certain humility as we approach the study of happiness, pointing out the un-nerving tendency of happiness to frustrate and circumvent those who would try to grasp it in pursuit. . . . Fortune’s wheel turns treacherously And out of happiness brings men to sorrow

the monk observes, in Chaucer’s The Canterbury Tales. We risk missing something in today’s post-Enlightenment world, I would argue, when we fail to acknowledge that un-nerving tendency, and when we fail pay heed to those traditions of knowledge – be they Classical (think of Greek Tragedy), or Jewish (think of the tale of Job), or Christian (think of the account of original sin) – which emphasized the elusive nature of happiness and its quest, the difficulty of ever fully securing it in our grasp, the little piece of us that, however happy we might seem, always seems to cry out for more. These are insights that one finds again and again in Western history. From Horace’s lapidary reflection: ‘Nihil est ab omni parte beatum.’ Nothing is completely happy. Or Rousseau’s frank avowal: ‘I doubt whether any of us knows the meaning of lasting happiness. Happiness leaves us, or we leave it.’ Or John Stuart Mill’s insight that if you ‘Ask yourself whether you are happy . . . you cease to be so.’ There are many other such poignant reflections. I like to point out that something of this same elusive quality is creeping about in the phrase the ‘pursuit of happiness’ itself. We focus, rightly, on the word happiness, but pursuit is interesting too. In the eighteenth century it had a somewhat harder meaning than it does today, closely related, in fact, to its cognates, ‘prosecute’ and ‘persecute’. If you look, for example in Samuel Johnson’s great eighteenth-century Dictionary of the English Language, you’ll find:

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‘To Pursue . . . 1. To chase; to follow in hostility.’ ‘Pursuit . . . 1. The act of following with hostile intention’. Johnson being the one who observed that a man may be happy in the future or in the past, but in the present, never, except when drunk. But this harder sense of ‘pursuit’ is interesting. The French talk about la chasse au bonheur, the hunt for happiness, as if one were in the process of stalking a wild, and potentially dangerous, beast. A beast, presumably, that one has to kill when it is finally cornered and can’t flee any more. So all this by way of registering a reminder that the pursuit of happiness and the uses to which happiness has been put have not always been happy. A reminder that no matter how hard we try to fix its meaning, the word and concept will always come to us charged with its religious and metaphysical past as the ultimate human end, the final place of rest, the solution and salvation to human dissatisfaction, the answer to the riddle of existence. In the early middle ages Boethius could observe that ‘God is happiness itself.’ I don’t think it is entirely an exaggeration to say that for many, today, happiness has become a sort of god. Which means that we, as its interpreters and perhaps prescribers, share in something of a priestly craft – at the very least share a moral responsibility that is greater than we might always appreciate at first glance. In this respect, the Oxford Don and Anglican Archbishop of Dublin, Richard Whately, was certainly right when he said in the nineteenth century that happiness is no laughing matter.

REFERENCES Carlyle, Thomas (1965), Past and Present, New York: New York University Press, edited by Richard D. Altick, 157. de Tocqueville, Alexis (1988), Democracy in America, New York: Harper Perennial, translated by George Lawrence and edited by J.P. Mayer, 2: 530. Freud, Sigmund (1989), Civilization and its Discontents, New York: W.W. Norton, translated and edited by James Strachey, Introduction by Peter Gay, 24–5. James, William (1994), The Varieties of Religious Experience, New York: Modern Library Edition, 78. McMahon, Darrin M. (2006), Happiness. A History, New York: Atlantic Monthly Press. Marx, Karl (1844 [1983]), ‘Contribution to the Critique of Hegel’s Philosophy of the Right: Introduction’, in The Portable Karl Marx, edited by Eugene Kamenka, New York and London: Penguin, 115.

2.

On the measurement and mismeasurement of happiness: contemporary theories and methodological directions Anthony D. Ong*

It has become clear that the phenomena referred to as human well-being is a mosaic of many component parts. This mosaic can be partitioned into a parsimonious set of dimensions, indicating measurements, that fairly completely account for individual differences among a large number of these components. The components that social scientists have been able to measure probably do not represent the entire range of experiences that constitute human well-being, but they are a goodly sample. Hundreds of different instruments have been designed to assess various features of human health and well-being. Analyses of these different instruments indicate that what is measured in common is fewer than a dozen broad dimensions indicating major kinds of positive human experience. Scientific understanding, thus, has moved away from the idea that human well-being can be well represented by a single dimension (often referred to as happiness). Well-being, to be sure, is many faceted. But to recognize that well-being has many facets is merely to start to understand it. Just what are the facets; how do they emerge in culture and in individuals? What are their functions? The volume makes it clear that well-being involves deep insight into the meaning and purpose of life. Yet well-being is not merely knowledge and comprehension of the moral imperatives of the good life, even as such insight and comprehension must be part of it. The moral authority of human well-being must extend beyond that needed to ensure the continuance of any particular group; it must deal adequately with the continuance of all humankind. Yet it must derive from acculturation within a family, within a kin group, within a particular society. Well-being must also derive from experience, but experience is not sufficient to produce it: great and diverse experience need not result in well-being. Finally, human well-being is distinct from any of what is referred to as human happiness, as Carol 33

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Ryff has pointed out (Ryff, 1989), but it must involve and stem from much of that happiness. So we begin with the understanding that human well-being is too complex to fully understand. Nevertheless, here an attempt is made to describe an important feature of well-being that involves some aspects of mature human happiness, even as it is more than such happiness. To clarify the distinction between well-being and happiness, I will first describe what the term ‘human happiness’ has come to mean within the context of the science of hedonic psychology (Kahneman et al., 1999). I will then describe how this concept must be broadened to include the development of eudaimonia (Waterman, 1993), one form of which is an important feature of human well-being. While an in-depth review is beyond the scope of this chapter, I do strive to critically evaluate and address conceptual and methodological issues surrounding the need for (1) reliable and theory-driven measures of positive health and well-being, (2) study designs that link information at different levels of analysis, and (3) innovative methodological approaches that are sensitive to complex dynamic relationships.

2.1

EMPIRICAL INVESTIGATIONS OF HUMAN WELL-BEING

Two lines of research bring us to our current theoretical understanding of the nature of human well-being. One results in what is referred to as the theory of subjective well-being (SWB; Diener, 1984). The other results from the theory of psychological well-being (PWB; Ryff, 1989). This chapter is directed at merging these two theories. To show why the unification is necessary, I will first outline the basis for the two theories and then describe how the two can and should be united. 2.1.1

Hedonic Well-being

Equating happiness with hedonic pleasure has a lengthy history that dates back to antiquity. Beginning with Epicurus, philosophers such as Erasmus, More, Hume, Hartley and Bentham believed that the goal of life is to experience the maximum amount of pleasure, and that happiness is the totality of one’s hedonic moments. Psychologists who have adopted the hedonic view have tended to focus on a broad conception of hedonism that includes preferences and judgments about the good/bad elements of life (Kahneman et al., 1999). Hedonic well-being is thus a scientific description of human happiness. There is a problem in describing human well-being in this way, however. Happiness is a singular word. But the

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accumulated evidence indicates that there is more than one kind of quality that can be said to be characteristic of human happiness. Diener (Diener, 1984; Diener et al., 1999) recognized this in his tripartite account of subjective well-being (positive affect negative affect and life satisfaction). Thus, the problem is that use of the singular word ‘happiness’ fosters belief that different positive human states are all forms of one thing, happiness, but this does not seem to be the case. It is thus better to use the plural of happiness and describe SWB as a theory of several forms of happiness. Better yet, the theory can be described simply as hedonic well-being. SWB theory is largely descriptive – an account of what are the adaptive characteristics that distinguish the human capacity for generating and coping with emotional reactions to life events. But the theory is also a description of variables with which these adaptive characteristics correlate, an account of how and why such relationships come about. It is thus also explanatory. Researchers have identified two facets of SWB: a cognitive judgment of life satisfaction and an emotional aspect consisting of independent positive and negative affect components. A person’s evaluation of their life may thus be in the form of cognitions and affect. Individuals are said to have high SWB if they experience high life satisfaction and frequent pleasant emotions such as joy and affection, and only infrequently experience unpleasant emotions such as sadness and anger. In contrast, individuals are said to have low SWB if they are dissatisfied with life, experience little joy and affection, and frequently feel negative emotions such as anger or anxiety (see ibid. for a review). 2.1.2

Eudaimonic Well-being

Despite the prevalence of the hedonic view, many philosophers have denigrated happiness per se as a principal standard of well-being. Aristotle, for example, posited that true happiness is found in the expression of virtue – that is, in doing what is worth doing. Eudaimonism is an ethical theory that refers to well-being as distinct from happiness. Eudaimonic theories maintain that not all desires would yield well-being when achieved. That is, even though they are pleasure producing, some outcomes are not ‘good’ for people and would not promote wellness. Waterman (1993) argued that whereas happiness is hedonically defined, the eudaimonic conception of well-being calls upon people to live in accordance with their ‘daimon’ or true self. He suggested that eudaimonic well-being occurs when people’s life activities are most congruent with deeply held values. Thus, from the eudaimonic perspective, happiness cannot be equated with human well-being. Embracing the concept of eudaimonia or self-realization as a central

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definitional aspect of well-being, Ryff and her colleagues (Keyes et al., 2002; Ryff, 1995; Ryff and Singer, 1998) have explored the question of eudaimonic well-being in the context of developing a lifespan theory of optimal experience. Echoing Waterman’s concerns, Ryff argues for wellbeing not simply as the attaining of pleasure, but as ‘the striving for perfection that represents the realization of one’s true potential’ (Ryff, 1995, p. 100). Ryff and Keyes (1995) presented a multidimensional approach to the measurement of psychological well-being (PWB) – as distinct from SWB – that taps six distinct aspects of human actualization: autonomy, personal growth, self-acceptance, life purpose, mastery and positive social connectedness. The extant evidence indicates that although measurement of SWB and PWB is not error-free, considerable progress has been made in identifying and measuring the separate elements of SWB and PWB. Reliable measures of these elements have been developed – the Positive and Negative Affect Schedule (PANAS; Watson et al., 1988), the Satisfaction With Life Scale (SWLS; Diener et al., 1985) and the Psychological Well-Being Scales (Ryff, 1989). Different forms of evidence have been put forth to indicate the validity of these elements. Evidence of discriminant validity of SWB elements has been supported with multi-trait, multi-method analyses (Lucas et al., 1996). Evidence of convergent validity of PWB elements has been indicated with common factor analyses (Ryff and Keyes, 1995). And evidence for the convergent and discriminant validity of all nine SWB and PWB elements has been supported with confirmatory factor analyses (Keyes et al., 2002). Thus, it is clear that the phenomenon of human wellbeing is multidimensional.

2.2

METHODOLOGICAL INNOVATIONS IN WELLBEING RESEARCH

Although the extant evidence has provided a basis for understanding the phenomena of well-being, other basic information is necessary to establish the nature of the phenomena. That is, individuals are believed to exhibit coherent patterns of experience that cannot be fully described or explained merely by locating individuals within a fixed system of trait dimensions (Allport, 1961). Thus, although nomothetic (between-person) analyses have yielded converging evidence for the construct validity of measures of SWB and PWB, very little attention has been given to investigating idiographic (within-person) relations among these elements. Perhaps nowhere more than in well-being research is the importance of repeated measurement and analysis so essential. Studies that include only

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one occasion of measurement provide a good example of ambiguities that arise when an assumption of stability is made. These ambiguities have been described in detail by Nesselroade (Nesselroade, 1984). When participants are measured on only one occasion, the inter-individual variability in the measurements can reflect three different sources: (1) stable differences among people (traits), (2) intra-individual variability (states), and (3) temporal measurement error. These three possible sources of variation are inextricably confounded when data are obtained on only one occasion, and it is impossible to separate them. Because phenomena may also vary reliably and lawfully within individuals, conclusions based on nomothetic research are premature without idiographic information. With few exceptions (for example, Zevon and Tellegen, 1982), however, construct validation of well-being measures has been based largely on nomothetic, rather than idiographic research. Moreover, virtually all of the within-person well-being evidence to date has centered on distinguishing the occurrence of hedonic emotional states. Little is known about whether the separate elements of SWB and PWB can be reliably and independently observed within individuals studied across time. To my knowledge, no study has provided evidence indicating that the reliability and independence of measurements that have been indicated in between-person analyses of SWB and PWB (Keyes et al., 2002) also obtains for within-person observations of these phenomena. Evidence of this possibility is needed. The fact that well-being has been observed to be a relatively stable and trait-like personality characteristic in interindividual differences research (Headey et al., 1993), raises the question of how SWB and PWB is maintained over time (for a discussion, see Ong et al., 2006). Because the process of change represents a main, central issue for the scientific study of well-being, research designs are needed that can capture ongoing processes of growth and adaptation. In this section I highlight the utility of longitudinal panel and intensive bursts designs. Arguments are presented that bear on the value of these designs as underutilized approaches that appear particularly appropriate to the investigation of intra-individual change and variability in SWB and PWB. Throughout, I argue that the strength of the process approach is an essential shift away from cross-sectional, single variable explanations toward person-centered accounts of positive health. 2.2.1

Longitudinal Panel Designs

Many of the most interesting research questions addressed in well-being research relate to how individuals change over time and what factors

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influence the development of adaptive change. Longitudinal panel designs are particularly well suited for evaluating models of long-term change or development. In the typical longitudinal panel design (1) data are collected at two or more points in time, (2) the same sample of people is interviewed at distinct points in time, and (3) data from the respondents are compared across these time points in order to monitor patterns of change. Although longitudinal panel designs vary with respect to the composition of the sample, the number of follow-up assessments and the intervals between assessments, such designs have two defining characteristics. First, the same research participants, who constitute the panel, are measured for two or more points in time (the measurement periods or waves). Second, at least one variable is measured for two or more waves. This is the longitudinal aspect of the data, which allows the measurement of qualitative or quantitative change within individuals from one wave to the next. In contrast to the longitudinal panel design, cross-sectional designs involve the assessment of research participants at only one measurement point (for a review, see Raudenbush, 2000). 2.2.2

Intensive Bursts Designs

There are times when the investigator is interested in closely observing change while it is occurring. In comparison with longitudinal panel designs, intensive bursts designs allow researchers to observe processes of change within a short but rapidly changing window of time. The use of electronic diaries (for example, palm pilots) allows for the study of the determinants and consequences of changes in well-being within people’s everyday lives. The short time intervals between events and self-reports improves accuracy and reduces bias. In addition to these improvements in measurement precision, repeated assessments of the same person over time solve a serious problem in inference that plagues research in this area. Variables that predict differences between people on an outcome like happiness may have no effect or even the opposite effect on the same outcome when measured as a change within the person observed over time (Tennen and Affleck, 1996). Only careful studies that evaluate changes over time in both the independent and dependent variable can safely make such assertions. Finally, electronic diaries have methodological advantages that are connected to the use of intensive bursts designs. First, electronic diaries allow individuals to report their behavior and experiences over the range of situational circumstances experienced in everyday life. Second, they allow for statistical modeling of behavior over time. Third, and most important, such procedures can test, rather than assume, the validity of the nomothetic approach.

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In addition to designing studies of change, one critical aspect of testing theories of change is fitting models of change to empirical data. Below I describe analytic possibilities that are available for longitudinal panel designs and for intensive bursts designs. I focus my comments on two general data analysis strategies, namely those associated with growth curve modeling and dynamic systems analysis, respectively. For a more thorough discussion of other statistical approaches for modeling change, the interested reader is referred to Collins and Horn (1991), Collins and Sayer (2000), Kenny and Zautra (2001), McArdle and Hamagami (2001) and Raudenbush (2001). 2.2.3

Growth Curve Modeling

One of the major goals of positive psychology is to determine factors that influence normal and optimal development. These factors may be fixed at a particular level (for example, gender, ethnicity) or variable (for example, physical health, emotions). Traditional statistical methods such as repeated measures analysis of variance cannot take into account the time-varying nature of covariates. The most commonly used approach to modeling change in continuous variables that allow for time-varying covariates is growth curve models. Growth curve models, such as hierarchical linear models (Raudenbush, 2000), fit growth trajectories for individuals and relate characteristics of these individual growth trajectories (for example, slope) to covariates. Because these models typically involve relatively few occasions of measurements, longitudinal panel designs are generally the temporal design of choice when fitting growth curve models. Growth curve modeling is an appropriate technique for studying individual change because repeated measures can be considered as nested within individuals and can be represented as a two-level hierarchical model. At the within-person level, each individual’s development is modeled as a unique growth trajectory. At the between-person level, the growth parameters of these trajectories become the outcome variables, which are then modeled as a function of person-level characteristics. For excellent overviews of growth curve and hierarchical linear models for longitudinal panel studies, the reader is referred to Raudenbush (2000) and McArdle and Nesselroade (2003). 2.2.4

Dynamic Systems Analysis

A recent implementation of intensive bursts designs is dynamic systems analysis. Fundamentally, a dynamical systems approach offers a way to formalize concepts of self-regulation. The focus is on modeling or

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representing the relationships between the current state of a variable or an ensemble of variables and the subsequent state of such variables (Boker and Nesselroade, 2002). One key advantage of the dynamic systems approach over other approaches to modeling dynamic processes is the capacity to represent ‘shocks’ or other inputs from outside the individual. For example, consider a model of self-regulation that reflects a ‘pendulum with friction’, which is hypothesized to best exemplify the intra-individual disregulation that may result from exposure to daily stress. This model is referred to as a damped linear oscillator. The equation for the damped linear oscillator can be expressed as a linear regression formula in which the acceleration of the pendulum is the outcome variable and the position and velocity of the pendulum are the predictor variables (Boker, 2001). From a developmental perspective, velocity may refer to the linear change in the system (for example, change in mood), and acceleration may pertain to the curvature (for example, the speed with which the mood change occurs). Differential equation models express effects within a system in terms of their derivatives (that is, the instantaneous rates of change of the variables), as well as in terms of the values of the variables themselves. For example, a differential equation model of emotion regulation following stress might relate daily affect to its slope, or first derivative (that is, how rapidly an individual’s mood was changing). A more complete model might include effects related to its curvature, or second derivative (that is, how rapidly mood was accelerating and decelerating in its change). These three parameters, initial position (emotion/affect), velocity (change) and acceleration (speed of change) represent a dynamical system in which the relationships between them define a central tendency of a family of trajectories that any one individual might have (Boker and Nesselroade, 2002). The regression coefficients from this structural equation model, in turn, define order parameters (for example, frequency and decay rate) of the system that best represents the interrelations between variability in affect and stress over time. The dynamic systems approach is both efficient and powerful, since it can identify intra-individual fluctuations in dynamics using relatively sparse data.

2.3

SUMMARY AND CONCLUSIONS

I have strived to demonstrate in this chapter that scientific understanding has moved away from the idea that human well-being can be well represented by a single dimension. Evidence accumulated over the course of this century has made it clear that the phenomenon of human well-being is multidimensional. Therein lies a problem in identifying particularly happy individuals; therein lies a problem of determining where to look

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for particularly happy individuals; therein lies a difficulty of examining a hypothesis stipulating that, on average, happy people will display more wisdom and character than unhappy people. Jahoda (1958) brought attention to this problem 50 years ago and it still does not have a ready solution. The use of eudaimonic indicators solves one problem but introduces another: in what sense is one better off with a higher ‘purpose in life’, to take one example, if unhappiness accompanies it? Researchers, thus, should strive to assess both hedonic and eudaimonic indicators of wellbeing to obtain a more complete understanding of positive human health. I have also suggested that one major limitation of current theorizing in positive psychology is inherent in the very properties of extant measurement tools. That is, most theories of well-being (SWB and PWB) are described in terms of Cartesian coordinates or factors. These factors may be rotated into an infinity of different positions, each equally adequate for describing the relationships among dimensions of well-being, but each calling for different concepts and different language for describing human well-being. A metatheory of simple structure has guided the rotation that has been accepted as the basis structure of SWB and PWB theory. This metatheory requires that manifest dimensions of well-being relate to a finite number of factors. This is a reasonable requirement for studies designed to indicate it – and many studies have been so designed – but it is not an indication of how well-being must be organized to account for relationships that are observed within and across individuals. A fundamental limitation of any theory built on a rectilinear system of factors is that it is not of a form that well describes natural phenomena: it is thus unlikely to be fully adequate. Rather, it is a system of a kind that can accurately describe rectangular structures built by humans – the angles of city streets or rooms of buildings – but not the rounded and irregular structures of nature. The phenomena of nature are not usually well described by the linear equations of a Cartesian coordinate system. A system of factors is not a system for representing rounded structures such as we see in the configurations of plants and animals or of the human brain. Nor is it a set of structural formulas such as those for the hydrocarbons, the chief constituents of living things. The equations that describe the outer structure and convolutions of brains must be parabolas, exponentials, hyperboles and the like. It is likely that the equations that best describe the inner organizations and workings of human well-being are of the same forms, not those that describe city blocks and buildings. Finally, I have underscored the importance of taking a process approach to understanding the complexity of positive human health and wellbeing. Extant theories of SWB and PWB provide few details about how well-being develops or about how positive psychological states interact

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and work together to produce optimal human functioning. These theories, thus, do little to indicate the dynamics of human adaptation. The kind of system that ultimately will best describe such adaptation and its development, I submit, will be functional and will map on to the human brain. To represent such adaptation and development mathematically, it might be more nearly of the form of a spiral of Archimedes, out of which evolves a repetitive building on what is known (induction), which leads to deductions that generate empirical studies and more induction, which leads to further deductions, which spawn further induction and so on. In the long run, knowing that science is a never-ending search for better explanations and that no theory of reality is final, we can be confident that SWB and PWB theory will be replaced by a better theory.

NOTE * Preparation of this chapter was supported, in part, by a grant from the National Institute on Aging (R01 AG00156).

REFERENCES Allport, G.W. (1961), Pattern and Growth in Personality, Oxford: Holt, Reinhart and Winston. Boker, S.M. (2001), ‘Differential models and differential structural equation modeling of intraindividual variability’ in L.M. Collins and A.G. Sayer (eds), New Methods for the Analysis of Change, Washington, DC: American Psychological Association, pp. 5–27. Boker, S.M. and J.R. Nesselroade (2002), ‘A method for modeling the intrinsic dynamics of intraindividual variability: Recovering the parameters of simulated oscillators in multi-wave panel data’, Multivariate Behavioral Research, 37, 127–60. Collins, L.M. and J.L. Horn (eds) (1991), Best Methods for the Analysis of Change: Recent Advances, Unanswered Questions, Future Directions, Washington, DC: American Psychological Association. Collins, L.M. and A.G. Sayer (2000), ‘Modeling growth and change processes: design, measurement, and analysis for research in social psychology’, in Charles M. Judd and Harry T. Reis (eds), Handbook of Research Methods in Social and Personality Psychology, New York: Cambridge University Press, pp. 478–95. Diener, E. (1984), ‘Subjective well-being’, Psychological Bulletin, 95, 542–75. Diener, E., R.A. Emmons, R.J. Larsen and S. Griffin (1985), ‘The Satisfaction With Life Scale’, Journal of Personality Assessment, 49, 71–5. Diener, E., E.M. Suh, R.E. Lucas and H.L. Smith (1999), ‘Subjective well-being: three decades of progress’, Psychological Bulletin, 125, 276–302. Headey, B.W., J. Kelley and A.J. Wearing (1993). ‘Dimensions of mental health: life satisfaction, positive affect, anxiety and depression’, Social Indicators Research, 29, 63–82.

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Jahoda, M. (1958), Current Concepts in Positive Mental Health, New York: Basic Books. Kahneman, D., E. Diener and N. Schwarz (eds.) (1999), Well-being: The Foundations of Hedonic Psychology, New York: Russell Sage Foundation. Kenny, D.A. and A. Zautra (2001), ‘Trait-state models for longitudinal data’, in L.M. Collins and A.G. Sayer (eds.), New Methods for the Analysis of Change, Washington, DC: American Psychological Association, pp. 243–63. Keyes, C.L., D. Shmotkin and C.D. Ryff (2002), ‘Optimizing well-being: the empirical encounter of two traditions’, Journal of Personality and Social Psychology, 82, 1007–22. Lucas, R.E., E. Diener and E. Suh (1996), ‘Discriminant validity of well-being measures’, Journal of Personality and Social Psychology, 71, 616–28. McArdle, J.J., and F. Hamagami (2001), ‘Latent difference score structural models for linear dynamic analyses with incomplete longitudinal data’, in L.M. Collins and A.G. Sayer (eds.), New Methods for the Analysis of Change, Washington, DC: American Psychological Association, pp. 139–75. McArdle, J.J. and J.R. Nesselroade (2003), ‘Growth curve analysis in contemporary psychological research’, in Wayne F. Velicer and John A. Schinka (eds), Handbook of Psychology: Research Methods in Psychology, Vol. 2, New York: John Wiley & Sons, Inc., pp.447–80. Nesselroade, J.R. (1984), ‘Concepts of intraindividual variability and change: impressions of Cattell’s influence on lifespan developmental psychology’, Multivariate Behavioral Research, 19, 269–86. Ong, A.D., J.L. Horn and D.A. Walsh (2006), ‘Stepping into the light: modeling the dynamics of hedonic and eudaimonic well-being’, in A.D. Ong and M. van Dulmen (eds), Oxford Handbook of Methods in Positive Psychology, New York: Oxford University Press, pp. 12–28. Raudenbush, S.W. (2000), ‘Comparing personal trajectories and drawing causal inferences from longitudinal data’, Annual Review of Psychology, 52, 501–25. Raudenbush, S.W. (2001), ‘Toward a coherent framework for comparing trajectories of individual change’, in A.G. Sayer and L.M. Collins (eds), New Methods for the Analysis of Change, Washington, DC: American Psychological Association, pp. 33–64. Ryff, C.D. (1989), ‘Happiness is everything, or is it? Explorations on the meaning of psychological well-being’, Journal of Personality and Social Psychology, 57, 1069–81. Ryff, C.D. (1995), ‘Psychological well-being in adult life’, Current Directions in Psychological Science, 4, 99–104. Ryff, C.D. and C.L.M. Keyes (1995), ‘The structure of psychological well-being revisited’, Journal of Personality and Social Psychology, 69, 719–27. Ryff, C.D. and B. Singer (1998), ‘Human health: new directions for the next millennium’, Psychological Inquiry, 9, 69–85. Tennen, H. and G. Affleck (1996), ‘Daily processes in coping with chronic pain: methods and analytic strategies’, in Norman S. Endler and Moshe Zeidner (eds), Handbook of Coping: Theory, Research, Applications, Oxford: John Wiley & Sons, pp.151–77. Waterman, A.S. (1993), ‘Two conceptions of happiness: contrasts of personal expressiveness (eudaimonia) and hedonic enjoyment’, Journal of Personality and Social Psychology, 64, 678–91.

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Watson, D., L.A. Clark and A. Tellegen (1988), ‘Development and validation of brief measures of positive and negative affect: the PANAS scales’, Journal of Personality and Social Psychology, 54, 1063–70. Zevon, M.A. and A. Tellegen (1982), ‘The structure of mood change: an idiographic/nomothetic analysis’, Journal of Personality and Social Psychology, 43, 111–22.

3.

How do we assess how happy we are? Tenets, implications and tenability of three theories Ruut Veenhoven1

3.1

THE PROBLEM

Happiness is highly valued in present day society. Not only do people aim at happiness in their own life but there is also growing support for the idea that we care for the happiness of other people and that governments should aim at creating greater happiness for a greater number of citizens (Bentham, 1789). This classic philosophy is not only more accepted these days, but also more practicable, now that scientific research provides more view on the conditions for happiness (Veenhoven, 2004). In that context, happiness is commonly understood as how much one likes the life one lives, or more formally, the degree to which one evaluates one’s life as a whole positively. A central element in this definition is subjective ‘evaluation’ or ‘liking’ of life, also referred to as ‘satisfaction’ with life. These words refer to a mental state but leave some ambiguity about the precise nature of that state. That question is differently answered in three theories linked to different theories about how we evaluate life. Set-point theory sees the evaluation as a stable attitude towards life and focuses more on the mental processes that maintain this attitude than on the processes that have brought it about. Comparison theory sees evaluation rather as a continuous judgment process involving the comparison of perceptions of life-as-it-is with notions of how-life-should-be. Affect theory sees happiness also as a continuous mental process, but now as an appraisal of how well one feels usually. These different descriptive theories of how we assess how happy we are have great implications for prescriptive theories of happiness. Set-point theory, and to a lesser extend also comparison theory, implies that there is little value in happiness and that there is also little chance of furthering happiness enduringly and this goes against the utilitarian tenet that we should aim at greater happiness for a greater number. 45

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This begs the question whether these theories adequately reflect reality or not. Do they apply at all and, if so, do they apply equally well or do some apply more than others? Over the last 15 years I have addressed these questions in several publications (Veenhoven, 1991, 1994, 1995, 1997). In this chapter I develop the argumentation further, linking up with an evolutional perspective and taking new empirical findings into consideration. I will also reflect on Cummins’s (Cummins et al. 2002) recent ‘homeostatic’ theory of happiness. Below I will start with a closer look at the concept of happiness and next review each of the above-mentioned theories about how we assess how happy we are. Each of these theories will be discussed in the following way. First, I describe the main tenets and variations. I then discuss in more detail what moral implications these theories have. Next, I evaluate each of these views by considering their theoretical plausibility and the empirical support. I start with a precise definition of happiness.

3.2

CONCEPT OF HAPPINESS

The word happiness is used in different meanings that are often mixed up. To avoid such confusion, I will review the main connotations and select one of these, which I analyse in more detail. 3.2.1

Meanings of the Word

When used in a broad sense, the word happiness is synonymous with ‘quality of life’ or ‘well-being’. In this meaning it denotes that life is good, but does not specify what is good about life. The word is also used in more specific ways, and these can be clarified with the help of the classification of qualities of life presented in Table 3.1. Four qualities of life This classification of meanings depends on two distinctions. Vertically there is a difference between chances for a good life and actual outcomes of life. Horizontally there is a distinction between ‘external’ and ‘internal’ qualities. Together, these distinctions mark four qualities of life, all of which have been denoted by the word ‘happiness’. Livability of the environment The left top quadrant denotes the meaning of good living conditions. Often the terms ‘quality of life’ and ‘well-being’ are used in this particular meaning, especially in the writings of ecologists and sociologists. Economists sometimes use the term ‘welfare’ for this

How do we assess how happy we are?

Table 3.1

Life-chances Life-results Source:

47

Four qualities of life Outer qualities

Inner qualities

Livability of environment Utility of life

Life-ability of the person Satisfaction

Veenhoven (2000a).

meaning. ‘Livability’ is a better word, because it refers explicitly to a characteristic of the environment. Politicians and social reformers typically stress this quality of life and sometimes refer to it as happiness. I rather see it as a condition for happiness and not happiness as such. One can live in excellent circumstances but still be unhappy, because of an inability to reap the chances. Life-ability of the person The right top quadrant denotes inner lifechances. That is: how well we are equipped to cope with the problems of life. This aspect of the good life is also known by different names. Doctors and psychologists especially also use the terms ‘quality of life’ and ‘wellbeing’ to denote this specific meaning. There are more names however. In biology the phenomenon is referred to as ‘adaptive potential’. On other occasions it is denoted by the medical term ‘health’, in the medium variant of the word.2 Sen (1992) calls this quality of life variant ‘capability’. I prefer the simple term ‘life-ability’, which contrasts elegantly with ‘livability’. This quality of life is central in the thinking of therapists and educators. I also see this as a prerequisite for happiness and not as happiness itself. Even a perfect person will be unhappy when living in Hell. Utility of life The left bottom quadrant represents the notion that a good life must be good for something more than itself. This presumes some higher value, such as ecological preservation or cultural development. Moral advisors emphasize this quality of life. This usefulness of life has also been denoted with the word happiness, but again I do not follow that use of words. In my language one can lead a useful life but still be unhappy. Satisfaction with life Finally, the bottom right quadrant represents the inner outcomes of life. That is the quality in the eye of the beholder. As we deal with conscious humans, this quality boils down to subjective appreciation of life. This is commonly referred to by terms such as ‘subjective well-being’, ‘life-satisfaction’ and also ‘happiness’. I follow this latter use of the word.

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Table 3.2

Happiness, economics and politics

Four kinds of satisfaction

Part of life Life as a whole

Passing

Enduring

Pleasure Top-experience

Part-satisfaction Life-satisfaction

Four kinds of satisfaction This brings us to the question of what ‘satisfaction’ is precisely. This is also a word with multiple meanings and again we can elucidate these meaning using a simple scheme. The scheme in Table 3.2 is based on two distinctions; vertically between satisfaction with ‘parts’ of life versus satisfaction with life ‘as a whole’, and horizontally between ‘passing’ satisfaction and ‘enduring’ satisfaction. These two bi-partitions yield again a four-fold taxonomy. Pleasures Passing satisfaction with a part of life is called ‘pleasure’. Pleasures can be sensoric, such as a glass of good wine, or mental, such as the reading of this text. The idea that we should maximize such satisfactions is called ‘hedonism’. The term happiness is sometimes used in this sense and then denotes a particular pleasant experience. I do not use the term happiness for this matter. Part-satisfactions Enduring satisfaction with a part of life is referred to as ‘part-satisfaction’. Such satisfactions can concern a domain of life, such as working life, and aspects of life, such as its variety. Sometimes the word happiness is used for such part-satisfactions, in particular for satisfaction with one’s career. I do not use the term happiness in this meaning. Peak-experience Passing satisfaction can be about life as a whole, in particular when the experience is intense, pervasive and ‘oceanic’. This ecstatic kind of satisfaction is usually referred to as ‘peak-experience’ or ‘bliss’. When poets write about happiness they usually describe an experience of this kind. Likewise religious writings use the word happiness often in the sense of a mystical ecstasis. Another word for this type of satisfaction is ‘Enlightenment’. I do not use the term happiness in this sense. Life-satisfaction Enduring satisfaction with one’s life as a whole is called ‘life-satisfaction’ and also commonly referred to as ‘happiness’ and as ‘subjective well-being’. I do use the word happiness in this meaning, and will use it interchangeably with ‘life-satisfaction’.

How do we assess how happy we are?

3.2.2

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Definitions of Happiness as Life-satisfaction

This brings us to the question of what ‘life-satisfaction’ is precisely. A review of the various definitions reveals that this concept is often linked to mental processes supposed to be involved, definitions of happiness reflecting theories of happiness. Affective definitions Several definitions depict happiness as an affective phenomenon. For instance, Wessman and Ricks (1966, pp. 240–1) wrote: ‘Happiness appears as an overall evaluation of the quality of the individual’s own experience in the conduct of his vital affairs. As such, happiness represents a conception abstracted from the flux of affective life, indicating a decided balance or positive affectivity over long periods of time.’ In a similar vein Fordyce (1972, p. 227) states ‘Happiness is a particular emotion. It is an overall evaluation made by the individual in accounting all his pleasant and unpleasant experiences in the recent past.’ These definitions are close to Jeremy Bentham’s (1789) famous definition of happiness as ‘the sum of pleasures and pains’, which also involves the notion of an ‘affect balance’. A contemporary variation on this theme is proposed by Daniel Kahneman (2000) in the notion of ‘objective happiness’, which is the ‘raw’ affective experience that underlies the overall evaluation of life.3 Cognitive definitions Happiness is also defined as a cognitive phenomenon, that is, as the result of a deliberate evaluation process. In that vein McDowel and Newell (1987, p. 204) describe life-satisfaction as a ‘Personal assessment of one’s condition compared to an external reference standard or to one’s aspirations’. Likewise, Shin and Johnson (1978, p. 478) defined life-satisfaction as a ‘global assessment of a person’s quality of life according to his chosen criteria’. Some of the definitions in this line stress the active achievement of life goals (for example, Annas, 2004), while others rather stress the absence of unfulfilled aspirations, for example, Schmitz (1930, p. 234) who depicted happiness as a ‘state of being without desires’. In all conceptualizations happiness is deemed to be higher, the smaller the distance between standard and reality. Attitudinal definitions Happiness has also been depicted as a happy disposition and as a positive attitude towards life. In this line Lieberman (1970, p. 40) wrote ‘at some point in life. Before even the age of 18, an individual becomes geared to a certain stable level of satisfaction, which – within a rather broad range of

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environmental circumstances – he maintains throughout life’. Some of the definitions of this kind stress the consistency in affective response, while others rather see it as a belief system. Mixed definitions Several definitions combine one or more of the above elements. For instance, Diener defines Subjective Well-Being (SWB) as being satisfied with life (attitude), while feeling good (affect). In his own words: ‘Thus a person is said to have high SWB if she or he experiences life satisfaction and frequent joy, and only infrequently experiences unpleasant emotions such as sadness or anger. Contrariwise, a person is said to have low SWB if she or he is dissatisfied with life, experiences little joy and affection and frequently feels negative emotions such as anger or anxiety’ (Diener et al., 1997, p. 25). All three elements are involved in Chekola’s (1974, p. 2002) definition of happiness as ‘realization of a life-plan and the absence of seriously felt dissatisfaction and an attitude of being displeased with or disliking one’s life’. Likewise Sumner (1997, pp. 145–6) describes ‘being happy’ as ‘having a certain kind of positive attitude toward your life, which in the fullest form has both a cognitive and an affective component. The cognitive aspect of happiness consists in a positive evaluation of your life, a judgment that at least on balance; it measures up favorably against your standard or expectations . . . The affective side of happiness consists in what we commonly call a sense of well-being, finding your life enriching or rewarding or feeling satisfied or fulfilled by it’. 3.2.3

My Conceptualization of ‘Overall’ Happiness and ‘Components’

In my own conceptualization of happiness similar distinctions are used, but in a more systematic way. I distinguish between ‘overall’ happiness and ‘components’ of happiness and assume that the latter function as ‘sub-totals’ in the overall evaluation of life. Overall happiness Overall happiness is defined as ‘the degree to which an individual judges the overall quality of his life as a whole favorably’ (Veenhoven, 1984, pp. 22–4). Thus defined, happiness appears as an attitude towards one’s own life that has some stability of its own and that involves related feelings and beliefs. These feelings and beliefs are seen as ‘components’ of happiness. Components of happiness When evaluating their lives, people can use two more or less distinct sources of information: their affects and their thoughts. We can ‘observe’

How do we assess how happy we are? Global assessment

51

OVERALL HAPPINESS Satisfaction with one’s life as a whole

Sub-totals

Hedonic level of affect Balance of pleasant and unpleasant affect

Contentment Perceived realization of wants

Information basis

Affective experience

Cognitive comparison

Figure 3.1

Happiness and its components

that we feel fine most of the time, and we can also ‘judge’ that life seems to meet our (conscious) demands. These appraisals do not necessarily coincide. We may feel fine generally, but nevertheless be aware that we failed to realize our aspirations. Or we may have surpassed our aspirations, but nevertheless feel miserable. The relative weight in the overall evaluation is variable in principle; it is an empirical question to what extent one component dominates the other (Figure 3.1). Hedonic level of affect We experience different kinds of affects: feelings, emotions and moods and these experiences have different dimensions, such as active – inactive and pleasant – unpleasant. This latter dimension is called ‘hedonic tone’. When we assess how well we feel we typically estimate the pleasantness in feelings, in emotions, as well as in moods. I call this ‘hedonic level of affect’ and this concept fits the above-mentioned ‘affective’ definitions of happiness. A person’s average hedonic level of affect can be assessed over different periods of time: an hour, a week, a year as well as over a lifetime. The focus here is on ‘current’ hedonic level. This concept does not presume subjective awareness of that average level. One can feel good most of the time, without being fully aware of that. Therefore this concept can be applied to beings who cannot reflect on their own life, such as animals and little children. Contentment Unlike animals and little children most adults can also evaluate their life with the use of reason and compare life as it is with notions of how one wants life to be. The degree to which individuals perceive their wants to be met is called ‘contentment’ and this concept equals the above-mentioned ‘cognitive’ definitions of happiness.

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This concept presupposes that the individual has developed some conscious wants and has formed an idea about their realization. The factual correctness of this idea is not at stake. This conception of happiness as a ‘trinity’ helps to place different theories about how we assess how happy we are.

3.3

SET-POINT THEORIES OF HAPPINESS

Set-point theories of happiness hold that we are programmed to experience a certain degree of happiness, largely irrespective of how well we are doing. In this view happiness just happens to us. 3.3.1

Variants

A classic religious version of this theory is Devine predestination, God having decided that some people will be happy and others not, just as he foresees who will enter Heaven and who will be dammed to Hell. Secular variants assume that happiness is geared by mental inclinations that are also beyond a person’s control. Genetic disposition This variant holds that happiness is largely determined by an innate disposition to enjoy life or not. A spokesman of this view is Lykken (1999), who claims to have shown that about 50 percent is heritable. There is uncertainty about the nature of this disposition, some see it in the reward system of the brain and link it to positive or negative ‘affectivity’ while others hold secondary effects responsible, such as inborn physical health. In the latter case happiness is essentially a variable state, though it tends to remain at the same level because of constancy in its determinants. Below I will not discuss this variant of set-point theory. Personality trait Another current view is that happiness depends very much on personality traits, that is, predispositions to react in a certain way. One of these ways is liking things or not and personality traits such as ‘extraversion’ and ‘neuroticism’ are seen to determine our affective reactions to and perceptions of things that happen to us. It is generally assumed that these traits have a genetic component. In this view personality molds the evaluation of life. Personality can also affect happiness through its impact on the course of life-events, and this is

How do we assess how happy we are?

53

central in the dynamic-equilibrium theory of Heady and Wearing (1992). Yet again, I do not consider that a set-point theory, because happiness itself is essentially a variable state in this idea. Cultural view A macro-level variant of this theory is that the view on life is embodied in the national character. In this line Inglehart (1990, p. 30) wrote that cross-national differences in happiness ‘reflect cognitive cultural norms, rather than individual grief and joy’. In an earlier paper I have depicted that view as the ‘Folklore theory of happiness’ (Veenhoven, 1995, p. 35). Homeostatic maintenance While the above set-point theories aim at explaining differences in happiness, there are also theories of this kind that focus at the general level of happiness. These are motivational theories that assume that we tend to maintain a comfortable level of happiness, even in adverse conditions. In that line Cummins et al. (2002) hold that we unconsciously keep happiness between 7 and 8 on a 10-step scale, just as we maintain a body temperature of 32°C. 3.3.2

Implications

These theories imply that there is little chance of creating greater happiness for a greater number, since happiness is a stable trait rather than a variable state and as such not responsive to external conditions. In this view one can at best try to raise that fixed level a bit, be it with genetic engineering or training. The theory also implies that there is little sense in raising happiness, since happiness is unrelated to the wider thriving of the individual. In this view being happy or not is comparable to liking chocolate or not; fine if you do but no real problem if you don’t. 3.3.3

Theoretical Plausibility

It is plausible that differences in stable conditions for happiness create stable differences in level of happiness and conditions for happiness can be external or internal (see Table 3.1). It is also plausible that happiness tends to remain at a similar high level in the favorable and stable conditions of modern society. Yet set-point theory holds that the stability is not in the preconditions, but in the evaluation itself and that is not so plausible.

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Why, then, do we evaluate life at all if we always end up with the same conclusion? In this light it is difficult to see why happiness is so prominent in people’s minds, for example, that they think of it almost every day (Freedman, 1978). One also wonders why evolution has developed the ability to evaluate if the evaluation of life boils down to a fixed response. Set-point theory implies that happiness does not serve any function in human life and that being happy or unhappy is as trivial as having brown or blond hair. It can hardly be reconciled with the fact that happiness is universally pursued and neither with the fact that being happy or not appears to be closely linked to how well we thrive. Taken to the extreme, set-point theory would predict that we are equally happy in Heaven as in Hell and this is hard to believe. 3.3.4

Empirical Support

At first sight there is strong empirical support for the set-point theory, happiness tending to be stable over time. Follow-up of individuals shows little change in happiness from one year to another and if changes occur, these are typically short-lived. Trend analysis of average happiness in nations also shows much stability. Yet, at a closer look, we also see change. Long-term follow-up of individuals reveals considerable mobility along the life-satisfaction ladder in modern society, Ehrhardt et al. (2000) estimated that over a lifetime only 30 percent of the original rank order in happiness will be left. Follow-up studies have also shown that at least some life-events bring about a permanent change in life-satisfaction, for instance, getting married or losing one’s job. Though people tend to adjust to external shocks in their lives, that adjustment is not always complete (Diener et al., 2006). Likewise, average happiness in nations appears not to be immutable, average happiness has risen gradually in most nations over the last 30 years (Veenhoven and Hagerty, 2006) while in some countries an abrupt fall in happiness occurred, for example, in Russia after the ‘Rubel crisis’ in the late 1990s (Veenhoven, 2000b). At first sight there is also empirical support for Cummins’s theory that we tend to maintain a level of satisfaction between 7 and 8. Studies in modern Western nations showed indeed a concentration of responses in these categories, but surveys in other parts of the world show another picture, for example, an average of 3.2 in Tanzania and in the abovementioned case of Russia a dip from 5.1 to 4.1. Another finding that contradicts this theory is the high number score of 9 and 10 in some Western nations, for example, a 20 percent score of 10 in Switzerland.

How do we assess how happy we are?

3.4

55

COGNITIVE THEORIES OF HAPPINESS

Cognitive theories hold that happiness is a product of human thinking and reflect discrepancies between perceptions of life as it is and notions of how life should be. Notions of how life should be are assumed to root in collective beliefs and to vary across cultures. This view on happiness is dominant in philosophy and also pervades the thinking of many social scientists. 3.4.1

Tenets

The basic assumption of this theory is that happiness is based on the comparison with standards, though there is a difference on the nature of these standards and ways of comparison. Another basic assumption is that collective beliefs are involved. Comparison The theory assumes that we have ‘standards’ of a good life and that we constantly weigh the reality of our life against these standards. Standards are presumed to be variable rather than fixed and to follow perceptions of possibilities. In other words, we would tend to judge life by what we think it can realistically be. Different theories stress different standards. In the variant of life-time comparison, the focus is on whether we are doing better or worse than before. In this view a happy youth will not add to happiness in adulthood. The social comparison variant stresses how well we are doing relative to other people, and in particular people like us. In this view happiness is surpassing the Jones’s. Several of these theories are combined in Michalos’s (1985) ‘Multiple Discrepancies Theory’ of happiness, which assumes that we not only compare with what we want and with what others have, but also with what we need and with what we deem fair. Social construction The idea that we compare to standards begs the question of where these standards come from. This is typically seen as an outcome of socialization, involving the adoption of collective notions of the good life, sometimes with minor modifications. These collective notions of the good life are seen as ‘social constructions’ that draw heavily on the wider culture and shared history. In this line some sociologists argue that happiness as such is also a social construction. In this view happiness is a culturally variable concept, comparable to the notion of ‘beauty’.

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Reflected appraisal A sociological variant holds that we not only compare life our self with our own standards, but that we also appraise our life through the eyes of others, in other words, that in assessing how happy we are we estimate how happy other people think we are. If so, this enhances the salience of shared standards of the good life. This theory is summarized in Figure 3.2. 3.4.2

Implications for Happiness Promotion

This theory holds that happiness does not depend on objective conditions of life, but on the standards by which these conditions are judged. As such, it also implies that there is little value in happiness. One reason is that happiness may be bought by a lowering of standards, as advocated in some variants of Buddhism. A second reason is the relativistic argument that all standards of the good life are mere collective illusions, with limited appeal in a particular time and place. Most cognitive theories imply also that there is little chance of creating greater happiness for a greater number, in particular the theories that assume that standards adjust to reality. Some variants of this theory predict that happiness will vary around the neutral level (for example, Unger, 1970), while some variants even predict that most people will be unhappy, for example, theories that stress the social salience of success in advertisements and the news. 3.4.3

Theoretical Plausibility

It is reasonable to assume that we use our thinking in appraising the quality of our life. Yet it is not so reasonable to assume that thinking is the only way to assess how happy we are. If so, little children cannot be happy, because they lack the ability to define standards of the good life and compare with reality. If thinking were the only way of assessing how we are doing one also wonders what our affect system is good for and why affective experience is so pervasive. Is affect then a mere remnant of the past? Still another qualm is that standards of the good may be less clear than assumed. We mostly have some notions in mind, but typically not a clear hierarchy of wants and having a ‘rational life plan’ seems to be more exception than a rule. There is also a problem with the implication that happiness does not depend on real conditions of life but on the intellectual yardsticks by which these are valued. This would mean that one can be perfectly happy

How do we assess how happy we are?

Global assessment

Sub-assessment

Information basis

Underlying process

Substrate

Figure 3.2

57

OVERALL HAPPINESS Satisfaction with one’s life as a whole

Contentment Perceived realization of wants

Cognitive comparison

Standard setting

Culture

Cognitive theory of how happiness is assessed

in Hell, provided that one does not know better or that one is socialized to believe that this is the best place to be. In this view there is no adaptive value in happiness and, in fact, not in thinking either. This problem is mainly in the assumptions of how collective notions of the good life come about. If one assumes that these are unique constructs, following the internal logic of particular belief systems one ends up concluding that happiness is of no consequence, which I deem implausible from an evolutionary point of view. If, on the other hand, one assumes that these notions reflect accumulated experience with the realities of life, the conclusion is rather that living up to these standards is mostly wise and that happiness is therefore an indication of proper living. As we will see below, this view is compatible with the ‘need’ theory of happiness.

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3.4.4

Happiness, economics and politics

Empirical Support

Correlational studies typically show a strong relationship between overall happiness and contentment. The smaller the gap between standard and reality, the higher the level of happiness (for example, Michalos, 1985). This correlation is generally interpreted as proof for the theory that happiness depends on the outcome of a comparison process, but causality could also work otherwise, happiness determining comparison, particularly the estimation of the size of gaps. This so-called ‘top-down’ effect was demonstrated in a follow-up study in Australia by Headey et al. (1991) for satisfaction with one’s standard of living and with one’s job. Correlational studies further show relationships between happiness and perceived achievement of specific goals, such as completing a study or raising a family. Yet this research also shows that success in some goals counts more than success in other goals, and in particular that success in material goals is relatively weakly related to happiness. It seems that achievement of intrinsic goals adds more to happiness than success in extrinsic goals (Kasser and Ryan, 1993) and this contradicts the idea that happiness is geared by socially constructed standards in the first place. There is also empirical support for the assumption that standards adjust over time and that effects of life-events on happiness are therefore shortlived. For instance, follow-up of people who had had a financial windfall showed an uplift of happiness that lasted only one year (Gardner and Oswald, 2001). Yet entering marriage appears to have more lasting effects on happiness, in particular for people who were not too happy when single, and severe physical handicaps, such as spinal cord injury, appear to reduce happiness permanently. For reviews of the data see Veenhoven (1994) and Diener et al. (2006). Another disconfirming finding is that most people tend to be happy most of the time, while life-time comparison theory would predict that the average is about neutral and some variants of social comparison theory imply that the average must be below neutral. A further fact that does not fit the theory is the close relationship between average happiness in nations and objective quality of life. Average happiness differs widely across nations (between 8.2 and 3.2 on scale 0–10) and about 75 percent of these differences can be explained by variation in ‘hard’ societal characteristics, such as economic affluence, freedom and democracy (Veenhoven, 2004). These findings contradict the idea of culturally unique standards and adjustment to the possible. Interestingly, there appears to be neither relationship between average happiness and income-inequality in nations nor a relationship with state welfare effort,

How do we assess how happy we are?

59

while these matters are widely seen as desirable. So, if notions of the good life affect happiness at all, not all affect happiness equally much.

3.5

AFFECTIVE THEORIES OF HAPPINESS

Affect theory holds that happiness is a reflection of how well we feel generally. In this view we do not ‘calculate’ happiness, but rather ‘infer’ it, the typical heuristic being ‘I feel good most of the time, hence I must be happy’ (Schwartz and Strack, 1991). 3.5.1

Tenets

In this line of thought one question is how we take stock of our affective experience. Another question is what makes us feel good or bad and this links up to the wider question about the functions of affect. Frequency of affect It would seem that the overall evaluation of life is geared by the most salient affective experiences and that these are typically intense affects. This view is common in fiction and is more or less implied in life-reviews. Yet research using the Experience Sampling Method shows that it is rather the relative frequency of positive to negative affect that matters (Diener et al., 1991). Mood as informant How do we assess that relative frequency? The cognitive view on affect procession suggests that we compute an affect balance in some way, using estimates of frequency and duration. A competing view is that this occurs automatically and that the balance reflects in mood. In this view mood is an affective meta-signal that, contrary to feelings and emotions, is not linked to specific objects. Emotions denote an affective reaction to something and prepare the organism to a response, while negative mood signals that there may be something wrong and urge to find out what that is. Gratification of needs Why do we feel good or bad at all? Probably because this informs us in how well we are doing. Affects are an integral part of our adaptive repertoire and seem to be linked to the gratification of human needs. ‘Needs’ are vital requirements for survival, such as eating, bonding and exercise. Nature seems to have safeguarded the gratification of these needs with affective signals such as hunger, love and zest. In this view positive mood signals that all needs are sufficiently met at the moment. ‘Needs’ in this

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theory should not be equated with ‘wants’ in the above discussion of cognitive theories. Needs are inborn and universal, while ‘wants’ are acquired and can be variable across cultures. Wants can concur more or less with needs. Motivation to act In this view negative and positive moods function as red and green lights on the human machine, indicating either that there is something wrong or that all systems are functioning properly. If so, this is likely to have behavioral consequences, negative mood urging to cautions and positive mood encouraging going on. This is what Fredrickson’s (2004) ‘broaden and build’ theory is about. This theory is summarized in Figure 3.3. 3.5.2

Implications for Happiness Promotion

In this view happiness is a desirable state, both because it signals good adaptation and because it enhances behavior that apparently works out well. This is at least so if one accepts that it is good that we live up to our nature. In this view it is also possible to create greater happiness for a greater number. If happiness depends in the end on the gratification of human needs, we can advance happiness both by improving the livability of the environment (left top quadrant in Table 3.1 and by enhancing individual life-abilities (right top quadrant in Table 3.1). There are limits to this, but even if the average happiness of 8.2 in present-day Denmark might be the highest possible level, there is still much room for improvement in the rest of the world. 3.5.3

Theoretical Plausibility

It is hard to imagine someone saying to enjoy life when feeling depressed most of the time. Such a person may say that their life is nevertheless ‘meaningful’ but that is not the same as ‘satisfying’; remember the distinction in Table 3.1 between the ‘usefulness’ of a life and satisfaction with life. This theory also makes sense in an evolutionary perspective. It is likely that evolution has developed ways of monitoring needs gratification, in particular in organisms that can choose. It is unlikely that rational thinking is the main way, since this developed late in evolution. It is quite likely that adaptation is guided by affective signals in the first place and that all higher animals can feel more or less well. It is unlikely

How do we assess how happy we are?

Global assessment

Sub-assessment

OVERALL HAPPINESS Satisfaction with one’s life as a whole

Hedonic level of affect Balance of pleasant and unpleasant affect

Information basis

Affective experience

Underlying process

Need gratification

Substrate

Figure 3.3

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Human nature

Affect theory of how happiness is assessed

that humans are an exception to this rule. The ability to think was added to an existing affect system and did not replace that. This can be seen in the structure of the human brain, where the affect system is located in the older parts that we have in common with other animals and where the capability to think is situated in the neo-cortex that is typical for humankind. 3.5.4

Empirical Support

Unlike ‘wants’, ‘needs’ cannot be measured and neither can ‘need gratification’. A direct test of this theory is therefore not possible. Still we can test the implications of this theory. One implication is that people will be unhappy in conditions where basic human needs remain unmet, such in chronic hunger, danger and loneliness. This prediction is supported by the finding that average happiness

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Global assessment

OVERALL HAPPINESS Satisfaction with one’s life as a whole 1

Sub-assessment

Hedonic level of affect Balance of pleasant and unpleasant affect

2

Contentment Perceived realization of wants

Information basis

Affective experience

3

Cognitive comparison

4

Underlying process

Need gratification

Standard setting 5

Substrate

Figure 3.4

Human nature

6

Culture

Causal effects in the evaluation of life

is low in poor countries with failed states. Support can also be seen in the rising happiness in modern nations (Veenhoven, 2005). At first sight the prediction is contradicted by absence of a correlation between individual happiness and income in rich nations, but this may mean that the material needs of even the poor are gratified. Gratification of social needs is less well secured in rich nations and consequently we do see a substantial impact of marriage and friendship on happiness. Another testable implication is that happy people must thrive better biologically. This appears indeed in greater longevity of the happy. Well controlled long-term follow-up studies show sizable effects, comparable to smoking or not (Veenhoven, 2008).

3.6

HOW APPRAISALS RELATE

So far I have depicted these ways of evaluating life as separate appraisals, which each influence the overall evaluation of life in their own way. Yet these mental processes are linked in several ways. Figure 3.4 summarizes some probable interactions.

How do we assess how happy we are?

3.6.1

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Set-points Root in Earlier Appraisals

If understood as a stabilized attitude, set-points must have developed in the past on the basis of experience. This is not necessarily only one’s own experience, since attitudes can also be copied. Still, in the case of this attitude towards one’s own life it is likely that one’s own experiences plays a role and as such it is likely that set-points root in earlier affective and cognitive appraisals. In this view set-points are an echo of the past that are likely to wane in the course of time and then be revised, in particular when major life-change urges to a reappraisal. In this case affective and cognitive appraisals appear on the scene again. 3.6.2

Hedonic Affect Influences Contentment

In this line it seems probably that hedonic level of affect plays a role in the comparison process, in particular in the assessment of the gap between want and reality. When feeling good we will tend to see small gaps and when feeling bad we may attribute that feeling to wide gaps. This affective ‘bias’ is probably stronger at the higher level of aggregation, it may not affect appraisals of success to specific standards too much, such as the appraisal of whether your dissertation met your scientific aspirations, but is likely to influence estimates of success in meeting all standards of the good life. In relation with overall life satisfaction this is known as the ‘top-down’ effect and this is depicted with arrow 1 in Figure 3.4. In this reasoning we could call it the ‘mood’ effect (arrow 2). Affective experience may also gear cognitive appraisal of life at a deeper level. Shared standards of the good life are likely to build on earlier experience of what leads to a satisfying life and in this way connect to human needs (arrow 5). In this view wants will typically be vessels for needs and will ‘false wants’ be an exception rather than the rule. A reversed effect is unlikely; cultural standards of the good life have no influence on innate human needs. Likewise, wider human nature influences wider human culture, or sets at least limits to cultural variation (arrow 6), while human culture does not shape human nature. 3.6.3

Comparison Impinges on Affect

An extreme version of cognitive theory holds that hedonic affect is entirely due to goal attainment; whatever that goal is (for example, Oatley, 1992). This is clearly not true, not only because we can feel good or bad for no apparent reason, but also because not all achievements are equally satisfying (cf. Kasser and Ryan, 1993).

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Still we do react affectively on meeting some standards and this is particularly true for meeting standards of performance. Possibly this is mainly due to the gratification of related needs, such as the needs for self-esteem and self-actualization, but we cannot rule out that the meeting of the standard in itself also generates positive affect. Affective reactions to comparison are particularly likely in the case of meeting standards in the eyes of others. Like other social animals we seem to have an innate need for acceptance by the congeners around us (cf. Maslow’s need for social respect) and one can well imagine why such a need has developed in evolution. If so, we are likely to enjoy meeting the shared standards of performance, even if the performance itself is not gratifying. This is another instance where needs and wants overlap and this effect is denoted with arrows 3 and in Figure 3.4.

3.7

WHY AFFECTIVE INFERENCE DOMINATES

The theories discussed above are not mutually exclusive. In assessing how happy we are we may draw on both affective experience and cognitive evaluation and it is also possible that we tend to stick to an idea of how happy we are once we have made up our mind. Still it seems to me that the reading of affects dominates the evaluation of life. There are four reasons to think so. (1) Affect theory does best as a complete explanation, while the other two theories rather depict an aspect of the appraisal process. (2) Affect theory fits in better to the other theories than reversely. (3) Affect theory is the most plausible in an evolutionary perspective. (4) Affect theory fits better to the available data. 3.7.1

Affect Theory Provides the Most Complete Explanation

There is probably some truth in all three of these theories; they have all intuitive appeal and supportive evidence. That is not to say that they qualify as a major explanation of how we appraise how happy we are, the theories may merely highlight an aspect of the mental process. As we have seen above, set-point theory highlights the tendency to stick to a particular view, unless circumstances urge to a re-evaluation. This is a common heuristic that operates also in other attitudes. I see this as a minor process and not as a main way of appraising satisfaction with life. If taken as the main mechanism, this theory debouches in absurdities, such as that happiness is insensitive to actual weal and woe. In the same vein, cognitive theory can be seen to highlight a part of the appraisal process and in particular the ‘checking’ of intuitive affective

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overall appraisal by conscious judgments of success on specific criteria. Cognitive theory cannot explain very well how one could calculate an overall evaluation, since clear priorities are mostly lacking. Cognitive theory can neither explain very well how standards come about and why there is so much resemblance in standards across cultures. If taken as the only way in which we assess how happy we are, cognitive theory leads into absurd conclusions, such as that we can be happy in Hell. Affective inference is more likely to function as the main manner of assessing satisfaction with life, in particular in combination with the assumption that hedonic level of affect reflects need gratification. It is hard to imagine how one could assess ‘satisfaction’ with life without considering how well one feels most of the time and the assumption that that heuristic dominates does not lead into bizarre consequences. 3.7.2

Affects Influence Set-point and Comparison More Than Reversely

In Section 3.6 I discussed the interrelations between the three theories and noted that affective experience is likely to play a major role in the development of attitudes to one’s life that is in the crystallization of set-points. The reverse effect is less likely, though an established attitude can influence the reading of our affects, it is unlikely to mold affective experience as such. In Section 3.6 I also argued that affective experience is likely to influence the cognitive appraisals of life. I distinguished four levels at which affects influence cognitive appraisal and claimed that only on one of these levels there is a comparable influence of cognition (cf. Figure 3.4). If so, affective experience is the most dominant force. 3.7.3

Affect Theory is Most Plausible in Evolutionary Perspective

Another way of appraising the plausibility of theories is considering how well they fit the wider perspective that humans are a product of evolution and that many human behaviors are typically functional in some way. Above I have considered all three theories in that light, below is a summary. Applies not only to human adults As discussed above, affective theory applies to all human beings, and possibly higher animals, while cognitive theory and set-point theory apply only to thinking beings. That would mean that the assessment of happiness changes profoundly when we grow up and that it changes again when we get demented. This does not seem probable to me. I can imagine that the development of abstract thinking adds something to the process

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of evaluation, but not that the affective information stream is turned off. Neither do I buy the implication that the happiness of children does reflect need gratification and the happiness of adults not. Functional This brings us to the wider point of adaptive significance. As noted above, set-point theory implies that there is no information value in happiness, since happiness is a fixed mind-set and not responsive to objective thriving. To a lesser extend this is also implied in cognitive theory, in which effects of improvement or deterioration are short-lived and where standards of comparison root in collective beliefs that vary across cultures. This boils down to the conclusion that happiness does not matter and that conclusion is absurd. Affective theory sees happiness as a reflection of need gratification and this makes more sense, especially in the context of a functional view on human consciousness and motivation. 3.7.4

Affect Theory Fits the Available Data Best

There is no direct evidence for the dominance of affective inference in the evaluation of life. Though this can be tested to some extent, nobody has done so as yet, at least not to my knowledge. The wider theory that hedonic balance of affect reflects need gratification can hardly be tested at all, since we cannot measure needs very well and particularly not psychological needs. Still there are several pieces of indirect evidence, most of which are already mentioned above. Primacy of affect A point, not yet mentioned above, is that evaluation appears to be an affective process in the first place. In a classic paper Zajonc (1984) has shown that affective appraisal precedes cognitive evaluation. Likewise, Damasio (1994) has shown that injuries in the parts of the brain where affects are processed leave patients unable to make choices, even when their thinking is still intact. This is another indication that cognition has not replaced affect in human evolution and that cognitive appraisals play at best an additional role in the assessment of happiness. Happiness linked to actual thriving Set-point theory and cognitive theory imply that we can evaluate life positively while doing badly from a biological-adaptive point of view. Affect theory rather holds that happiness reflects how well life fits the demands implied in human nature. This latter view is confirmed in two pieces of evidence. People tend to be happier when living in favorable

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conditions rather than in misery and happiness goes together with mental and physical health. Universal conditions for happiness Cognitive theory implies that conditions for happiness can differ wildly across cultures; while affect theory rather predicts that there will be much similarity in conditions for happiness. This latter point is confirmed in two lines of research. First, comparison of average happiness across nations has shown that 75 percent of the differences can be explained with the same societal characteristics. Second, analysis within nations shows striking similarities all over the world, for instance, being married appears to go with greater happiness all over the world. This point is discussed in more detail in Veenhoven (2010).

3.8

CONCLUSION

There are different theories of how we assess how happy we are: (1) the theory that we echo an earlier evaluation and try to maintain it, (2) the theory that we calculate happiness constantly by comparing life as it is with standards of how life should be, and (3) that we infer happiness from ongoing affective experience and that this affective experience reflects need gratification. These three theories are not mutually exclusive but may differ in import. Affective inference seems to dominate the appraisal of life.

NOTES 1. I thank Mark Chekola for his valuable comments. 2. In the ‘core-affect’ variant happiness set-point is an affective phenomenon, be it a matter of non-responsive affect. Likewise, in the ‘outlook’ variant set-point is a cognitive phenomenon and a tendency to see the glass as either half full or half empty. 3. In this view ‘subjective’ happiness results from the cognitive processing of this affective information.

REFERENCES Annas, J. (2004), ‘Happiness as achievement’, Deadalus: Journal of the American Academy of Arts and Science, 133, 44–51 Bentham, J. (1789), Introduction to the Principles of Morals and Legislation, London: Payne. Chekola, M.G. (1974), ‘The concept of happiness’, PhD Dissertation, University of Michigan, Ann Arbor, USA.

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Cummins, B., E Gullone and L.A. Lau (2002), ‘A model of subjective well-being homeostasis: the role of personality’, in E. Gullone and R.A. Cummins (eds) The Universality of Subjective Well-being Indicators, Netherlands: Kluwer, pp. 7–46. Damasio, A. (1994), Descartes Error, New York: Putman. Diener, E., W. Pavot and E Sandwick (1991), ‘Happiness is the frequency, not intensity, of positive versus negative affect’, in F. Strack, M. Argyle and N. Schwarz (eds), Subjective Well-Being, Oxford: Pergamon. Diener, E., E. Suh, and S. Oishi (1997), ‘Recent findings on subjective wellbeing’, Indian Journal of Clinical Psychology, 24, 25–41. Diener, E., R.E. Lucas and C.N. Scollon (2006), ‘Beyond the hedonic treadmill: revising the adaptation theory of wellbeing’, American Psychologist, 61, 305–14. Ehrhardt, J.J., W.E. Saris and R. Veenhoven (2000), ‘Stability of life-satisfaction over time: analysis of change in ranks in a national population’, Journal of Happiness Studies, 1, 177–205 Fordyce, M.W. (1972), ‘Happiness, its daily variation and its relation to values’, PhD Dissertation, US International University, San Diego, CA. Fredrickson, B.L. (2004), ‘The broaden-and-build theory of positive emotions’, Philosophical Transactions, Biological Sciences, 359, 1367–77. Freedman, J.L. (1978), Happy People, New York: Harcourt Brace Jovanovich. Gardner, J. and A. Oswald (2001), ‘Does money buy happiness? A longitudinal study using data on windfalls’, Working Paper, University of Warwick. Headey, B., R. Veenhoven and A. Wearing (1991), ‘Top-down versus bottom-up: theories of subjective well-being’, Social Indicators Research, 24, 81–100. Headey, B. and A. Wearing (1992), Understanding Happiness; A theory of Subjective Well-being, Melbourne, Australia: Longman Cheshire. Inglehart, R. (1990), Culture Shift in Advanced Industrial Society, Princeton: Princeton University Press. Kahneman, D. (1999), ‘Objective happiness’ in D. Kahneman, E. Diener and N. Schwarz (eds), Well-Being: The Foundations of Hedonic Psychology, Russell Sage Foundation, New York, pp. 3–25. Kahneman, D. (2000), ‘Experienced utility and objective happiness: a moment based approach’, in D. Kahneman and A. Tverski (eds), Choices, Values and Frames, New York: Cambridge University Press. Kasser, T. and R.M. Ryan (1993), ‘The dark side of the American dream, correlates of financial success as a central life aspiration’, Journal of Personality and Social Psychology, 65, 410–22 Lieberman, L.R. (1970), ‘Life satisfaction in the young and the old’, Psychological Reports, 27, 75–9. Lykken, D.T. (1999), Happiness: What Studies on Twins Show Us About Nature, Nurture and the Happiness Set-point, New York: Golden Books. McDowell, I. and C. Newell (1987), Measuring Health: A Guide to Rating Scales and Questionnaires, New York: Oxford University Press. Michalos, A.C. (1985), ‘Multiple Discrepancies Theory (MDT)’, Social Indicators Research, 16, 347–413. Oatley, K. (1992), Best Laid Schemes: The Psychology of Emotions, Cambridge: Cambridge University Press. Schmitz, O.A. (1930), ‘Glück und lebenskunst (Happiness and the art of living)’, Psychologische Rundschau, 2, 233–8.

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Schwarz, N. and F. Strack (1991), ‘Evaluating one’s life: a judgment model of subjective well-being’, in F. Strack, M. Argyle and N. Schwarz (eds), Subjective Well-being, Oxford: Pergamon, pp. 27–47. Shin, D. and D.M. Johnson (1978), ‘Avowed happiness as the overall assessment of the quality of life’, Social Indicators Research, 5, 475–92. Sumner, L.W. (1996), Welfare, Happiness and Ethics, New York: Oxford University Press. Unger, H.E. (1970), ‘The feeling of happiness’, Psychology, 7, 27–33. Veenhoven, R. (1984), Conditions of Happiness, Dordrecht: Reidel. Veenhoven, R. (1991), ‘Is happiness relative?’, Social Indicators Research, 24, 1–34. Veenhoven, R (1994), ‘Is happiness a trait? Tests of the theory that a better society does not make people any happier’, Social Indicators Research, 32, 101–60. Veenhoven, R. (1995), ‘The cross-national pattern of happiness. Test of predictions implied in three theories of happiness’, Social Indicators Research, 34, 33–68. Veenhoven, R. (1997), ‘Advances in the understanding of happiness’, (in French), Revue québécoise de psychologie, 18(2), 29–74. Veenhoven, R. (2000a), ‘The four qualities of life: ordering concepts and measures of the good life’, Journal of Happiness Studies, 1, 1–39. Veenhoven, R. (2000b), ‘Are the Russians as unhappy as they say they are? Comparability of self-reports across nations’, Journal of Happiness Studies, 2, 111–36. Veenhoven, R. (2004), ‘Happiness as an aim in public policy: the greatest happiness principle’, in P.A. Linley and S. Joseph (eds), Positive Psychology in Practice, New York: Wiley, pp. 658–78. Veenhoven, R. (2005), ‘Is life getting better? How long and happily people live in modern society’, European Psychologist, 10, 330–43. Veenhoven, R. (2008), ‘Healthy happiness: effects of happiness on physical health and the consequences for preventive health care’, Journal of Happiness Studies, 9, 449–64. Veenhoven, R. (2010), ‘How universal is happiness?’, in E. Diener, J.F. Helliwell and D. Kahneman (eds), International Differences in Well-being, Oxford: Oxford University Press. Veenhoven, R. and M. Hagerty (2006), ‘Rising happiness in nations, 1946–2004. A reply to Easterlin’, Social Indicators Research, 77, 1–16. Wessman, A.E. and D.F. Ricks (1966), Mood and Personality, New York: Holt, Rinehart and Wilson. Zajonc, R.B. (1984), ‘On the primacy of affect’, American Psychologist, 39, 117–23.

4.

Happiness and domain satisfaction: new directions for the economics of happiness Richard A. Easterlin and Onnicha Sawangfa1

The purpose of this chapter is to see to what extent the domain satisfaction model of psychology explains four different patterns of happiness in the USA: (1) the positive cross-sectional relation of happiness to socioeconomic status, (2) the nearly horizontal time series trend, (3) the hill pattern of life cycle happiness, and (4) the decline across generations. The domain model sees each of these happiness patterns as the net result of the corresponding patterns of satisfaction that people have in each of several realms of life – in the present analysis, finances, family life, work and health. These domain satisfaction patterns do not simply replicate the happiness pattern – with regard to age, for example, happiness may go up, but satisfaction with finances, down. Thus, given that the domain satisfaction patterns may differ from that for happiness, and also among themselves, the questions of interest here are specifically the following. Do the patterns by socio-economic status of satisfaction with each of the following – finances, family life, work and health – come together in a way that predicts the positive cross-sectional relation of happiness to socioeconomic status? Do the life cycle patterns of satisfaction in each of these four domains account for the hill pattern of life cycle happiness? Do the time series trends in satisfaction with finances, family life, work and health explain the nearly horizontal time series trend in happiness? Finally, is the decline in happiness across cohorts the net outcome of the cohort patterns of satisfaction in each of the four domains?

4.1

CONCEPTUAL FRAMEWORK

Economists typically adopt the view that well-being depends on actual life circumstances, and that one can safely infer well-being simply from observing these circumstances. The influence of this view is apparent even 70

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in the burgeoning literature on the economics of happiness where, despite frequent acknowledgment of subjective factors, many studies consist mainly of regressing happiness on an array of objective variables – income, work status, health, marital status and the like. (See the surveys in Clark et al., 2008; DiTella and MacCulloch, 2006; Frey and Stutzer, 2002a and 2002b; Graham, 2005 and 2009; Layard, 2005.) Psychologists, in contrast, view the effect on well-being of objective conditions as mediated by psychological processes through which people adjust somewhat to ups and downs in their life circumstances. Their skepticism of the economists’ view is well represented by psychologist Angus Campbell’s complaint over three decades ago: ‘I cannot feel satisfied that the correspondence between such objective measures as amount of money earned, number of rooms occupied, or type of job held, and the subjective satisfaction with these conditions of life, is close enough to warrant accepting the one as replacement for the other’ (Campbell, 1972, p. 442; cf. also Lyubomirsky, 2001). This statement appeared in a volume significantly titled The ‘Human’ Meaning of Social Change (emphasis added). In contrast to economists’ focus on objective conditions, Campbell proposed a framework in which objective conditions were replaced by reports on the satisfaction people expressed with those conditions (Campbell et al., 1976; Campbell, 1981). This approach is sometimes termed multiple discrepancy theory (Michalos, 1986, 1991; cf. also Diener et al., 1999b; Solberg et al., 2002). In this framework global happiness or overall satisfaction with life is seen as the net outcome of reported satisfaction with major domains of life, such as financial situation, family life and so on. Satisfaction in each domain is, in turn, viewed as reflecting the extent to which objective outcomes in that domain match the respondent’s goals or needs in that area, and satisfaction may vary with changes in goals, objective conditions or both. In economics similar models comparing attainments to aspirations date back to March and Simon (1968); for a recent example, see de la Croix (1998). An advantage of this approach is that judgments on domain satisfaction reflect both subjective factors of the type emphasized in psychology and objective circumstances stressed by economics. In the domain of family life, for example, one’s goals, simply put, might be a happy marriage with two children and warm family relationships. Satisfaction with family life would reflect the extent to which objective circumstances match these goals – the greater the shortfall, the less the satisfaction with family life. Over time, subjective goals, objective circumstances or both may change, and thereby alter judgments on domain satisfaction. Given objective conditions, goals may be adjusted to accord more closely with actual circumstances, in line with the process of hedonic adaptation emphasized by

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psychologists. Given goals, objective circumstances may shift closer to or farther from goals, altering satisfaction along the lines stressed by economists. Thus, in contrast to the objective measures used in economic models – in the case of family life, such things as marital status and number of children – reports on satisfaction with family life reflect the influence of subjective norms as well as objective circumstances. Another advantage of Campbell’s domain approach is that it classifies into a tractable set of life domains the everyday specific circumstances to which people refer when asked about the factors affecting their happiness (Cantril, 1965; Kahneman et al., 2004; Robinson and Godbey, 1997, ch.17). Of course, there is not complete agreement on what domains of life are conceptually preferable, and the classification of life domains remains a subject of continuing research. Virtually all life domain studies agree, however, that four domains are of major importance – finances, family circumstances, health and work. These four, for example, with slightly different labels, are at the head of Cummins’s (1996) meta-analysis of the domains of life satisfaction. It is these four that are studied here as predictors of the patterns of happiness by socio-economic status, time, age and cohort.

4.2

PRIOR WORK

Economic research on domain satisfaction has heretofore been quite limited, and much of what has been done focuses on explaining, not overall happiness, but satisfaction with specific economic circumstances, for example, job satisfaction, housing satisfaction, financial satisfaction, satisfaction with income, satisfaction with standard of living and so on (Diaz-Serrano, 2006; Hayo and Seifert, 2003; Hsieh, 2003; Solberg et al., 2002; Vera-Toscano et al., 2006; Warr, 1999). Few studies explore the relation of global happiness to the different domains. An important exception is the work of van Praag and Ferrer-i-Carbonell (2004), which examines the extent to which differences among individuals in overall satisfaction are related to satisfaction with a variety of life domains, several of which correspond to those studied here (see Chapters 3 and 4; also van Praag et al., 2003). Their results, based on data for the UK and Germany, support the importance of the domains studied here, and suggest that domain satisfaction variables provide a better statistical explanation of happiness than objective conditions (for a similar result with regard to wages and hours of work, see Clark, 2005). In another interesting study Rojas (2007) uses the domain satisfaction approach to study individual happiness in Mexico, focusing on domains deriving from the philosophical rather than social science literature. In a recent article Easterlin (2006) uses

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the domain approach to study happiness over the life cycle. The present chapter extends the Easterlin analysis to the variation in happiness by socio-economic status, time and birth cohort. Outside of economics work relating happiness to domain satisfaction is more extensive (see, for example, the bibliography in Veenhoven, 2005, section 12-a). One of the most ambitious projects brings together studies of individual data for 12 European countries of both domain satisfaction and satisfaction with life in general (Saris et al., 1996). The domains vary somewhat among countries, but one result common to all countries is that two domains are consistently positively related to overall life satisfaction – material living conditions (captured in satisfaction with housing and satisfaction with finances) and ‘social contacts’, reflecting the importance to well-being of personal relationships (ibid., p. 227; on personal relationships and well-being, see Ryff, 1995; Ryan and Deci, 2000). The counterparts of these two in the present study are financial satisfaction and satisfaction with family life. All of these earlier studies, both within and outside of economics, focus on explaining how happiness varies in relation to one particular variable, usually among individuals at a point in time. In contrast, the aim here is to test how well the domain satisfaction approach explains mean happiness within the US population in relation to each of four different variables – by socio-economic status (education), over time (year), over the life cycle (age) and across generations (birth cohort). For each variable the test is the same, to see how well the actual relation of happiness to that variable can be predicted from the corresponding patterns for the four domain satisfaction variables – financial situation, family life, work and health.

4.3

DATA AND METHODS

The data are from the US General Social Survey (GSS) conducted by the National Opinion Research Center (Davis and Smith, 2002). This is a nationally representative survey conducted annually from 1972 to 1993 (with a few exceptions) and biannually from 1994 to 2006. The present analysis is based on data for 1973–94, because two of the variables of interest, family and health satisfaction, are included in the GSS only during this time span. The GSS is a survey of households, and weighted responses are used here to represent more accurately the population of persons (ibid., pp. 1392–3 of codebook). For happiness there are three response options; for financial satisfaction, also three options; for job satisfaction (including housework), four options; family satisfaction, seven options; and health satisfaction, seven

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options. The specific question for each variable is given in Appendix 4.A1. In the present analysis the response of an individual to each question is assigned an integer value, with a range from least satisfied (or happy) equal to 1, up to the total number of response options (for example, 3 for happiness, 7 for health satisfaction). Socio-economic status is measured by years of schooling, ranging from zero to 20. The age range is from 18 to 89; birth cohort, from 1884 to 1976. Year is in terms of time dummies with 1973 being the reference year. The use of time dummies enables us to separate period from age and cohort effects (cf. Blanchflower and Oswald, 2007). Descriptive statistics are given in Appendix 4.A2. The basic procedure consists of the following steps: 1.

A regression of happiness on age, cohort, education, gender, race and year (in dummy form) is estimated from the individual data for 1973–94 (see Appendix 4.A3, column 1). Both linear and quadratic forms are tried for the age, cohort and education variables, and the form yielding the best fit in terms of significant t-statistics is selected. This single regression is then used to estimate how happiness varies in relation to each of the four variables (age, cohort, education and year) controlling for the other three. We call these estimated values ‘actual happiness’. Actual happiness differs from the raw mean of happiness in relation to any given variable, such as education, in that it controls for other, essentially fixed, characteristics of individuals. Thus, in the case of education, the estimated happiness-education pattern controls for differences from one level of education to another in the composition of the population by age, cohort, gender and race, and also in period effects. Formally, we have: Happy 5 C(1)(age, cohort, education, gender, race, year dummy), where C(1) denotes Equation (4.1) in Appendix 4.A3. The typical pattern of variation of happiness in regard to a given variable, say, years of schooling, is then estimated by entering in this regression the mean values of the other variables (age, cohort, gender, race and year), while allowing that variable to range from its minimum to maximum value as given in Appendix 4.A2 (for education, from zero to 20 years of schooling). Thus, Happy for the ith year of schooling 5 C(1)(age, cohort, male, black, educationi, t1973, t1974, . . ., t1994)

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where age is the mean age, cohort is the mean birth cohort and so on. Since years of schooling range from 0 to 20, following the above procedure for each level of education results in a series: Happy_Ed(0), Happy_Ed(1), . . ., Happy_Ed(20), where Happy_Ed(j) is actual happiness of a person with j years of schooling. This series is plotted in Figures 4.1(a) and 4.2(a) as actual happiness, the happiness pattern that is to be predicted. 2. A similar procedure is followed to derive the typical pattern of variation of satisfaction in each of the four domains. First, a regression is estimated of satisfaction in a given domain in relation to age, cohort, education, gender, race and year (in dummy form) as presented in Appendix 4.A3, columns 2–5. Then, the typical pattern of variation of satisfaction in that domain in regard to a given variable, say, education, is estimated by entering in the regression the mean values of all other variables, while allowing that variable to range from its lowest to highest value as given in Appendix 4.A2. Thus, similarly to the computation of actual happiness by level of education, the series of actual domain satisfaction by education can be obtained from C(2), C(3), C(4) and C(5), respectively: (a) (b) (c) (d)

3.

Satfin_Ed(0), Satfin_Ed(1), . . ., Satfin_Ed(20); Satfam_Ed(0), Satfam_Ed(1), . . ., Satfam_Ed(20); Satjob_Ed(0), Satjob_Ed(1), . . ., Satjob_Ed(20); and Sathealth_Ed(0), Sathealth_Ed(1), . . ., Sathealth_Ed(20).

These series are plotted in Figure 4.3(a). A regression is estimated from the individual data of the relation of happiness to the four domain satisfaction variables – financial satisfaction (Satfin), family satisfaction (Satfam), work satisfaction (Satjob) and health satisfaction (Sathealth) – to establish the relative impact of each domain on happiness (Appendix 4.A4). Formally, Happy 5 D(Satfin, Satfam, Satjob, Sathealth). All domains turn out to have a significant positive effect on happiness, as one might expect, with family and financial satisfaction having the greatest weight. Although there is some variation in the domain weight by demographic characteristics, such as sex and age, they are not sizeable enough to alter the basic results obtained here.

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A prediction of the variation of happiness with regard to each variable (education, time, age and cohort) is obtained by substituting in the step 3 regression equation the domain satisfaction values estimated in step 2. For the cross-section analysis, for example, predicted happiness for a given education level is estimated by entering in the step 3 regression equation the four domain satisfaction values for that level of education derived in step 2. Thus, mean predicted happiness for zero years of schooling, controlling for age, cohort, gender, race and year, is computed as: PredHappy_Ed(0) 5 D(Satfin_Ed(0), Satfam_Ed(0), Satjob_Ed(0), Sathealth_Ed(0)). Similarly, PredHappy_Ed(1) 5 D(Satfin_Ed(1), Satfam_Ed(1), Satjob_Ed(1), Sathealth_Ed(1)). This procedure is repeated for all other levels of education to obtain the predicted pattern of happiness in relation to education. The series PredHappy_Ed(0), PredHappy_Ed(1), . . ., PredHappy_Ed(20) is then plotted as predicted happiness in Figure 4.2(a).

The regression technique used is ordered logit, because responses to the several variables are categorical and number three or more. Ordinary least squares regressions yield virtually identical results, suggesting that the findings are robust with regard to methodology. In step 3, in estimating the relation of happiness to domain satisfaction from individual data, a question arises about possible bias in reports on satisfaction (cf. Diener and Lucas, 1999a, p. 215; van Praag and Ferreri-Carbonell, 2004, ch. 4). Responses on satisfaction – whether with life in general or an individual domain – are known to be influenced by personality traits. Consider two persons with identical objective conditions and subjective goals. If one of them is neurotic, then it is likely that this person’s responses on satisfaction with both life in general and the various domains of life will be lower than the other person’s, because neurotics tend to assess their circumstances more negatively than others (Diener and Lucas, 1999a). However, a purpose of the step 3 regression is to establish

Happiness and domain satisfaction

77

the relative weights in determining happiness of the four domain satisfaction variables. Because the happiness and domain satisfaction responses for any given individual would be similarly biased by personality, the estimate of relative weights for that individual, and correspondingly for the population as a whole, should be free of personality bias. Another purpose of the step 3 regression is to predict actual happiness from domain satisfaction. If personality bias exists in an individual’s report on happiness, then actual happiness, which is based on this report, is biased by personality. Similarly, personality bias in an individual’s report on domain satisfaction leads to personality bias in actual domain satisfaction. Predicted happiness, derived from actual domain satisfaction, is then also biased by personality. But since the personality bias in actual happiness is the same as that in actual domain satisfaction and, thus, in predicted happiness, the predictive power of the domain model judged by comparing actual happiness with predicted happiness should not be influenced by personality bias.

4.4

RESULTS

Actual Happiness The happiness patterns to be explained are both familiar and unfamiliar. Most familiar, perhaps, is the positive cross-sectional association of happiness to socio-economic status (Figure 4.1a). Also well-known is the fairly flat relation of happiness to time (Figure 4.1b). (The fluctuations in the figure are due to the use of time dummies.) Less familiar are the patterns in relation to age and cohort. Over the life cycle happiness rises slightly to mid-life and declines slowly thereafter (Figure 4.1c; cf. also Easterlin, 2006; Mroczek and Spiro, 2005). Although the swing in happiness is mild, it is statistically significant. The pattern differs from the usual U-shaped relation to age reported in the economics literature, because the U-shaped happiness-age relation is the result of a multivariate regression in which controls are included, not only for the variables used here (education, time, cohort, gender, race), but also for life circumstances (income, work status, marital status, health) (Blanchflower and Oswald, 2004, 2007). Controls for life circumstances would be inappropriate here and also in regard to the happiness patterns for education, time and cohort, because the specific purpose of the analysis is to test whether satisfaction with life circumstances, which reflects both objective life circumstances and subjective norms, explains the happiness patterns observed.

2.5

18

0

24

2

30

4

36

6

10

12

42

48 54 Age

60

(c) By Age

14

66

Years of Schooling

8

(a) By Years of Schooling

72

16

78

84

18

90

20

1884 1894 1904 1914 1924 1934 1944 1954 1964 1974 Cohort

(d) By Birth Cohort

Year

1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993

(b) By Year

Mean actual happiness by years of schooling, year, age and birth cohort, 1973–94

Values in each panel are after controlling for the three variables heading the other panels, and also gender and race. See Appendix 4.A3.

Figure 4.1

Note:

Mean Happiness

2.4

2.3

2.2

2.1

2

2.5

2.4

2.3

2.2

2.1

2

Mean Happiness

2.5 2.4 2.3 2.2 2.1 2 2.5 2.4 2.3 2.2 2.1 2

78

2.5

2.4

2.3

2.2

2.1

2

4

6

Predicted

Actual

(c) By Age

8 10 12 14 Years of Schooling

16

18

20

Predicted

Actual

18 24 30 36 42 48 54 60 66 72 78 84 90 Age

0

(a) By Years of Schooling

Predicted

Actual

1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 Year

(b) By Year

(d) By Cohort

1884 1894 1904 1914 1924 1934 1944 1954 1964 1974 Cohort

Predicted

Actual

Mean predicted and actual happiness by years of schooling, year, age and birth cohort, 1973–94

Values in each panel are after controlling for the three variables heading the other panels, and also gender and race. See Appendix 4.A3.

Figure 4.2

Note:

Mean Happiness

Mean Happiness

2

2.5

2.4

2.3

2.1

2

2.2

2.5 2.4 2.3 2.1 2 2.1 2

2.2

2.3

2.4

2.5

2.2

2.5 2.4 2.3 2.1 2 2.1 2

2.2

2.3

2.4

2.5

2.2

2.5 2.4 2.3 2.2 2.1 2 2.5 2.4 2.3 2.2 2.1 2

79

Figure 4.3

4.7

5

80 Satfam

Satfam

5.3 5.6 5.9 6.2 6.5 6.8

4.7

5

5.3 5.6 5.9 6.2 6.5 6.8 Satfin

2.1 2.2 2.3 2.4

1.7 1.8 1.9

2

2.1 2.2 2.3 2.4

0 2

SATFIN

4

1977

SATFAM

HAPPY

1973

2

1981 1985

Year

(b.1) By Year

1989

20

1993

SATFIN

18

SATFAM

16

HAPPY

6 8 10 12 14 Years of Schooling

(a.1) By Years of Schooling

(continues on p. 81)

Satfin 1.7 1.8 1.9

1.7 1.8 1.9

2

1.7 1.8 1.9

2.1 2.2 2.3 2.4

Happy

2 2.1 2.2 2.3 2.4 Happy Satjob

Satjob 2.5

2.71

2.92

3.13

3.34

2.5

3.55

2.71

2.92

3.13

3.34

3.55

1973

0 2

SATJOB

1977

4 6

SATHEALTH

1981 1985

Year

SATHEALTH

16

1989

SATJOB

(b.2) By Year

8 10 12 14 Years of Schooling

(a.2) By Years of Schooling

20

1993

18

4

4

4.3 4.6 4.9 5.2 5.5 5.8 6.1

4.3

4.6

4.9

5.2

5.5

5.8

6.1

Sathealth

Sathealth

2.1 2.2 2.3 2.4 2.5

2

Satfam

7

SATFIN

SATFAM

HAPPY

(c.1) By Age

SATFIN

SATFAM

HAPPY

SATJOB

SATHEALTH

1884 1894 1904 1914 1924 1934 1944 1954 1964 1974 Cohort

(d.2) By Birth Cohort

18 24 30 36 42 48 54 60 66 72 78 84 90 Age

SATJOB

SATHEALTH

(c.2) By Age 5.8 6.1

Mean domain satisfaction and actual happiness by years of schooling, year, age and birth cohort, 1973–94

Cohort

1884 1894 1904 1914 1924 1934 1944 1954 1964 1974

(d.1) By Birth Cohort

18 24 30 36 42 48 54 60 66 72 78 84 90 Age

See note to Figure 1.

Figure 4.3

Note:

Satfin

Satfin

1.8 1.9

2.1 2.2 2.3 2.4 2.5

4.9 5.2 5.5 5.8 6.1 6.4 6.7

7

6.7

6.4

Satfam 5.8 6.1

5.5

5.2

4.9

1.8 1.9 1.9

2

2.1

2.2

2.3

2.4

2.5

2

2.1 2.2 2.3 2.4 2.5 Happy Happy

3.8 3.59 3.38 3.17 2.96 2.75

1.8

2

1.8 1.9

Satjob Satjob

3.8 3.59 3.38 3.17 2.96 2.75

Sathealth Sathealth

5.2 5.5 4.3 4.6 4.9 4 5.8 6.1 5.5 5.2 4.9 4.6 4.3 4

81

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Happiness, economics and politics

Least studied is how happiness varies by cohort.2 For cohorts born between the late nineteenth century and the 1970s, the relation of happiness to cohort is negative and curvilinear, with the lowest happiness levels found in the cohorts born in the mid-1950s (Figure 4.1d). Thus, the happiness of younger cohorts is, on average, significantly less than older, except that among the most recent cohorts there is a slight upturn in happiness. The magnitude of the happiness differences among cohorts is not very great, but it is somewhat larger than the changes found in the time series and life cycle patterns. The difference among cohorts found here is after controlling for cohort differences in age, education, period influences, gender and race. If data were available for a single year only, then it would be impossible to distinguish the cohort pattern from that for age. If, for example, in the survey year 1980 mean happiness were to increase from age 20 (that is, persons born in 1960) to age 80 (persons born in 1900), then the cohort pattern would be negative, the reverse of that for age, with happiness declining from the cohort of 1900 to that of 1960. (If the age pattern were hill-shaped moving from left to right on the x-axis, the cohort pattern would be hillshaped too – in effect, the cohort pattern traverses the same hill in reverse fashion.) With data for only one year, there would be no way of deciding whether one is observing the relation of happiness to age or to cohort. Our data, however, span 21 years, and thus in deriving cohort effects we compare the happiness of 21 different cohorts at a given age, and, correspondingly, in deriving age effects the happiness at 21 different ages of a given cohort. The fact that our age and cohort patterns of happiness are not simply the reverse of each other (as is true also of the age and cohort patterns for the individual domains) indicates that we are successfully differentiating between age and cohort influences. 4.4.1

Predicted Happiness

There are four fairly disparate patterns of happiness to be explained – a positive cross-sectional relation to education, a fairly flat relation to time, the ‘hill’ pattern of the life cycle and a negative curvilinear relation across cohorts. How well do the domain satisfaction patterns predict these patterns of happiness? The answer, based on the procedures outlined in steps 2–4 above, is reasonably well. The cross-sectional relation of happiness to education is closely predicted by the cross-sectional patterns of happiness to education derived from the domain model (Figure 4.2a). The predicted time series pattern of happiness based on the time series patterns of satisfaction in each domain corresponds closely to the actual horizontal time series

Happiness and domain satisfaction

Table 4.1

83

Mean squared error of the prediction of happiness

Variable Years of Schooling Year Age Birth Cohort

Mean Squared Error 0.00 033 0.00 054 0.00 028 0.00 152

pattern (Figure 4.2b). The life cycle happiness predicted by the life cycle patterns of domain satisfaction follow the ‘hill’ pattern of actual happiness, although the predicted movement peaks slightly earlier, at age 43 compared with 52, and the amplitude is slightly less than the actual (Figure 4.2c). Least satisfactory is the prediction of the cohort pattern. Although happiness of younger cohorts is correctly predicted to be less than older, the predicted curve is virtually linear rather than concave upward, so that the upturn among the youngest cohorts is missed (Figure 4.2d). Table 4.1 compares the mean squared error of the prediction of happiness by education, year, age and cohort. The most satisfactory prediction is that for life cycle happiness. It is closely followed by the predictions for years of schooling and the time series pattern of happiness. Confirming the visual observation of Figure 4.2, the least satisfactory is the prediction of the cohort pattern, with a mean squared error more than five times that of the life cycle prediction. 4.4.2

Domain Satisfaction

As a general matter, the four domain patterns for any one variable typically differ from each other, and the domains dominating the prediction of happiness are not the same for all four variables. This is brought out in Figure 4.3, which presents for each variable the actual domain patterns and, for comparison, that for actual happiness. The left hand panel presents the patterns for the domains of family life and financial satisfaction; the right hand panel, the patterns for satisfaction with work and health. By comparing the actual domain patterns with that for actual happiness, one is able to form a tentative impression of which domains are chiefly responsible for the happiness pattern for any given variable. Perhaps most striking is that more educated persons are happier because they enjoy greater satisfaction in all four realms of life. For family life, finances, work and health, satisfaction trends upward with the level of education (Figure 4.3, panels a.1 and a.2). The rate of change, however, varies among the domains. Satisfaction with family life and health

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increases at a decreasing rate, while satisfaction with finances grows at an increasing rate. Only for satisfaction with work is the trend linear like that for actual happiness. The fairly flat relation of happiness to time appears from the figure to reflect similar patterns in the four domains (panels b.1 and b.2). However, if one fits ordinary least squares trend lines to the fluctuating lines in the figures, some subtle differences emerge. All of the patterns have very slight, but significant trends. Actual happiness has a small uptrend, amounting to a total increase for the period of 0.013 on the happiness scale of one to three. This is the equivalent of a net upward shift by one response category – say, from ‘pretty happy’ to ‘very happy’ – of 1.3 percent of respondents over the entire 21 year period. This is not very much of a shift, although it is statistically significant. Based on the fitted trends, the corresponding shift for each domain (all of them significant) are for financial satisfaction 13.2 percent, work satisfaction 12.3 percent, family life satisfaction −0.5 percent and health satisfaction 11.4 percent. Thus, the very slight uptrend for actual happiness is the net outcome of the slight positive trends in satisfaction with finances, work and health outweighing the slight negative trend in satisfaction with family life. Turning to the age patterns, one finds that the increase to mid-life of life cycle happiness is due to increasing satisfaction with family life and work outweighing negative changes in satisfaction with finances and health (Figure 4.3, panels c.1 and c.2). The decline of happiness beyond mid-life occurs because declines in satisfaction with family life and work join the downtrend in satisfaction with health. The adverse impact on happiness of these negative trends is moderated, however, by increasing satisfaction that people express with their financial situation as they move into older age. Finally, the lower happiness of younger compared with older cohorts is due to downtrends in satisfaction in three domains – finances, work and health (Figure 4.3, panels d.1 and d.2). Satisfaction with family life does not differ between older and younger cohorts, despite the striking differences in family life between today’s cohorts and those of their parents and grandparents. The slight upturn in actual happiness among the youngest cohorts cannot be explained by the domains studied here, because none of the domains shows an improvement of younger relative to older cohorts. One important conclusion that emerges from surveying the domain patterns is that no single domain is the key to happiness. Rather, happiness is the net outcome of satisfaction with all of the major life domains, and the domain patterns frequently differ from each other. Moreover, the importance of any given domain varies depending on the happiness relationship being studied – cross-sectionally by education, over time, through the life cycle or across generations.

Happiness and domain satisfaction

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85

CONCLUSIONS

How well does the domain satisfaction model predict the way in which mean happiness varies by socio-economic status, year, age and birth cohort? The answer is quite well for the first three – education, year and age – and not too badly for the fourth, cohort. Some skeptics might say the success of the predictions is no great surprise – due to the common influence of personality, reports of happiness and satisfaction with finances, family life, work and health all are highly correlated in data for individuals. But we are analysing here the relations among group means, not individual data, and as can readily be seen from Figure 4.3 the patterns of the domain means often differ from that for happiness and among themselves. The observation that the happiness and domain satisfaction variables are highly positively correlated among individuals does not imply, for example, that the mean values by age of happiness and the four domain satisfaction variables will also be positively correlated. Personality tends to be stable from one age to another while the means for happiness and domain satisfaction follow different and sometimes contrary paths with regard to age. Similarly, unless one believes that personality varies systematically by socio-economic status, birth cohort and over time, there is no reason to suppose that the individual-based correlation among the happiness and domain satisfaction variables would result in corresponding correlations among the group means for these categories. Put differently, the point is not whether personality varies among individuals in a way that would explain individual differences in happiness, but whether, on average, it varies by age, level of education, year and cohort in ways that would generate the prediction of happiness by these characteristics. To our knowledge there is no research demonstrating that personality varies by age, level of education, year and cohort in the same way as happiness. Some might contend that because actual happiness is derived from the same explanatory variables as are the domain means (Appendix 4.A3), it is inevitable that actual happiness and happiness as predicted by these domain means would come together well. An argument similar to that just given applies here. There is no reason to suppose that a weighted average of the four domain means at, say, a certain age should equal actual happiness at that age. Different life cycle patterns among the four domains need not together produce a life cycle pattern of happiness that fits nicely with the life cycle pattern of actual happiness. It would be interesting to see if happiness regressions of the type found in the economics literature, based only on objective variables, do as well in predicting the happiness patterns as the domain satisfaction variables used

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here. If, for example, one estimates the life cycle pattern of such ‘objective’ variables as income, marital status, employment status and health, would one be able to predict from these patterns the actual life cycle pattern of happiness? We venture that the answer is no – that Angus Campbell is right when he says that subjective well-being depends not on objective conditions alone, but on the psychological processing of objective circumstances, as captured in reports on satisfaction with these conditions. The fact that the domain patterns studied here come together reasonably well to predict actual happiness provides new support for the meaningfulness of subjective data on well-being and its components. Thus, while a skeptic of the present analysis might point to the startling contrast between the life cycle pattern for happiness and that for satisfaction with finances – almost diametrical opposites – it turns out that when the movements in the other domains are accounted for, along with that for financial satisfaction, the hill pattern observed for actual happiness is predicted fairly closely by the domain patterns. This close prediction would be unlikely to occur if no credence could be given to what people say about their feelings. In addition, the similarity between the present patterns of predicted and actual happiness supports the conclusion that the four domains studied here are probably the most important in determining happiness, a result consistent with the literature on domain satisfaction. But these four domains do not tell the whole story of happiness movements, as is made especially clear here by the disparity between the predicted and actual happiness patterns by birth cohort. Finally, depending on the happiness relationship being studied – by socio-economic status, time, age or cohort – the role played by different domains in determining happiness tends to vary. Happiness is the net outcome of satisfaction with all of the major domains of life, and no single domain is sufficient to explain the various patterns of overall happiness. This is in many ways a first pass at testing fairly comprehensively Campbell’s domain satisfaction model, and while the model performs reasonably well, the results raise a number of questions for further research. For example, would increasing the number of life domains improve the predictions? What chiefly determines the domain satisfaction patterns – objective conditions like those emphasized in economics or subjective factors stressed in psychology? To what extent are there interrelations among the various domains themselves? The domain satisfaction model provides a new and reasonable start on unraveling the mysteries of happiness – a new direction, perhaps, for research on the economics of happiness. But it is only a start.

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NOTES 1. For valuable comments we are grateful to Andrew Clark, Andrew Oswald, John Strauss, Anke Zimmermann, and participants in the Conference on New Directions in the Study of Happiness: US and International Perspectives, University of Notre Dame, 22–24 October 2006. Laura Angelescu provided excellent research assistance; financial help was provided by the University of Southern California. 2. An exception is the article by Blanchflower and Oswald (2000), which focuses on the trend of happiness among younger persons since 1972. However, their analysis controls for differences among cohorts in life circumstances, whereas the present analysis does not.

REFERENCES Blanchflower, D.G. and A. Oswald (2000), ‘The rising well-being of the young’, in D.G. Blanchflower and R.B. Freeman (eds), Youth Employment and Joblessness in Advanced Countries, Cambridge, MA: NBER, pp. 289–328. Blanchflower, D.G. and A. Oswald (2004), ‘Well-being over time in Britain and the USA’, Journal of Public Economics, 88, 1359–86. Blanchflower, D.G. and A. Oswald (2007), ‘Is well-being U-shaped over the life cycle?’, IZA Discussion Paper No. 3075, Bonn: Institute for the Study of Labor (IZA). Campbell, A. (1972), ‘Aspiration, satisfaction, and fulfillment’, in A. Campbell and P.E. Converse (eds), The Human Meaning of Social Change, New York: Russell Sage, pp. 441–66. Campbell, A. (1981), The Sense of Well-Being in America, New York: McGrawHill. Campbell, A., P.E. Converse, and W.L. Rodgers (1976), The Quality of American Life, New York: Russell Sage Foundation. Cantril, H. (1965), The Pattern of Human Concerns, New Brunswick, NJ: Rutgers University Press. Clark, A.E. (2005), ‘What makes a good job? Evidence from OECD countries in S. Bazen’, in C. Lucifora and W. Salverda (eds), Job Quality and Employer Behaviour, Basingstoke: Palgrave MacMillan, pp. 11–30. Clark, A.E., P. Frijters and M.A. Shields (2008), ‘Relative income happiness and utility: an explanation for the Eastern Paradox and other puzzles’, Journal of Economic Literature, 46 (1), 95–144. Cummins, R.A. (1996), ‘The domains of life satisfaction: an attempt to order chaos’, Social Indicators Research, 38, 303–28. Davis, J.A. and T.W. Smith (2002), General Social Surveys, 1972–2002. University of Connecticut, Storrs, CT: The Roper Center for Public Opinion Research. Machine-readable data file: Principal Investigator, James A. Davis; Director and Co-principal Investigator, Tom W. Smith; Co-principal Investigator, Peter Marsden; National Opinion Research Center, producer; The Roper Center for Public Opinion Research, University of Connecticut, distributor. One data file (43 p 698 logical records and one codebook (1769 pp.). de la Croix, D. (1998), ‘Growth and the relativity of satisfaction’, Mathematical Social Sciences, 36, 105–25.

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Diaz-Serrano, L. (2006), ‘Housing satisfaction, homeownership and housing mobility: a panel data analysis for twelve EU countries’, IZA Discussion Papers No. 2318, Bonn: Institute for the Study of Labor (IZA). Diener, E. and R.E Lucas (1999a), ‘Personality and subjective well-being’, in D. Kahneman, E. Diener and N. Schwarz (eds), Well-being: The Foundations of Hedonic Psychology, New York: Russell Sage, pp. 213–29. Diener, E., E.M. Suh, R.E. Lucas and H.L. Smith (1999b), ‘Subjective well-being: three decades of progress’, Psychological Bulletin, 125, 276–302. DiTella, R. and R. MacCulloch (2006), ‘Some uses of happiness data in economics’, Journal of Economic Perspectives, 20, 25–46. Easterlin, R.A. (2006), ‘Life cycle happiness and its sources: intersections of psychology, economics and demography’, Journal of Economic Psychology, 27, 463–82. Frey, B.S. and A. Stutzer (2002a), Happiness and Economics, Princeton, NJ: Princeton University Press. Frey, B.S. and A. Stutzer (2002b), ‘What can economists learn from happiness research?’, Journal of Economic Literature, 40, 402–35. Graham, C. (2005), ‘Insights on development from the economics of happiness’, World Bank Research Observer. 1–31. Graham, C. (2009), ‘Happiness, economics of’, in S. Durlauf and L. Blume (eds), The New Palgrave Dictionary of Economics Online, 2nd edn, Basingstoke: Palgrave-Macmillan, last accessed 2 May 2009. Hayo, B. and W. Seifert (2003), ‘Subjective economic well-being in Eastern Europe’ Journal of Economic Psychology, 24, 329–48 Hsieh, C.M. (2003), ‘Income, age and financial satisfaction’, International Journal of Aging & Human Development, 56, 89–112. Kahneman, D., A.B. Krueger, D.A. Schkade, N. Schwarz and A.A. Stone (2004), ‘A survey method for characterizing daily life experience: the Day Reconstruction Method (DRM)’, Science, 306, 1776–80. Layard, R. (2005), Happiness: Lessons from a New Science, New York: Penguin Press. Lyubomirsky, S. (2001), ‘Why are some people happier than others? The role of cognitive and motivational processes on well-being’, American Psychologist, 56 (3), 239–49. March, J.G. and H.A. Simon (1968), Organizations, New York: John Wiley. Michalos, A.C. (1986), ‘Job satisfaction, marital satisfaction and the quality of life’, in F.M. Andrews (ed.), Research on the Quality of Life, University of Michigan, Ann Arbor: Survey Research Center, Institute for Social Research, pp. 57–83. Michalos, A.C. (1991), Global Report on Student Well-being, Vol. I. Life Satisfactions, New York: Springer-Verlag. Mroczek, D.K. and A. Spiro, III (2005), ‘Changes in life satisfaction during adulthood: findings from the veterans affairs normative aging study’, Journal of Personality and Social Psychology, 88 (1), 189–202. Robinson, J.P. and G. Godbey (1997), Time for Life: The Surprising Ways Americans Use Their Time, 2nd edn, University Park, PA: Pennsylvania State University Press. Rojas, M. (2007), ‘The complexity of well-being: a life satisfaction conception and domains-of-life approach’, in I. Gough and J.A. McGregor (eds) Well-being in Developing Countries: From Theory to Research, New York: Cambridge University Press, pp. 259–80. Ryan, R.M. and E.L. Deci (2000), ‘Self-determination theory and the facilitation of

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intrinsic motivation, social development, and well-being’, American Psychologist, 55 (1), 68–78. Ryff, C.D. (1995), ‘Psychological well-being in adult life’, Current Directions in Psychological Science, 4, 99–104. Saris, W.E., R. Veenhoven, A.C. Scherpenzeel, and B. Bunting (eds) (1996), A Comparative Study of Satisfaction with Life in Europe, Budapest: Eötvös University Press. Solberg, E.C., E. Diener, D. Wirtz, R.E. Lucas and S. Oishi (2002), ‘Wanting, having, and satisfaction: examining the role of desire discrepancies in satisfaction with income’, Journal of Personality and Social Psychology, 83, 725–34. van Praag, B.M.S. and A. Ferrer-i-Carbonell (2004), Happiness Quantified: A Satisfaction Calculus Approach, Oxford: Oxford University Press, ch. 3. van Praag, B.M.S., P. Frijters and A. Ferrer-i-Carbonell (2003), ‘The anatomy of subjective well-being’, Journal of Economic Behavior and Organization, 51, 29–49. Veenhoven, R. (2005), ‘World Database of Happiness’, http://worlddatabaseofhappiness.eur.nl, last accessed 28 April 2009. Vera-Toscano E., V. Ateca-Amestoy and R. Serrano-del-Rosal (2006), ‘Building financial satisfaction’, Social Indicators Research, 77, 211–43. Warr, P. (1999), ‘Well-being and the workplace’, in D. Kahneman, E. Diener and N. Schwarz (eds), Well-being: The Foundations of Hedonic Psychology, New York: Russel Sage Foundation, pp. 392–412.

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APPENDIX 4.A1

QUESTIONS AND RESPONSE CATEGORIES FOR HAPPINESS AND SATISFACTION VARIABLES

HAPPY: Taken all together, how would you say things are these days – would you say that you are very happy, pretty happy or not too happy? (Coded 3, 2, 1 respectively.) SATFIN: We are interested in how people are getting along financially these days. So far as you and your family are concerned, would you say that you are pretty well satisfied with your present financial situation, more or less satisfied, or not satisfied at all? (Coded 3, 2, 1 respectively.) SATJOB: (Asked of persons currently working, temporarily not at work or keeping house.) On the whole, how satisfied are you with the work you do – would you say you are very satisfied, moderately satisfied, a little dissatisfied or very dissatisfied? (Coded from 4 down to 1.) SATFAM: For each area of life I am going to name, tell me the number that shows how much satisfaction you get from that area. Your family life 1. 2. 3. 4. 5. 6. 7.

A very great deal A great deal Quite a bit A fair amount Some A little None

(Reverse coded here.) SATHEALTH: Same as SATFAM, except ‘Your family life’ is replaced by ‘Your health and physical condition.’

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APPENDIX 4.A2

91

DESCRIPTIVE STATISTICS

Table 4.A1 Variable

Number of Observations

Mean

Standard Deviation

Minimum Maximum

Happy Satfin Satjob Satfam Sathealth

29 651 29 728 23 808 23 207 23 252

2.22 2.04 2.66 4.66 4.24

0.63 0.74 0.92 1.62 1.68

1 1 1 1 1

3 3 4 7 7

Age Birth Cohort (1880 = 0) Years of Schooling Male Black

29 853 29 853

43.89 60.10

17.18 18.34

18 4

89 96

29 853 29 853 29 853

12.35 0.45 0.11

3.12 0.50 0.31

0 0 0

20 1 1

t1973 t1974 t1975 t1976 t1977 t1978 t1980 t1982 t1983 t1984 t1985 t1986 t1987 t1988 t1989 t1990 t1991 t1993 t1994

29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853 29 853

0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.10

0.22 0.22 0.22 0.21 0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.21 0.22 0.23 0.30

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

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APPENDIX 4.A3 Table 4.A2

Independent Variable Age Agesq Coh Cohsq Educ

STEPS 1 AND 2 EQUATIONS

Regression of happiness and each domain satisfaction variable on specified independent variables: ordered logit statistics Dependent Variable Happy (1) 0.022 772 (0.001)** −0.00 022 (0.001)** −0.02 851 (0.000)** 0.00 019 (0.000)** 0.055 533 (0.000)**

Educsq Male Black t1973 t1974 t1975 t1976 t1977 t1978 t1980 t1982 t1983 t1984 t1985 t1986

−0.09 836 (0.000)** −0.69 836 (0.000)** ------------0.035 135 (0.648) −0.09 603 (0.199) −0.05 226 (0.471) 0.043 856 (0.538) 0.10 802 (0.110) 0.006 386 (0.927) 0.017 871 (0.793) −0.12 173 (0.062)+ 0.07 414 (0.281) −0.14 544 (0.024)* 0.022 754 (0.732)

Satfin (2)

Satfam (3)

−0.04 344 (0.000)** 0.000 514 (0.000)** −0.01 713 (0.000)**

0.044 079 (0.000)** −0.00 043 (0.000)**

0.035 612 (0.050)+ 0.002 054 (0.005)** 0.012 652 (0.596) −0.61 869 (0.000)**

0.075 085 (0.000)** −0.00 192 (0.023)* −0.17 479 (0.000)** −0.45 077 (0.000)**

------------−0.00 994 (0.886) −0.05 083 (0.466) −0.01 693 (0.800) 0.224 268 (0.001)** 0.133 804 (0.051)+ −0.08 415 (0.197) −0.1 206 (0.054)+ −0.1 065 (0.099)+ 0.021 233 (0.737) 0.024 798 (0.697) 0.090 113 (0.178)

Reference Year 0.077 578 (0.281) 0.171 288 (0.019)* −0.05 673 (0.419) 0.039 493 (0.584) 0.007 053 (0.922) 0.199 211 (0.007)** 0.303 385 (0.000)** −0.03 378 (0.637) 0.208 851 (0.005)**

−0.12 431 (0.085)+

Satjob (4) 0.043 668 (0.000)** −0.0 004 (0.000)** −0.03 556 (0.000)** 0.000 164 (0.018)* 0.047 991 (0.000)**

0.021 695 (0.423) −0.43 641 (0.000)** ------------−0.07021 (0.373) 0.187315 (0.021)* 0.060301 (0.441) 0.00468 (0.949) 0.159489 (0.034)* −0.04797 (0.520) 0.02714 (0.707) 0.141 839 (0.045)* −0.01 138 (0.881) 0.073 894 (0.302) 0.231 755 (0.002)**

Sathealth (5) −0.01 198 (0.060)+ −0.0 001 (0.018)* −0.0 089 (0.064)+

0.210 914 (0.000)** −0.00 579 (0.000)** 0.138 811 (0.000)** −0.16 603 (0.000)** ------------0.038 031 (0.583) 0.014 605 (0.826) −0.00 767 (0.906) 0.079 327 (0.254) −0.01 189 (0.856) 0.177 236 (0.009)** 0.352 281 (0.000)** -0.0 688 (0.319) 0.212 522 (0.003)**

−0.11 249 (0.141)

Happiness and domain satisfaction

Table 4.A2 Independent Variable t1987

(continued) Dependent Variable Happy (1)

Satfin (2)

−0.02 126 (0.759) 0.162 877 (0.016)* 0.068 958 (0.307) 0.15 064 (0.032)* 0.013 087 (0.852)

0.172 639 (0.006)** 0.158 673 (0.015)* 0.119 368 (0.076)+ 0.051 672 (0.473) 0.077 566 (0.252)

t1994

−0.12 405 (0.059)+

0.120 657 (0.060)+

cut1:Constant

−2.03 755 (0.000)** 0.79 881 (0.052)+

−2.19 873 (0.000)** −0.14 451 (0.713)

t1988 t1989 t1990 t1991 t1993

cut2:Constant

93

cut3:Constant cut4:Constant cut5:Constant cut6:Constant Observations 29 651 Pseudo 0.014 R-squared Chi2 607.512 Log Likelihood −27 328.6

Satfam (3)

Satjob (4)

0.06 154 (0.410) 0.107 415 (0.196) 0.066 921 (0.407) 0.052 268 (0.526) 0.065 499 (0.420) 0.0 394 (0.621) 0.028 085 (0.780)

−0.04 379 (0.554) 0.121 667 (0.107) 0.09 812 (0.194) 0.115 772 (0.145) 0.100 156 (0.200)

−2.92 248 (0.000)** −2.0 171 (0.000)** −1.36 141 (0.000)** −0.47 882 (0.006)** 0.285 209 (0.102) 1.808 822 (0.000)**

−3.07 068 (0.000)** −1.72 014 (0.000)** 0.234 316 (0.608)

Sathealth (5) 0.163 291 (0.039)* 0.087 871 (0.309) 0.001 555 (0.986) 0.141 139 (0.136) −0.01 768 (0.855) 0.019 645 (0.845)

0.12 954 (0.074)+ −3.54 667 (0.000)** −2.42 659 (0.000)** −1.77 893 (0.000)** −0.65 057 (0.189) 0.075 143 (0.879) 1.529 096 (0.002)**

29 728 0.031

23 207 0.007

23 808 0.02

23 252 0.016

1 734.832 −30 710.4

371.977 −31 389.3

879.21 −25 354

1 052.814 −37 052.7

Note: + significant at 10%; * significant at 5%; ** significant at 1%; robust p-value in parentheses.

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APPENDIX 4.A4 Table 4.A3

STEP 3 EQUATION

Regression of happiness on domain satisfaction variables:ordered logit statistics

Independent Variable

Happy

Satfin

0.573 019 (0.000)** 0.498 200 (0.000)** 0.460 422 (0.000)** 0.242 419 (0.000)** 4.299 545 (0.000)** 7.743 151 (0.000)**

Satjob Satfam Sathealth cut1:Constant cut2:Constant Observations Pseudo R-squared Chi2 Log Likelihood

18 440 0.133 3 200.648 −14 855.8

Note: + significant at 10%; * significant at 5%; ** significant at 1%; robust p-value in parentheses.

PART II

Happiness and economics

5.

Happiness when temptation overwhelms willpower Alois Stutzer1

5.1

INTRODUCTION

Saint Anthony of Egypt was tempted by the devil, who appeared in the guise of a monk offering Anthony bread while he was fasting. Anthony overcame the temptation and pursued his long-term plans. As mere mortals we sometimes lack the willpower to withstand the seductions of window displays, to curb our hunger for salty and fatty titbits, to control anti-social emotions and so on. Accordingly, some of us end up obese, addicted to drugs, indebted, with poor job market outcomes or with unsuccessful relationships. Independently of whether the involved behavior is perceived morally condemnable, it is often understood to reduce individuals’ welfare. But how do we know that some choices are suboptimal according to people’s own evaluation? On what foundation do we judge whether people make mistakes? Addressing these questions is highly relevant for public policy if the goal is to understand environments that make people best off. If some choices are suboptimal, conditions can be searched for that make these mistakes less likely. The scientific analysis of suboptimal choices is not an easy task though. The rational choice perspective in traditional economic theory is purely equipped to offer guidance in studying systematic errors in consumption choice. According to its basic view, individuals know what they choose. They are able to predict costs and benefits of pursuing some activity or consuming some good now and in the future. After people have chosen some options, these options are implemented without problems. The preferred course of action can be pursued and people’s behavior in expectations maximizes their welfare. This implies that behavior reveals consistent preferences. Systematic errors in consumption choice are thus ruled out by assumption. This approach makes it almost impossible to detect and understand suboptimal consumption decisions due to problems of, for example, limited willpower.2 97

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We propose the economics of happiness3 as an alternative approach to study phenomena where temptation might overwhelm willpower. This chapter contributes to the cross-disciplinary field of economics and psychology (see, for example, Camerer et al., 2004; De Cremer et al., 2006; Frey and Stutzer, 2007; Rabin, 1998) and establishes a closer link between the study of suboptimal choices and the research on subjective well-being (see also Hsee et al., 2008). Based on individuals’ judgments of the quality of their lives, it is, in principle, possible to derive whether some observed behavior is suboptimal and is therefore reducing a person’s welfare. This approach draws on empirical research in which the dependent variable is reported subjective well-being or life satisfaction and consumption behavior serves as the main explanatory variable. This approach is promising as it puts forward a proxy for individuals’ welfare to evaluate choice behavior. However, the approach is subject to the same econometric difficulties faced by studies that examine the determinants of behavior, that is, the possibility of omitted variable bias and endogeneity bias. Here, the economics of happiness is applied to further the understanding of important consumption decisions. We mention recent evidence on TV viewing and smoking. In more detail, we discuss eating habits in Western countries where obesity has become a major health issue. Research in economics has provided important insights into how technological progress reduced the relative price of food and contributed to the increase in obesity. However, the increased availability of food might well have overstrained willpower and led to suboptimal consumption decisions relative to people’s own standards. It is indeed found that obesity decreases the well-being of individuals who report limited self-control while it does not do so for others. In the following section theoretical and empirical challenges of using the happiness approach to study suboptimal choices are discussed. First, the key characteristics and the normative basis of the approach based on individuals’ judgments about the quality of their lives are disclosed. Second, issues in the empirical identification are raised. Sections 5.3–5 present evidence on willpower and subjective well-being for three important domains of consumption: TV viewing, smoking and eating. Section 5.6 offers concluding remarks.

Happiness when temptation overwhelms willpower

5.2 5.2.1

99

THE HAPPINESS APPROACH TO SUBOPTIMAL DECISIONS AND INDIVIDUAL WELFARE Normative Basis and Evaluation Metric

Limits of the revealed preference approach The normative basis of the study of consumer choice in economics is the idea of consumer sovereignty. Individuals’ choices are considered to be the result of rational utility maximization. This view is, however, challenged by research in economics and psychology that reports a large number of different anomalies in a real-life decision-making context. Anomalies are understood in the sense of individual behavior violating certain axioms underlying the rational consumer hypothesis (Kahneman et al., 1991). One of the most challenging deviations from utility maximizing consumption choice is due to people having limited willpower. Standard economics is mute about willpower and assumes that people are able to make and implement decisions according to their long-term preferences. Viewed this way, consuming goods and pursuing activities that some people consider addictive, or at least forming bad habits, such as smoking cigarettes or taking cocaine, watching TV or driving expensive cars are considered a rational act. Contrary to this view, many people judge their own and other people’s consumption behavior as irrational in the sense that they think that they would be better off if they would consume less of these goods and care more for their future well-being. Such self-control problems involve two aspects: myopia and procrastination. In both cases the present is emphasized at the expense of the long term. When affected by myopia, people focus on consuming in the present and lack discernment or long-range perspective in their thinking and planning, thus undermining their well-being over time. In this respect, generally goods offering immediate benefits at negligible immediate marginal costs are tempting. Procrastination focuses on putting off or delaying an onerous activity more than a person would have liked when having evaluated it beforehand. In other words, willpower is necessary to stand temptations to fulfill immediate desires that conflict with long-term goals.4 Based on revealed preference, it is difficult, if not impossible, to discriminate between the view of consumers as rational sovereign actors and consumers facing limited willpower. Promises of a complementary happiness approach Two extensions of the traditional emphasis on ex ante evaluation and observed decision are insightful in the study of individual welfare. First, the standard economic concept of revealed preference is complemented

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with the concept of individual judgment on the quality of one’s life, what might be called the happiness approach. This separation of concepts makes it possible that judgments about experiences systematically diverge from orderings of options derived from observed behavior. The second extension is closely related to the first, and emphasizes ex post evaluations as a valuable source of information about the possibility of bounded rationality in people’s decision making. How do people fare and judge their situation after they have made decisions? The key idea is thus that judgments on people’s life are captured as a proxy for their individual welfare. Thereby the standards underlying people’s judgment are assumed to be those that the individual would like to pursue in order to maximize welfare. Thus the identification of mistakes hinges on the presumption that individuals pursue individual welfare based on some stable evaluation standards. Moreover, whether mistakes are properly identified depends on whether the evaluation metric fits people’s judgment of their life. The normative basis of the approach thus goes beyond assuming the pursuit of happiness but also involves the choice of the concrete evaluation metric to elicit people’s judgments.5 Thus ambiguities remain when choosing the empirical concept in order to measure individual welfare.6 Some people might favor a distant look reflecting on one’s life after the fact, while others favor the reasoned ex ante evaluations as their standards. Still others might give priority to how they felt when experiencing the course of life. Imagine those people who see happiness or high individual welfare as something like the ‘positive, persistent attitude towards both particular experiences and life experience more generally that a person feels upon repeated reflection’ (Kelman, 2005, pp. 408ff.). For them, general evaluations of their satisfaction with life as a whole might be an appropriate metric to capture judgments about individual welfare. For those people who equate individual welfare with moment-tomoment affect, individual welfare might be measured relatively best by approaches like the experience sampling method (Csikszentmihalyi and Hunter, 2003; Scollon et al., 2003) or the day reconstruction method (Kahneman et al., 2004). The relevance of the (normative) choice of an elicitation mechanism is underscored for the specific application to willpower. While the benefits of immediate gratification seem easily accessible in moment-to-moment measurement of individual affect, this same measure is likely to miss the value that people attribute to resisting a temptation and to exercising willpower. When looking for an empirical tool to collect information about people’s judgment, it is thus important to reveal the concrete metric.

Happiness when temptation overwhelms willpower

5.2.2

101

Empirical Identification of Suboptimal Choices Due to Limited Willpower

Before we discuss the testing strategies based on individual welfare judgments, we briefly mention two previous approaches. Both of them look for patterns of behavior that cannot easily be reconciled with standard utility maximization. Prediction of behavior with indicators of limited self-control This approach starts out with a standard model of individual behavior. It is studied whether the explanatory power of the (empirical) model is increased when the variation in people’s level of self-control is taken into account. Empirically, limited self-control is captured (1) by using behavioral markers, like not having a bank account or having had many hangovers from alcohol consumption in the recent past (see, for example, DellaVigna and Paserman, 2005), (2) by letting people in experiments choose between immediate payoffs and higher delayed payoffs (Thaler, 1981), or (3) by measures of self-report. There is a rich literature in psychology on developing and applying survey measures of self-control (for example, Tangney et al., 2004) or related psychological measures like conscientiousness7 (for an application in economics, see Ameriks et al., 2007) and mastery8. In addition, there are more specific survey measures relying on scenarios (ibid.) or direct reporting of self-control problems in some specific aspect of consumption. Self-infliction of costs A problem of self-control is diagnosed if people are observed spending a lot of time or money on changing their behavior. For instance, in the context of obesity, this ‘smoking gun’ approach looks for evidence like, for example, spending a lot of money on staying at a clinic where mainly sugarless tea is served. More generally, self-binding mechanisms are voluntarily chosen to reduce the utility of some activity or to make short-term revisions of consumption plans less attractive. Ex post evaluation based on individual judgments on the quality of one’s life This approach puts forward a proxy for individual welfare to evaluate choice behavior. Expressed in simple terms, it is studied whether some specific behavioral patterns are related to higher or lower reported subjective well-being. However, the approach is subject to the same econometric difficulties faced by studies that examine the determinants of behavior, that is, the possibility of omitted variable bias and endogeneity bias. Two specific strategies to deal with the issue of endogeneity will be discussed in the following sections on TV viewing and smoking.

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In this section a general strategy is proposed that combines various sources of information to what might be called a thick description of limited willpower and subjective well-being. It is studied whether the ex post evaluation of some behavior systematically varies between groups of people who have differing amounts of willpower. As we will apply this approach to the phenomenon of obesity in Section 5.5, it is also introduced in this context in order to clarify the ideas and arguments. The central hypothesis states obesity makes people worse off in terms of reported subjective well-being if the increased body mass is due to a self-control problem. However, if people are not lacking willpower, a body mass index (BMI) above 30 does not enter negatively into the evaluation of people’s well-being. Any correlation between the level of willpower and subjective well-being as such is statistically captured in the constant term. Three comments serve to clarify the underlying assumptions, strengths and weaknesses of the approach: 1.

It is no problem for the approach if – in terms of an application to obesity – fat people are jollier. The approach does not rely on a specific benchmark correlation between the phenomenon under study and subjective well-being. A strong preference for food (and thus a higher BMI) can be positively or negatively correlated with reported well-being. It is predicted that obese people judge their overall wellbeing less favorably than people of normal weight when they indicate limited willpower rather than when they do not. 2. The approach explicitly and directly tests for effects on individual welfare. Importantly, individuals are free to judge and evaluate a certain life-path. This involves, for example, the weighting of shortterm pleasures versus the pursuit of long-term goals. 3. The testing strategy relies on two qualities of the self-control problem under study. First, individuals are aware of their limited willpower (as self-reports are used). Second, self-control behavior is generalized across different consumption decisions. This means that limited willpower affects behavior across-the-board. Depending on the application, this latter assumption might be questionable. In the case of obesity, it means that a high BMI need not be positively correlated with the exertion of willpower in other areas. There is, however, the possible scenario that people prefer to be weak-willed and fat rather than to be weak-willed and a chain smoker. Weak-willed people who are obese would then not necessarily judge their well-being less favorably than those who are not obese, and the testing strategy fails to identify limited willpower reducing individual welfare.

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The assumption that self-control behavior generalizes across activities, however, can be relaxed in the concrete application. Consumption activities that are close substitutes for people with limited willpower can be simultaneously taken into account in the empirical analysis. In sum, this general strategy combines the idea of exploiting supplementary information on the variation in a person’s level of willpower and the idea of an ex post evaluation based on reported subjective well-being.

5.3 5.3.1

TV VIEWING A Controversial Mass Phenomenon

There are countries where people over their lifetime spend as many hours watching TV as they devote to paid work (Corneo, 2005). TV viewing is thus by far the most important leisuretime activity in modern societies. The largest number of heavy TV viewers9 in Europe is found in Greece. As much as 36.8 percent of the population (age 15 and older) reports that they spend three hours a day or more watching TV. At the other end of the ranking, there are 8.4 percent heavy TV viewers in Switzerland (Frey et al., 2007 based on the European Social Survey). Revealed preference therefore suggests that, for many people, TV consumption is an important source of well-being. This assessment is in contrast to the mixed appraisal of TV viewing in society. Television has been called a ‘plug-in-drug’, keeping people glued to the screen and impeding the enjoyment of more valuable experiences. Accordingly, the expansion of TV consumption has a negative connotation, being associated with a decline in social capital, an increase in violence and crime, and a weakening of democracy.10 In sum, there is a strong popular notion that people watch too much TV. They watch more than they would like to watch, both ex ante and ex post.11 The reason why TV may lend itself to overconsumption is mainly due to the immediate benefits and the negligible immediate marginal cost of engaging in this activity. One just has to push a button. In contrast to going to the cinema, the theater or any outdoor activity, there is no need to be appropriately dressed before leaving the house, and there is no need to buy a ticket or to reserve a seat in advance. Watching TV does not require any special physical or cognitive abilities (Kubey and Csikszentmihalyi, 1990, p. 173). Unlike other leisure activities, TV viewing does not need to be coordinated with other persons. It is quite possible to sit alone in front of the TV, while other leisure activities, such as tennis or golf, require a partner with similar time availability and similar preferences. As

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a consequence, watching TV has, compared to other leisure activities, an exceedingly low or nonexistent entry barrier. At the same time, it offers entertainment value and is considered to be one of the best ways of reducing stress. Moreover, while watching TV immediate marginal costs are even lower and having a remote control is an invitation to ultra short-term optimization (zapping). Many of the costs resulting from such consumption behavior are not experienced immediately, or not predicted at all. These characteristics of the consumption good induce many individuals to fall prey to excessive TV viewing. Here, the role of limited willpower in TV viewing is addressed with regard to consumers’ welfare. It is hypothesized that, for people facing similar restrictions, heavy TV viewing indicates overstrained willpower rather than a love of TV. Accordingly, heavy TV consumption is expected to result in lower reported subjective well-being. In such a situation an increase in the price of TV viewing would be expected to increase the well-being of TV viewers with a self-control problem as the higher price were to serve as a selfbinding mechanism (analogous to the argument in Gruber and Mullainathan, 2005). For most consumers, the price of viewing an additional hour of TV, however, is zero. It is thus not easy to pursue this empirical approach to test the rational consumer hypothesis (at least as long as pay per view is not more common). An interesting alternative might be the extreme case of no TV. While it is definitely not optimal, it might be attractive compared to unrestrained consumption. The introduction of TV would represent a situation for a possible comparison. However, in most countries this technological innovation gained ground too early in the twentieth century in order to be able to match it with data on reported subjective well-being. There are, however, some natural experiments about access to TV that provide some insights as to the consequences of TV for factors that are closely related to individual well-being. A certain Canadian city was unable to receive any TV signals up until 1973, due to its location in a steep valley. Otherwise, it was similar to two cities in the vicinity used as control cases. A study by Williams (1986) suggests that the introduction of TV crowded out other activities, in particular those outside the home, such as taking part in sports’ activities or attending clubs. It also reduced the reading abilities and creative thinking of children and fostered more aggressive behavior and stereotyped ideas about gender roles. TV also reduced the problem solving capacities of adults. Another study by Hennigan et al. (1982), based on a natural experiment, takes a look at the advent of TV in the USA which, due to technical reasons, took place at different times in different places. Petty crime, but not violent crime, increased. Observing the same time period in the USA, Gentzkow (2006) finds that the advent of TV reduced voter turnout.

Happiness when temptation overwhelms willpower

5.3.2

105

The Subjective Well-being of Heavy TV Viewers

Direct evidence on the relationship between TV viewing and reported subjective well-being is scarce. So far, mainly the subjective well-being of heavy TV viewers is analysed, controlling for many individual characteristics. Such an approach is followed in a large study on TV viewing and life satisfaction for 22 European countries in 2002–03 (Frey et al., 2007). It was found that the more people spend time watching TV, the lower their reported satisfaction with life, ceteris paribus. The result of the econometric analysis is consistent with the hypothesis that heavy TV viewers suffer significant reductions in their utility because they are unable to fully control their TV consumption: They watch too much according to their own evaluation.12 Where do the costs of the misallocation of time come from? There are lost alternatives in the present, like engaging in more stimulating activities or socializing. It is, for example, found that people watching a lot of TV spend less time with family and friends and invest less in relational goods in general (Bruni and Stanca, 2008). But there are also costs in the future. One might be tired the next morning because of not getting enough sleep. Seen long term, people might change their beliefs about the world and about the sources of well-being. In particular, the exposure to the healthy, wealthy and good-looking people on TV is expected to increase people’s aspirations with regard to their own body, but also with regard to their consumption standard. There is substantial research on the relationship between TV viewing and materialism (for example, Kasser, 2002) and financial satisfaction (Bruni and Stanca, 2006; Layard, 2005). Most studies find a positive correlation between extensive TV consumption and those outcomes that are related to lower subjective well-being. In the study for 22 European countries mentioned above (Frey et al., 2007), half of the correlation between TV consumption and life satisfaction can be attributed to heavy TV viewers having lower financial satisfaction, attributing more importance to being rich, feeling less safe, trusting other people less and thinking that they are involved less in social activities than their peers.13 Because these costs are not experienced immediately, individuals with time inconsistent preferences are unable to adhere to the amount of TV viewing they planned or which, in retrospect, they would consider optimal for themselves. 5.3.3

Willpower and the Role of the Choice Set

An alternative way of testing whether heavy TV viewers experience reduced individual well-being because of their consumption choice refers

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to people’s opportunity set. Benesch et al. (2006) study whether the effect of having a larger number of TV channels available, that is, a larger choice set, raises people’s subjective well-being, as would be expected by standard economic theory. The expansion and diversification of media supply, due to VCR, cable or satellite has, in many countries, gone hand in hand with increased television viewing time (see the collected studies in Becker and Schoenbach, 1989). Again, the longer time spent in front of the TV set is consistent with rational consumers, as well as with TV viewers who are subject to a self-control problem. A study on the introduction of cable TV in Israel (comparing neighborhoods with a difference-in-difference approach) reports people’s evaluation of their consumption choice (Weimann, 1996). It is found that with cable TV and thus more channels there is a significant increase in the percentage of viewers agreeing to the statements ‘I often watch television more than I intend to’ (28 percent before cable introduction and 41 percent one year after) and ‘watching television is often a waste of time’ (24 percent before cable introduction and 36 percent after). The expanded choice set due to the technological change seems to have led to an increase in the number of people watching more TV than they planned to, or more than they think is good for them.14 Benesch et al. (2006) test the hypothesis based on recent data from the European Social Survey, World Values Survey and Television Key Facts from IP Germany. In a first step consumers who possibly have a self-control problem are identified as those people with a large positive residual in a regression explaining the amount of TV viewing according to individual socio-demographic characteristics (referred to as ‘heavy viewers’). In a second step the effect of a higher number of TV channels on subjective well-being is estimated for heavy TV viewers in comparison with moderate TV viewers. Based on more than 70 000 individual observations from 45 country samples, they find a statistically significantly negative interaction term between (residual) TV viewing and the number of TV channels, and calculate a negative marginal effect of additional TV channels on the wellbeing of heavy viewers. This is consistent with the hypothesis of limited self-control being involved in the phenomenon of mass TV consumption.

5.4

SMOKING

Recently, many Western countries have introduced extended smoking restrictions. Based on the standard economic model, we would predict that smokers would heavily oppose them. Smokers could always voluntarily refrain from smoking and these restrictions are thus only perceived as an additional restriction on the choice set. However, if it is taken into account

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107

that some smokers might suffer limited willpower to quit smoking, they might welcome smoking restrictions as a kind of self-control mechanism. Hersch (2005), in fact, finds for the USA using data from the Current Population Survey that smokers who plan to quit smoking are more supportive of smoking regulations than are other smokers. A similar reasoning holds for tobacco taxes. Different behavioral models can make systematically different predictions for the effect of excise taxes on individual welfare, while they may all predict reduced consumption of the good that is taxed. People suffer a loss when a normal good is taxed, but experience increased utility when the tax helps to overcome a bad habit like smoking. Accordingly, people might oppose sin taxes as being discriminatory against particular pleasures in life or advocate them to encourage individuals to improve their lot. In a nutshell, the standard economic model predicts that recent increases in cigarette taxes and restrictions on smoking reduce smoking and make individuals worse off. A model that incorporates limited willpower, however, predicts that smoking is reduced while individual utility might be increased. Research on happiness can contribute to this debate and directly study the effect of tobacco taxes on people’s subjective well-being. In two longitudinal analyses across the USA and Canadian states Gruber and Mullainathan (2005) perform such a test with data from the General Social Survey. They analyse the effect of changes in state tobacco taxes on the reported happiness of people who are predicted to smoke at the prevailing tobacco tax. They arrive at the result that a real cigarette tax of 50 cents15 significantly reduces the likelihood of being unhappy among those with a propensity to be smokers. In fact, they would, with a 50 cents tax, be just as likely to report being unhappy as those not predicted to be smokers (that is, the proportion of smokers in the lowest happiness category would fall by 7.5 percentage points). This result favors models of time-inconsistent smoking behavior, in which people have problems with self-control.16 Moreover, the result shows that price increases can serve as a self-commitment device. Problems of self-control with smoking also arise due to temptation (Bernheim and Rangel, 2004). Alternative tests would relate the happiness of potential smokers to clean air laws. These tests would capture exogenous changes in cues or moments of temptation. A comparison of results would allow assessing the boundaries of prices as a means of affecting self-regulation. Research findings on subjective well-being with regard to self-control problems with smoking complement other evidence suggesting self-control problems in a systematic way. There is a large market offering all kinds of drugs and therapies to people who want to stop smoking. In fact, eight out

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of ten smokers would like to quit smoking and try it every eight and a half months on average (Gruber and Koszegi, 2001).

5.5 5.5.1

OBESITY Can Obesity be Explained by Genes and Relative Prices?

Obesity is on the rise in many Western countries and, with it, illnesses such as diabetes and heart disease. Observers call it an ‘obesity pandemic’, comparable to big threats such as global warming and bird flu, or talk of it as the epidemiological landslide of the last two decades. Overweight and obesity is defined relative to people’s weight to height ratio in metric units, as captured in the body mass index (BMI): BMI 5 kg/m2. Adults with a BMI ≥ 30 kg/m2 are classified as obese and those with a BMI ≥ 25 kg/m2 as overweight. In many European countries the prevalence of obesity has risen three-fold or more since the 1980s (Sanz-de-Galdeano, 2005; WHO Europe, 2005). In Europe adults today have an average BMI of almost 26.5. Worldwide, the percentage of obese adults varies greatly: around 3 percent in South Korea and Japan, 8 percent in Switzerland, over 22 percent in the UK and more than 30 percent in the USA (Figure 5.1). In the USA adult obesity rates have more than doubled since the 1980s. In the year 2000, three in ten adults were classified as obese (Flegal et al., 2002). Overweight accounts for 10–13 percent of deaths and 8–15 percent of healthy days lost due to disability and premature mortality (DALY) in the European Region (World Health Organization, 2002). A debate has started about the economic causes of this phenomenon, as well as its consequences (see, for example, Cutler et al., 2003; Finkelstein et al., 2005; Rashad, 2006). Increased obesity has been explained as the relationship between energy expenditure and energy intake. Energy expenditure is lower nowadays because manual labor has been replaced by more sedentary work due to technological changes (Lakdawalla and Philipson, 2002). However, this trend started long before the obesity endemic took off. The increase in calories consumed fit the obesity pattern better and is of sufficient magnitude to account for its increased prevalence (Putnum and Allshouse, 1999). In particular, higher snack calories are responsible for higher energy intake for men, and for even higher energy intake for women (Cutler et al., 2003). What is the economic rationale behind the shifting energy household? Looking at relative prices suggests that, since the early 1980s, there has been a decrease in price for calorie-dense foods and drinks compared to

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35 30

Percentage

25 20 15 10 5

Ko Sw J rea itz apa er n N lan or d w ay Ita Au ly s F tri D ran a N en ce et m he a rl rk Sw and e s Po den Be lan lg d Ic ium el a S nd Fi pain n Po lan G rtug d er a C m l ze ch Ire any R lan ep d N C ub ew a lic Ze nad a a H Lu u lan xe ng d m ar Sl o A bo y U vak us urg ni R tra te e li d pu a Ki b ng lic d U ni M om te ex d ic St o at es

0

Note: Percentage of population aged 15 and over, with a BMI greater than 30 (2003 or latest available year). Source:

OECD (2005).

Figure 5.1

Obesity across countries

fruit and vegetables, which are less energy-dense (Finkelstein et al., 2005). These price reductions were made possible by new technologies in food production, in particular for prepackaged and/or prepared food. People have reacted by eating more frequently (snacking), eating bigger portions and spending less time on preparing meals. The question arises how these increases in body weight, causing considerable harm to people’s health, are to be evaluated. Do people eat too much? What is the standard for ‘too much’ if people can choose when and how much they want to eat? Traditional economics advises us to resort to consumer sovereignty under such conditions. Even with full information about the benefits of physical activity, the nutrient content of food, and the health consequences of obesity, some fraction of the population will optimally choose to engage in a lifestyle that leads to weight gain because the costs (in terms of time, money, and opportunity costs) of not doing so are just too high. (Ibid., 2005, p. 252)

This might apply even more because health insurances and taxpayers finance a large amount of the monetary costs of obesity. Moreover,

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obesity can be rationalized, assuming a high discount rate for future outcomes. The argument for variation in individual discount rates as an explanation for increased obesity is put forward, for example, by Komlos et al. (2004).17 However, the possibility of individuals consuming ‘too much’ food is excluded by assumption in the revealed preference approach. Yet, in order to justify this view, one would have to reconcile the prevalence of obesity with other behavioral regularities, like people spending large sums of money on diets and health clubs, or people’s weight yo-yoing as they go from one diet to the next.18 An alternative approach accepts that people might face self-control problems when exposed to the temptation of immediate gratification from food when they are hungry or have a craving for something sweet, fatty or salty (see, for example, Offer 2001). There is a rich literature on the control of eating, emphasizing physiological mechanisms (Blundell and Gillett, 2001; Smith, 2006). In particular, humans are endowed with a system of weight regulation that favors weight gain over weight loss to reduce any future risk of starvation. While this ability was evolutionary advantageous, it is a challenge to conscious control of food intake today. People consume more food and calories and eat more frequently than that they consider good for themselves when they think about and plan their diet. People are aware of this phenomenon, but more so in others than themselves (Taylor et al., 2006). They judge their own and other people’s consumption behavior as irrational in the sense that they think that they would be better off if they would consume less and care more about their future well-being.19 5.5.2

Previous Evidence on Obesity and Subjective Well-being

Reported subjective well-being provides information about people’s evaluation of their situation after they have decided about their food and beverage consumption. Two predictions summarize the conflicting views on the role of limited willpower in obesity. If technical ‘progress’ in producing fatty food is indeed a major driving force behind obesity, the standard economic model predicts that individuals will become heavier and happier. However, if individuals have self-control problems, we would expect them to become heavier and less happy. There is a growing literature on empirical research, studying whether obese people are less satisfied. According to an empirical investigation for roughly 8000 young women, obesity is related to lower satisfaction with work, family relationships, partner relationship and social activities (but not satisfaction with friendships) (Ball et al., 2004). Other studies

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report correlations between obesity and symptoms of depression, whereby the risk of depression is higher for obese women than obese men (for example, McElroy et al., 2004; Needham and Crosnoe, 2005). These findings, however, provide only limited insights, as the correlations can be due to third variables affecting both eating behavior and subjective wellbeing, or because low life satisfaction and stress can lead to obesity. The latter has been studied in a longitudinal analysis for 5867 pairs of twins (Korkeila et al., 1998). It is found that a high level of stress, as well as a low level of life satisfaction, are both predictors of weight gain over six years and for certain groups of people over 15 years of age. Another panel study addresses the reverse relationship. Taking baseline mental health into account, it analyses the long-term consequences of obesity, finding an increased risk for depression (Roberts et al., 2002). These results are valuable to assess the relevance of the phenomenon, but they have to be supplemented with further evidence to identify the contribution of selfcontrol problems to the link between obesity and subjective well-being. Alternatively, it is possible to characterize conditions where attempts to recapture self-control are encouraged. It is to be expected that those people who stand to lose a lot from being obese, or who have access to resources, are more successful in controlling their behavior. For example, obese women seem to suffer a salary and promotion penalty even more than obese men (see, for example, Baum and Ford, 2004; Finkelstein et al., 2005). They have strong incentives to control their body weight and might suffer more when their lack of willpower leads to failure. Consistent with this point of view, people in the top income quintile, or in professions with a low prevalence of obesity, report the largest well-being costs of obesity (Felton and Graham, 2005). People with a higher education or income level are more likely to view themselves as overweight, keeping the level of the BMI constant (Oswald and Powdthavee, 2007). 5.5.3

Willpower, Obesity and Subjective Well-Being

Hypothesis and data Based on the preceding subsection, it is hypothesized that the well-being of people with limited self-control is reduced when they are obese, while the well-being of people with strong willpower is not affected. This hypothesis follows the general testing strategy proposed in section 5.2 in order to better understand suboptimal consumption decisions. Here an empirical analysis is presented based on a unique data set combining information on people’s weight, height, perceived control over their life and eating behavior, as well as a multi-item measure of subjective well-being. The original analysis is developed and described in detail in Stutzer (2007).

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The data are from the Swiss Health Survey 2002 compiled by the Swiss Federal Statistical Office. They combine responses from a telephone survey and a questionnaire mailing going to the same people. The sampling population was the resident population aged 15 and over. Interviewed were 19 706 individuals and 16 141 of them responded to a supplementary written questionnaire. For 19 471 respondents there is complete information about their body mass. Based on a weighted distribution of the BMI index, the percentage of obese people in the adult population amounted to 7.7 percent in 2002, an increase of 2.3 percentage points since 1992. Overweight are 29.4 percent and normal weight are 49.9 percent. There is also a substantial fraction of 13.0 percent having a BMI below 20 and thus being underweight. People’s subjective well-being is assessed using eight questions from the Bern Questionnaire of Subjective Well-Being (Grob et al., 1991). The questions are reported in the Appendix 5A.1. The main analysis is for the compound measure based on the eight items. Variation in self-control between people is assessed using a general measure of reported mastery and a specific measure of reported willpower in pursuing a healthy diet. The mastery scale is from Pearlin et al. (1981), whereby four out of seven questions were included in the survey (see Appendix 5A.1). In the analysed sample 24.1 percent of the subjects report that they feel in control of their life, that is, all questions of limited mastery are completely denied. Domain-specific willpower is derived from the following survey item: ‘Many people – maybe you too – attach importance to a healthy diet. Do you see obstacles for somebody who pursues a healthy diet? Please tick all reasons that apply! . . . “lack of willpower, lack of belief in success” ’. Limited willpower with regard to a healthy diet is reported by 25.5 percent of people in the sample. Results People’s body mass is compared to their subjective well-being.20 According to the basic hypothesis, obesity is expected to negatively affect the subjective well-being of those with limited willpower. For them, obesity is not meant to be the outcome of rational food consumption but rather of time-inconsistent behavior. The dependent variable ‘reported subjective well-being’ is now an ordinal measure. Ordered probit regressions are estimated and marginal effects are calculated for the top category of subjective well-being. For dummy variables, the marginal effects indicate a change in the probability of reporting high subjective well-being. In Table 5.1 results for two different specifications are presented. Specification I includes people’s body mass, dividing it into four categories, as well as categorizations of their age and sex. This specification assures that no other choice variables pick up any potential negative consequence of obesity

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Table 5.1

113

BMI and reported subjective well-being Full Sample

General Indicator of Self-control: Mastery

Specific Indicator of Self-control: Lack of Willpower is an Obstacle to a Healthy Diet

Limited Full Limited Full Self-control Self-control Self-control Self-control Marginal Effects for the Top Category of Subjective Well-being Specification I Underweight Normal weight Overweight Obese Control variables Baseline prob. No. of obs. Pseudo R2 Specification II Underweight Normal weight Overweight Obese

−0.012** (4.43e-3) −0.003 (3.46e-3) −0.014** (5.16e-3) 0.099 15108 0.002 −0.008 (*) (4.32e-3) −0.004 (3.32e-3) −0.008 (5.17e-3)

Control variables Baseline prob. No. of obs. Pseudo R2

0.092 15108 0.021

−0.010** 0.029 −0.012 (3.13e-3) (2.05e-2) (8.18e-3) Reference group −0.001 −0.018 −0.010 (2.66e-3) (1.26e-2) (6.46e-3) −0.012** −0.003 −0.034** (3.76e-3) (2.09e-2) (7.63e-3) Age categories and sex included 0.055 0.230 0.086 10681 3392 3458 0.002 0.004 0.003

−0.011* (5.39e-3)

−0.007* −0.028 −0.010 (3.01e-3) (2.04e-2) (7.71e-3) Reference group −0.002 −0.012 −0.010 (*) (2.49e-3) (1.26e-2) (6.07e-3) −0.008* 0.013 −0.027** (3.69e-3) (2.15e-2) (7.49e-3) All factors included (see appendix A.1) 0.050 0.225 0.078 10681 3392 3458 0.021 0.019 0.027

−0.006 (5.31e-3)

−0.001 (4.18e-3) −0.002 (6.83e-3) 0.097 10117 0.002

−0.002 (4.01e-3) 0.005 (6.88e-3)

0.090 10117 0.021

Note: Marginal effects based on ordered probit regression. Standard errors in parentheses. Significance levels: (*) 0.05 < p < 0.1, * 0.01 < p < 0.05, ** p < 0.01. Source:

Stutzer (2007) based on Swiss Health Survey 2002.

on well-being. Specification II includes a large set of covariates of subjective well-being. The Swiss Health Survey provides sufficient information about individual characteristics to specify a microeconometric well-being function that is similar to the ones usually applied when testing economic issues. Table 5.A1 in the Appendix 5A.1 presents the results for such a specification, including all the control variables and covering the full

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sample. They confirm previous findings in the literature on the correlates of happiness. The findings for the BMI are also shown in the lower half of the first column in Table 5.1. In both equations with the full sample, obesity is negatively correlated with subjective well-being. However, the partial correlation is not statistically significant in specification II. Moreover, the partial correlations are not yet a test of the theoretical prediction. A very high BMI is hypothesized to negatively affect well-being if it is the result of limited self-control, but not otherwise. Therefore, the partial correlation between obesity and subjective well-being are estimated separately for people with full and limited self-control. Both indicators of self-control are applied: mastery and domain-specific willpower. With two specifications each, results from eight estimations are summarized in Table 5.1. Consistent with the basic hypothesis, obesity is related with lower subjective well-being when people have limited self-control but no statistically significant effect is found for the sample of people classified as having full self-control. The marginal effect is largest with specification I for the sample of people who report a lack of willpower as being an obstacle to a healthy diet. The probability of reporting high subjective well-being is 3.4 percentage points lower for people who are obese rather than normal weight, whereby the baseline probability for people in the reference group is 8.6 percent. Together, the pieces of evidence from the study of people’s subjective well-being indicate that the phenomenon of obesity can only be understood when going beyond revealed preference and the assumption of unlimited consumer sovereignty, but taking limited willpower into account. 5.5.4

Three Open Issues

The general approach proposed in this chapter to study the effect of limited willpower on individual welfare raises three related issues that we have not yet taken up. These are the generalization of self-control behavior, reverse causality, and the distinction between outcome and process as possible reasons for reduced well-being when somebody is a heavy TV viewer, a smoker or obese. The three issues are again discussed for the case of obesity. The first issue has to do with the nature of limited willpower. People are exposed to many opportunities, with low immediate marginal costs, but high marginal benefits. The question arises whether people with a selfcontrol problem make myopic decisions when faced with all, or most, of these opportunities, or whether they are able to control some challenges to willpower, but find it too difficult to control all of them. The latter view fits in with the idea that there is a limited capacity for self-regulation.

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Resisting one temptation may result in poorer regulation of a concurrent desire for immediate gratification, or vice versa (Muraven et al., 1998). For the identification of limited willpower in the proposed approach, it has to be assumed that either self-control behavior generalizes across-theboard or tempting activities that are close substitutes have to be taken into account statistically.21 The idea that self-control resembles a muscle might be particularly relevant in understanding the interplay between obesity and smoking (Gruber and Frakes, 2006). People who work at controlling their eating habits might give up on resisting smoking and vice versa. In the presented study by Stutzer (2007) on the negative effect of obesity, information about whether somebody is a smoker or non-smoker is also included. For the main specification II, with the specific indicator of selfcontrol, almost identical marginal effects as before are found. For people with limited self-control, the marginal effect of obesity is −0.026 (−0.027 before). For people with full self-control, the marginal effect of obesity is 0.005 (0.005 before). The main result is thus robust to the inclusion of the closest substitute to yielding to the temptation to overconsume. The second issue concerns causality. To what extent do the consequences of obesity due to limited willpower reduce subjective well-being and to what extent does the experience of reduced well-being lead to stress/ frustration eating and obesity? This is a valid concern, even though based on the approach proposed in this chapter the correlation between obesity and subjective well-being is not interpreted as such, but rather the differential effect for people with full and limited self-control. The data set used in Stutzer (2007) captures whether somebody turns to eating when stressed. Stress eating is found to negatively correlate with subjective well-being in the full sample, keeping body mass constant. Moreover, the marginal effects are sizeable. While the baseline probability of people reporting subjective well-being in the top category is 8.4 percent, this probability is reduced by between 1.7 and 3.7 percentage points if stress eating is not ‘very untypical’ but is either ‘rather untypical’ or ‘very typical’. However, the differential effect of obesity on subjective well-being between people with limited and full self-control is not explained by stress eating. For the general indicator of self-control, the difference in the marginal effects of obesity on individual well-being is slightly larger when comparing people with limited and full selfcontrol. For the specifications applying the specific indicator of self-control, the difference in marginal effects is slightly reduced. However, people who lack the willpower to stick to a healthy diet still report a significantly lower subjective well-being when they are obese (marginal effect is −2.0 percentage points), while there is no such negative effect for people who report full selfcontrol. A direct test for reverse causation thus cannot explain the reduced well-being of obese people in the case of limited willpower.

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The third question is whether reduced willpower as such, rather than its consequences, is responsible for lower well-being. Limited willpower might well repeatedly lead to experiencing frustration because plans regarding one’s diet are not realized. People who experience self-control problems then suffer reduced self-esteem, and thus lower subjective well-being. Related empirical evidence is found in a community sample of 2000 adults (Greeno et al., 1998). In addition to a higher BMI, the lack of perceived eating control was associated with lower satisfaction with life. For men, it was only the lack of eating control that was correlated with reported subjective well-being. This line of reasoning is important in order to understand the relationship between appearance norms, body image and eating disorders (Derenne and Beresin, 2006). In the analysis presented above, this aspect is not studied directly. However, the effect of limited willpower on the level of people’s well-being is statistically taken into account when estimating separate equations as it enters into the constant term.

5.6

CONCLUDING REMARKS

This chapter has started out with the provocative question on how to judge whether people make suboptimal consumption choices according to their own evaluation. Within standard neoclassical economics this issue would not have been raised. Standard economic theory assumes that individuals do not commit any systematic errors in their consumption decisions, because they know their own preferences best and are able to make and implement the consequent choices. Limited willpower is no concern. No doubt, it is very likely that individuals are quite capable of making satisfactory consumption decisions for most of the goods most of the time. The main message of this chapter is that it is necessary to go beyond this narrow approach. One should take into account the methodological advances made possible by happiness research. They allow us to empirically test whether individuals do or do not make suboptimal decisions due to limited willpower, rather than simply assuming that they do not, as is the case in revealed preference theory. The possibility to proxy individual welfare in a satisfactory way using data on reported subjective well-being enables economists to empirically study the difference between decisions made and the individual welfare produced. We see a large potential in this approach to study many areas of consumption choice for which popular discourse and most other disciplines acknowledge people’s difficulties in the pursuit of happiness. The proposed approach, however, also requires particular transparency as every empirical analysis gives priority to a specific measure of subjective

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well-being as a criterion of individual welfare. This involves a strong normative judgment. We are aware that different indicators of individual welfare potentially offer different evaluations of what are suboptimal decisions. They thus capture different aspects of people’s pursuit of happiness. For example, people might gain utility from exerting willpower because they have resisted a temptation. Or they judge their life favorably because their life course contributes to positive self-signaling, identity, goal completion, mastery or meaning (for economic analyses of these human motives see, for example, Akerlof and Kranton, 2000; Loewenstein, 1999). When thinking about policy proposals, it is important to know whether and to what extent people face a self-control problem when tempted by the abundance of consumption opportunities. For instance, take the abundance of food and the observed obesity. Is obesity rational and reflecting an appetite for food so that it can be reduced to an issue of externalities in a publicly regulated and funded health system? Or does it reflect ignorance and a lack of imagination of its consequences, requiring some sort of information policy? Or must obesity be treated like smoking, where some people lack willpower to control their behavior? The challenge for research is to disentangle the various behavioral reasons for obesity. But even if these questions can be answered for the three specific areas discussed, the suboptimal consumption patterns due to limited willpower are no cause for immediate government intervention. Moreover, it is doubtful whether ‘the government’ is able to make better decisions in the interests of the persons concerned (see Frey and Stutzer, 2006). It is presumably more effective to support individuals subject to self-control problems by providing ways of overcoming their weakness, for example by proposing self-binding mechanisms (for a broader discussion see, for example, O’Donoghue and Rabin, 2005). It should thus be clear that this analysis is not a normative evaluation from the point of view of a benevolent social planner. Rather, the focus is on the suboptimal choices in consumption that individuals commit according to their own perception, placing people in a less favorable position in terms of their own welfare evaluation. Thus the policy goal remains a search for institutions under which suboptimal choices are less likely and people are better off accepting their limited willpower.

NOTES 1.

I am grateful to Thomas Brändle, Bruno Frey and Michael Zehnder and the participants of the Conference on New Directions in the Study of Happiness at the University of Notre Dame for helpful comments.

118 2. 3. 4.

5. 6. 7.

8. 9. 10. 11. 12. 13. 14.

15. 16.

17. 18.

Happiness, economics and politics In a recent debate on behavioral welfare economics the possibilities and limits of a choice-based approach to identify mistakes have been controversially discussed (see Bernheim and Rangel, 2007; Gul and Pesendorfer, 2007; Koszegi and Rabin, 2007). For an introduction to the economics of happiness, see, for example, Frey and Stutzer (2002a, b), Layard (2005) and Frey (2008). In economics time inconsistent preferences are most prominently formulated in models of hyperbolic discounting (see, for example, Laibson, 1997). A low discount factor (that is, a discount factor decreased by b, b [ (0,1)) is applied between the present and some point in time in the near future and a constant discount factor d thereafter. An excellent account of the recent extensive empirical and theoretical literature on time inconsistent preferences is provided in Frederick et al. (2002). An excellent account of the ambiguities of welfare in the context of economics and hedonic psychology is provided in Kelman (2005). There is in fact a debate in happiness research about how to measure subjective wellbeing that might be better understood from the angle of proponents’ preferred welfare concept (see Helliwell, 2006; Kahneman and Riis, 2005; Kahneman et al., 2004). ‘Conscientiousness describes socially prescribed impulse control that facilitates taskand goal-directed behaviors, such as thinking before acting, delaying gratification, following norms and rules, and planning, organizing, and prioritizing tasks’ (John and Srivastava, 1999, p. 121). ‘Mastery refers to the extent to which people see themselves as being in control of the forces that importantly affect their lives’ (Pearlin et al., 1981, p. 340). By ‘heavy TV viewers’, people are meant who spend a great deal of time watching TV, and not TV viewers who are overweight (although watching a lot of TV is sedentary and invites people to snack, which can in turn lead to obesity). The case for negative impacts of TV consumption on society is, for example, made by Kubey (1996), Putnam (2000), Sparks and Sparks (2002) and Gentzkow (2006). Regarding television consumption, there is some (anecdotal) evidence that individuals may have self-control problems. Forty percent of US adults and 70 percent of US teenagers admit that they watch too much TV (Kubey and Czikszentmihalyi, 2002). However, the potential correlation is also consistent with a hypothesis according to which unhappy people resort to TV viewing. This might lead to a mutually reinforcing relationship. While these correlations are suggestive, it has to be kept in mind that third factors could be driving differences in the different attitudes as well as in TV viewing. Asking people directly whether they think that they watch too much TV could lead to answers that are motivated by social desirability. It should be noted that surveys on general life satisfaction are less likely to be affected by such a bias, at least not one that is systematically correlated with some specific consumption behavior. The average real (in 1999 US$) cigarette tax in the USA is 31.6 cents in the sample (Gruber and Mullainathan, 2005, p. 5). In another study the negative internality from suffering a self-control problem and being a smoker is assessed (Jürges, 2004). The monthly compensation required to make a smoker as well off as a nonsmoker is estimated to be approximately 500 euros. However, the effects of smoking on life satisfaction were not identified, based on changes in exogenous conditions restricting the possibilities to smoke. In an empirical analysis for the Netherlands Borghans and Golsteyn (2006) conclude, however, that it is unlikely that BMI increased because of an increase in the timediscount rate. This argumentation on the revealed preference approach does not exclude that observed behavior can give clear indications of a problem with the control of body mass, for example, when people inflict costs on themselves in order to make eating chocolate less attractive. However, the revealed preference approach gives no reason to search for such contradictory patterns in consumption behavior. On the contrary, it urges the researcher to look for rationalizations.

Happiness when temptation overwhelms willpower 19.

20.

21.

119

With regard to obesity, the self-control issue is explicitly addressed in Cutler et al. (2003), whereby its relevance in the assessment of consumers’ welfare is discounted because it would require only some exercise on the part of overweight people to balance their energy household. Observed inactivity thus seems to indicate that overweight people do not suffer from their body mass. However, the trade-off is calculated, assuming that people have self-control problems with eating, but not with taking physical exercise. This asymmetry does not fit our casual observations. Stutzer (2007) also studies the covariates of body mass in a multinomial regression analysis. In addition to standard demographic and socio-economic factors, indicators of ignorance and limited willpower are included. It is found that people who report that health is not a relevant issue for them are statistically significantly more likely to be obese than people who report that health is either relevant or very important for them. The relative risk ratio indicates a 1.51 greater probability. Consistent with this, people who care about their diet are less likely to be obese, with a risk ratio of 0.81 relative to people who do not care. Moreover, people who report a lack of willpower when it comes to a healthy diet have a higher probability of being obese, the relative risk ratio being 1.41. This condition can also explain why a domain-specific indicator of willpower is a better predictor of obesity and reduced well-being of obese people than a general indicator of perceived control.

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Camerer, Colin, George Loewenstein and Matthew Rabin (eds) (2004), Advances in Behavioral Economics, New York: Russell Sage Foundation. Corneo, Giacomo (2005), ‘Work and television’, European Journal of Political Economy, 21 (1), 99–113. Csikszentmihalyi, Mihaly and Jeremy Hunter (2003), ‘Happiness in everyday life: the uses of experience sampling’, Journal of Happiness Studies, 4 (2), 185–99. Cutler, David M., Edward L. Glaeser and Jesse M. Shapiro (2003), ‘Why have Americans become more obese?’, Journal of Economic Perspectives, 17 (3), 93–118. De Cremer, David, Marcel Zeelenberg and J. Keith Murnighan (eds) (2006), Social Psychology and Economics, Mahwah, NJ: Lawrence Erlbaum. DellaVigna, Stefano and M. Daniele Paserman (2005), ‘Job search and impatience’, Journal of Labor Economics, 23 (3), 527–88. Derenne, Jennifer L. and Eugene V. Beresin (2006), ‘Body image, media, and eating disorders’, Academic Psychiatry, 30 (3), 257–61. Felton, Andrew and Carol Graham (2005), ‘Variance in obesity across cohorts and countries: a norms-based explanation using happiness surveys’, Mimeo, The Brookings Institution. Finkelstein, Eric A., Christopher J. Ruhm and Katherine M. Kosa (2005), ‘Economic causes and consequences of obesity’, Annual Review of Public Health, 26, 239–57. Flegal, Katherine M., Margaret D. Carroll, Cynthia L. Ogden and Clifford L. Johnson (2002), ‘Prevalence and trends in obesity among US adults, 1999–2000’, JAMA, 288 (14), 1723–7. Frederick, Shane, George Loewenstein and Ted O’Donoghue (2002), ‘Time discounting and time preference: a critical review’, Journal of Economic Literature, 40 (2), 351–401. Frey, Bruno S. (2008), Happiness: A Revolution in Economics, Cambridge, MA: MIT Press. Frey, Bruno S. and Alois Stutzer (2002a), Happiness and Economics: How the Economy and Institutions Affect Well-Being, Princeton, NJ and Oxford: Princeton University Press. Frey, Bruno S. and Alois Stutzer (2002b), ‘What can economists learn from happiness research?’, Journal of Economic Literature, 40 (2), 402–35. Frey, Bruno S. and Alois Stutzer (2006), ‘Mispredicting utility and the political process’, in Edward J. McCaffery and Joel Slemrod (eds), Behavioral Public Finance, New York: Russell Sage Foundation, pp. 113–40. Frey, Bruno S. and Alois Stutzer (eds) (2007), Economics and Psychology. A Promising New Cross-Disciplinary Field, Cambridge, MA: MIT Press. Frey, Bruno S., Christine Benesch and Alois Stutzer (2007), ‘Does watching TV make us happy?’, Journal of Economic Psychology, 28 (3), 283–313. Gentzkow, Matthew (2006), ‘Television and voter turnout’, Quarterly Journal of Economics, 121 (3), 931–72. Greeno, Catherine G., Christine Jackson, Elizabeth L. Williams and Stephen P. Fortmann (1998), ‘The effect of perceived control over eating on the life satisfaction of women and men: results from a community sample’, International Journal of Eating Disorders, 24 (4), 415–19. Grob, Alexander, Ruth Luthi, Florian G. Kaiser and August Flammer (1991), ‘Berner Fragebogen zum Wohlbefinden Jugendlicher (Bfw)’. The Bern subjective well-being questionnaire for adolescents (Bfw), Diagnostica, 37 (1), 66–75.

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Gruber, Jonathan H. and Botond Koszegi (2001), ‘Is addiction “Rational”? Theory and evidence’, Quarterly Journal of Economics, 116 (4), 1261–303. Gruber, Jonathan H. and Michael Frakes (2006), ‘Does falling smoking lead to rising obesity?’, Journal of Health Economics, 25 (2), 183–97. Gruber, Jonathan H. and Sendhil Mullainathan (2005), ‘Do cigarette taxes make smokers happier?’, Advances in Economic Analysis and Policy, 5 (1), 1–43. Gul, Faruk and Wolfgang Pesendorfer (2007), ‘Welfare without happiness’, American Economic Review, 97 (2), 471–6. Helliwell, John F. (2006), ‘Well-being, social capital and public policy: what’s new?’, Economic Journal, 116 (510), C34–C45. Hennigan, Karen M., Linda Heath, J.D. Wharton, M.L. Delrosario, T.D. Cook and B.J. Calder (1982), ‘Impact of the Introduction of Television on Crime in the United-States: empirical-findings and theoretical implications’, Journal of Personality and Social Psychology, 42 (3), 461–77. Hersch, Joni (2005), ‘Smoking restrictions as a self-control mechanism’, Journal of Risk and Uncertainty, 31 (1), 5–21. Hsee, Christopher K., Yuval Rottenstreich and Alois Stutzer (2008), ‘Suboptimal choices and the need for experienced individual well-being in economic analysis’, Mimeo, University of Basel. John, Oliver P. and Sanjay Srivastava (1999), ‘The big five trait taxonomy: history, measurement, and theoretical perspectives’, in Lawrence A. Pervin and Oliver P. John (eds), Handbook of Personality: Theory and Research, New York: Guilford Press, pp. 102–38. Jürges, Hendrik (2004), ‘The welfare costs of addiction’, Schmollers Jahrbuch, 124 (3), 327–53. Kahneman, Daniel and Jason Riis (2005), ‘Living, and thinking about it: two perspectives on life’, in Felicia A. Huppert, Nick Baylis and Barry Keverne (eds), The Science of Well Being, Oxford: Oxford University Press, pp. 285–301. Kahneman, Daniel, Jack L. Knetsch and Richard H. Thaler (1991), ‘The endowment effect, loss aversion, and status quo bias: anomalies’, Journal of Economic Perspectives, 5 (1), 193–206. Kahneman, Daniel, Alan B. Krueger, David A. Schkade, Norbert Schwarz and Arthur A. Stone (2004), ‘A survey method for characterizing daily life experience: the day reconstruction method’, Science, 306 (5702), 1776–80. Kasser, Tim (2002), The High Price of Materialism, Cambridge, MA: MIT Press. Kelman, Mark (2005), ‘Hedonic psychology and the ambiguities of “Welfare”’, Philosophy and Public Affairs, 33 (4), 391–412. Komlos, John, Patricia K. Smith and Barry Bogin (2004), ‘Obesity and the rate of time preference: is there a connection?’, Journal of Biosocial Science, 36 (2), 209–19. Korkeila, M., J. Kaprio, A. Rissanen, M. Koskenvuo and T.I.A. Sorensen (1998), ‘Predictors of major weight gain in adult Finns: stress, life satisfaction and personality traits’, International Journal of Obesity, 22 (10), 949–57. Koszegi, Botond and Matthew Rabin (2007), ‘Mistakes in choice-based welfare analysis’, American Economic Review, 97 (2), 477–81. Kubey, Robert (1996), ‘Television dependence, diagnosis, and prevention: with commentary on video games, pornography, and media education’, in Tannis M. Williams (ed.), Tuning into Young Viewers: Social Science Perspectives on Television, Thousand Oaks, CA: Sage, pp. 221–60.

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Kubey, Robert and Mihaly Csikszentmihalyi (1990), Television and the Quality of Life. How Viewing Shapes Everyday Experience, Hillsdale, NJ: Lawrence Erlbaum Associates. Kubey, Robert and Mihaly Czikszentmihalyi (2002), ‘Television addiction is no mere metaphor’, Scientific American, 286 (2), 74–80. Laibson, David (1997), ‘Golden eggs and hyperbolic discounting’, Quarterly Journal of Economics, 112 (2), 443–77. Lakdawalla, Darius and Tomas Philipson (2002), ‘The growth of obesity and technological change: a theoretical and empirical examination’, NBER Working Paper No. 8946, Cambridge, Massachusetts. Layard, Richard (2005), Happiness: Lessons from a New Science, New York: Penguin. Loewenstein, George (1999), ‘Because it is there: the challenge of mountaineering . . . for utility theory’, Kyklos, 52 (3), 315–44. McElroy, Susan L., Renu Kotwal, Shishuka Malhotra, Erik B. Nelson, Paul E. Keck and Charles B. Nemeroff (2004), ‘Are mood disorders and obesity related? A review for the mental health professional’, Journal of Clinical Psychiatry, 65 (5), 634–51. Muraven, Mark, Dianne M. Tice and Roy F. Baumeister (1998), ‘Self-control as limited resource: regulatory depletion patterns’, Journal of Personality and Social Psychology, 74 (3), 774–89. Needham, Belinda L. and Robert Crosnoe (2005), ‘Overweight status and depressive symptoms during adolescence’, Journal of Adolescent Health, 36 (1), 48–55. O’Donoghue, Ted and Matthew Rabin (2005), ‘Incentives and self-control’, Mimeo, Cornell University and University of California at Berkley. OECD (2005), OECD Factbook 2005: Economic, Environmental and Social Statistics, Paris: OECD. Offer, Avner (2001), ‘Body weight and self-control in the United States and Britain since the 1950s’, Social History of Medicine, 14 (1), 79–106. Oswald, Andrew and Nattavudh Powdthavee (2007), ‘Obesity, unhappiness, and the challenge of affluence: theory and evidence’, Economic Journal, 117 (523), F441–59. Pearlin, Leonard I., Elizabeth G. Menaghan, Morton A. Lieberman and Joseph T. Mullan (1981), ‘The stress process’, Journal of Health and Social Behavior, 22 (4), 337–56. Putnam, Robert D. (2000), Bowling Alone: The Collapse and Revival of American Community, New York: Simon & Schuster. Putnum, Judith Jones and Jane E. Allshouse (1999), ‘Food consumption, prices, and expenditures, 1970–1997’, Food and Rural Economic Division, Economic Research Service, Statistical Bulletin No. 965, US Department of Agriculture, Washington, DC. Rabin, Matthew (1998), ‘Psychology and economics’, Journal of Economic Literature, 36 (1), 11–46. Rashad, Inas (2006), ‘Structural estimation of caloric intake, exercise, smoking, and obesity’; Quarterly Review of Economics and Finance, 46 (2), 268–83. Roberts, Robert E., William J. Strawbridge, Stephane Deleger and George A. Kaplan (2002), ‘Are the fat more jolly?’, Annals of Behavioral Medicine, 24 (3), 169–80. Sanz-de-Galdeano, Anna (2005), ‘The obesity epidemic in Europe’, Discussion Paper No.1814, IZA, Bonn.

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Scollon, Christie Napa, Chu Kim Prieto and Ed Diener (2003), ‘Experience sampling: promises and pitfalls, strengths and weaknesses’, Journal of Happiness Studies, 4 (1), 5–34. Smith, Trenton G. (2006), ‘Reconciling psychology with economics: obesity, behavioral biology, and rational overeating’, Working Paper No. 2006-4, School of Economic Sciences, Washington State University. Sparks, Glenn G. and Cheri W. Sparks (2002), ‘Effects of media violence’, in Jennings Bryant and Dolf Zillmann (eds), Media Effects. Advances in Theory and Research, Mahwah, NJ: Lawrence Erlbaum Associates, pp. 269–85. Stutzer, Alois (2007), ‘Limited self-control, obesity and the loss of happiness’, WWZ Discussion Paper No. 0707, University of Basel. Tangney, June P., Roy F. Baumeister and Angie Luzio Boone (2004), ‘High selfcontrol predicts good adjustment, less pathology, better grades, and interpersonal success’, Journal of Personality, 72 (2), 271–324. Taylor, Paul, Cary Funk and Peyton Craighill (2006), ‘Americans see weight problems everywhere but in the mirror. A social trends report’, Pew Research Center, Washington, DC. Thaler, Richard H. (1981), ‘Some empirical evidence on dynamic consistency’, Economic Letters, 8 (3), 201–7. Weimann, Gabriel (1996), ‘Cable comes to the holy land: the impact on cable TV on Israeli viewers’, Journal of Broadcasting & Electronic Media, 40, 243–57. WHO Europe (2005), ‘The challenge of obesity in the WHO European Region’, Fact Sheet EURO, 13. Williams, Tannis Macbeth (ed.) (1986), The Impact of Television. A Natural Experiment in Three Communities, Orlando, FL: Academic Press. World Health Organization (2002), The World Health Report 2002, Geneva: World Health Organization.

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APPENDIX 5A.1

SCALES APPLIED IN THE SWISS HEALTH SURVEY AND STUDIED IN STUTZER (2007)

Subjective Well-being (translated from Grob et al., 1991) To what extent do the following statements apply to you? ● ● ● ● ● ● ● ●

My future looks bright. I enjoy life more than most people. I am satisfied with how my life plans materialize. I deal well with those things in my life that cannot be changed. Whatever happens, I make the best out of it. I enjoy my life. My life is meaningful to me. My life is on the right track.

Possible answers: 1 5 completely wrong, 2 5 very wrong, 3 5 rather wrong, 4 5 rather accurate, 5 5 very accurate, 6 5 completely accurate. The responses are added together (SWB_tot) and summarized on a six point scale according to the following criteria: SWB_tot .5 44 & SWB_tot ,5 48 S SWB 5 6 SWB_tot .5 40 & SWB_tot , 44 S SWB 5 5 SWB_tot .5 36 & SWB_tot , 40 S SWB 5 4 SWB_tot .5 32 & SWB_tot , 36 S SWB 5 3 SWB_tot .5 28 & SWB_tot , 32 S SWB 5 2 SWB_tot .5 8 & SWB_tot , 28 S SWB 5 1 Mastery (based on four out of seven questions from Pearlin et al., 1981) When you think about your life, how strongly do you agree or disagree with these statements about yourself? ● ● ● ●

There is really no way I can solve some of the problems I have. Sometimes I feel that I’m being pushed around in life. I have little control over the things that happen to me. I often feel helpless in dealing with the problems of life.

Possible responses: completely agree, rather agree, rather disagree, completely disagree.

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Table 5.A1

125

Covariates of subjective well-being in Switzerland, 2002 Ordered probit regression Coefficient

BMI Underweight Normal weight Overweight Obese Demographic factors Age 15–19 Age 20–24 Age 25–29 Age 30–34 Age 35–39 Age 40–44 Age 45–49 Age 50–54 Age 55–59 Age 60–64 Age 65–69 Age 70–74 Age 75–79 Age 80 and older Female Level of education Mandatory schooling Secondary general edu. Secondary prof. education Tertiary professional edu. University Marital status Married Single Widowed Divorced Separated Household composition 1 adult 2 adults

−0.053(*) −0.022 −0.047 0.125(*) 0.293** 0.195** 0.120**

z-value

Marginal effect for a score of 6

−1.91 −0.008(*) Reference group −1.08 −0.004 −1.42 −0.008

z-value

−1.96 −1.09 −1.46

−0.064(*) −0.040 −0.037 0.034 0.135** 0.353** 0.357** 0.405** 0.525** 0.086**

1.74 0.022 5.04 0.058** 4.39 0.036** 3.35 0.021** Reference group −1.78 −0.010(*) −1.01 −0.006 −0.88 −0.006 0.83 0.006 3.04 0.024** 5.86 0.071** 5.39 0.072** 5.74 0.084** 6.68 0.117** 4.11 0.014**

1.62 4.33 3.96 3.15 −1.84 −1.03 −0.90 0.82 2.83 4.96 4.53 4.73 5.27 4.12

−0.047 0.030

Reference group −1.09 −0.008 1.07 0.005

−1.12 1.07

0.104**

2.71

0.018*

2.57

0.021

0.50

0.004

0.49

−0.214** −0.077(*) −0.113** −0.238**

Reference group −6.37 −0.033** −1.76 −0.012(*) −3.02 −0.018** −3.18 −0.034**

−6.78 −1.84 −3.22 −3.78

0.098**

Reference group 3.28 0.016**

3.29

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Table 5.A1

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(continued) Ordered probit regression Coefficient

3 adults 4 adults and more No children 1 child 2 children 3 children and more Citizenship status Foreigner Main life circumstances Full-time job Part-time job Family business In education Unemployed Housework Retired Chronically ill Income Ln(equivalence income) No. of obs. Pseudo R2

0.095* 0.182** 0.049 0.063(*) 0.123*

z-value

Marginal effect for a score of 6

2.40 0.016* 3.97 0.033** Reference group 1.55 0.008 1.83 0.011(*) 2.53 0.022*

z-value

2.28 3.61 1.51 1.78 2.36

−0.119**

−4.06

−0.018**

−4.33

−0.059* 0.121 −0.004 −0.367** −0.027 −0.182** −0.578**

Reference group −2.56 −0.010** 1.04 0.022 −0.08 −0.001 −5.46 −0.048** −1.02 −0.004 −3.46 −0.028** −9.23 −0.065**

−2.62 0.97 −0.08 −7.20 −1.03 −3.75 −14.40

1.415** 15 108 0.021

8.43

0.422**

6.56

Note: Ordered probit regression. Further control variables not shown are ‘education not defined’, ‘other paid activity’, ‘other life circumstances’, ‘income not available’, ‘interview in French’, ‘interview in Italian’. Significance levels: (*) 0.05 < p <0.1, * 0.01 < p < 0.05, ** p < 0.01. Source: Stutzer (2007) based on Swiss Health Survey 2002.

6.

Happiness and the relative consumption hypothesis Amitava Krishna Dutt1

6.1

INTRODUCTION

A popular bumper sticker from the 1980s declares that the person ‘who dies with the most toys wins’. Whether or not it was intended to be ironic, the statement faithfully reflects the popular perception that more is better and that success is measured in terms of money and the ability to consume. The sentiment is also reflected in the view adopted by mainstream neoclassical economics that utility depends on the amount of goods and services consumed: loosely speaking, people prefer more to less, and that the (desirable) efficiency of the economy is measured in terms of the goods and services available. While such a view has always found dissenters – among, for instance, moral philosophers and religious traditions, and among those who are concerned with the effects of consumerism on the environment and community – it has recently been found to be at variance which a large amount of data on the relationship between people’s self-reported happiness and their income and consumption. The pioneering contributions of Easterlin (1974, 1995, 2001), and subsequent work by Oswald (1997), Deiner and Oishi (2000) and Frey and Stutzer (2002), among others, suggest a number of empirical regularities. Time series data for individual countries do not reflect significant (and in some cases any) increases in the average level of self-reported happiness over time, despite significant increases in income and consumption. Panel data on specific individuals over their lives suggest that despite increases in income, these individuals usually do not show significant increases in self-reported happiness. Cross-sectional studies across countries suggest that countries with higher levels of per capita income and consumption do not have higher average levels of selfreported happiness beyond a certain level of income which is far below the income of the rich countries of the world. Even individuals who win lotteries have been found to report no greater happiness after a few years. To be sure, there is some support for the consumption-happiness connection. 127

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Cross-sectional studies within countries seem consistent with it: people in higher income groups with higher levels of consumption report higher levels of self-reported happiness than people in lower income groups; it seems that it is better to be rich than poor in a particular society at a particular point in time. Cross-country studies suggest a positive income-happiness link at low levels of income and, some have suggested, even at higher levels of income. A few studies find that in some cases people are happier – even if temporarily – if their consumption and income increases. However, the bulk of the evidence seems to contradict the consumption-happiness relationship. Many explanations have been proposed for why people (at least those who are able to) continue to increase their levels of consumption, seemingly without bounds, and why doing so fails to (at least significantly) make them happier. This chapter argues that the relative consumption hypothesis, which makes individual happiness depend on their consumption relative to the consumption of others in addition to their absolute level of consumption (and other determinants), offers a simple, powerful and fairly comprehensive way of explaining the paradox. This hypothesis – in some form – has been widely discussed in the literature. This chapter contributes by providing a simple formulation and geometric presentation of it (Section 6.3), by comparing it to alternative formulations and explanations of the hypothesis (Section 6.4), discussing its explanatory power in relation to that of competing hypothesis (Section 6.5) and by discussing some implications of it to illustrate its ability to explain some empirical findings concerning happiness and economics (Section 6.6).

6.2

THE RELATIVE CONSUMPTION HYPOTHESIS

A hypothesis about the dependence of an individual’s consumption, and of its effects on that individual’s satisfaction, on the consumption by others has been expressed in a number of ways, including: consuming because others consume, positional consumption, interdependent consumption and preferences, and the relative consumption hypothesis. Although it is not clear that these expressions are precisely equivalent, they seem to involve two main features: first, that the consumption level of individuals depends positively on what (at least some) others consume, and second that the level of utility, satisfaction or happiness that people obtain from consumption is affected by what an individual consumes in comparison to what others consume. A simple formalization of these ideas, following the suggestion of Duesenberry (1949), is obtained by assuming that the consumer’s utility

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129

depends on their consumption relative to that of others, in addition to the absolute level of consumption and other relevant variables. Thus, we assume ui 5 u (ci, ci/c, xi, X ),

(6.1)

where ci denotes the level of consumption of individual i, c the average level of consumption of all individuals, xi a vector of all other influences on the utility of individual i which are specific to that individual (for instance, time spent on leisure by the individual, whether one is unemployed or not), and X a vector of all societal or general influences on the utility of the individual (for instance, the state of the environment, the general rate of unemployment and the nature of government). The partial derivative u1 can be taken to be positive out of deference for the standard approach to consumption. The central feature of the present approach is that the partial u2 is positive, and depicts the notion that the utility derived by an individual depends on the consumption level of that person relative to the average consumption of others, or what is referred to as relative consumption. The other two arguments, with individual partials depending on the nature of the relevant variable, are meant to take into account other relevant influences on happiness. The notion that an individual’s consumption increases when the consumption of others (represented by c) increases requires some restrictions on the utility function, as we shall see shortly. To embed such a utility function into a complete model of the economy we take a simple example of this utility function given by ui 5 u (ci, ci/c, li),

(6.2)

where li denotes the number of hours of leisure for person i.2 In addition to assuming that ui . 0 for all i, we assume that all individuals have a production function given by yi 5 y(ni),

(6.3)

where y9 . 0 and y0 # 0. Individuals need to satisfy their budget or production constraint, ci # yi

(6.4)

li 1 ni 5 1,

(6.5)

and the time constraint

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u2 u1

ci

u i2

u i1

E2

y

E1

0

ni

Figure 6.1

li

1

Social sub-optimality of equilibrium

where the total time available to an individual is normalized to unity. Each individual maximizes utility by choosing ci, li, and ni, taking as given c. This simple model can be analysed graphically using Figure 6.1. This figure uses three sets of curves. First, the production function is shown by line y. Second, we can draw the consumer indifference curves over consumption and leisure assuming that the individual’s consumption is equal to the average level of consumption. Assuming ci 5 c, we obtain the indifference map of the individual i, from the utility function u (ci 1, li). Indifference curves from this map are shown by the solid lines marked uj. The highest indifference curve that the individual can reach on the indifference map given the production function is u1. If this were the consumer’s indifference map (which it is not, since it is a hypothetical one drawn for ci 5 c), the consumer would choose point E1. Third, we have the individual’s actual indifferent curve with c given. Draw the individual’s indifference curve through this point with c given by the consumption level at E1. This indifference curve will be flatter than the hypothetical one shown by u1, since the additional consumption required to compensate for a given reduction in leisure is less than in the hypothetical case, because additional consumption yields additional utility

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131

for both absolute and relative consumption reasons, as long as u2 . 0. The indifference curve is shown by the dashed indifference curve u1i . The individual’s indifference map for a given level of c is shown by the dashed indifference curves. For this indifference map individual’s utility, for the given level of c, is maximized at E2. The individual’s equilibrium for the given level of c shown by the level of consumption at E1 is therefore at a higher level of consumption and labor and a lower level of leisure than what is shown at E1. Since all individuals are identical because they have identical utility and production functions, their consumption level is equal to the average consumption level. Thus, point E2 need not be the equilibrium for the economy, at which not only is each individual maximizing utility given the average level of consumption, but also each individual’s consumption is equal to the average level of consumption. If we assume, to begin with, that a rise in the average level of consumption leaves the shape of the indifference curves unchanged by changes in the average level of consumption but reduces the level of utility denoted by each indifference curve, then E2 is indeed the equilibrium of the economy, since the individual chooses the same point whatever the average level of consumption. At this equilibrium it is clear that each individual obtains a lower level of utility than at E1. Since in equilibrium each individual’s consumption is equal to the average level of consumption, the solid indifference curves denote the correct level of utility. Since E2 is on lower indifference curves than is E1 (since u2 , u1), all individuals are worse off at the equilibrium at E2 than at E1, which yields the highest level of utility under the condition that all individuals consume at the same level. Our assumption that the individual’s optimal level of consumption is independent of the average level of consumption of all individuals contradicts the notion that people consume more because others do so. For the model to ensure that people consume more when others do, a rise in c must make the indifference curve of the consumer flatter at point E2, so that the individual’s new equilibrium will be to the right of E2.3 If this condition holds, ci rises with c, implying a reaction curve for the ith individual given by ci 5 r(c) with r9 . 0. With some further restrictions on the utility function which ensure that r9 , 1 we can show that there will exist an equilibrium at which c 5 r(c), which determines the equilibrium for the economy. This equilibrium will lie to the right of E2. However, it will remain true that at this equilibrium the dashed indifference curve (with given c) will be flatter than the solid indifference curve (with ci 5 c), so that, as shown earlier, the equilibrium level of consumption will imply

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a higher level of consumption and work, and a lower level of leisure, than at the socially optimal level shown by E1. The consumption externality (due to the fact that c enters as an argument in the individual utility function), as one would expect, implies that the equilibrium for the model is not socially optimal. But does the model also imply that growth increases consumption without significantly improving utility? Suppose that economic growth results from an exogenous improvement in technology. Consider the special case in which the production function reflects constant returns to labor, so that it is a straight line through the origin, as in Figure 6.2. Assume that technological change shifts the production function from y1 to y2. The equilibrium with the production function at y1 is shown by E1, where the production line is tangent to the dashed indifference curve showing utility level u1i . When the production line shifts to y2, suppose first that the effect of increases in ci on the effect on the marginal rate of substitution between consumption and leisure is ‘small’ (which is more likely to hold if the curvature of the indifference curves is small), so that the individual moves from E1 to a point on the y2 line to the right of E1. Since ci increases, average consumption, c, also increases, which, as discussed earlier, makes the individual’s indifference map become flatter, as shown by the dotted indifference curve. This flattening of the indifference curve and the fact that the production line is steeper pushes the individual’s equilibrium choice to the right of E1, to a point like E2. There is nothing in our assumptions to rule out that E2 is not to the right of the solid indifference curve through E1. If this is indeed the case, technological change will imply a sufficiently large increase in consumption and decline in leisure to reduce utility as measured by the solid indifference curves. Four observations about this result are in order. First, it requires that labor time increases with technological change.4 Second, it is more likely to occur the steeper are the solid indifference curves (which happens when u1, measuring the direct consumption effect, is smaller) and the stronger the tendency of average consumption to result in increases in marginal utility of a person’s own consumption. Note that the assumption that higher average levels of consumption drives up optimal levels of individual consumption plays an important role in this result, but does not do so generating the result of the social sub-optimality of the decentralized equilibrium. Third, it is more likely to occur the stronger is the substitution effect than the income effect of improvements in technology, which is the case that leads to upward-rising supply curves of labor. Finally, if we introduce diminishing returns into the analysis, as in Figure 6.1, the likelihood of this occurring is higher when the strength of diminishing returns is weaker and the effect of the technological change in increasing the marginal product of labor is greater.

Happiness and the relative consumption hypothesis

ci u

1

u

2

133

2

y

1

E2

ui

2

ui

0

1

E1

ni

Figure 6.2

6.3

y

li

1

Immiserizing growth

ALTERNATIVE EXPLANATIONS AND FORMULATIONS OF THE RELATIVE CONSUMPTION HYPOTHESIS

In the previous section we considered a simple formulation of the relative consumption hypothesis and examined its implications for inefficiency and for the growth-happiness relationship. We now review explanations of why the level of individual consumption and the utility that person derived from it may depend on what others consume, and compare the relative consumption formulation to some others available in the literature. 6.3.1

Alternative Explanations

The variety of explanations of the relative consumptions hypothesis may be classified into one of six categories. In the first individuals are seen as deriving – or perceiving that they derive – benefits in terms of higher levels of income by consuming more than others with whom they are competing. Examples include spending more on clothing than others to make a good impression on prospective employers and clients, spending more on education to become more

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attractive to potential employers, and consuming more in general to attract more desirable mates who will help them to increase their absolute levels of income and consumption (Cole et al., 1992; Frank, 1999). This motive for increasing consumption can be called the instrumental motive because relative consumption is not valued for its own sake but for its effect on absolute consumption. A second set of explanations focuses on the nature of certain goods that makes the utility derived from them depend on what others consume. Following Hirsch (1976), we can call them positional goods. For instance, if what one wishes to consume is a good view of nature (say, the seashore), then the height of one’s house or apartment and its distance from the seashore are relevant, but what is important is not so much the absolute height of one’s house and the distance from the seashore, but what these are in comparison to the houses owned by others. Hirsch (1976) has argued that goods are very likely to have such positional properties if their supply is very limited. A third explanation concerns information issues. The acquisition of goods by others serves as a form of publicity for the goods, and may make us want to increase our consumption of them. Duesenberry (1949, pp. 26–7) argues that sometimes individuals . . . come in contact with goods superior to the ones they use with a certain frequency. Each such contact is a demonstration of the superiority of those goods and a threat to the existence of current consumption pattern. . . . For any particular family the frequency of contact with superior goods will increase primarily as the consumption expenditures of others increase. When that occurs, impulses to increase expenditure will increase in frequency, and strength and resistance to them will be inadequate.

A fourth category involves network externalities. If many people in society have telephones, answering machines, fax machines or email, not having them excludes us from the flow of information or from other experiences we value and reduces our level of happiness. In cases where these network effects affect one’s income (for instance, failure to make a sale or obtain a job interview) this is equivalent to the instrumental motive. In other cases, in which people’s happiness directly depends on these externalities (for example, by being in contact with one’s friends) we see that relative consumption matters directly as well. The notion of network externalities can be extended to goods such as books and music, if their consumption allows discussions with others and the ability to make friends. A fifth relates to consumption norms. If most people consume something, a consumption norm is created which makes individuals ‘need’

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to consume it. Smith (1776, pp. 351–2) wrote about this more than two centuries ago: By necessaries I understand not only the commodities which are indispensably necessary for the support of life, but what ever the custom of the country renders it indecent for creditable people, even the lowest order to be without . . . Custom . . . has rendered leather shoes a necessary of life in England. The poorest creditable person of either sex would be ashamed to appear in public without them.

The need being fulfilled here, according to Sen (1983), is the need of not being ashamed; Smith is clearly arguing that the commodity capable of satisfying this need depends on what many others do, and is therefore changeable as customs change. In our times, if most people have straight teeth, it is likely to make the rest be ashamed to have crooked teeth, so that parents obtain braces for their children to avoid shame. Although consumption norms are likely to be strongest for goods visible to others, they may apply to other goods as well, because not consuming them can damage one’s self-respect. A final explanation is status. If we define status as the position one has in society as perceived by others on a scale of income or wealth, and assume that individuals prefer a higher status than a lower status, and that income or wealth are not directly observable but consumption (at least of some kinds) is, individuals will try to consume more to improve their status. Although the importance of status and conspicuous consumption has been pointed out by several writers in the last three centuries or so, it has not been absorbed into mainstream economic theory and given its due (Mason, 1998). Its importance was recognized by John Rae, to some extent by Smith, and by Nassau Senior, but then de-emphasized by the marginalists. Veblen (1899) emphasized that individuals seek to gain status through the conspicuous consumption of leisure, and more importantly, of goods. Duesenberry (1949, pp. 28–32) also stressed the role of status in increasing consumption especially in societies with a high degree of social mobility. Until very recently, however, these contributions have not had much impact on mainstream economics, and status consumption has been studied more by other social scientists such as sociologists and anthropologists, and by marketing researchers (see Mason, 1998). Recent work by economists has paid more attention to the status issue, both in the theoretical and empirical literatures (see, for instance, Bagwell and Bernheim, 1996; Frank, 1999; Schor, 1998). It may be noted that all six of these explanations can account for why people consume more when others do and for why people’s utility depends on why their relative consumption affects their utility. The information and network externality explanations are consistent with the idea that

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absolute levels of consumption increase utility significantly, but the other arguments are likely to imply that absolute increases in consumption do not significantly increase utility: for instance, if consumption increases to increase status or maintain one’s self-respect, increases in average consumption are likely to completely nullify the positive effects of increases in one’s own consumption. Two comments on the relative importance of these explanations is in order. First, individuals may consume specific goods for a number of the reasons discussed above, which may reinforce each other. Thus, even if a professional buys more expensive clothing for the instrumental reason, they may be doing it partly for the status or social norms motives. This implies that latter two motives may be more prevalent than is sometimes believed. Second, some of the explanations apply to particular goods, whereas the norms and, especially, the status explanations apply to a broad range of goods. Thus, network externalities, instrumental reasons, intrinsically positional properties and information issues may be important for specific goods. It is not appropriate to identify the status conferring value of one isolated good; status-motivated consumption is more accurately identified by a whole range of products (Mason, 1998, p. 132). Douglas and Isherwood (1978) argue that it is impossible to determine the meaning or value of goods in post-modern societies by taking each good individually, since goods reveal their purpose only when they are considered together. This meaning is particularly important for status-related consumption. This implies that consumption norms and status consumption explanations are likely to be much more important empirically than the other explanations. 6.3.2

Alternative Formulations

The relative consumption formulation is different from some alternative formulations which have been proposed, and may be briefly compared to them.5 One formulation, due to Frank (1985) and also adopted by Robson (1992) and Hopkins and Kornienko (2004), introduces relative consumption considerations into the utility function by making the level of consumption of positional and non-positional goods, and the rank the consumer has in the distribution of consumption of positional goods. This approach assumes that ui 5 u(xi, yi, R(xi)), where xi is the level of consumption of the positional good, yi the level of consumption of the non-positional good, and R(xi) is in the unit interval

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and shows the percentile ranking of xi in the population of xi values. This formulation differs from the relative consumption formulation because this one considers two types of consumption goods while ours incorporates only one, and it makes utility depend on the percentile rank in the consumption of the positional good rather than on consumption relative to that of others. The first difference is minor, since leisure can be thought of as a nonpositional consumption good, an interpretation at times given by Frank. However, our general formulation makes it clear that we should think of leisure only as an example of something for which relative consumption is not important, and can include other goods, saving and public goods. This broadening of interpretation suggests that increases in leisure may not be necessary for immiserizing growth, as suggested in our discussion above, and that the result can follow from a deterioration in public services, the environment or what is sometimes called social capital (see, for instance, Bartolini and Bonatti, 2003). The second difference is more substantive. Although the two approaches are similar in introducing consumption externalities and in implying the inefficiency of decentralized equilibrium, they are not equivalent: relative consumption can change without changes in an individual’s rank and rank can change without changes in relative consumption. It can be argued that the relative formulation has some advantages over the rank formulation: it is simpler because it can treat all individuals in equilibrium; and it is more inclusive since it captures more of the reasons why people consume because others do so, being relevant for information, social norm, network externality reasons, as well as some aspects of instrumental mechanisms for higher consumption and status, while the rank formalization seems to be relevant mainly for some kinds of instrumental and status reasons, and for some intrinsically positional goods. The advantage of the rank formalization over the relative consumption lies in its greater sensitivity to changes in the consumption level of people who are close to individuals in rank and hence more likely to be in their ‘reference’ group. However, changes in media and communications have extended reference groups well beyond those who are close in terms of consumption and income, and the relative consumption formalization may capture this situation better. A second formulation does not introduce relative consumption into the utility function at all, but allows relative consumption to affect utility indirectly. In this formulation, although utility depends directly on absolute consumption (and not relative consumption), the utility maximizing individual finds that utility depends on relative consumption, because relative consumption affects the consumer’s absolute consumption and income. For

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the simple case in which we can ignore work and leisure, this can be shown with the following equations: ui 5 u(ci) ci 5 y i yi 5 y(ci/c). This last equation states that individuals can obtain more income if they consume more than others, to show how productive they are. This implies, ui 5 u(y(ci /c)), implying the relative consumption hypothesis. It is, in other words, what we called the instrumental approach to relative consumption. Postlewaite (1998) makes a spirited case in favor of this approach. There is clearly a case for using this approach in cases in which relative consumption is actually of instrumental importance for raising income and consumption. These cases are also more common than is sometimes thought to be the case, as the discussion by Cole et al. (1992) suggests. However, Postlewaite (1998) goes on to argue against incorporating externalities directly into the utility function. He argues that (neoclassical) economics has done very well by parsimoniously making utility depend only on consumption and income and omitting other things like externalities, and that this parsimony has made it attractive and successful, and made it avoid the slippery slope of making the optimizing approach tautologous by incorporating whatever one wants into the utility function. By avoiding reduced form utility functions, this formulation is more capable of understanding how precisely concern with relative issues arises through the interaction of market and non-market spheres, and provides a better understanding of how to deal with social non-optimality due to the presence of such relative concerns, that is, by understanding the institutional environment in which relative concerns arise and changing them. These arguments, however, are questionable for a number of reasons. First, it is not clear that the success of neoclassical economics has to do with its parsimonious assumptions rather than reasons related to network externalities and increasing returns that provide higher payoffs to economists who follow this approach in comparison to those who do not, and of its (although sometimes troubled) relation with free market ideology and conservative ideas. Moreover, to the extent that its success can be

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traced to its intellectual content, it may have to do more with the ability of neoclassical economics to immunize itself against, and react to, criticism by modifying itself in directions that have reduced its parsimony. Second, it is not clear that introducing relative concerns in non-market spheres with suitable stories introduces any more discipline than does the route of modifying the utility function. We are free to make up almost any story we want to obtain the result that relative concerns affect absolute consumption, without being able to evaluate their relevance directly. Third, there may be a case for introducing relative concerns directly into the utility function because they may reflect not reduced forms, but because people truly have utility functions of that type. It is hard to argue that people want to consume more to avoid shame because by consuming more they believe that they will obtain higher income than others. There may, in fact, be evolutionary mechanisms at work which make people have relative concerns hardwired into their utility functions, as many have argued, including Frank (1999). Fourth, utility functions can be thought of as part of a simple methodological approach with which to organize thinking, and it may be convenient and parsimonious methodology to tell stories based on the assumption that people have relative concerns This is not to argue that this approach is better than Postlewaite’s, but that there is room for both. The attractiveness of introducing relative concerns arises from the fact that one can examine the implications of so doing to model a variety of stories discussed earlier in a simple way. Finally, and directly relevant to the questions this chapter deals with, this formulation fails to explain why utility does not increase when consumption and income increase, since utility depends positively on absolute consumption. A final approach that can be compared to the relative income hypothesis is one that has been used by Easterlin (2001) in his attempt to develop a unified theory to explain the income-happiness relationship. Easterlin makes subjective well-being of a person depend positively on income and negatively on the level of aspirations. Given the level of aspirations, an increase in income leads to an increase in subjective well-being, and this relationship guides consumer decisions. However, when income actually rises, the level of aspirations also rises, and experienced utility may not rise overall, or rise less than it would have had aspirations not increased. The relative consumption approach is in the spirit of Easterlin’s approach, but has some advantages over it. First, Easterlin’s aspirations theory may be too general to be a useful theory. We are not told what aspirations depend on and therefore do not know why they increase with income. We do not know whether aspirations change because they follow from human nature or are context specific, and therefore this formulation does not tell us what to do about its implications. Second, and related to the non-specificity

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problems, it does not tell us why people systematically ignore the effects of increases in consumption and income on their aspirations, and also why aspirations increase with income in a manner which just about offsets gains in income. In all these respects, the relative consumption hypothesis is arguably superior because it focuses on particular sets of mechanisms such as status, social norms and other issues which are both broad and specific. It also sheds light on why people consume more – because of externalities – and why utility does not rise appreciably with consumption. However, Easterlin’s approach is more general than the specific relative consumption hypothesis, because it draws attention to possible reasons for which aspirations may change that may be unrelated to issues in which an individual’s utility or happiness depends on one’s consumption relative to that of others. We turn now to these issues.

6.4

ALTERNATIVES TO THE RELATIVE CONSUMPTION EXPLANATION

There are several other explanations of why consumption increases without significantly increasing happiness. This section discusses these alternatives and examines their relationship with the relative consumption hypothesis. 6.4.1

Needs

A needs-based explanation starts from the observation that the amount of real income required to satisfy a given level of needs has increased. This observation explains both why consumption increases and why these increases have not made people better off. People who are used to meeting a given level of needs have to consume more goods and services to meeting those needs. But since the same level of needs is being satisfied, people are no better off. Segal (1998) argues that, at least in the USA, although consumption has increased significantly, the amount of income required to satisfy fundamental economic needs (for such things as safe housing, education, transportation and food) has also increased significantly, so that people are not really better off: they are merely consuming more to satisfy the same needs that they earlier satisfied with less goods. While this explanation seems plausible enough, it is not clear that increases in the consumption of a large range of goods only reflects the reduced efficiency of goods in fulfilling needs, and that they do not imply higher need-fulfillment. For instance, when Segal argues that the needrequired income for housing has grown considerably because real house

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prices (for the median sales price of existing homes) have increased significantly, and because of the decline in personal safety, which has increased the need for safe and more expensive housing, he does not take into account that the quality of (median price) houses may have improved as well, implying that the more expensive houses are satisfying additional needs and thereby increasing happiness. Moreover, it is not clear from the explanation why the efficiency of goods in satisfying needs has fallen in such a way that consumption improvements satisfy just the same needs. One plausible explanation which is often given is the role of the relative consumption. We have already discussed how, for instance, in the case of footwear, what is required to satisfy the need not to be ashamed may depend on what others consume. Sometimes consumption needs may not just reflect psychological processes, but may translate into the non-availability or inferiority of less expensive substitutes and therefore create the necessity of spending more to meet virtually the same needs. As more people use private cars as means of transportation the support for public transportation may diminish, public transportation services may decline or even diminish, requiring other people to buy cars as well. As more people consume expensive goods cheaper substitutes may not be produced if the market for them is not large enough to make them profitable to cover costs in the presence of fixed costs or increasing returns to scale. As more people use refrigeration, small nearby groceries for daily shopping may vanish, requiring others to shop less frequently at distant supermarkets and buy refrigerators. As people buy bigger cars, it can become less safe to drive in smaller cars, requiring small-car owners to buy bigger and more expensive cars. In all these cases increases in consumption by others induce people to consume more. But all this is one variant of our relative consumption hypothesis. 6.4.2

Adaptation and Habit Formation

The psychological literature has drawn attention to the roles of habit formation and adaptation. The essential idea is that people get used to the state they are in so that changes in, rather than levels of, relevant states produce positive affect. Regarding consumption, utility depends more on positive changes in the level of consumption, rather than on the level of consumption. This implies that people will seek to increase consumption to increase their utility, but once they have done so, and attained a higher level of consumption, their level of utility will be no higher, unless they continue to increase their level of consumption. Within economics several contributions, including those by Scitovsky (1976), who discusses the contradictions between comfort and stimulation, and Frank (1999) have discussed this issue and analysed its implications.

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These ideas are different from our relative consumption hypothesis in which it is consumption relative to others that matters. This approach has been formalized in terms of a relative consumption hypothesis, but rather than making utility depend on consumption relative to that of others, it makes it depend on consumption relative to that of that person in the past. However, there is some relation between them and our relative consumption hypothesis. First, habit formation may partly reflect internal adaptation, but it is also likely to have a social aspect, that is, people may get used to things not just because they consume them, but also because others do, and this may become embodied in social norms, as in de la Croix’s (1998) model. Second, as Scitovsky (1976) notes, not all consumer goods lead to boredom. Some goods, as Frank (1999) argues, lead to gains that last. If people buy and seek novelty in goods that they see others consuming, and not goods that they can spend many hours and years enjoying, they are more likely to get bored with them. Thus, consuming goods because others consume them is likely to lead people to become more adapted to them, preventing them from buying goods which provide lasting gains. 6.4.3

Consumption and Time

The fact that consumption takes time directly (the act of consumption takes time) and indirectly (it takes time to work and earn income to buy consumption goods) can imply that increases in consumption can occur without increases in happiness. As Linder (1970) has insightfully argued, since consumption takes time, and since time is the ultimate scarce resource, increases in the purchase of consumer goods need not increase the consumers’ utility because they do not have the time required to actually consume them. Moreover, increases in the time required for work to earn income, and for consumption, reduces the time people can spend on other things which can increase their happiness, such as time spent with friends and family, in doing physical activities, indulging in hobbies which provide ‘flow’ and in sleeping. Though these arguments seem plausible enough, further reflection suggests that they are open to some criticisms, and sometimes require the defense of the relative consumption hypothesis. First, although in many cases consumption does take time, there are many kinds of consumption that take very little, or no, time at all. Things consumed for status reasons are only for show, and do not take time for enjoyment. Second, some consumer goods and services (such as household equipment like washing and drying machines, faster travel and faster communications through email) may appear to save time, but there is little evidence that they actually do so, since people insist on higher standards of cleanliness and because they

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travel and communicate more; Binswanger (2006) refers to this as the time saving treadmill. Third, if people do need time to consume, why do they not take the time constraint into account in deciding how much to buy and consume? While it is possible that people sometimes do not realize that they have a time constraint when they buy things (perhaps because they are myopic about the future) and do not take into account the opportunity cost of time in the same way as they take into account actual monetary costs (as suggested by behavioral economists), these arguments are unlikely to appeal to those economists who rigidly adhere to the notion of the optimizing agent. A plausible explanation for the emergence of time constraints is that the consumers value their relative consumption in addition to their absolute level of consumption which, as discussed earlier, leads to working too much and having too little leisure. This also makes them switch increasingly to consumption goods which do not take much time to consume, a substitution effect brought about by the shortage of time (see Dutt, 2009). Moreover, having less time to spend on obtaining information about goods, consumers may rely more on observing what others are consuming in judging their desirability. All this increases the importance of relative consumption. 6.4.4

Corporations, the Media and Sales Promotion

Increases in consumption have often been explained in terms of the sales promotion activities of firms and the media. Galbraith (1958) argues that wants increase as production increases, in large part because as production increases firms try to sell more, produce new goods and spend more on sales promotion. Thus firms are not necessarily responding to ‘wants’, but actually creating them through their own efforts, and Galbraith argues that since these are artificially created wants, their satisfaction does not really make consumers better off. Such arguments concerning the role of sales promotion in increasing consumption and in explaining why such increases may not increase happiness have been severely criticized by several writers (see Dutt, 2008, for a review). Some have argued that there is no evidence that increases in total advertising expenditure increases total consumption (although it may shift purchases from one firm to another). Others argue that consumers are not mere pawns in the hands of firms and the media, and have the final say on what they buy. Moreover, even if external influences such as sales promotion influence what and how much people buy, it does not follow that people are not made better off by such purchases. These criticisms, however, do not hold water: the empirical research does not take

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a sufficiently broad view of sales promotion expenditure, the argument about the ability of sales promotion activity to influence consumer decisions overlooks a great deal of behavioral economics evidence and theory, and the absence of a relation between consumption and happiness over time seems to vindicate Galbraith’s position about the effects of increasing consumption on happiness (see Dutt, 2008). Although, in principle, the activities of firms can have an effect on consumer behavior by increasing their aspirations in a manner unrelated to the relative consumption hypothesis, sales promotion activities of firms and the relative consumption hypothesis – keeping up with the Joneses, for instance – are related. First, advertisements, television shows and films extend the reference groups of consumers, making them want to consume what other people do, including celebrities and imagined people, with whom they would not otherwise come into contact. Second, advertisers often work on consumers in complicated ways which exploit their propensity to emulate and seek status, by suggesting – in subtle and sometimes not so subtle ways – why this or that product will increase their status or make them more like people who are rich and beautiful. Thus, firms and the media may have an important role in ensuring the relevance of the relative consumption effect. 6.4.5

Consumer Finance and Debt

Consumer borrowing and debt can explain both increases in consumption and why consumers do not become happier by consuming more. Increases in consumption are explained by the fact that consumers have easier access to credit, something that has occurred not only in rich countries like the USA, but also in less developed countries, and something that is reflected in a strong upward trend in consumer debt-GDP ratios in many countries. As people obtain more credit and consume more, however, their debt level increases, and this can reduce their happiness, as is suggested by Brown et al. (2005) who use British Household Panel data to show that levels of outstanding debt other than home mortgage debt have a significantly negative effect on happiness, controlling for other variables such as family income, age and other personal characteristics, savings and expected changes in financial conditions. This explanation, however, is open to some criticisms. First, it can be asked why, when credit is offered, people willingly borrow to increase their consumption. In other words, why do individuals increase their consumption to an extent that they are worse off because of increases in debt. Second, it is sometimes argued that high levels of indebtedness and consequent bankruptcy are primarily due to unexpected events like

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medical expenses due to health problems, unemployment and divorce (Sullivan et al., 2000). But one can still ask: why do consumers not save enough to protect themselves against such contingencies? Third, although the numbers in high levels of debt and running into financial problems is increasing, the number of people with such problems is not large enough to explain the non-increasing levels of happiness. The third argument makes us look elsewhere for an explanation of why consumption does not significantly increase happiness, and underscores the importance of the relative consumption effect. Moreover, one can plausibly respond to the first two arguments by appealing to the relative consumption hypothesis: people desire to consume more even though it does not increase their happiness, and do not save enough for precautionary purposes, because they are induced to do so because their utility depends on relative consumption.

6.5

AN IMPLICATION OF THE RELATIVE CONSUMPTION HYPOTHESIS

The relative consumption hypothesis has many implications in addition to those discussed earlier, that is, inefficiency and the possibility of growth without increases in happiness. In this section we examine one such implication that has relevance to the economics of happiness which, as far as I know, has not been discussed in the literature. This implication is that ethical and religious perspectives can have a role to play in achieving greater happiness as judged by people themselves. The discussion of this chapter suggests that increases in the level of consumption do not lead to significant increases in happiness, and in fact may result in a loss of happiness, for a variety of reasons, of which a very important one is that a person’s level of happiness depends on what that person consumes relative to others. We have also argued that a major reason for this is because we try to consume more than others to gain status, and because we are ashamed to fall behind other people. These kinds of feelings arise because we compete with others in the sphere of consumption and income, according to the status motive because we want to get ahead of others, and in the norms motive because we dislike falling behind others. In modern times competition prevails in a variety of spheres, but because comparisons are most easily made in the metric of money, income and consumption has, in many societies, become the main sphere of competition. People try to keep up with others, or consume more than them, because they are in competition with each other in the sphere of consumption.

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Even if competitiveness is a given characteristic of human beings, we can choose to compete in things other than consumption by narrowing the sphere of competition to become the best writer, the best poet, the best writer of sonnets, the best writer of sonnets in English, the best writer of sonnets in a country and so on. There are societal forces that work against such narrowing. How to compare a writer of science fiction to a writer of crime fiction, and how exactly to decide who is a better crime writer? It is tempting to fall back to the measuring rod of money, and hence consumption. An antidote to these broadening forces could be a narrowing force, which reminds us that the most satisfying form of competition is to compete with oneself and not to some other person or persons – to be the best person one can be. Most of the world’s religions have in one way or another recommended this type of quest (see Dutt, 2001). A narrowing in the sphere of competition, aided by such religious and ethical crutches, can arguably make consumption less dependent on the consumption of others. Consumption can be reduced and also be allocated to goods and services which yield more lasting happiness. There is evidence which suggests that those who have greater religious involvement tend to have higher levels of happiness and lower levels of distress (see Deheija et al., 2005; Deiner et al., 1999; Ellison, 1991; Parmagent, 2002; Smith et al., 2003). Here religious involvement is measured by church attendance, belief in religious doctrine such as Heaven and Hell, and contributions to religious organizations. Various influences of religious involvement on happiness have been suggested in the literature, including consumption smoothing (controlling for income and consumption expenditure, when religious organizations provide in kind assistance to its members), ability to deal better with stressful events (Deheija et al., 2005) and the creation of social networks (Putnam, 2000). In addition to these influences, our analysis suggests that religious involvement, by reducing the competitive role of consumption, has a positive effect on happiness, even though religiosity may not be the only way this can take place.

6.6

CONCLUSION

This chapter has provided a simple formulation of the relative consumption hypothesis, according to which, the utility of the consumer depends on consumption relative to the consumption of others, among other variables, including absolute levels of consumption. It has also argued in favor of the wider acceptance of this hypothesis by showing that: it provides a simple and parsimonious theory of consumption; it implies that individual

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maximizing behavior can result in social inefficiency; it is consistent with empirical results such as the absence of a strong link between income/ consumption and happiness and a positive relation between happiness and religiosity; it captures the essence of a variety of explanations of why the consumption and happiness of people depend on the consumption of others; and that it is related to, and strengthens, a variety of explanations of why people increase their consumption and often do not increase their happiness as a result. The hypothesis has, of course, been provided in a very simple form, and has been incorporated into a simple model which is static and in which all individuals are assumed to be identical. Modifying the hypothesis, for instance, to incorporate different peer groups for different individuals, and complicating the model to allow for dynamics due to saving, investment and technological change, and to introduce differences between individuals in terms of income, can only magnify its relevance.

NOTES 1. An earlier and longer version of this chapter was presented at the conference on New Directions in the Study of Happiness, University of Notre Dame. I am grateful to the participants of the conference for useful comments. 2. Note that individual utility does not depend on relative leisure, but only on their absolute amount of leisure. Veblen (1899) discussed the importance of conspicuous leisure as well as conspicuous consumption, but argued that at advanced stages of the economy the importance of conspicuous leisure would pale in comparison to that of consumption. 3. The slope of the indifference curve will fall with an increase in c if (u12 1 u22 1 u2 /c) c u32 c , u1 1 u2/c u3 which states that the elasticity of the marginal utility of individual consumption (for both absolute and relative reasons) with respect to average consumption is less than the elasticity of the marginal utility of leisure with respect to average consumption. It is plausible that the marginal utility of leisure increases with a rise in relative consumption, or that u32 . 0, because as people have a higher relative level of consumption they enjoy increases in leisure more. It is also plausible that the marginal utility of individual consumption for absolute and relative consumption reasons diminishes as they have a higher level of relative consumption so that (u12 1 u22 1 u2/c) , 0 (despite the fact that the third term is positive). Thus, it is likely that the condition is satisfied. 4. To see this, note that since relative consumption does not change due to technological change, if there is even a small increase in utility due to an increase in absolute consumption, it is necessary for there to be an increase in labor time and a reduction in leisure to prevent utility from increasing when there is technological change. Formally, we have u2yn dni dui 5 2 1 u1yA, dA c dA where the production function is written as yi 5 y(ni, A), and where yn is the marginal product of labor and yA is the partial derivative of output with respect to a uniform change in the technological parameter, A. This shows that for utility to fall with a rise

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Happiness, economics and politics in A, dni/dA . 0. An expression for dni/dA can be obtained by taking the first order condition for utility maximization, that is, u2 au1 1 byn 2 u3 5 0, c

imposing the equilibrium condition ci 5 c, totally differentiating it with respect to A and solving explicitly for dni/dA. It can be shown that the expression can take either sign. 5. A number of previous contributions adopt formalizations very similar to ours, so that ours can claim to do no more than draw on them to provide a simpler and perhaps more transparent exposition. For instance, Dupor and Liu (2003) assume that individual utility depend on consumption (positively), and the average consumption of others (negatively), but our more specific formulation with relative consumption as an argument in the utility function provides arguably a more transparent demonstration of the sub-optimality of decentralized equilibria, and also address the growth-happiness relationship. Carroll et al. (1997) and Alvarez-Quadrado et al. (2004) examine growth models with status consumption using the relative consumption argument, but adopt Cobb-Douglas instantaneous utility functions which imply that individual consumption is independent of the consumption of others. Closer to our formulation are those in the more complex growth models of de la Croix (1998) and Cooper et al. (2001).

REFERENCES Alvarez-Cuadrado, Francisco, Goncalo Monteiro and Stephen J. Turnovsky (2004), ‘Habit formation, catching up with the Joneses, and economic growth’, Journal of Economic Growth, 9, 47–80. Bagwell, Laurie and B. David Bernheim (1996), ‘Veblen effects in a theory of conspicuous consumption’, American Economic Review, 83 (6), June, 349–73. Bartolini, Stefano and Luigi Bonatti (2003), ‘Endogenous growth and negative externalities’, Journal of Economics, 79, 123–44. Binswanger, Mathias (2006), ‘Why does income growth fail to make us happier? Searching for treadmills behind the paradox of happiness’, Journal of Socioeconomics, 35, 366–81. Brown, Sarah, Karl Taylor and Stephen Wheatly Price (2005), ‘Debt and distress: Evaluating the psychological cost of credit’, Journal of Economic Psychology, 26, 642–61. Carroll, Christopher, Jody Overland and David Weil (1997), ‘Comparison utility in a growth model’, Journal of Economic Growth, 2, 239–67. Cole, Hal L., G.J. Mailath and Andrew Postlewaite (1992), ‘Social norms, saving behavior and growth’, Journal of Political Economy, 100, 1092–125. Cooper, Ben, Cecilia Garcia-Penalosa and Peter Funk (2001), ‘Status effects and negative utility growth’, Economic Journal, 111, July, 642–65. de la Croix, David (1998), ‘Growth and the relativity of satisfaction’, Mathematical Social Sciences, 36, 105–25. Deheija, Rajeev, Thomas DeLeire and Ezro Luttmer (2005), ‘Insuring consumption and happiness through religious organizations’, NBER Working Paper No. 11576, National Bureau of Economic Research, Cambridge, Massachusetts. Diener, Ed and Shigehiro Oishi (2000), ‘Money and happiness: income and subjective well-being across nations’, in Ed Diener and Eunkook K. Suh (eds), Culture and Subjective Well-being, Cambridge: MA, MIT Press, pp. 185–218. Diener, Ed, Eunkook K. Suh, Richard E. Lucas and Heidi L. Smith (1999),

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‘Subjective well-being: three decades of progress’, Psychological Bulletin, 125 (2), 276–303. Douglas, M and B. Isherwood (1978), The World of Goods, London: Penguin Books, reprinted 1980, revised edition, London: Routledge, 1996. Duesenberry, James (1949), Income, Saving and the Theory of Consumption Behavior, Cambridge, MA: Harvard University Press. Dupor, Bill and Wen-Fang Liu (2003), ‘Jealousy and equilibrium overconsumption’, American Economic Review, 93 (1), March, 423–8. Dutt, Amitava Krishna (2001), ‘Consumption, happiness and religion’, in A.K. Dutt and K. Jameson (eds), Crossing the Mainstream: Ethical and Methodological Issues in Economics, Notre Dame: University of Notre Dame Press, pp. 133–69. Dutt, Amitava Krishna (2008), ‘The dependence effect, consumption and happiness: Galbraith revisited’, Review of Political Economy, 20 (4), October, 527–50. Dutt, Amitava Krishna (2009), ‘Consumption takes time: some implications for happiness’, in John Vint, Stan Metcalf, H. Kurz, P. Samuelson and N. Salvadori (eds), Economic Theory and Economic Thought: Essays in Honor of Ian Steedman, London: Routledge. Easterlin, Richard (1974), ‘Does economic growth improve the human lot? some empirical evidence’, in Paul David and Melvin Reder (eds), Nations and Households in Economic Growth: Essays in Honor of Moses Abramovitz, Palo Alto, CA: Stanford University Press, reprinted in Richard Easterlin (ed.) (2002), Happiness in Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar Publishing, pp. 89–125. Easterlin, Richard (1995). ‘Will raising the incomes of all increase the happiness of all?’ Journal of Economic Behavior and Organization, 27, 35–47. Easterlin, Richard (2001), ‘Income and happiness: towards a unified theory’, Economic Journal, 111, July, 465–84, reprinted in Richard Easterlin (ed.) (2002), Happiness in Economics, Cheltenham, UK and Northampton, MA, USA: Edward Elgar Publishing. Ellison, Christopher G. (1991), ‘Religious involvement and subjective well-being’, Journal of Health and Social Behavior, 32 (1), 80–99. Frank, Robert (1985), ‘Demand for unobservable and other non-positional goods’, American Economic Review, 75 (1), March, 101–16. Frank, Robert (1999), Luxury Fever. Why Money Fails to Satisfy in an Era of Excess, New York: The Free Press. Frey, Bruno S. and Alois Stutzer (2002), Happiness and Economics, Princeton, NJ: Princeton University Press. Galbraith, John Kenneth (1958), The Affluent Society, London: Hamilton. Hirsch, Fred (1976), Social Limits Growth, Cambridge, MA: Harvard University Press. Hopkins, Ed and Tatiana Kornienko (2004), ‘Running to keep in the same place: consumer choice as a game of status’, American Economic Review, 94 (4), September, 1085–107. Linder, Staffan Burenstam (1970), The Harried Leisure Class, New York: Columbia University Press. Mason, Roger (1998), The Economics of Conspicuous Consumption. Theory and Thought since 1700, Cheltenham, UK and Lyme, NH, USA: Edward Elgar Publishing.

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Oswald, Andrew J. (1997), ‘Happiness and economic performance’, Economic Journal, November, 1815–31. Parmagent, Kenneth I. (2002), ‘The bitter and the sweet: an evaluation of the costs and benefits of religiousness’, Psychological Inquiry, 13 (3), 168–81. Postlewaite, Andrew (1998), ‘The social basis of interdependent preferences’, European Economic Review, 42, 779–800. Putnam, Robert (2000). Bowling Alone. The Collapse and Revival of American Community, New York: Touchstone Books. Robson, Arthur (1992), ‘Status, the distribution of wealth, and social attitudes to risk’, Econometrica, 60 (4), July, 837–57. Schor, Juliet (1998), The Overspent American. Upscaling, Downshifting and The New Consumer, New York: Basic Books. Scitovsky, Tibor (1976), The Joyless Economy. An Inquiry into Human Satisfaction and Consumer Dissatisfaction, Oxford: Oxford University Press, revised second edition, 1992. Segal, Jerome M. (1998), ‘Consumer expenditures and the growth of need-required income’, in David C. Crocker and Toby Linden (eds), Ethics of Consumption. The Good Life, Justice and Global Stewardship, Lanham, MD: Rowan and Littlefield, pp. 342–65. Sen, Amartya (1983), ‘Poor, relatively speaking’, Oxford Economic Papers, 35, July, 153–9. Smith, Adam (1776), An Inquiry into the Nature and Causes of the Wealth of Nations, London: W. Strahan and T. Cadell. Smith, Timothy B., Michael E. McCullough and Justin Poll (2003), ‘Religiousness and depression: evidence for a main effect and the moderating influence of stressful life events’, Psychological Review, 129 (4), 614–36. Sullivan, Teresa A., Elizabeth Warren and Jay Lawrence Westerbrook (2000), The Fragile Middle Class. Americans in Debt, New Haven, CN: Yale University Press. Veblen, Thorstein (1899), The Theory of the Leisure Class. An Economic Study of Institutions, London and New York: Macmillan.

7.

The Easterlin Paradox revisited Robert H. Frank

For more than three decades social scientists have debated the Easterlin Paradox. In his celebrated 1974 paper, ‘Does economic growth improve the human lot?’, Richard Easterlin called attention to two seemingly contradictory patterns in data on the relationship between income and measured happiness. One is that in any country at a single point in time measured happiness levels rise with income. The second is that as average income levels rise over time within a country average measured happiness levels remain the same. If wealthy people are happier than poor people at any moment, he asked, why doesn’t rising income make people happier over time? The answer, he suggested, was that once a threshold level of absolute income is attained, further increases serve only to shift the frame of reference that defines what people consider necessary. His conclusion was that in advanced economies there is no longer any compelling reason to pursue economic growth. In this chapter, I will examine Easterlin’s argument in the light of research findings published in the wake of his original paper. My summary conclusion is that economic growth is far more important than his analysis suggests. The chapter is organized as follows: Section 7.1 briefly reviews the kinds of data that led Easterlin to his original conclusion. Section 7.2 describes a recent study suggesting that happiness may indeed rise over time as income rises. Section 7.3 makes the point that many conditions believed to be conducive to human welfare tend to improve as a result of economic growth. Section 7.4 discusses why such improvements might not trigger increases in measured happiness. Section 7.5 provides concluding remarks.

7.1

INCOME AND MEASURED HAPPINESS

Ever since the Second World War, social scientists have gathered data on human happiness levels in different countries. The most commonly used measures are derived from survey data. Some surveys ask subjects to 151

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classify themselves into one of three categories: very happy, fairly happy or not happy. Others ask them to respond on a 10-point scale to questions like, ‘All things considered, how satisfied are you with your life these days?’ Although it might seem natural to be skeptical about people’s responses to such questions, evidence suggests that they capture something of interest. People who say they are happy, for example, are more likely to be rated as happy by their friends; less likely to suffer from psychosomatic illnesses; less likely to seek psychological counseling; and less likely to attempt suicide. They are also more likely to initiate contacts with friends; more likely to respond to requests for assistance; and more likely to exhibit brain wave patterns associated with positive affect.1 The first component of the Easterlin Paradox is well-illustrated in Figure 7.1. Each of the heavy squares in the scatter represents the average happiness level of a large number of subjects with the same income level. The upward-sloping pattern in the scatter is typical of findings from crosssection studies in other countries. Subjects with higher incomes report much higher levels of happiness on the average. The second component of the Easterlin Paradox is vividly captured in the Japanese survey data shown in Figure 7.2. As the steeply upwardsloping darker line shows, the period in question was clearly one of rapidly

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rising real income growth in Japan. Yet the dotted line, which tracks average happiness, shows almost no variation during the same period. That across the board income growth might color people’s expectations about what constitutes an adequate standard of living seems indisputable. But Easterlin makes a bolder claim – namely, that once people’s most important material needs are met, further gains in absolute income yield no real benefits at all. Is this bolder claim plausible?

7.2

A RECENT STUDY’S CHALLENGE

In a widely discussed 2008 paper Betsey Stevenson and Justin Wolfers argue that Easterlin’s failure to find a positive income-happiness gradient within countries over time was a consequence of data limitations. Easterlin’s error, they write, was ‘to confound the absence of evidence for such a link with evidence of its absence’ (Stevenson and Wolfers, 2008b, p. 3). They argue, for example, that the link’s absence in the Japanese data might be explained by substantial changes in the wording of the survey questions posed over the years covered. Using the more voluminous surveys that have become available in recent years, Stevenson and Wolfers estimate significantly positive income-happiness relationships for eight of the ten European economies they examined. In response, Easterlin cites conspicuous exceptions to this pattern, such as the USA and China, where average happiness levels have remained

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largely unchanged despite substantial growth in incomes. Stevenson and Wolfers concede that the evidence regarding average happiness levels over time is ‘fragile’ and ‘messy’. But argue that, on balance, it supports the hypothesis that income growth promotes happiness. As I argue in the next sections, however, happiness survey data are a flimsy foundation for judgments – pro or con – about the social desirability of economic growth. But before moving on, I note that Stevenson and Wolfers incorrectly attribute to me the view that growth doesn’t matter. Thus, they write: ‘Indeed, Frank (2005, p. 67) infers that (findings like the ones described in Figures 7.1 and 7.2) “are not only consistent with the view that relative income is a far better predictor of happiness than absolute income, but they also seem to suggest that absolute income may not matter at all”’ (Stevenson and Wolfers, 2008a, p. 1). The title of the paper from which this quote was taken is ‘Does absolute income matter?’ The sentences that immediately follow the one quoted suggest why I think the answer to that question is yes: Some social scientists who have pondered the significance of this finding have concluded that, at least for people in the world’s richest countries, no useful purpose is served by further accumulations of wealth.2 On its face, this should be a surprising conclusion, since there are so many seemingly useful things that having additional wealth would enable us to do. Would we really not be any happier if, say, the environment were a little cleaner, or if we could take a little more time off, or even just eliminate a few of the hassles of everyday life? (Frank, 2005, pp. 67–8).

7.3

HAPPINESS AND WELFARE

Happiness is a good thing. If you had to choose between two otherwise equal environments and knew that people were generally happier in one of them, you would probably choose it. But happiness is not the only thing we value. We value autonomy. We value political freedom, economic security, robust health, good schools and safe neighborhoods. The list goes on. Because happiness and welfare, though linked, are not the same, economic growth might still promote welfare even if it did nothing to increase happiness. And indeed, there is compelling evidence that – contra Easterlin – economic growth improves the human lot. In the nineteenth century, for example, it was common for couples with five children to see two or more of them die before reaching their tenth birthday. Life expectancy at birth was about 40 years. Workplace injuries were much more common. People worked longer hours under more

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difficult conditions. There were few effective remedies for pain and serious illnesses. Urban air was dirtier and drinking water was unsafe. A much higher proportion of children went to bed hungry. That conditions have improved so dramatically in the intervening years has been a simple and direct consequence of economic growth. Economic growth also affects the human condition in other, less direct, ways. In his book The Moral Consequences of Economic Growth, for example, the economist Benjamin Friedman argues that economic growth is a vital precondition for social and political progress (Friedman, 2006). His thesis in brief is that people whose incomes are growing rapidly find it much easier to be generous toward others than those whose incomes are static or declining. Thus, in his account it was no coincidence that as the US economy rapidly expanded during the two decades following the Korean War (when average income doubled), voting rights were expanded, segregation was outlawed, and fair housing and equal employment opportunity laws were enacted. In contrast, public attitudes toward the disadvantaged became distinctly less generous between 1975 and 1995, a period during which the median real wage actually declined. There is also a link between economic growth and the physical environment. Contrary to popular perceptions, the relationship between growth and pollution is not positive but rather U-shaped. Primitive societies have very little pollution. As industrialization begins, pollution grows. But beyond some point, economic growth becomes associated with cleaner environments. The developed societies of the West are now well into the latter region. Reducing our carbon footprint through development of renewable energy sources and public transportation will be extremely costly. Like the dollars necessary to finance progressive social programs, the dollars necessary to finance these investments will be easier to generate if incomes are growing more rapidly.

7.4

WHY DOESN’T GROWTH HAVE MORE IMPACT ON MEASURED HAPPINESS?

If economic growth changes the environment in ways that make human beings more likely to thrive, why doesn’t it also create easily measurable increases in human happiness? To explore this question, we must look to the evolutionary forces that molded the human nervous system. The purpose of all animal motivational systems, according to evolutionary biologists, is to promote actions that increase the organism’s probability of survival and reproduction. Thus, apes are said to enjoy sweets

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because the sugars in ripened fruit are more easily digested than those in unripe fruit. But the ultimate purpose of the motivational system is not to make people feel happy, but rather to create appetites for behaviors that promote successful life outcomes. To be effective, this system should be flexible and adaptive, which it is. For example, people who become disabled typically experience deep depression after their accidents, but often adapt surprisingly quickly, soon reporting a mix of moods similar to what they had experienced before. Lottery winners, for their part, invariably experience joy on receiving their windfalls, but often describe such feelings as fleeting. Since life is a continuing competitive struggle, this is as it should be. Accident victims who can recover their psychological footing quickly will function more effectively in their new circumstances than those who dwell unhappily on their misfortune. Windfall recipients who quickly recover their hunger for more will compete more effectively than those who linger in complacent euphoria. A Holocaust survivor once told me that his existence in the camps took place in two separate psychological spaces. In one he was acutely aware of the unspeakable horror of his situation. But in the other life seemed eerily normal. In this second space each day presented challenges, and days in which he coped relatively successfully with them felt much like the good days of the past. To survive, he explained, it was critical to spend as much time as possible in the second space and as little as possible in the first. These observations highlight the weakness of happiness measures as a metric of welfare. The fact that people adapt quickly to new circumstances, good or bad, is just a design feature of the brain’s motivational system. The fact that a paraplegic may continue to be happy does not imply that his condition has not reduced his welfare. Indeed, many well-adjusted paraplegics report that they would undergo surgery entailing substantial risk of death if doing so promised to restore their mobility. Similarly, the fact that people may adapt quickly to higher incomes says nothing about whether economic growth makes them better off.

7.5

CONCLUDING REMARKS

A simple thought experiment helps summarize my main point. Imagine two parallel universes, one just like the one we live in now and another in which everyone’s income is twice what it is now. Suppose that in both cases you would be the median earner, with an annual income of $100 000 in one case and $200 000 in the other. Suppose further that you will feel equally happy in the two universes. And suppose, finally, that you know

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that people in the richer universe would spend more to protect the environment from toxic waste, and that this would result in healthier and longer, even if not happier, lives for all. Can there be any question that it would be better to live in the second universe? Easterlin’s original claim was that because economic growth didn’t seem to increase measured happiness, there was no reason to pursue it. But again, happiness and welfare are different concepts. So even if it could be shown that economic growth does nothing to increase measured human happiness, we would have no reason to conclude that it does not promote human welfare.

NOTES 1. For a detailed survey of studies that support these claims, see Frank (1999, ch. 5). 2. See, for example, Townsend (1979).

REFERENCES Diener, Ed, Ed Sandvik, Larry Seidlitz and Marissa Diener (1993), ‘The relationship between income and subjective well-being: relative or absolute?’, Social Indicators Research, 28, 195–223. Easterlin, Richard (1974), ‘Does economic growth improve the human lot?’, in Paul David and Melvin Reder (eds), Nations and Households in Economic Growth: Essays in Honor of Moses Abramovitz, New York: Academic Press, pp. 89–125. Easterlin, Richard (1995), ‘Will raising the incomes of all increase the happiness of all’, Journal of Economic Behavior and Organization, 27, 35–47. Frank, Robert H. (1999), Luxury Fever, New York: The Free Press. Frank, Robert H. (2005), ‘Does absolute income matter?’, in P.L. Porta and L. Bruni (eds), Economics and Happiness, Oxford University Press, pp. 65–90. Friedman, Benjamin (2006), The Moral Consequences of Economic Growth, New York: Vintage. Stevenson, Betsey and Justin Wolfers (2008a), ‘Economic growth and subjective well-being: reassessing the Easterlin Paradox’, SSRN Working Paper, Series No. 2394, available at http://search.ssrn.com/sol3/papers.cfm?abstract_id51121237, last accessed 20 May 2009. Stevenson, Betsey and Justin Wolfers (2008b), ‘Economic growth and subjective well-being: Reassessing the Easterlin paradox’, Brookings Papers on Economic Activity, 1, 1–87. Townsend, Peter (1979), ‘The Development of research on poverty’, in Social Security Research: The Definition and Measurement of Poverty, Department of Health and Social Research, London: HMSO. Veenhoven, Ruut (1993), Happiness in Nations: Subjective Appreciation of Life in 56 Nations, Rotterdam: Erasmus University.

8.

Does inequality matter to individual welfare?1 An initial exploration based on happiness surveys from Latin America Carol Graham and Andrew Felton

The effect of inequality on individual welfare remains a debated question in economics. It is a topic where strong normative judgments outweigh the existing empirical evidence, and debate is often acrimonious and polarized. For those who interpret inequality as a sign of opportunity and/or of rewards to productivity, it is difficult to accept that there are negative effects. For those that see inequality as a reflection of persistent disadvantage for particular segments of society, it is hard to see positive elements. And for those who are primarily concerned with the fostering of income growth (and perhaps with the reduction of absolute poverty), inequality is beside the point – a ‘luxury’ problem of sorts. Yet evidence from several empirical studies suggests that relative income differences matter to individual welfare, and in ways which are relevant to economic and political decisions. Relative differences seem to matter in two ways. The first is a levels effect. Two individuals of the same level of income perceive themselves differently if the average wealth of their relevant peer groups is different. There is also a related adaptation effect: as people’s incomes rise, so do their expectations. Thus it takes more income to increase their utility the same amount than when their income was at a lower level. This can be explained conventionally by declining marginal utility of wealth. We attempt to show in this chapter, however, that relative differences are important as well as absolute differences. An additional element of inequality – which we know even less about – is inequality per se – inequality defined more broadly than in terms of personal finances – on individual welfare. Broader definitions of inequality – such as between groups, among neighbors, and within and across skill and education cohorts – may be as if not more important to individual welfare as financial gaps. Inequality more broadly conceived incorporates, among other things, norms of equity and views about fairness and 158

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redistribution, which vary across cultures and societies.2 Not surprisingly, accurately measuring this broader inequality is a conceptual and empirical challenge. An extensive literature examines the effects of inequality on aggregate growth outcomes and explores the possible channels, such as incentives for working and saving. These studies suggest that inequality can have perverse effects on aggregate welfare. Even then, there are mixed results. Barro (2001) finds that inequality is bad for economic growth for countries with per capital GNPs below $5000 but good for growth for countries with GNPs above that level. Birdsall et al. (1995) and Birdsall and Londono (1997) find that inequality has negative effects on growth for developing countries, operating via channels such as initial asset endowments, savings rates, investments in education and expectations. Benabou (2000) posits that unequal distributions can lead to a steady state of persistent inequality because political rights as well as economic goods are unequally distributed. These and other studies establish the many channels by which inequality can either be ‘destructive’ – creating disincentives for savings and investments and even for voting – or ‘constructive’ – rewarding productivity and innovation.3 Yet studies of aggregate outcomes do not address the issue of the direct effects of inequality on individual welfare, nor the effects of inequality more broadly defined. While there is a rich theoretical literature on the topic, empirical work demonstrating such effects is less common. The findings thus far are mixed, making it difficult to draw more generalized conclusions beyond the particular countries where the studies are carried out.4 The recent interest among economists in using surveys of reported wellbeing as a way to gauge individual utility and its relation to a range of economic and social phenomena provides a new tool with which to assess the effects of inequality. Happiness surveys are, of course, not without limitations and biases.5 Yet they are particularly useful in the study of inequality because it is an area where a revealed preferences approach has limited utility.6 Take, for example, a poor Bolivian who may be made very unhappy by inequality in their country. Even if these effects are very large, short of emigrating, it is hard for them to reveal a preferred distribution. Granted, proxies for preferences, such as voting patterns, can provide insights into individuals’ preferences about inequality, and several studies have attempted to do just that and have contributed to our understanding.7 Yet surveys of reported well-being provide a direct tool for measuring the effects of inequality on respondents’ well-being. Alesina et al. (2004), for example, use happiness surveys and rely on country- and state-level Gini coefficients to examine the effects of

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inequality in Europe and the USA. They find that people have a lower tendency to report themselves happy when inequality is high, controlling for individual income. Yet they also find that reactions to inequality vary according to geography, political preferences and individual wealth.8 Other studies, based on data for different countries and time periods, find positive effects of inequality on well-being.9 One explanation for the mixed results is that most of our standard measures of inequality, such as Gini coefficients and 90/10 ratios, do not capture all of the channels through which inequality affects individual welfare. They are aggregate, static measures based on the distribution of national or regional incomes. Gini coefficients provide an aggregate picture, but they do not capture changes in income mobility rates, nor do they change much over time. Chile, for example, is a country which has changed dramatically in the past three decades, both in terms of the structure of its economy and polity, and in terms of social mobility. Yet the Gini coefficient in Chile is roughly the same today as it was in the 1960s (Contreras et al., 2004). Thus these measures capture some aspects of inequality, but they are less well suited to identifying others, which may depend on contextual variables at much lower levels of aggregation. In this chapter, we explore the effects of inequality on individual welfare using both standard and less conventional measures of inequality. We also attempt to assess the effects of inequality per se, and the channels via which it could potentially operate. We build from the existing work in the economics of happiness – and other work on several aspects of inequality – to explore the effects of these different definitions of inequality on the individual welfare – or more specifically the happiness – of a large sample of respondents in Latin America. In its usage of different measures of inequality and its attempts to identify additional affects of inequality per se, the chapter is by definition exploratory. Because we do not have an exact definition of inequality per se, we cannot predict ex ante why it might make people happy or unhappy. Yet we suspect that this less measurable, less well-defined element of inequality is precisely what makes people feel strongly about it, either positively or negatively. As one means of exploring this broader concept of inequality (no doubt an imperfect one), we focus on a number of variables which capture respondents’ perceptions of rank and status. We also examine how these perceptions vary according to reference group size. Conceptually, the simple financial definition of inequality can be thought of as a measure of outcomes which reflect different utility functions between labor and leisure and different endowments. Thus those who prefer to work more have more income and those that prefer to work less have less income. The broader definition of inequality per se, meanwhile,

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can be thought of as the differences among people, such as race, family background, location, quality of education and other factors which can be difficult to measure but that play a major role in determining opportunities and outcomes. In a normative sense, most people would not have deep concerns about the former kind of inequality, while many, although not all, would have concerns about these other sorts of differences and their role in limiting access to opportunity. We rely on happiness surveys to distinguish between the effects of each kind of inequality. The happiness literature, meanwhile, shows that at some level GDP per capita and happiness are correlated (see Figure 8.1). Yet that research has also shed light on many other dimensions of welfare – such as employment status, health and social welfare policy – which are both relevant to GDP and matter a great deal to happiness, but which are not captured by GDP. In an analogous manner, the Gini coefficient does not pretend to measure anything broader than income inequality, along the simple lines described above. Our hope is that in the same way that happiness surveys highlight dimensions of welfare which are related to but distinct from income, they can prove a useful tool for better understanding the many dimensions of inequality and its effects on well-being.

8.1

WHAT WE KNOW ABOUT INEQUALITY AND INDIVIDUAL WELFARE

Richard Easterlin pioneered the economics of happiness with his crosscountry work, which showed that, after a minimum per capita income level, average happiness levels do not increase as countries grow wealthier over time. His finding has since been corroborated by many others, albeit with some adjustments.10 Within countries, however, wealthier individuals tend to be happier than poorer ones. What about inequality then? Much of the literature on the economics of happiness finds that, after basic needs are met, relative differences matter at least if not more than absolute levels to reported well-being in many contexts.11 In other words, in addition to the consistent and positive effects of wealth or income on happiness within countries, most individuals’ welfare is affected in some way (positively or negatively) by relative income differences between themselves and a relevant comparator group. A less explored question is whether inequality per se matters. In other words, does relative position matter above and beyond the income effects of the gap between a respondent and their relevant reference point? And if so, what element of inequality matters? Is it income gaps within societies as measured by the Gini? Is it within group inequalities at a smaller level,

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such as at that of region or city and town? Is it across groups, such as skill cohorts or races? Is it rank or status?12 To date, the studies that have tried to explore the direct effects of inequality on well-being – via a number of different approaches – have had varied results. Alesina et al.’s (2004) study in Europe and the USA (states) finds that inequality has generally negative effects on reported well-being, but with differences across groups. It has negative effects for the poor in Europe, while in the USA, the only group that seems to be made worse off by inequality is left-leaning rich people! This supports the intuition behind other studies, which show that a strong belief in exceptional prospects for individual mobility persists across income groups in the USA. It explains high tolerance for inequality, regardless of substantial evidence suggesting that there is no more mobility in the USA than in its OECD counterparts (Graham and Young, 2003; McMurrer and Sawhill, 1998). It is also possible that state-level inequality – as captured by the Gini – may not be a relevant reference point, particularly given the high levels of physical mobility of US workers across state boundaries. Regardless, the study highlights the extent to which inequality can have different effects on individual welfare, depending on both the context and the measure of inequality that is available. Other authors have found divergent effects of inequality on well-being, depending on the data and the countries that are used. Clark (2003) uses data from the British Household Panel Survey (from 1991 to 2002), and finds that regional inequality – as measured by the Gini – and life satisfaction are positively correlated. At the same time, he finds that average reference group income (regional level) is negatively correlated with life satisfaction (holding income constant), as in many other studies. Clark also examines the mobility traits of his respondents and finds that those respondents that have experienced the most income variability or larger pay rises are more likely to be positively affected by income inequality in their reference group. He posits that for these respondents, inequality is a sign of opportunity. Clark notes that his results are in keeping with an earlier study by Tomes (1986), which finds that inequality is positively correlated with well-being for men in Canada (across districts). Yet he also notes that many other authors have found a negative relationship. Hagerty (1999) uses aggregate data from eight countries and shows that average happiness levels are lower in those with wider distributions. Blanchflower and Oswald (2003) find a small negative effect of state level inequality in the USA. Luttmer (2004) uses panel data from the US National Survey of Families and Households (NSFH), matched with local earnings data from Public Use Micro-data Areas (PUMAs), geographic units which have

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roughly 15 000 inhabitants, to explore the effects of inequality on welfare. The panel nature of the data allows him to control for individual level effects and for selection bias. He finds that, all else held equal, higher earnings of neighbors are associated with lower levels of self-reported happiness. This finding holds for life satisfaction as defined as ‘satisfaction with one’s financial situation’ rather than for satisfaction with other aspects of respondents’ lives, such as health and marital status. Luttmer’s findings highlight the importance of relative income differences as people assess the adequacy of their personal income compared to those around them. One way of interpreting Luttmer’s findings is to think about income distributions in general. Most distributions are roughly lognormal, bounded on the left and skewed to the right. Inequality in essence measures the variance of a given distribution. Variance disproportionately occurs on the right – in the wealthier parts of the distribution. When inequality increases, the mean increases relative to the median.13 Thus an increase in inequality is likely to make the median respondent feel worse off because they are objectively further from average income levels than they were before, even though their absolute income level did not change. If the gaps between the mean and the median are visible (as they would be with conspicuous consumption in a smaller reference group like the ones Luttmer analyses), the median respondent may also perceive that they are poorer than before because they cannot afford to purchase the same goods as their neighbors are now buying. Studies of inequality in Russia, meanwhile, find no direct effects of inequality on well-being. Claudia Senik, using the Russian Longitudinal Monitoring Survey (RLMS) data (1995–2000), finds no relationship between happiness and regional level Gini coefficients. Eggers et al. (2006), using the same survey for different years, corroborate Senik’s findings. They also find that respondents (both employed and unemployed) are happier in regions with higher unemployment rates. They posit that inequality in Russia tends to accompany economic change and marketoriented reforms, while unemployment rates are higher in regions where reform has been less extensive. Inequality may be a signal of progress and mobility for those who are engaged in and benefiting from reform, yet a threat or the source of envy for those who are not.14 In a more recent paper, Di Tella and MacCulloch (2003) use the US General Society Survey and the Eurobarometro data to test whether inequality has an additional effect on well-being above and beyond reflecting differences in personal income levels. They do not find additional effects of relative status above and beyond those of differences in personal incomes. They posit that this lack of concern helps explain the persistence of flat levels of happiness despite rising levels of inequality in the past decades.

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Other studies, which explore the role of different reference norms in mediating the effects of inequality on well-being, are suggestive. Oswald et al. (2004), in a study of British workers, find that rank within firms is more important to workers’ well-being than salary levels. In a study in South Africa, Kingdon and Knight (2004) find that the income of others within respondents’ local residential area has positive effects on well-being (controlling, of course, for respondents’ own income). Yet the income of more distant others (beyond the residential area) has negative effects. Similarly, in a study in Peru, Graham and Pettinato (2002b) find that respondents tend to be more critical of their economic situation when they compare themselves to others in their country than when they compare themselves to others in their community. Race-based comparator groups are also important in racially divided South Africa. The studies suggest a strong role for reference norms such as rank, race and community in mediating the effects of inequality on well-being. One reason that the effects of inequality are of interest to scholars and policy makers is the seemingly obvious link to public attitudes about welfare and other social insurance policies. Yet the empirical evidence suggests that the link is not that obvious, as in the case of the effects of inequality on welfare. In a study in Europe Moene and Wallerstein (2003) find no relationship between inequality and support for welfare spending in general, but that spending on insurance (unemployment and disability) is higher where inequality is lower. They attribute this to selfinterest: the median voter believes they are more likely to benefit from such expenditures if inequality is lower. Schwarze and Harpfer (2004) link life satisfaction data to pre- and post-government income distribution at the regional level in Germany. They find only weak evidence that Germans are inequality averse, and instead that redistributive spending imposes an excess burden on middle income earners.15 Graham and Sukhtankar (2004) find that respondents that support redistribution in the USA are less happy, on average, than others, while in Latin America those that favor redistribution are happier than others. And, rather surprisingly, support for lower taxes and less welfare spending in Latin America is negatively correlated with wealth, a correlation which has been increasing in strength in the past few years in the region.16 This rather counterintuitive finding could be the result of a new enlightened self-interest on the part of elites, or it may reflect the reality that the poor have traditionally benefited the least from public expenditures in the region.17 Regardless of the explanation, these findings suggest that inequality can play into support for redistribution in ways that diverge markedly from the standard theories. Median voter theory, for example,

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predicts that the poor should be the strongest supporters of redistribution, as they stand to benefit most. In this chapter we rely on a large data set for Latin America to explore the effects of inequality on welfare. We first explore the direct effects of inequality on well-being, and how they vary according to different reference groups. We also tried to capture broader concepts of inequality (inequality per se), which include inequality pertaining to race, status and access to opportunities. We thus analysed a number of measures of perceived economic well-being and relative position, and also looked for links between these perceptions and public attitudes about redistribution. Finally, we looked at how the costs of unemployment on well-being vary in relation to inequality.

8.2

DATA

In this chapter we use the methodological approach provided by the economics of happiness. Economists who work in the area broadly define happiness and/or subjective well-being as satisfaction with life in general. Indeed, the three sets of terms are used interchangeably in most studies. Most studies of happiness are based on a very simple set of survey questions that typically ask respondents: ‘How satisfied are you with your life?’ or ‘How happy are you with your life?’ Answers to this open-ended question incorporate psychological as well as material and socio-demographic factors. Critics used to defining welfare or utility in material or income terms bemoan the lack of precise definition in these questions. Yet the economists who use these surveys emphasize their advantages in making comparisons across cohorts of individuals – in which they find a surprising consistency in the patterns of responses both within and across countries, such as in the effects of age, health and marriage on happiness. Psychologists, meanwhile, find a significant degree of ‘validation’ in subjective well-being surveys, wherein individuals who report higher levels of happiness actually smile more, as well as meet several other psychological measures of wellbeing.18 Finally, although economists prefer to use revealed preferences as their measure of utility, this technique at times presupposes an agency that the subject does not possess. In this instance, we are measuring the effect of social arrangements on individuals, arrangements they are usually powerless to affect and for which revealed preferences are inapplicable. The happiness questions are often based on a 4-point scale: ‘how happy or satisfied are you with your life’, with two answers above and two below neutral.19 The correlation coefficient between happiness and life

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167

satisfaction questions is approximately 0.50, and the micro-econometric equations have almost identical forms.20 The data are most useful in the aggregate, rather than at the individual level. How an individual answers a question on happiness, for example, can be biased by day to day events, like the break-up of a relationship or a grade on a test. Thus the same person could answer such questions quite differently from day to day or year to year. Despite that, there is a remarkable consistency in the determinants of happiness across large samples of respondents, both across countries and over time. Our own analysis of the determinants of happiness in Latin America and Russia finds that Latin American respondents are, for the most part, remarkably similar to those in the OECD countries and other countries where happiness has been studied (Graham and Pettinato, 2001, 2002b). In this chapter we use the annual survey provided by the Latinobarómetro organization (1997–2004). The survey consists of approximately 1000 interviews in each of 18 countries in Latin America.21 The samples are conducted annually by a prestigious research firm in each country, and are nationally representative except for Chile, Colombia and Paraguay.22 The survey is comparable to the Eurobarometro survey for European countries in design and focus. The survey does not interview the same people every year, so we cannot examine attitudes changing over time except in the aggregate. A standard set of demographic questions are asked every year. Accurately measuring income in developing countries where most respondents work in the informal sector and cannot record a fixed salary is notoriously difficult. Thus many surveys rely on reported expenditures, which tend to be more accurate, if less able to capture the assets of the very wealthy. The Latinobarómetro has neither, and instead relies on the interviewer’s assessment of household socio-economic status (SES) as well as a long list of questions about ownership of goods and assets, upon which we compile our wealth index. The index is based on ownership of 11 types of assets, ranging from drinking water and plumbing to computers and second homes.23 There are also standard questions in the survey about life satisfaction, perceived economic well-being and future prospects for respondents’ children, position on a notional economic ladder and views about the respondent’s country’s future prospects. There are a range of questions about preference for and satisfaction with market policies and democracy, as well as confidence in public institutions and views about redistribution (these vary by year of the survey). To avoid large swings in our sample size, we primarily use the 2004 data in our regressions. This is a large set (N 5 19 605) with each country

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having over 1000 observations. We occasionally use data from other years in order to make use of questions that were asked only in that year, such as health status, and in a few instances use the entire pooled set of respondents for 1997–2004. To establish a benchmark of the determinants of happiness in the region both across countries and over time, we ran our standard happiness regression on the entire pooled data set (including both country and year dummies). We cannot include the health variable in the pooled set, as it does not appear in all years. Regardless, our across time findings are very close to our findings based on annual surveys, and the determinants of happiness in Latin America are very similar to those in the USA and Europe, with the exception of a few variables.24 (Table 8.1). Women are happier than men in the USA, for example, but men are happier than women in Latin America, which may be explained by unequal gender rights. Age has the typical U-shaped curve in Latin America, with the low point at 51 years; it tends to be in the early forties for the USA and Europe.

8.3

DIRECT EFFECTS OF INEQUALITY

In this section we take advantage of having a range of measures of inequality to explore whether its effects vary depending on how it is measured and on reference group size. In the next section we rely on our data on perceptions of inequality to attempt to capture the broader elements of inequality, with the objective of better understanding the effects of inequality per se on well-being. For the 17 countries in our sample we use the latest available national level Gini coefficients on income as well as two measures of personal income and relative position. In addition to country-level and individual relationships, we explore variance according to the size of the cities that respondents live in. Our objective in this section is to compare the effects of these different measures of inequality on reported well-being, as well as to attempt to better sort out the difference between concerns about personal income and those about inequality and injustice more generally. We first focused on inequality as measured by the Gini coefficient (Table 8.2). We included the variable with our standard happiness equation, which is comparable to those used in most happiness studies: an ordered logit estimation with reported happiness as the dependent variable, and including the usual socio-demographic traits, such as age, education, wealth, gender, marital status, employment status and self-reported health status as independent variables.25 We used the pooled data set (1997–2004) and included country dummies and cluster controls at the country level.26

169

−0.034 0.0004 −0.002 0.097 0.044 0.067 −0.289 −0.051 −0.104 0.027 0.9 0.665 −0.306 −0.708 −0.097

Age Age squared Years education Married dummy Male dummy

Wealth (0-11) Unemployment dummy Self-employment dummy Retired dummy Student dummy Small town dummy Big city dummy Argentina Bolivia Brazil

Coefficient

24.60** −12.57** −3.73** −3.78** 1.12 23.22** 32.79** −10.28** −22.72** −3.19**

−16.21** 14.25** −1.52 7.68** 3.79**

z-score

1997–2004 data

Determinants of happiness

Independent variables

Table 8.1

Age Age squared Years education Married dummy Male dummy Health (1-5) Wealth (0-11) Unemployment dummy Self-employment dummy Retired dummy Student dummy Small town dummy Big city dummy Argentina Bolivia Brazil

Independent variables

0.013 0.175 −0.023 0.415 0.095 −0.375 −0.068 0.177 0.059 0.074 −0.06 0.385 −0.33 −0.001

−0.041

Coefficient

−8.15** 7.18** 3.44** 5.79** −0.81 23.71** 12.49** −6.73** −2.05* 2.55* 0.99 1.56 −1.86 5.03** −4.11** −0.01

z-score

2004 data only

170

(continued)

Notes:

0.278 0.861 −0.232 −0.505 0.228 0.385 0.523 0.224 0.114 0.369 −0.078 −0.822 0.685

Coefficient

105885

9.25** 26.78** −7.88** −16.73** 7.07** 11.88** 15.97** 7.45** 3.48** 11.68** −2.10* −26.11** 22.24**

z-score

1997–2004 data

Observations Low point of age: 51.5

Colombia Costa Rica Chile Ecuador El Salvador Guatemala Honduras Mexico Nicaragua Panama Paraguay Peru Venezuela Dominican Republic

Independent variables

Ordered logit estimation of a 1–4 scale of happiness; *significant at 5%; ** significant at 1%.

Observations Low point of age: 51.0

Colombia Costa Rica Chile Ecuador El Salvador Guatemala Honduras Mexico Nicaragua Panama Paraguay Peru Venezuela

Independent variables

Table 8.1

1.17 1.392 0.195 −0.314 0.675 1.187 1.418 0.467 0.634 1.118 0.32 −0.254 1.433 1.012

Coefficient

19152

14.75** 16.72** 2.54* −4.02** 8.21** 13.87** 16.40** 5.96** 7.40** 13.78** 3.38** −3.19** 17.50** 12.21**

z-score

2004 data only

Does inequality matter to individual welfare?

Table 8.2(a)

Inequality variables

Gini category

Country

Low (Gini ≤ .50)

Uruguay Costa Rica Venezuela Peru Dominican Republic Argentina El Salvador Mexico Honduras Nicaragua Ecuador Panama Paraguay Chile Colombia Bolivia Guatemala Brazil

Medium (.50 < Gini ≤ .55) High (.55 < Gini)

171

Gini coefficient 44.6 46.5 47.6 49.4 49.7 52.2 53.2 54.6 55.0 55.9 56.2 56.4 56.8 57.1 57.6 57.8 58.3 59

Table 8.2(b) Gini category Low Medium High

Mean happiness

Mean wealth

2.949 2.979 2.796

6.040 6.214 5.481

coefficient

z-score

−0.1650

−10.83**

Table 8.2(c)

Standardized Gini coef.

Notes: Ordered logit estimation of a 1-5 scale of whether taxes are too high in [country]. Controls include demographic variables from Table 1 (except health, not available in this data set) and standardized Gini coefficient.

As is shown in Table 8.2, respondents in medium Gini countries are happier then either those in low or high Gini countries, with the least happy respondents being in the high Gini countries. These findings are crude at best: we cannot control for individual specific traits as we would

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in a panel and, other than cluster controls, we cannot account for traits specific to the country groupings that might affect the results. Still, the finding for the high Gini countries suggests that there may be direct wellbeing costs from living in an environment of exceptionally high levels of inequality. Given that Latin America as a region displays the highest levels of inequality in the world, this is certainly plausible. We explored whether the unhappiness costs of being in a high Gini country also translated into support for more redistribution. We used a question from 2003, which asked respondents whether taxes were too high, too low or just right. We found that respondents in higher Gini countries were less likely to think that taxes were too high than were those in low Gini countries, suggesting a link between higher levels of inequality and support for redistribution. Yet, as discussed above, within countries in the region it is wealthier rather than poor individuals that express greater support for redistribution. The redistribution story does not seem to conform to any obvious patterns. The above results are suggestive, but are rife with the problems of using country-level measures to gauge the effects of inequality on welfare at the individual level. There are two fundamental problems in our view. The first is our inability to capture unobservable traits that are shared by the particular countries that fall into our rankings or categories. We can control (crudely) for the effects of such traits by clustering, but this does not answer the question of what the unobserved effects are. Figure 8.1, for example, shows that there are some similarities in average happiness levels across countries in the region that seem to reflect cultural and locational similarities more than anything else. Second, it is not clear that these aggregate country-level measures capture the things about inequality that matter to individuals. Most people do not even know what a Gini coefficient is, much less what the coefficient is for their country and how that compares to other countries. They perceive inequality in terms of how their income or other assets compare to those of others in a relevant reference group, which could be as small as the neighborhood and as large as the global economy. They may also be affected by non-income inequalities, such as racial and gender disparities. Standard income-based measures are not well suited to capturing these broader definitions of inequality. We first attempted to see if reference group income had negative effects on individuals’ well-being, controlling for individual wealth levels, as Luttmer does for US PUMAS. We ran a standard happiness regression, with the usual socio-demographic controls, but including a variable representing the average wealth level for the country each respondent lives in (clustering for correlated errors at the country level). Because we rely

Does inequality matter to individual welfare?

Table 8.3

173

Average vs. relative wealth Average wealth calculated by: country

individual 0.1117583 wealth 5.44** average −0.0523256 wealth −0.70 relative wealth country N dummies* citysml Y dummies cluster by: country

country

country city size

0.1121746 −6.9** 0.0594327 0.0543354 0.78 −0.92 0.1117583 5.44** N N

country city size

country city size

0.0968018 7.96** 0.0578392 −0.0805081 0.99 −2.19* 0.1121746 6.9** N Y

country city size

0.0162937 0.42 0.0968018 7.96** Y

Y

Y

Y

Y

Y

country

country |citysml

country citysml

country citysml

country citysml

Notes: Ordered logit estimation of a 1-4 scale of happiness; * significant at 5%; ** significant at 1%. Demographic variables in all regressions: age, age squared, years education, married, male, health, unemp, selfemp, retired, and student. * When calculating average wealth at the country level, country dummies cannot be included in the regression due to multicollinearity. When we run split sample regressions, by city size, average wealth is positive and significant for small cities. * t-statistics underneath coefficients.

on the 2004 sample (which is the only one which has both the Dominican Republic and the self-reported health variable in it), and have only one year’s observation for average wealth, we cannot include country dummies (the variables are linearly dependent). We get the expected positive and significant sign on individual wealth, and a negative but insignificant sign on average wealth, as shown in Table 8.3. We have posited that reference norms other than those at the country level are important in mediating the effects of inequality on well-being. As one way of testing this (and of getting around the above problem), we calculated average wealth for respondents in the sample according to city size (small, medium and large cities), and also included individual wealth in the equation. Small cities are defined as having less than 5000 respondents, while large cities have over 100 000 respondents or are the national capital. This breakdown also reflects the survey’s population distribution, which has spikes at just below 5000 and at over 100 000. The population size for each grouping in each country is about 2700 for small towns, 7300 for medium towns and 9600 for big cities, which is similar to the range of Luttmer’s PUMAs (roughly 15 000 inhabitants each). As is evident from

174

Happiness, economics and politics 0.3

Percentage

0.2

0.1

0 < 5,000

10,001–20,000 40,001–50,000

> 100,001 Capitol

City size 0.5

Percentage

0.4

0.3

0.2

0.1

0 1

Figure 8.2

2 City size

3

Histogram of respondents by city size

Tables 8.1 and 8.5a, in general respondents are happier in smaller cities and less happy in big ones. This also allows us to focus on the difference between rural areas, normal cities and large metropolitan areas. See Figure 8.2 for the histogram of city sizes. We then repeated the above exercise, but calculated average wealth for each city size level within each country. With this less aggregated specification for average wealth, we are able to include country dummies. In

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this instance, we again get the positive sign on individual wealth, but a negative and significant sign on average wealth. Thus, in Latin America, having wealthier neighbors or city-mates, controlling for an individual’s own wealth, lowers self reported happiness. This is similar to what Luttmar finds for earnings areas/PUMAs in the USA. Relative differences matter to respondents in Latin America, above and beyond the effects of individual income. The above regressions used the following formula, where X is a vector of individual characteristics that have been found to matter to happiness, such as marital status, education, health and so on: Y 5 X b 1 avg wealth b2 1 wealth b1. This is equivalent to the approach used in the Di Tella and MacCulloch paper described above.27 In addition, though, they decompose income into average national income and relative income, which is the difference between individual income and average income. We do the same for our wealth index, labeling the former variable avgwealth and the latter, relwealth. The sum of the two is individual income. This means that if the coefficients on the two variables are the same in a happiness regression, then happiness is increasing in wealth with no regard to relative status. For example, if average income increases by one measurement unit but a person’s income remains constant, then that person’s happiness increases by the coefficient on avgwealth but decreases by the coefficient on relwealth. If they are the same, then the person’s happiness is unchanged. If relwealth is more important than avgwealth, as one studying these variables might posit, then happiness would decrease. The equivalence between the Di Tella and MacCulloch and Luttmer techniques is demonstrated below: Y 5 X b 1 avgwealth b3 1 relwealth b4  (DiTella and MacCulloch) 5 X b 1 avgwealth b3 1 (wealth 2 avgwealth) b4 5 X b 1 avgwealth (b3 2 b4) 1 wealth b4  (Luttmar) Therefore, the Di Tella and MacCulloch approach provides the same information as the Luttmer technique, but making explicit the effects of relative as well as average wealth on happiness. Di Tella and MacCulloch use data from the US General Social Survey and the Eurobarometer and find that the effect of each of these components is the same – with a coefficient of 0.5 on each. Thus they reject the hypothesis that relative income

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per se – above and beyond being a concern for personal income – matters. We repeat this exercise with our data for Latin America, although we must use our 0–11 wealth index rather than income, and thus do not take logs. In strong contrast to the findings for the USA and Europe, we find that the coefficient on average wealth is insignificant, while the coefficient on relative wealth is positive and significant (Table 8.3). The implication is that only relative income, above and beyond average wealth, matters positively to well-being in the region. Thus relative wealth contributes to greater than average happiness for those that are above mean income – the wealthy. It results in lesser than average happiness for those who are below mean income – the poor (as the value on relative wealth for those below mean income is negative, making them that much less happy). We repeated the same regressions with our country/city size specification of average and relative wealth, including country dummies. Each observation for relative wealth is the respondent’s distance from the mean wealth level of other respondents in similar sized cities in their country. As in the case of the country-level specification, we get an insignificant sign on average wealth, and a positive and significant sign on relative wealth, confirming the importance of relative wealth to Latin American respondents, this time using a different reference norm (Table 8.3). Unlike the results for Europeans and Americans in country-level and state-level studies, Latin Americans seem to be concerned with relative differences above and beyond their being a product of total individual income.28 The high levels of inequality in Latin America may underlie our respondents’ higher levels of concern for relative than absolute differences. We also explored the effects of relative and absolute wealth according to which quintile respondents were in. Much of the theory – and some of the empirical work on the role of relative versus absolute income – suggests that absolute income gains matter more to those below a certain minimum level of income. Relative income matters more, meanwhile, as people get wealthier and are no longer concerned about meeting basic needs. In an analogous sense, cross-country happiness comparisons find that economic growth leads to higher average happiness levels at low levels of per capita incomes but not at higher ones. Our results do not necessarily fit the theory. We grouped respondents into quintiles for our sample, based on our wealth index, to see if the coefficients on relative and absolute wealth differed by quintile. Thus, in each quintile category, the observation on average wealth is the average wealth for the respondent’s country; the respondent gets a 0 for the quintiles that they are not in, and the average wealth figure for the quintile they are in. Relative wealth works similarly; respondents get zero values for the

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177

quintiles they are not in, and then the value of each respondents’ particular relative wealth is recorded in the quintile group that they correspond to. When we include our quintile variables in the regression, we find that average wealth remains insignificant, while individuals in quintiles 1, 2 and 5 retain concerns about relative wealth. (The coefficient on relative wealth for the fifth quintile is positive and significant at the 15 percent level only.) The coefficient on relative wealth for the fourth quintile is significant and negative, meanwhile, but only at the 10 percent level. This suggests that relative income differences make these respondents less happy, even though they are above mean income. This may be because their distance from the mean and/or the poor does not seem big enough, because they think their distance from the rich is too great, or both. The most significant effects seem to be those for respondents in the lowest two quintiles. As they are below mean income, the positive coefficient on relative wealth translates into lower happiness levels (Figures 8.3a and 8.3b). Inequality in Latin America seems to make the poor much less happy and the rich moderately happier. We then repeated our work at the country/city size reference group level. As above, this was a simple grouping of respondents by wealth quintile – in this instance based on the city size/country intersection. In this case respondents are grouped in quintiles which correspond to their country and also to their city size – small, medium and large. Thus respondents who live in big, wealthier cities are likely to be in a higher quintile when grouped at the country level than when compared to wealthier respondents in their city size reference group. We ran the same regression as above but for country/city size average and relative wealth, and including country dummies. In this instance, though, we again get an insignificant effect on average wealth, and strong (positive) effects of relative wealth for the wealthiest quintile. Relative wealth is positive and significant at the 10 percent level for those in the first and fourth quintiles (and a negative but insignificant effect on quintile 3). Thus the effect holds weakly for the poorest, but flips for those in the fourth quintile. Some of this may be specification driven: those respondents that are in quintile 4 at the country level are likely to be in quintile 3 when compared with other respondents in big cities, for example (Figures 8.3a and 8.3b). With the city size rather than country level reference group, the effects of relative wealth seem to be stronger for the rich rather than for the poor. It may well be that when compared to those in a smaller reference group, the poor feel less distanced from the rich, and therefore suffer less negative effects of inequality. The rich, meanwhile, may feel relatively better off with a smaller reference group than they do in a larger one. In other words, a respondent who is wealthy compared to those in their small town

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Average wealth quintile

1 2 3 4 5

coefficient 0.0495 0.0552 –0.0114 0.1067 0.0613

Relative wealth quintile

1 2 3 4 5

0.1690 0.5994 0.5442 –0.2873 0.0450

z-score 0.61 0.80 –0.14 1.25 0.85 3.12** 3.35** 1.77 –1.82 1.49

0.6 avg wealth coefficient relwealth coefficient 0.4

0.2

0.0

–0.2

1

2

3 Quintile

4

5

Notes: Average wealth computed by country. Control variables: standard demographic variables, clustered by country.

Figure 8.3a

Relative wealth and happiness, by wealth quintiles

reference group is probably less wealthy in relative terms when compared to the larger, country-level reference group. Regardless of the nuances, relative differences seem to matter to well-being in the region, even when a different reference group is used. These differences seem to matter most to those at the top and bottom of the distribution. To explore differences across reference groups more closely, we ran the average/relative wealth regression separately for each city size. In a departure from most of the above findings, in which average wealth is insignificant, we get a positive and significant sign on average wealth for respondents in small cities. While the sign on relative wealth remains positive and significant, the value on the coefficient is smaller than that for average wealth (although the t-statistic is much higher). This suggests that both average and relative wealth levels matter to the well-being of those

Does inequality matter to individual welfare? coefficient

z-score

Average wealth quintile

1 2 3 4 5

0.018 0.028 0.041 0.019 0.002

0.49 0.78 1.02 0.49 0.04

Relative wealth quintile

1 2 3 4 5

0.065 0.085 –0.151 0.149 0.157

1.72 1.57 –1.22 1.92 3.94**

179

Avg. wealth by country and city size 2 Average wealth Relative wealth

Coefficient

1

0

–0.1

–0.2 1

2

3 Wealth quintile

4

5

Notes: Average wealth computed at country/citysml intersection. Control variables: standard demographic variables and country dummies, clustered by country/city size.

Figure 8.3b

Relative wealth and happiness, by wealth quintiles

in the small cities, our smallest size reference group, and also those with the lowest levels of average wealth. For our larger and wealthier reference groups (the larger city and country levels), in contrast, relative wealth seems to be the only wealth variable that matters.29

8.4

WHAT DO THESE RESULTS MEAN? A SIMPLE ILLUSTRATION

What does all of this mean in plain language? We illustrate in Figure 8.4 with a simple exercise comparing a typical respondent in the bottom and top quintiles from Honduras and Chile. Average wealth levels, on our 0–11 scale wealth index, are 4.78 for Honduras and 7.75 in Chile – almost twice

180

Happiness, economics and politics Rich Hondurans: wealth = 8.0 RichChileans: wealth = 10.3 Average Honduran wealth: 4.8

Honduran gap: 3.3 Chilean gap: 2.5

POOR

RICH

Honduran gap: 2.1 Chilean gap: 2.5 Average Chilean wealth: 7.8 Poor Hondurans: wealth = 2.6 Poor Chileans: wealth = 5.3 Happiness Gap = wealth gap * coefficient ÷ 4 Calculated Happiness Gap Chile wealth gap Honduras wealth gap Chile-Honduras difference difference * coefficient/4 = Honduran happiness differential

Poor –2.489 –2.142 0.347 0.43%

Rich 2.521 3.261 0.740 0.93%

Mean Happiness (1–5 scale) Wealth quintile 1 2 3 4 5 Total

Chile 2.54 2.74 2.77 2.94 3.08 2.79

Honduras 3.11 3.15 3.17 3.13 3.30 3.17

Overall 2.73 2.85 2.91 2.97 3.08 2.88

Mean Wealth (1–11 scale) Chile 5.26 7.00 8.00 9.00 10.27 7.76

Honduras 2.64 4.00 5.00 6.00 8.04 4.78

Overall 3.12 5.00 6.00 7.46 9.63 5.81

Note: Regionwide results: rich are 3.83 points higher than mean; poor are 2.68 points lower than mean. These gaps * .05/4 5 5%. happiness for the rich and 3%, happiness for the poor.

Figure 8.4 Happiness gap in Honduras and Chile as high in the latter. Average wealth in the bottom quintile in Honduras is 2.64 and in Chile is 5.26, over twice as high in the latter. Average wealth in quintile 5 in Honduras is 8.04 and in Chile it is 10.27. If rising personal wealth is sufficient to increase happiness, then the typical respondent in Chile should be happier than in Honduras, and a poor respondent in Chile should be much happier than in Honduras, while a wealthy one should be moderately happier. Yet, as the coefficient on average wealth is insignificant, it suggests this is not the case.

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Instead, it is relative income, or the gap between each individual’s income and the average that matters. For the typical poor (quintile 1) respondent in Honduras, the gap between their income and the average is 2.14 points. In Chile the gap between the quintile 1 respondent and the average is 2.49 points. If we multiply the difference between these figures (0.35) times the coefficient from an OLS regression on relative wealth for the region (0.05) then we can assume that poor (quintile 1) respondents in Honduras are about one-half of 1 percent (0.017 divided by the 4-point happiness scale) happier than poor respondents in Chile, even though the average wealth levels of the poor in Chile are over twice as high!30 For those in the top quintiles, meanwhile, the gap between the wealth of those in the top quintile in Honduras and the average wealth is 3.26, while that for Chile is 2.52. If we multiply this difference (0.74) times the coefficient on relative wealth, we can assume that respondents in the top quintile in Honduras are about 1 percent happier than those in Chile, even though they are significantly less wealthy. Conducting a similar exercise at the regional level, meanwhile, we see that the average wealth of respondents in quintile 5 is 9.63, or 3.83 points higher than the regional mean wealth of 5.80, while the typical respondent in the first quintile, with a mean wealth of 3.12, is 2.68 points below the mean. Multiplying these gaps times the coefficient on relative wealth (0.05) and dividing by the 4-point scale, this implies that the rich are made 5 percent happier by their relative difference between themselves and the average, while the poor are made 3 percent less happy by inequality. This is a property of the skewed nature of the wealth distribution (which is even greater when using income as the measure rather than our wealth index), as the rich are further away from the mean than the poor are. It is important to note that this is an illustrative exercise which is intended to suggest the magnitude and direction of the effects that we find, rather than to attach a real value. There are a number of issues that we cannot resolve, such as the arbitrary nature of our scaling assumptions. Short of a viable alternative, these calculations assume that a move one point up or down the happiness scale has a similar effect regardless of where on that scale the respondent is. Yet it may well be that moving from somewhat unhappy to somewhat happy matters more to individuals’ lives than does moving from somewhat happy to very happy. We unfortunately cannot resolve that question here. Our findings suggest that inequality matters much more to well-being in the region – including for those in low income groups – than the standard theory implies. The latter stresses the importance of absolute income gains for those at the bottom of the distribution. Much of the literature on the effects of inequality (discussed above) posits that in contexts where it has

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positive effects on happiness, it is because it signals future opportunities. This can only occur if beliefs in the prospects for upward mobility are high. In Latin America, in contrast, it is likely that persistently high levels of inequality signal to the poor that there are persistent disadvantages (and possibly other kinds of discrimination which our variables do not allow us to measure) and to the rich that there are persistent advantages. On reflection, these results should not come as a surprise in a region where inequality levels are higher than in the USA or Europe, and where the institutions equalizing opportunities, such as educational and labor markets, function far less efficiently and equitably.

8.5

PERCEPTIONS OF INEQUALITY AND WELLBEING

In addition to examining the direct effects of inequality on well-being, we attempted to capture the effects of inequality per se – for example, inequality defined more broadly than in income terms. In this section we attempt to capture this broader definition of inequality through a number of different variables which capture respondents’ perceptions of inequality, status, economic success and prospects for upward mobility. In previous work we find that respondents’ prospects for upward mobility (POUM), for example, are positively correlated with happiness and even with better labor market performance in future periods.31 Here we explore the relationship of several of these variables with well-being, and how that relationship varies according to reference group size. Two questions in particular allow us to separate feelings of status from other economic concerns or utility of wealth. One of these is a catch-all question asking ‘In general, how would you describe your present economic situation and that of your family?’ This variable is consistently one of the most significant to well-being, usually more so than any other except health. The other is the economic ladder question (ELQ), included in many other well-being surveys besides the Latinobarómetro, which asks respondents to place themselves on a 10-step ladder where the poorest are on step one and the richest on step ten. This question is also an important predictor of happiness, even when other questions about wealth are included. It is purely a relative ranking of wealth. When combined with the personal economy question, it allows us to decompose the utility of wealth into status and other effects. The frame of reference for the ELQ is left up to the respondent. The question does not specify whether the ladder represents their country or a smaller or larger reference group (such as the city or the world). Responses

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183

Table 8.4 (a) Summary statistics for ELQ and economic satisfaction Means of variables

economic satisfaction (1-4 scale)

ELQ (1-10 scale)

wealth (1-11 scale)

2.88 2.96 3.01

3.66 3.74 4.25

4.38 5.34 6.56

Small town Medium city Big city

education happy (1-16 scale) (1-5 scale) 7.37 7.16 9.53

2.72 2.94

Table 8.4 (b) Correlation between different measures of wealth wealth

socio-economic status

personal economic satisfaction

wealth

1

socio-economic status*

0.5112

1

personal economic satisfaction ELQ

0.2521

0.2477

1

0.3956

0.327

0.3131

Note:

ELQ

1

* As judged by the interviewer.

suggest that people in fact take all of these frames into account. Wealthier countries have higher ELQ scores, suggesting international comparisons; ELQ increases (as does wealth) with city size, suggesting country-wide comparisons; but ELQ increases more slowly with city size than wealth does, indicating local comparisons. Meanwhile, personal economic satisfaction increases with city size, but given the increase in the other variables, there is actually a negative coefficient on the big city dummy variable in the regression. Summary statistics for the ELQ and personal economy question are in Table 8.4. What do these subjective variables, personal economy and ELQ, allow us to measure that the objective variables used before do not? For one thing, they may do a better job of measuring the elusive concept of relative status than looking at relative wealth alone. When regressing happiness on four measurements of wealth (wealth, ELQ, personal economy and socio-economic status, plus standard demographic variables and country dummies), the latter two subjective variables were more significant, both statistically and practically, than the objective variables. There is obviously some collinearity among these variables, but there is also a fair

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amount of variance (the correlation is , 0.6 between any two of them, see Table 8.4) and the results hold up using both OLS and ordered logit regressions. It also holds up when measuring relative wealth at the country and country/city size level, with and without the relevant dummies. In fact, a happiness regression with our full set of 30 control variables (but not the personal economy question) gives an R-squared value of 0.069, while using the personal economy question as the only explanatory variable gives an R-squared value of 0.038. When we include both personal economic ranking and the ELQ in a happiness regression, we find that the coefficient on the personal economic ranking is much greater than that for the ELQ (Table 8.5). Even after adjusting for scale (there are twice as many possible responses on the ELQ as there are on the personal score), this suggests that people’s subjective assessment of their overall personal situation is much more important to their happiness than is their subjective assessment of their relative position. How can we reconcile this with our previous finding that relative wealth is all that matters to happiness? Indeed, it is consistent with that result. Relative wealth is presumably an important factor in the personal economy question. Since ELQ is not perfectly correlated with personal economy, the fact that the ELQ is significant at all indicates that relative status has bearing on happiness outside of a purely economic context. We looked at the determinants of ELQ scores (in other words, using the ELQ as the dependent variable). As in the case of happiness, ELQ scores display a U-shaped relationship with age, first decreasing until approximately 57 years and then increasing (a similar shape to that of happiness). Education, wealth and self-reported health are positively correlated with ELQ scores, while men and the unemployed are more likely to report lower ELQ scores. Since men are, on average, wealthier than women, this suggests that they also have higher economic standards than women do (Table 8.6). We then looked at how these scores varied according to where people live (city sizes). Wealth levels are, on average, higher in large cities than in small ones. In contrast, we found that respondents’ subjective personal economic rankings were lower in big cities and higher in small towns! (Table 8.7a). In our view this perceptions gap is in keeping with other findings in the happiness literature. It is suggestive of Luttmer’s recent work on US earnings areas and our own findings on average country-level wealth. In both cases respondents of similar income or wealth levels are less happy when their peers or compatriots have higher levels of wealth. James Duesenberry’s classic work on savings also resonates. He finds that, holding income levels constant, respondents that live in neighborhoods with higher average levels of wealth are less satisfied with their incomes than those that live in less wealthy neighborhoods.

Does inequality matter to individual welfare?

Table 8.5(a)

185

The economic ladder and personal economic satisfaction

age age squared education wealth married male health unemployed self-employed retired student small town big city

coefficient

z-score

−0.0773 0.0007 0.0153 0.2035 0.1069 −0.0537 0.4354 −0.4945 −0.0822 0.0704 −0.1513 0.0809 −0.1110

−14.54** 11.66** 3.71** 24.96** 3.37** −1.81* 23.73** −8.48** −2.37** 0.97 −2.4 1.63 −3.26**

Notes: Ordered logit estimation of a 1-4 scale of personal economic satisfaction. Controls include standard demographic variables and country dummies.

Table 8.5 (b)

wealth average wealth small town big city

coefficient

z-score

0.2075 −0.1800 −0.0519 0.0647

14.22** −2.71** −0.69 1.08

Notes: Ordered logit estimation of a 1-4 scale of personal economic satisfaction. * t-statistics underneath coefficients.

Table 8.5 (c)

wealth socio-economic status ELQ persecon

coefficient

z-score

0.0361 0.0457 0.0704 0.5913

3.26** 1.83 4.76** 15.34**

Notes: Ordered logit estimation of a 1-5 scale of happiness. Controls include standard demographic variables and country dummies.

186

Table 8.6

Happiness, economics and politics

Determinants of ELQ

age age squared education wealth married male health unemployed self-employed retired student small town big city constant

coefficient

z-score

−0.0259 0.0002 0.0587 0.1883 0.0340 −0.1075 0.2278 −0.1033 −0.0231 0.0976 0.0976 0.0472 0.0802 2.3861

−6.29** 4.93** 18.23** 30** 1.37 −4.6** 16.25** −2.27** −0.85 1.7 1.96 1.2 3.01** 20.53**

Notes: Low point of age: 57.9. OLS regression of the 1-10 scale economic ladder question. Controls: standard demographic variables including wealth and country dummies (not shown). Second regression which included educational inequality clustered by country.

ELQ, on the other hand, rises with city size (as does wealth), and even after controlling for socio-demographic data, ELQ rankings tend to be higher in big cities. Once again, this appears to be a reference group effect: people in small cities are more likely to know how others around them live than are those in medium or large ones. And, for the most part, they are fairly on par with their neighbors, as there is less variance in wealth levels in smaller cities. People in big cities, meanwhile, are probably aware that objective economic conditions in the countryside and smaller towns are worse than they are in the major cities. We next explored whether the average or relative aspects of the ELQ and personal economy rankings mattered more to happiness. We repeated the technique of separating the variables into an average component and a relative component for ELQ and the personal economy question.32 Using an F test, we could not reject the hypothesis that the coefficients for average and relative personal economy are equal and positive. On the other hand, average ELQ was completely insignificant, while relative ELQ was significantly positive. Thus, although people in, for example, large cities with wealthy neighbors realize that they are wealthier than people in rural areas, this brings them no additional happiness because they are concerned

187

−5.98** 4.56** 11.05** 21.71** 1.52 −4.29** 9.59** −2.59** −0.85

1.44 1.69 0.69 2.12**

0.098 0.098 0.047 0.080

z-score

−0.026 0.000 0.059 0.188 0.034 −0.107 0.228 −0.103 −0.023

coefficient

retired student small town big city

age age squared education wealth married male health unemployed self-employed

relative ELQ

0.091 0.091 0.214 −0.291

−0.026 0.000 0.056 0.184 0.030 −0.106 0.226 −0.105 −0.016

coefficient

Components of the ELQ and relative ELQ

1.34 1.58 4.47** −8.74**

−6.14** 4.59** 10.74** 22.21** 1.32 −4.26** 9.57** −2.6** −0.6

z-score

retired student smalltown bigcity avgELQ

age age2 yedu wealth married male health unemp selfemp

relative ELQ

Notes: OLS regression of a 1-10 scale of the economic ladder question. Controls include standard demographic variables and country dummies, clustered by country/city size. Average ELQ is computed at the country/city size level.

age age squared education wealth married male health unemployed selfemployed retired student small town big city

ELQ

Table 8.7a

0.093 0.093 0.157 −0.164 −0.341

−0.026 0.000 0.057 0.186 0.031 −0.106 0.227 −0.105 −0.019

coefficient

1.380 1.620 4.080** −5.490** −6.750**

−6.040** 4.580** 10.830** 22.000** 1.390* −4.280** 9.580** −2.600** −0.680

z-score

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Table 8.7b

Happiness, economics and politics

Average and relative ELQ and happiness

happy average ELQ relative ELQ

coefficient

z-score

0.1297 0.1245

1.76 6.65**

Notes: OLS regression of a 1-5 scale of happiness. Controls include standard demographic variables and country dummies, clustered by country/city size. Average ELQ is computed at the country/city size level.

happy average personal economy relative personal economy

coefficient

z-score

1.006 0.623

4.12** 14.9**

Notes: OLS regression of a 1-5 scale of happiness. Controls include standard demographic variables and country dummies, clustered by country/city size. Average personal economic satisfaction is computed at the country/city size level.

about their relative position vis-à-vis their rich neighbors in the cities. Furthermore, although a person’s ELQ rises with the average ELQ around them, that person’s relative ELQ tends to decrease with higher status neighbors. These findings are very much in keeping with our findings based on objective measures of relative and average wealth (Table 8.7b). We can use similar methods to look at intergenerational mobility. One question asks: ‘Do you believe that [your children] will live better, the same, or worse off than how you live today?’ Another question asks respondents to rank their children’s future status on the ELQ. The combination of the two can be used to examine effects of status and wealth shifts, where the first variable (POUMkids) allows us to factor out the effect of an overall rise in living standards. We can then create a variable, generational POUM, by subtracting respondents’ own ELQ score from their children’s, to look at expected shifts in status as well as wealth. At the country level, the highest average generational POUM score was for Chile (77 percent), while the lowest was for Costa Rica (19 percent). One can imagine that being in a fast growing economy with a great deal of economic change, such as Chile, would suggest better prospects for one’s children’s getting ahead than would living in one such as Costa Rica, where social insurance systems are basically sound, but where economic reform has been slow and growth performance moderate at best.

Does inequality matter to individual welfare?

Table 8.8a

age age2 yedu wealth married male health unemp selfemp retired student smalltown bigcity

189

Generational POUM coefficient

z-score

−0.0162 0.0001 −0.0097 −0.0260 0.0185 −0.0302 0.0554 0.1203 −0.0159 −0.1544 0.0655 −0.1350 0.0935

−3.33** 2.54** −2.57** −3.52** 0.63 −1.09 3.36** 2.23** −0.5 −2.29** 1.09 −2.88** 2.98**

Notes: Low point of age: 59.43. OLS regression of a -10-10 scale of the generational POUM question. Controls include standard demographic variables and country dummies.

At the individual level, the generational POUM displayed a U-shaped age relationship, with the low point at 55 years. There was also an upside down U shaped relationship with education, with the turning point being 8.75 years of education, which is greater than primary but short of completed secondary school. This is closely linked to our findings on unemployment (discussed below), with the probability of being unemployed having a similar relationship with age and education, where the turning point of the latter is about 9.2 years of school. The unemployed are disproportionately represented among those with completed or almost completed secondary education (Table 8.9). Employed respondents with this educational profile, meanwhile, had lower expectations for their children’s mobility than did those with more or less education. Individuals with this profile have fared worse compared to those with university and higher technical skills, whose earnings have increased in both relative and absolute terms; and worse in relative terms compared to those with lower levels (basic only) of education.33 Those respondents that were actually unemployed had a higher generational POUM than the average. This probably reflects hope and optimism as much as objective conditions. Our earlier work suggests that most people retain hope for their children, even when in difficult straits.34 And given that the ELQ rankings of most unemployed people

190

Table 8.8b

Happiness, economics and politics

Time to achieve desired standard of living How long will it take you to achieve your desired standard of living?

City size

Small town Medium city Big city Total

Will never 21-30 11-20 6-10 3-5 achieve years years years years 18% 38% 44% 100%

14% 17% 12% 12% 35% 38% 34% 36% 51% 46% 54% 52% 100% 100% 100% 100% coefficient

age age2 yedu wealth married male health unemp selfemp retired student smalltown bigcity

0.0139 −0.0001 −0.0354 −0.0558 −0.0799 0.0975 −0.2300 0.0763 −0.0845 −0.3161 0.1955 0.1343 0.0216

1-2 Have Total years achieved already 11% 7% 13% 39% 39% 36% 50% 55% 51% 100% 100% 100% z-score 2.6** −1.15 −8.93** −7.41** −2.6** 3.45** −13.3** 1.4 −2.55** −4.01** 3.52** 2.78** 0.67

Notes: Dependent variable monotonically increasing with age within the sample range. Ordered logit regression of a 1-7 scale of the time to achieve desired standard of living question. Controls include standard demographic variables and country dummies.

tend to be low, they would not have to rank their children particularly high to have a positive generational POUM. Scores were lowest in small towns and highest in the big cities, which not coincidentally have the greatest and most varied employment educational and employment opportunities. A related inequality perceptions variable was the time respondents thought it would take to reach their desired standard of living. The question was phrased as: ‘How long do you think it will take you to reach your desired standard of living?’ with possible answers ranging from ‘I already have it’ to several different year categories (1 to 2 years, 5 to 10 years and so on) to ‘never’. As shown in Table 8.9b, respondents who live in small

Does inequality matter to individual welfare?

Table 8.9a

191

Cost of unemployment

unemployed

coefficient

z-score

−0.342

−6.05 **

Notes: Ordered logit regression of a 1-5 scale of happiness for 2004 data set. Controls include standard demographic variables and country dummies.

unemployed unemployed*gini coefficient

coefficient

z-score

−1.347 0.018

−5.18 ** 3.80 **

Notes: Ordered logit regression of a 1-5 scale of happiness for pooled 1997-2004 data set. Controls include standard demographic variables and year dummies.

unemployed (incomplete primary) unemployed (completed primary) unemployed (incomplete secondary) unemployed (completed secondary) unemployed (incomplete tertiary) unemployed (completed tertiary)

coefficient

z-score

−0.485 −0.205 −0.511 −0.562 0.027 −0.246

−3.83** −1.63 −4.46** −5.17** 0.13 −1.39

Notes: Ordered logit regression of a 1-5 scale of happiness. Controls include standard demographic variables and country dummies. Costs of unemployment by education level. Base case is illiterate.

towns are more likely to report ‘never’, while there was no significant difference in the responses of those that live in big cities from those in medium ones. It is likely that those in small towns, particularly rural ones, are well aware that the greatest opportunities for both education and employment are in larger urban areas rather than in their small towns. Meanwhile, those respondents with completed secondary school were the most likely to answer ‘never’ or the next lowest score. Again, trends in returns to education are likely playing a role. To help explain our findings, we examined a variable which asked respondents to choose what affected them most among the many reasons for which there was unequal treatment of people in their countries. Possible answers ranged from skin color to poverty to age. Respondents in small towns were more likely to say that poverty and lack of education

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Table 8.9b

Fear of unemployment

small town big city

coefficient

z-score

−0.256 0.081

−4.34** 1.87

Notes: Ordered logit regression of a 1-5 scale of fear of unemployment. Controls include standard demographic variables (except dummy variables for jobs that are not in the workforce) and country dummies.

gini coefficient

coefficient

z-score

0.017

4.45**

Notes: Ordered logit regression of a 1-5 scale of fear of unemployment. Controls include standard demographic variables (except dummy variables for jobs that are not in the workforce).

were the primary reasons, while those in big cities were more likely to report corruption or the need to pay bribes. These findings suggest that both sets of respondents perceive that there is inequality and injustice. Yet the responses suggest that those in small towns feel that they do not have access to opportunity due to their own poverty and education (explaining a higher tendency to the ‘never’ responses on the above question), while those in big cities are more likely to believe that opportunities and access are monopolized by those with greater means or connections. Those in small towns seem more concerned about their own poverty compared to the rest of society, while those in large cities are more concerned with their access to opportunities compared with more ‘connected’ folks. In both instances the concerns cited run in the opposite direction of an interpretation in which inequality signals opportunity and mobility, which is more typical for the USA and for Europe.

8.6

THE COSTS OF UNEMPLOYMENT AND INEQUALITY

Continuing with our methodology of looking at the effects of inequality on specific subgroups, we here analyse the impact on happiness of unemployment. Previous happiness research has found that unemployment is

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193

one of the most traumatic events that can happen to people. One of the reasons for this is of course the loss of income; however, there is also a cultural stigma to unemployment that impacts happiness. The typical unemployed person in our study is a male who has attended some high school (on average ten years of education). The unemployed percentage of the population increases with city size. This may be an artifact of the data, however, because people in rural areas are more likely to be outside the formal labor force altogether and unemployment is a less relevant concept for them. We sought additional information about how inequality affects welfare via our knowledge of the effects of unemployment on happiness. The strength of these effects – for example, the ‘costs’ of unemployment – tend to vary across countries and regions. We build from the work of others. Di Tella, MacCulloch and Oswald find that respondents in the USA and Europe are made more unhappy by higher unemployment rates than they are by inflation. In other words, the typical respondent – including employed respondents – would accept higher levels of inflation if it would eliminate the insecurity associated with higher unemployment rates. Several studies have shown that increased unemployment in general lessens the impact on unemployed individuals. Clark and Oswald (1994) find that the unemployed in Britain are less unhappy in districts where the unemployment rate is higher. The costs to happiness that comes from the decreased probability of finding a job seems to be lower than the gains to happiness that come from being less stigmatized and accompanied by more unemployed counterparts. Similarly, Stutzer and Lalive (2004) find that unemployed respondents are less happy in cantons that have voted to reduce unemployment benefits in Switzerland (controlling for benefit levels), as the stigma from unemployment is higher. As discussed above, Eggers, Gaddy, and Graham find that both employed and unemployed respondents are happier in regions with higher unemployment rates in Russia. We, too, find positive effects of general unemployment on happiness, both using an unemployment rate calculated from our own data and the latest statistics available from the United Nations Economic Commission for Latin America and the Caribbean (ECLAC). These are country-wide unemployment rates and have statistically significant positive effects on happiness. As in the above studies, higher overall unemployment may reduce the stigma effect on individuals. The results must be tempered, though, by the limited information that open unemployment rates can provide in a region with high levels of informal employment (exceeding 50 percent in a few countries). Inequality in countries also has an effect on happiness among the

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unemployed. Using our pooled data set from 1997–2004, we ran a standard happiness regression, including a control variable for being unemployed, and then adding interaction terms for being unemployed in a high or low Gini country. We find that the costs to happiness of being unemployed are lower in higher Gini countries (Table 8.9a). In other words, unemployed respondents in countries with higher inequality are actually happier than those in countries with low inequality. Countries with high inequality are also, on balance, poorer than other countries, so the unemployed may have less far to fall in those countries. Another reason may be the higher levels of informal employment in the poorer and more unequal countries in the region, thereby resulting in less stigma for the unemployed. Or it may be due to some other countrylevel unobservable that we are not accounting for. And, while the costs of being unemployed are lower in higher Gini countries, fear of unemployment (among the employed) is higher, in keeping with our intuition about greater levels of informality and associated insecurity. Thus in higher inequality countries the lower stigma for the unemployed is accompanied by greater insecurity for the employed. Job instability has particularly affected those with a high school level of education, and if we look at the happiness impact of unemployment among different educational groups, it turns out that, in addition to having the highest rate of unemployment, those with a high school education are also made most unhappy by unemployment. In fact, unemployment has a statistically insignificant effect on happiness on the ends of the education spectrum (Table 8.9b). College-educated people are also less likely to fear unemployment than those with less education. And unemployment is a less relevant concept for the illiterate, who are most likely to be outside the formal labor market to begin with, and those with higher education are more likely to be able to find another job than those with secondary school education. We also examined the costs to unemployment by city size. As in the case of our Gini coefficients, we find that the costs of unemployment are lower in big cities than they are in small towns, suggesting that there is a lower stigma effect in big cities. Yet also as in the case of inequality (as measured by the Gini), fear of unemployment is higher in the big cities, presumably because labor markets are more integrated into the international economy and volatility is more of a factor, while relying on farming as a safety net is not an option the way it is in smaller towns (Table 8.9b). Our findings are suggestive of how the costs of being unemployed can vary across countries and according to different measures of inequality. Inequality seems to be correlated with a lower ‘stigma’ for the unemployed, but with a higher fear of unemployment for the employed.

Does inequality matter to individual welfare?

8.7

195

CONCLUSIONS

This chapter was an attempt to explore the effects of relative income differences, as well as of inequality more broadly defined (inequality per se), on well-being in Latin America, the region with the highest inequality in the world. We find large and consistent effects of relative income differences (and concerns for relative income differences) on well-being. At the same time, average country and city size wealth, holding individual incomes constant, had no significant effects on well-being, with the exception of the smaller, poorer cities. This suggests that inequality or relative position matters more in Latin America than it does in other places, such as Europe and the USA. Rather surprisingly, the strong effects of inequality (or relative wealth more specifically) held for both the poorest and the wealthiest groups. The effects of relative income contribute to the happiness of those who are above average income and result in lower happiness levels for those who are below it. A back of the envelope calculation suggests that inequality in the region makes those in the highest quintiles 5 percent happier than the average and those in the poorest quintile 3 percent less happy, regardless of differences in average or individual wealth levels within and across these groups. Various studies of inequality and well-being in the USA and Europe find modest effects in one direction or the other (positive or negative), or else inconclusive evidence that inequality matters at all. A common explanation for these mixed findings is that in Europe and the USA inequality can be a signal of income mobility and opportunity as much as it is a signal of injustice. In Latin America, a region where the gaps between the poor and the wealthy are much larger and more persistent, inequality seems to be a signal of persistent advantage for the very wealthy and persistent disadvantage for the poor, rather than a signal of future opportunities. We also analysed trends in respondents’ perceptions of inequality, rank and opportunity as a means to gauge the effects of broader, non-income definitions of inequality – inequality per se – on well-being. Our findings support the importance of relative differences in these realms to wellbeing, and suggest that they may be more important than income-based differences. And concerns for status or relative differences were higher among those respondents whose reference norms are higher – in places where there is higher average wealth and with greater variance in levels (and probably more information and awareness), as in big cities. Inequality and perceived inequality play a mediating role in the effects of unemployment on well-being. Higher levels of inequality seem to lower the costs of unemployment for the unemployed (perhaps by reducing stigma), but increase insecurity or fear of unemployment for the employed.

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Our findings are, by definition, suggestive rather than conclusive. We set out to explore the effects of relative income differences on well-being, using a range of measures, including some unconventional ones, as well as to try and shed light on an as yet loosely defined concept – inequality per se – using perceptions about status and opportunity. Most of the measures suggest that inequality has perverse effects on welfare in Latin America. It is associated with lower well-being for those at the bottom of the distribution in particular and for those with below average wealth levels in general. Our findings on perceptions of status and opportunity run in the same direction. Not all of the effects of inequality are negative; the wealthy are made happier by higher relative differences. Yet this is not necessarily optimal in a normative sense (depending on one’s priors). And while the unemployed seem to suffer lower well-being costs in contexts of higher inequality, it is also linked to higher fear of unemployment. The implications of our findings for policy are less clear. The modest evidence that we have on support for redistribution in the region suggests that there is not much support for it among the poor – precisely the group that is most hurt by inequality. At the same time, the concerns that we find among respondents about poverty and lack of equal access to education and other opportunities suggest that it would be much easier – and arguably much more efficient – to generate support for policies that can help increase access to education and opportunity. That, however, is a major challenge, and the subject for another paper.

NOTES 1.

2. 3. 4.

5. 6. 7.

The authors thank William Dickens, Richard Easterlin, Branko Milanovic, Andrew Oswald, Alois Stutzer and Peyton Young for helpful comments on earlier drafts. An earlier, summary version of this chapter was published in the Journal of Economic Inequality, January 2006. For an excellent description of the role of equity norms in mediating a number of important economic outcomes that markets alone cannot determine, see Young (1995). Nancy Birdsall and I discuss these two kinds of inequality at length in the introduction to Birdsall et al. (1998). Theoretical studies include the works of Danny Quah, Sam Bowles and Herbert Gintes, Steven Durlauf, Francois Bourguignon, Robert Frank and Roland Banabou, among others. Earlier works include those of John Rawls and A.C. Pigou. For an excellent summary of many of the issues involved, see Arrow et al. (2000). For a description of the possible biases in survey research, see Bertrand and Mullainathan (2001). For a complementary approach which focuses on procedural utility, see Frey et al. (2004). See, among others, Benabou and Ok (2001), Boeri et al. (2001), Graham (2003), Pitketty (1995) and Schwarze and Harpfer (2004). Acemoglu and Robinson (2002), meanwhile,

Does inequality matter to individual welfare?

8. 9. 10.

11.

12. 13.

14.

15.

16. 17.

18. 19. 20.

21. 22.

197

develop a political economy theory of the Kuznets Curve in which the reduction of inequality depends on a credible threat of revolution by the poor. They also find stark differences among different income groups, however (discussed below). See Alesina et al. (2004). See Clark (2003) on Britain and Tomes (1986) on men in Canada. Both of these studies are discussed in greater detail below. Easterlin (1974, 1995, 2001, 2003) used 30 surveys from 19 countries, including some developing countries. Similar results, or minor modifications of them, have been found by both economists and psychologists. See, among others, Blanchflower and Oswald (2004) and Diener et al. (1993). For an excellent review of much of this literature, see Frey and Stutzer (2002). See Diener et al. (1993), Easterlin (1974, 2003), Frank (1999) and Luttmer (2004). A recent cross-country study by Ball and Chernova (2004), based on the World Values Survey, finds that the effects of relative income on happiness are up to four times as great as those of absolute incomes, although the effects of absolute incomes are still positive and significant. For an excellent definition of these latter inequalities, often called horizontal inequalities, see Ravallion (2004). For example, for a lognormal distribution (often used to model income/wealth distribu2 tions) based on a normal distribution N (m, s2) , the mean is em1s /2 and the median is em. Since the mean is conditional on the variance but the median is not, a mean-preserving increase in the variance will increase the ratio of the mean to the median (Aitchison, 1957; Moene and Wallerstein, 2003). Opinion polls in Russia suggest that the inequality that most matters to the average citizen is that between Moscow – the reform capital – and the rest of the country, rather than the more general cross-regional differences that are captured by the Gini (VTsIOM, 2004). Boeri et al. (2001), meanwhile, find that most Europeans want to shift expenditures from pensions to unemployment insurance. This effect is stronger where labor markets are more rigid, such as in Italy and Spain (for example, it is harder to fire people so results in less labor mobility, flexibility and higher unemployment). We also squared the wealth variable in order to see if there was a quadratic effect, which would suggest a shift in attitudes (and support for lower taxes) for the very wealthy. Yet we did not find evidence of such a shift. The question on taxes and redistribution (LOWTAX) is phrased: ‘do you support lower taxes, even if welfare spending suffers’, making it very clear to respondents that there are trade-offs to lower taxes. See Graham and Sukhtankar (2004) and Graham (2003). See, for example, Diener and Biswas-Diener (2000). There is a debate among psychologists on the optimum scale for well-being questions. While there is not complete agreement on the range, most agree that a longer scale than 1 to 4 allows for more accuracy (Cummins and Gullone 2002). Blanchflower and Oswald (2004) get a correlation coefficient of 0.56 for British data for 1975–1992 where both questions are available; Graham and Pettinato (2002b) get a correlation coefficient of 0.50 for Latin American data for 2000–01, in which alternative phrasing was used in different years. The Dominican Republic was included for the first year in 2004, raising the country total to 18. Due to logistical and other constraints, the survey only has 70 percent coverage in Chile, 51 percent in Colombia and 30 percent in Paraguay. The survey is produced by Latinobarómetro, a non-profit organization based in Santiago, Chile and directed by Marta Lagos (http://www.latinobarometro.org). The first survey was carried out in 1995 and covered eight countries. Access to the data is by purchase, with a 4 year lag in public release. Graham has worked with the survey team for years and assisted with fund raising, and therefore has access to the data.

198 23.

24.

25.

26.

27. 28. 29.

30. 31. 32. 33. 34.

Happiness, economics and politics The correlation coefficient between the interviewer’s assessment of SES and our index is 0.50. We also estimated a latent wealth variable using primary component analysis of the items in the wealth index, but this alternative does not substantively change our results (Filmer and Pritchett, 2001). Another major difference is that the self-employed are happier than average in the USA and Europe but less happy in Latin America. While these respondents are selfemployed by choice in the former context, in the latter they are in the informal sector due to lack of other alternatives. For this and all other regressions involving the Gini coefficient, we replaced the number by the standard deviation from the regional mean in order to make the coefficients easier to interpret. (In other words, we now think of the differences in terms of standard deviations rather than as incremental changes between closely bunched numbers.) We used the most recent number available; the years range from 1999 to 2004. Since the Gini coefficient changes so slowly for most countries, this should not affect the results. The mean for the countries involved was 53.7, from a minimum of 44.6 to a maximum of 59. The Gini coefficient for the USA, in comparison, is 41.8 [United Nations, 2004]. An additional issue is that the phrasing and placement of the happiness question changed slightly from 1997–99 to all of the subsequent years. In order to control for any bias introduced by this, we split the sample according to happy question type, and get essentially the same results. These split sample regressions available from the authors upon request. Di Tella and MacCulloch (2003). At the PUMAs level, Luttmer does find that Americans are concerned about relative income differences. The coefficient on average wealth for small cities is 0.245 and the t-statistic is 1.920; on relative wealth, it is 0.152 and the t-statistic is 5.815; for medium cities the coefficient for relative wealth is 0.103 and the t-statistic is 3.716; for large cities these figures are, relatively, 0.110 and 4.784. In order to calculate these coefficients, we used OLS to regress happiness, although we used ordered logistic regression in the rest of the chapter. Graham and Pettinato (2002b) and Graham et al. (2004). In other words, the average ranking for the relevant reference group – country or country/city size – and the distance of the individual respondent’s ranking from that average. Behrman et al. (2001). In perceptions surveys in Peru, for example, we found that a much higher percent of respondents ranked their own past progress negatively than assessed their children’s future prospects negatively [Graham and Pettinato, 2002a].

REFERENCES Acemoglu, D. and J. Robinson (2002), ‘The political economy of the Kuznets Curve’, Review of Development Economics, 6 (2), 183–203. Aitchison, J. (1957), The Lognormal Distribution, Cambridge: Cambridge University Press. Alesina, A., R. Di Tella and R. MacCulloch (2004), ‘Inequality and happiness: are Europeans and Americans different?’, Journal of Public Economics, 88, 2009–42. Arrow, K., S. Bowles and S. Durlauf (2000), Meritocracy and Economic Inequality, Princeton, NJ: Princeton University Press. Ball, R. and K. Chernova (2004), ‘Absolute income, relative income, and happiness’, paper presented at the International Society of Quality of Life Studies, Philadelphia, November.

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Barro, R. (2001), ‘Inequality, growth, and investment’, in K. Hassett and R.G. Hubbard (eds), Inequality and Tax Policy, Washington, DC: The AEI Press, pp. 1–38. Behrman, J., N. Birdsall and M. Szekely (2001), ‘Economic reform and wage differentials in Latin America’, Carnegie Endowment Working Papers. Benabou, R. (2000), ‘Unequal societies: income redistribution and the social contract’, American Economic Review, 90, March, 96–129. Benabou, R. and E. Ok (2001), ‘Social mobility and the demand for redistribution: the POUM hypothesis’, Quarterly Journal of Economics, 116, 447–87. Bertrand, Marianne and Sendil Mullainathan (2001), ‘Do people mean what they say? Implications for subjective survey data’, American Economic Review, 91, 67–72. Birdsall, N. (2000), ‘Unequal societies: income distribution and the social contract’, American Economic Review, 90, 96–129. Birdsall, N., D. Ross and R. Sabot (1995), ‘Inequality and growth reconsidered’, World Bank Economic Review, 9, 477–508. Birdsall, N. and J.L. Londono (1997), ‘Asset inequality matters: an assessment of the World Bank’s approach to poverty reduction’, American Economic Review, 87, 32–7. Birdsall, Nancy and Carol Graham (2000), New Markets, New Opportunities: Economic and Social Mobility in a Changing World, Washington, DC: The Brookings Institution Press and the Carnegie Endowment for International peace. Birdsall, N., C. Graham and R. Sabot (eds) (1998), Beyond Trade-offs: Market Reforms and Equitable Growth in Latin America, Washington, DC: The Brookings Institution Press and the Inter-American Development Bank. Blanchflower, D. and A. Oswald (2003), ‘Does inequality reduce happiness? Evidence from the states of the USA from the 1970’s to the 1990’s’, Journal of Public Economics, 88, 1359–87. Blanchflower, D. and A. Oswald (2004), ‘Well-being over time in Britain and the USA’, Journal of Public Economics, 88, 1359–87. Boeri, T., A. Borsh-Supan and G. Tabellini (2001), ‘Welfare state reform: a survey of what Europeans want’, Economic Policy, London. Brown, G., J. Gardner, A. Oswald and J. Qian, (2003), ‘Does wage rank affect well being?’, Paper presented to the Brookings/Warwick Conference on ‘Does Inequality Matter? Lessons from the Economics of Happiness’, Washington, DC, 5–6 June. Clark, A. (2003), ‘Inequality-aversion and income mobility: a direct test’, DELTA Working Paper 2003-11, Paris, France. Clark, A. and A. Oswald (1994), ‘Unhappiness and unemployment’, The Economic Journal, 104, 648–59. Contreras, D., R. Cooper, J. Herman and C. Neilson (2004), ‘Dinamica de la Pobreza y Movilidad Social: Chile 1996–2001’, Mimeo, Santiago, Chile. Cummins, R. and E. Gullone (2002), ‘Why we should not use 5-point Likert scales: the case for subjective quality of life measurement’, in Proceedings: Second International Conference on Quality of Life in Cities, Singapore: National University of Singapore, pp. 74–93. Diener, E. and R. Biswas-Diener (2000), ‘Income and subjective well-being: will money make us happy?’, Mimeo, University of Indiana, Champlain. Diener, E., E. Sandvik, L. Seidlitz and M. Diener (1993), ‘The relationship between

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income and subjective well-being: relative or absolute?’, Social Indicators Research, 28, 195–223. Di Tella, R. and R. MacCulloch (2003), ‘Income, happiness, and inequality as measures of welfare’, paper presented to the Brookings-Warwick University Conference on ‘Why Inequality Matters: Lessons from the Economics of Happiness’, Washington, DC, 5–6 June. Easterlin, R. (1974), ‘Does economic growth improve the human lot? Some empirical evidence’, in P. David and M. Reder (eds), Nations and Households in Economic Growth, New York: Academic Press, pp. 804–79. Easterlin, R. (1995), ‘Will raising the incomes of all increase the happiness of all?’, Journal of Economic Behavior and Organization, 27, 35–48. Easterlin, R. (2001), ‘Life cycle welfare: trends and differences’, Journal of Happiness Studies, 2, 1–12. Easterlin, R. (2003), ‘Income and happiness: towards a unified theory’, The Economic Journal, 111, 465–84. Eggers, A., C. Gaddy and C. Graham (2006), ‘Unemployment and well being in Russia in the 1990’s: can society’s suffering be individuals’ solace?’, Journal of Socio-Economics, 35 (2), 209–42. Filmer, D. and L. Pritchett (2001), ‘Estimating wealth effects without expenditure data or tears: an application to educational enrollments in states of India’, Demography, 38 (1), 115–32. Frank, R. (1999), Luxury Fever: Money and Happiness in an Era of Excess, New York: The Free Press. Frey, B. and A. Stutzer (2002), ‘What can economists learn from happiness research?’, Journal of Economic Literature, 20, 402–35. Frey, B., M. Benz and A. Stutzer (2004), ‘Introducing procedural utility: not only what but also how matters’, Journal of Institutional and Theoretical Economics, 160 (3), 377–401. Graham, C. and S. Pettinato (2001), ‘Happiness, markets and democracy: Latin America in comparative perspective’, Journal of Happiness Studies, 2 (3), 237–68. Graham, C. and S. Pettinato (2002a), ‘Frustrated achievers: winners, losers, and subjective well being in new market economies’, Journal of Development Studies, 38 (4), 100–40. Graham, C. and S. Pettinato (2002b), Happiness and Hardship: Opportunity and Insecurity in New Market Economies, Washington, DC: The Brookings Institution Press. Graham, C. and S. Sukhtankar (2004), ‘Is economic crisis reducing support for markets and democracy in Latin America? Some evidence from surveys of public opinion and well being’, Journal of Latin American Studies, 36, 349–77. Graham, C. and P. Young (2003), ‘Ignorance fills the income gulf’, The Boston Globe, 23 June. Graham, C. and P. Young (2004), Rags to Riches? The American Dream is Less Common in the United States than Elsewhere, Washington, DC: The Century Foundation Press. Graham, C., A. Eggers and S. Sukhtankar (2004), ‘Does happiness pay? some evidence from panel data for Russia’, Journal of Economic Behavior and Organization, 55. Hagerty, M. (1999), ‘Social comparisons of income in one’s community: evidence from national surveys of income and happiness’, Mimeo, San Diego, California.

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Kingdon, G. and J. Knight (2004), ‘Community, comparisons and subjective wellbeing in a divided society’, WPS No. 2004-21, Centre for the Study of African Economies, Department of Economics, University of Oxford. Luttmer, Erzo (2004), ‘Neighbors as negatives: relative earnings and well-being’, Quarterly Journal of Economics, 120 (3), 963–1002. McMurrer, D. and I. Sawhill (1998), Getting Ahead: Economic and Social Mobility in the United States, Washington, DC: Urban Institute Press. Moene, K. and M. Wallerstein (2003), ‘Earnings inequality and welfare spending: a disaggregated analysis’, World Politics, 55 (4), 292–303. Oswald, A. with Jonathan Gardner (2004), ‘How is mortality affected by money, marriage and stress?’, Journal of Health Economics, 23, 1181–207. Pitketty, T. (1995), ‘Social mobility and redistributive politics’, Quarterly Journal of Economics, 110, 551–84. Ravallion, M. (2004), ‘Competing concepts of inequality in the globalization debate’, in S. Collins and C. Graham (eds) (2004), Brookings Trade Forum 2004: Globalization, Poverty, and Inequality. Washington, DC: The Brookings Institution Press. Schwarze, J. and M. Harpfer (2004), ‘Are people inequality averse and do they prefer redistribution by the state? Evidence from German longitudinal data on life satisfaction’, Frankfurt: Working Paper No. 707, German Institute for Economic Research. Stutzer, A. and R. Lalive (2004), ‘The role of social work norms in job searching and subjective well being’, Journal of the European Economic Association, 2 (4), 696–71. Tomes, N. (1986), ‘Income distribution, happiness, and satisfaction: a direct test of the interdependent preferences model’, Journal of Economic Psychology, 7, 425–46. VTsIOM (2004), ‘Moskva glazami Rossiyan’ (‘Moscow as seen by Russians’), Press Release No. 113, 3 September. Young, P. (1995), Equity: In Theory and Practice, Princeton, NJ: Princeton University Press. United Nations Development Program (2004), Human Development Indicators, www.hdr.undp.org.

9.

Perceptions of discrimination, effort to obtain psychological balance, and relative wages: can we infer a happiness gradient? Arthur Goldsmith*

1

OVERVIEW

There is ample evidence that blacks receive lower wages than whites with comparable characteristics and background (Altonji and Blank, 1999; Couch and Daly, 2002; Darity and Mason, 1998; Goldsmith et al., 2006a; Mason 1997). Estimates of the racial wage gap for males typically range between 12–15 percent.1 Social psychologists report that relative income is an important determinant of happiness or well-being. Thus, to the extent that black workers face wage discrimination there is likely to be an associated gap in well-being. This chapter offers, and tests, a theory of how a person’s perception that they face workplace discrimination influences their behavior, and hence, their wages. The theory is developed by extending the neoclassical theory of wage determination to incorporate the insights of Festinger’s (1957) theory of cognitive dissonance – one of the most innovative and prominent theories of behavior in social psychology.2 Our model advances the notion that workers simultaneously derive satisfaction from both the wage they earn and from being in psychological balance which is governed by a perception of ‘fair’ treatment. We interpret Festinger as asserting that thoughts or cognitions that do not ‘fit’ together, result in dissonance and that thoughts must be largely consistent for a person to attain psychological balance. In our view, a person who believes they face wage discrimination is thrust into an unbalanced psychological state since they think they are not treated fairly – the wage they receive falls short of their perceived contribution to the revenues of the firm that is governed by their skills and effort. This person can be expected to make cognitive adjustments in an effort to reach psychological balance.

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Employers may discriminate by undervaluing the talents of minorities, due to negative stereotypes they hold. If employers learn the error of their ways by observing workers, then employees who believe they are discriminated against can simply wait for their employer to adjust their perspective and the wage they pay, leading them to psychological equilibrium. The dangers of this strategy are two-fold. First, as effort declines so will productivity and wages. Second, if effort declines too much the worker may be fired. Another approach might be to reduce their effort level so their productivity falls into line with their wage. This strategy of curtailing effort to reach psychological balance will result in a negative relation between wages and perceptions of wage discrimination. Alternatively, workers who believe they are subject to wage discrimination may decide that greater effort will break down negative stereotype beliefs about themselves held by employers. The idea is that this will lead employers to upgrade their evaluation of the worker’s productivity and to pay them a higher wage. In this scenario workers who believes they are subject to wage discrimination will actually earn a higher wage. Thus, the impact on a worker’s wage of perceived exposure to wage discrimination is unclear. A number of studies have attempted to determine if worker selfreports of exposure to workplace discrimination are closely aligned with conventional statistical measures of wage discrimination (Darity et al., 2006; Hallock et al., 1998; Kuhn, 1987). However, there is a paucity of empirical work attempting to offer an explanation for how perceptions of discrimination might influence wages. Neumark and McLennan (1995) assert that people who believe they face workplace discrimination have less of an incentive to invest in human capital leading to lower wages. Our approach differs from theirs in that we investigate how perceptions of discrimination might influence wages for workers with a given level of skills as they seek psychological equilibrium. Using data drawn from the Multi City Study of Urban Inequality (MCSUI) we estimate wage equations to shed light on how individuals who believe they face discrimination respond. This chapter is organized as follows. In Section 9.2 we present Festinger’s theory of cognitive dissonance and integrate this with the conventional neoclassical theory of wage determination. In addition, we discuss how a perception of wage discrimination may lead to cognitive dissonance that destroys psychological balance. Strategies for restoring psychological balance are identified and their influence on the racial wage gap is determined. Section 9.3 documents the frequencies of perceptions of wage discrimination because of race for our subsample of white and black workers drawn from the MCSUI. The data are described in this section along with our empirical procedures. In addition, we present estimates

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of the influence of perceived wage discrimination on wages. Concluding thoughts are offered in Section 9.5.

9.2 9.2.1

COGNITIVE DISSONANCE AND PSYCHOLOGICAL EQUILIBRIUM Cognitive Dissonance Theory

Festinger’s theory of cognitive dissonance posits a link between attitudes and cognitive processes that may lead to behavioral change.3 His theory suggests that individuals seek harmony between their cognitions or thoughts. Festinger hypothesized that disharmony makes a person uncomfortable and tense. The discomfort fostered by dissonance motivates cognitive changes designed to restore harmony. Festinger (1957, p. 9) defined anything a person perceives to ‘know’ about themselves, others and their environment as a cognitive element. The relation between any two cognitive elements may be dissonant, consonant or irrelevant. A dissonant relation exists between two cognitive elements when, in the perceiver’s mind, they do not seem to ‘fit’ together (ibid., p. 13). Festinger proposed that the amount of dissonance associated with any two inconsistent cognitive elements grows with the importance of these elements to the perceiver. He expects the importance of a cognitive element to depend on two factors, the intensity with which an attitude or belief is held and the proximity of the element to the individual’s self-perception. Finally, as the magnitude of the inconsistency rises so does the pressure to eliminate or, at least, to reduce it. Festinger believed that dissonance is typically resolved by altering an inconsistent cognition, reducing its importance, or through the availability of new information. The next section explores how Festinger’s theory of cognitive dissonance can explain the behavior of persons that believe they face wage discrimination leading to changes in their wage rate. 9.2.2

Perceptions of Wage Discrimination, Workplace Effort and Cognitive Dissonance

Consider a firm that hires white (w) and black (b) workers from a pool of labor, and believes initially that all the members of a racial group are homogenous. Over time employers are presumed to observe worker effort and thus treat workers as heterogenous. Suppose the firm has an initial expectation (E) of worker productivity and believes that the marginal

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product of black workers is less than the expected productivity of white workers, (MP E ) b , (MP E ) w, although black and white workers are actually equally productive. Following conventional neoclassical economic theory suppose the firm pays workers a real wage (W) equivalent to their expected marginal product MPE since firms only observe, and hence learn, an employee’s actual productivity over time. { (W) b 5 (MP E ) b } , { (W) w 5 (MP E ) W } .

(9.1)

The racial wage gap identified in Equation (9.1) is the result of statistical discrimination, since the firm has formed an inaccurate perception of black worker productivity based on stereotypical beliefs (Arrow, 1973; Coate and Loury, 1993; Lundberg and Startz, 1983).4 This type of discrimination may well occur at firms since research by social psychologists (Fiske and Ruscher, 1993; Fiske et al., 2002) provides empirical evidence that persons tend to hold negative stereotypes based on race and ethnicity.5 Workers are presumed to form their own expectation of their produc|| tivity (MP E ) . Psychologists Carver and Scheier (1981, p. 186) argue that individuals establish a target or goal called a ‘standard’ to guide their behavior. In our view, the typical person who takes a job establishes a standard of being ‘treated fairly’, which entails earning a real wage at least equal to their judgment of their marginal product. | | E) (W) $ (M P .

(9.2)

We assert that psychological balance or equilibrium occurs when workers believe they are treated fairly. In addition to having a sense of their own productivity, workers are assumed to know the firms judgment of the productivity of white workers, since firms tout this as the performance level of the ideal worker. Suppose white workers’ expectations of productivity are equivalent to their firm’s expectations of their performance, so white workers are in psychological equilibrium | |E) (M P w 5 (MP E ) w 5 (W) w.

(9.3)

Suppose there are two groups of black workers. Group 1 is composed of black employees who are in psychological balance since they form an expectation of their productivity in line with the judgment made by the employer | | E) 1 (M P b 5 (MP E ) b 5 (W) b.

(9.4)

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Group 2 contains black workers who believe, accurately, that they are just as productive as white workers | | E) 2 [ (MP E ) b 5 (W) b ] , (M P b 5 (MP E ) w 5 (W) w

(9.5)

but, these workers are not in psychological balance since their pay is determined by the employers’ judgment of their productivity which falls short of their own assessment. All black workers at this firm are subject to statistical discrimination since the firm has formed an unjustifiably low expectation of black worker productivity. However, only the black workers in Group 2 recognize that they face statistical discrimination since Group 1 workers attribute the racial wage gap to a difference in productivity. Moreover, the workers in Group 2 experience cognitive dissonance, since their desire to be treated || fairly, (W) b 5 (MP E ) 2b, and their belief that they are not (see Equation 9.5 above), due to discrimination, are cognitions that do not match. Workers in this predicament may attempt to restore psychological balance by altering their effort on the job. Of course one way to eliminate this source of cognitive uncomfort would be to simply quit their job, but this reaction is often not pragmatic so we focus on alternative strategies below. A standard assumption of neoclassical economics is that a worker’s effort on the job, e, contributes to their productivity, MP(e), and that as ( (e) ) their effort rises so does their marginal product, 0 MP . 0. Worker effort 0 (e) is expected to depend on a number of factors including competition from the jobless and the extent of employer monitoring (Shapiro and Stiglitz, 1984), and pay relative to what they might expect to earn for comparable work with other employers (Akerlof, 1982).6 Following Akerlof we assert that a worker’s perception of how they are treated by their employer with respect to wages may influence their level of effort. However, our approach differs from Akerlof’s in two ways. First, the extent to which people alter their effort is governed by a desire to be in psychological equilibrium. Second, we allow effort to act as a signal of skills or as a mechanism for breaking down stereotypes about talent. In the next section we identify and describe three different strategies – retaliatory exertion or shirking, waiting and notification – a worker can adopt to restore psychological balance if they believe they face statistical discrimination. 9.2.3

Statistical Discrimination: Worker Strategies to Restore Cognitive Equilibrium

When a worker believes they are treated unfairly, leading them to experience cognitive dissonance, they can alter their level of effort in hopes of

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restoring cognitive balance by creating a situation where the wage falls in line with their perceived productivity. However, the direction of the change in effort is expected to depend on their assumptions about the behavior of firms. Economists Farmer and Terrell (1996) developed a theory of racial wage differences based on the idea that employers underestimate the skills of minority workers, a form of statistical discrimination, but that over time through direct exposure to minority workers they learn their assumptions are false and update accordingly. In a recent paper Goldsmith et al. (2006b) find evidence consistent with the notion that employers undervalue the skills that minority workers bring to the job, but that as employers get to know minority workers they raise the value they apply to skills acquired with other firms. We formalize this perspective by assuming that as time, () t, advances employers learn, L, more about their workers, 0L0 (tt) . 0. If they come to realize that the racial beliefs or negative stereotypes (S) they hold about black worker productivity are false they will adjust those stereotypes 0S 0L and they will begin to break down or improve, 0L 0 (t) , 0. This learning, in turn, will lead to a more favorable view of black worker productivity, 0 (MPE) b 0S 0L 0S 0L 0 (t) . 0. Thus, black workers facing statistical discrimination could adopt a strategy of waiting to reach a psychological balance. The idea would be to simply wait until employers revise their judgment of black workers’ productivity until it conforms with the productivity of white workers, (MP Er) b 5 (MP E ) w . (MP E ) b, with whom they are just as productive. Presumably, as the employer revises their estimate of black worker productivity they will pay black employees a higher wage. Suppose black workers do not change the assessment of their performance on the job. Recall that the initial situation for black workers in Group 1 and in Group 2 are respectively | | E) 1 { (W) b 5 (MP E ) b } 5 (M P b , (W) w

(9.6)

| | E) 2 { (W) b 5 (MP E ) b } , (M P b 5 (W) w.

(9.7)

As a result of waiting and firms ultimately forming an accurate assessment of black workers the situation for black workers is now | | E) 1 [ (Wr) b 5 (MP Er) b ] 5 (W) w . (M P b

(9.6a)

| | E) 2 { (Wr) b 5 (MP Er) b } 5 (M P b 5 (W) w.

(9.7a)

Notice that black workers all received a wage increase resulting in them being paid a wage equivalent to that of white workers, and both groups of

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black workers are now in psychological equilibrium. However, for black workers in Group 1, their new wage exceeds their own forecast of their productivity. Of course, waiting might be a lengthy process, in which case the workers who recognize they are facing discrimination, those in Group 2, will suffer cognitive discomfort for an extended period. If these workers believe that employers are slow to learn, or are only willing to partially adjust wages toward worker productivity, they may embrace an alternative strategy to establish psychological equilibrium. The black workers in Group 2 who understand that they face statistical discrimination may engage in a strategy of retaliatory exertion or shirking to eliminate the cognitive dissonance they experience and thus gain psychological balance. This strategy entails reducing their effort enough (er , e) to lower their assessment of their own marginal product to | | Er ( || (M P er , e)) 2b , (MP E (e)) 2b until it is in line with the employers’ perception of their performance level. However, the decline in effort must be below the threshold at which the employer discovers them, in which case they will fired. If Group 2 workers follow the shirking strategy then | | Er ( )) 2 { (W) b 5 (MP E ) b } 5 (M P er b , (W) w.

(9.7b)

In this case the workers gain psychological balance but the cost is twofold. First, their behavior ultimately verifies the employers’ initial prejudicial judgment that black workers are less productive than white workers, which reinforces their impulse to both hold false stereotypes and to practice statistical discrimination. Second, Group 2 workers will earn a wage that is unchanged and persistently lower than it would have been had they not faced discrimination or had they waited for employers to learn they were discriminating. Thus, they are only likely to adopt a strategy of reduced effort if they both find the cognitive costs of psychological disequilibrium to be large and sense that employers are slow to alter stereotypical beliefs. The shirking strategy results in black workers in both groups earning the same wage, as is the case if Group 2 workers adopt the waiting strategy to reach psychological balance. However, if they opt to shirk, then all black workers – those who perceive that they are being discriminated against and those who think they are treated fairly – will earn less than white workers. Faced with statistical discrimination, members of Group 2 may adopt behaviors to signal their differences from the stereotypical belief held by their employer. One strategy would be to exert such a high level of effort (es . e) that managers take notice or learn (00L (e) . 0) that the negative racial stereotype beliefs they hold are inaccurate (0 (0SL) , 0) which leads 0S 0L 7 them to reduce the extent of their negative perceptions 0L 0 (e) , 0. This

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209

development, in turn, leads employersE to favorably reassess their judg( ) 2b 0S 0L ment of the workers’ productivity, 0 MP 0S 0L 0 (e) . 0. However, we assume that racial stereotypes only respond to an adjustment in effort that exceeds a threshold level e* considered extraordinary. We refer to this as the notification approach to restore psychological balance. Essentially, we assume that over time employers treat workers as heterogenous based on their effort level, but are only able to detect large changes in effort. The extraordinary level of effort associated with notification eliminates the employers’ negative stereotype regarding black workers in Group 2, making blacks in Group 2 equally as productive as white workers in the eyes of the firm. Moreover, the extraordinary level of effort put forth by workers in Group 2 also raises the employers’ assessment of their productivity relative to white workers, who put forth less effort. Thus, { (W s ) 2b 5 (MP Es (es . e*)) 2b } . (W) w.

(9.7c)

Given no alteration effort on the part of black workers in Group 1 the employer has no reason to alter their perception of the productivity of workers in this group or their wages so

{ (W) 1b 5 (MP E ) 1b } , { (W s ) 2b 5 (MP Es (es . e*)) 2b } .

The black workers in Group 2 are likely to increase their judgment of their own productivity given their extraordinary level of effort, | | Es ( || (M P es . e*)) 2b . (MP E ) 2b. However, the informed action strategy will place them in a psychological equilibrium so long as their new view of their level of productivity does not exceed the employers’ view. The strategy black workers adopt in their effort to overcome the cognitive dissonance caused by wage discrimination will influence wages between whites and blacks and between blacks based on their view of whether they face discrimination. Table 9.1 presents the predicted wage effects for each of the three strategies to yield psychological balance that are examined. If notification is adopted we expect a wage hierarchy resulting in (W) 1b , (W) w , (W) 2b. A shirking strategy produces a different outcome, (W) 1b 5 (W) 2b , (W) w, while waiting yields neither intra-group nor inter-group wage differences, (W) 1b 5 (W) 2b 5 (W) w. The next section describes the empirical procedures we use to estimate the link between workers’ perceptions that they face wage discrimination and the wages they receive. Our estimates are used to speculate on which, if any, of the strategies identified are adopted by those who believe they face discrimination.

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Table 9.1

Expected wage impact when black workers in Group 2 believe they face statistical discrimination

Strategy for attaining psychological equilibrium Waiting Shirking Notification Reference Group

Intra-group Wages

Inter-group Wages

(w) 1b vs

(w) 1b vs (w) w

9.3.1

(w) 2b vs (w) w

(w) 1b 5 (w) 2b (w) 1b 5 (w) w (w) 2b 5 (w) 1b 5 (w) 2b (w) 1b , (w) w (w) 2b , 1 2 1 (w) b , (w) b (w) b , (w) w (w) 2b . Rows in Regression Tables Corresponding to Test of the Intra-group and Inter-group Wage Differences

Whites who believe they do Row 8 not face discrimination Whites who believe they do Row 8 not face discrimination

9.3

(w) 2b

Row 1

Row 6

Row 9

Row 7

(w) w (w) w (w) w

DATA AND METHODOLOGY Data

Data from the Multi City Study of Urban Inequality (MSCUI) are used in this study. The MCSUI is an interview-based survey of close to 9000 households and 2400 firms administered in the cities of Los Angeles, Boston, Atlanta and Detroit between 1992 and1994.8 MCSUI respondents included whites, blacks, Hispanics, Asians and persons coded as ‘other’. In conducting the Household Survey, from which we use data, attempts were made to ‘race match’, by assigning interviewers of a certain race or ethnicity to respondents of that same race/ethnicity. The MCSUI data are well suited for our study because participants were asked whether they believed they had faced workplace discrimination due to race in general and during hiring, or when promotion decisions were made. Exposure to promotion discrimination is captured by an affirmative response to the question: Have you ever felt at any time in the past that others at your place of employment got promotions or pay raises faster than you did because of your race? Contact with hiring discrimination is gauged by the question: Have you ever felt at any time in the past that you were refused a job because of your race? Respondents were also asked a more general question: During the past year were you discriminated

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211

against at your work because of your race? We believe respondents interpreted this as meaning exposure to wage discrimination, since the question is asked in the section of the survey seeking information about wages and fringe benefits. We restrict the analysis to men ages 21–65 who were working, and who were not self-employed, when the MCSUI survey was conducted. Women and the elderly are excluded to minimize biases arising from selective labor force participation. We further restrict the MCSUI sample to blacks and whites to focus on black-white wage differences. Survey participants were asked to report their hourly wage. Persons who do not provide their wage are excluded from the sub-sample we analyse. In addition, workers who report an hourly wage below $2 or above $100 are considered outliers and are excluded. In the MCSUI data persons with reported earnings in excess of $100 000 are excluded as well. Moreover, we do not use data from Detroit since information from that metropolitan area was not collected on a number of variables contained in our study. Data on a rich array of socioeconomic and demographic factors are provided by the MCSUI including information on a person’s human capital, workplace characteristics if employed, the neighborhood where they reside at the time of the survey, and retrospective personal and family characteristics when the interviewee was a youth. Persons were excluded from our sample if they did not report information on the full set of variables used in our most fully specified wage equation. The MCSUI data we analyse (given the restrictions we impose) contains 948 observations, 513 whites and 435 blacks, when we estimate our preferred model specifications. Summary statistics Table 9.2 reports summary statistics for whites and for blacks for all of the variables used in our analysis. The data are reported in a series of panels which correspond to sets of variables that are recursively introduced to the empirical analysis. The panels provide information on wages and perceived exposure to discrimination, human capital, demographics, workplace characteristics, family and personal characteristics as a youth – referred as ‘pre-market factors’ – and current neighborhood characteristics. Variable definitions are presented in Appendix 9A.1 Table 9A.1.9 Mean hourly wages and perceptions of discrimination are reported in Panel A of Table 9.2. The typical black worker reports hourly pay of $12.61 while the average white respondent reports earning $15.94 per hour, a 21 percent difference. Blacks report much higher levels of perceived discrimination at work due to race than whites. Thirty percent of blacks, and 10 percent of whites, claim to have faced hiring discrimination. One in four

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Table 9.2

Happiness, economics and politics

Summary statistics for variables used in the econometric analysis: males

Variables

Hourly wage Workplace discrimination Schooling H.S. drop out High school

Community college Attend college College

Age Younger than 35 years of age Married

Union Work part-time Firm size/100 Atlanta

Mother high school graduate Father high school graduate

White (n = 513) 15.94 (7.73) 0.06 (0.24)

Black Variables (n = 435)

White (n = 513)

Black (n = 435)

Panel A Wages and Perceived Discrimination 12.61*** Promotion 0.06 (6.17) discrimination (0.24) 0.21*** Hiring 0.10 (0.41) discrimination (0.30)

0.25*** (0.44) 0.30*** (0.46)

14.64 (1.99) 0.03 (0.16) 0.36 (0.48)

13.84*** (2.16) 0.07*** (0.26) 0.53*** (0.50)

0.15 (0.35) 0.31 (0.46) 0.16 (0.37)

0.13 (0.34) 0.17*** (0.38) 0.09*** (0.29)

Panel B Human Capital Tenure Disability Did not complete H.S. by age 19 < 35 and Ave. H.S. grade ≤ C Self-esteem

6.53 (7.68) 0.12 (0.33) 0.46 (0.50)

5.57 (6.57) 0.14 (0.35) 0.34 (0.48)

0.07 (0.26) 3.34 (1.36)

0.06 (0.24) 3.32 (1.25)

37.64 (10.58) 0.57 (0.49) 0.61 (0.49)

Panel C Demographic Characteristics 35.71 Number of 0.60 (9.92) dependents (0.95) 0.49 Foreign Resident 0.05 (0.50) at age 16 (0.22) 0.52** (0.50)

0.23 (0.42) 0.09 (0.28) 0.58 (1.54) 0.14 (0.35)

Panel D Workplace Features and Location 0.30** Boston 0.38 (0.46) (0.49) 0.18 Los Angeles 0.48 (0.39) (0.50) 0.52 1994 0.46 (1.23) (0.50) 0.29*** (0.46)

0.77 (0.42) 0.72 (0.45)

Panel E Pre-market Factors 0.63*** Religious (0.48) attendance 0.50*** Jail as a youth (0.50)

0.28 (0.45) 0.14 (0.35)

0.86*** (1.25) 0.25** (0.44)

0.13** (0.34) 0.57 (0.50) 0.45 (0.50)

0.57*** (0.50) 0.12 (0.33)

Perceptions of discrimination: can we infer a happiness gradient?

Table 9.2

(continued)

Variables

White (n = 513)

Welfare as a youth Public housing as a youth Father raised Grandparent raised Good schools Good police

213

0.06 (0.24) 0.00 (0.06) 0.03 (0.17) 0.03 (0.16) 0.56 (0.50) 0.77 (0.42)

Black Variables (n = 435) 0.17*** (0.38) 0.04*** (0.20) 0.05 (0.21) 0.04*** (0.19)

Both parents raised Mother raised Other Raised

White (n = 513)

Black (n = 435)

0.82 (0.38) 0.13 (0.34) 0.01 (0.06)

0.67*** (0.47) 0.23*** (0.42) 0.03** (0.18)

Panel F Current Neighborhood Characteristics 0.41** Low crime 0.08 (0.49) (0.28) 0.49*** (0.50)

0.16*** (0.37)

Note: Weighted means are reported, with their standard errors in parentheses, for the sub-sample used to estimate Model 3 and Model 4. t-tests for differences in the means were conducted with *** Statistically significant at the 99% level, 95% level and 90% level identified by ***, ** and *, respectively. Source:

Multi City Survey of Urban Inequality (MCSUI).

blacks reports having been subject to promotion discrimination, but only 6 percent of whites feel they were treated unfairly regarding advancement. Moreover, 20 percent of the black respondents believe they faced wage discrimination while only 6 percent of whites hold this belief. Inspection of Table 9.2 reveals that on most variables there is substantial variation in mean values between whites and blacks. White workers have higher values on many variables that are known to contribute to wages, such as years of schooling and tenure. In addition, the typical white worker relative to the average black employee in the sample had more educated parents, was more likely to be raised in a two-parent family and was less likely to have been poor as a youth. Thus, casual inspection of the wage and characteristic data reported in Table 9.2 suggests that a portion of the higher wages earned by whites relative to blacks is due to having better productivity linked characteristics. Whether there is a link between perceived exposure to discrimination and wages, for black workers, and whether such a belief is associated with the racial wage gap is unclear. However, the theory set out in this chapter suggests that workers who believe they face discrimination may engage in strategies to reach psychological equilibrium, such as retaliatory exertion,

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that may reduce the black-white pay gap. In the next section we conduct a rigorous and systematic examination of the link between perceptions of workplace discrimination and wages using regression analysis to determine whether a worker’s wage is influenced by their belief they have been subject to discrimination and if such a belief influences the relative wages of white and black workers after controlling for conventional wage determinants. 9.3.2

Methodology

We estimate reduced form wage equations using ordinary least squares to determine if within racial groups, and across racial groups, there is a difference in wages between those workers who believe they have been subject to workplace discrimination and employees who feel they have been treated fairly. The model we estimate is specified as follows ln wi 5 a 1 b (Blacki) 1 g (PerDisci) 1 y (Black*PerDisci) 1 l (Xi) 1 mi (9.8) where ln w is the log of the wage a worker receives on their job. Black and PerDisc are indicator variables that identify black employees and those workers who believe they have faced workplace discrimination. These indicators are interacted to determine if the impact of perceived exposure to discrimination varies for white and black workers. The vector X contains all of the other determinants of the wage rate. Equation (9.8) is estimated three different times, once for each of the three alternative measures of workplace discrimination, using data drawn from the MCSUI. White workers who believe they have not faced workplace discrimination are the reference category for the model. Given this wage specification we are able to estimate the effect on the wage rate of perceived exposure to discrimination (Wdis) and to being treated fairly (Wnodis) for white (w) and black (b) workers. Using these estimates we are able to construct a number of comparisons including those that shed light on how blacks that perceive they face discrimination nodis respond in an effort to attain psychological balance (W dis 5 b 2 Wb dis nodis nodis nodis g 1 y; W b 2 W w 5 b 1 g 1 y; and W b 2 W w 5 b) . We estimate a number of different versions of Equation (9.8). We begin our analysis by estimating a sparse OLS wage regression that contains only variables that indicate a person’s race, and their belief about whether they have faced wage discrimination (Model 1) and move to regressions that add controls for an individual’s skills and their socio-demographic characteristics (Model 2), and their work environment characteristics (Model 3) – yielding a garden variety wage equation.10 Then we augment

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215

this conventional wage equation with family characteristics as a youth and current neighborhood descriptors (Model 4). Models 3 and 4 constitute our preferred model specifications, so our discussion of findings will focus on these models. We also estimate a model that extends Model 3 by adding controls for occupation of employment (Model 5). However, we recognize that a worker’s race may influence their assignment to a job or type of work in which case occupation is not exogenous. Thus, caution should be used when interpreting our results from Model 5. In the next section we present our estimates of equation 9.8 for model specifications 1–5.

9.4

EMPIRICAL RESULTS

Tables 9.3A, 9.3B, and 9.3C are summary tables that present our estimates of the impact of each of the three forms of perceived discrimination (workplace, hiring and promotion) on wages for reduced form log wage regressions. Our findings for Model specifications 1–5 are presented in these tables. Intra-group effects are reported in rows 2 and 8 while our intergroup findings are presented in rows 6 and 9. Our estimates of the racial wage gap when white and black workers report similar views on exposure to discrimination are set out in rows 1 and 7. Coefficient estimates for all of the variables included in the models are available from the authors upon request. Virtually all of the estimated coefficients have the expected sign and are highly significant at conventional levels. Appendix 9A.1 Table 9A.2 is a summary table that indicates which hypotheses our findings are consistent with for each of the measures of discrimination. Panel A of Appendix 9A.1 Table 9A.2 summarizes our findings when white workers who believe they have been treated fairly is the reference group. 9.4.1

Common Perceptions of Discrimination and the Racial Wage Gap

A racial wage gap suggests that there will be a racial happiness gap, ceteris paribus. We find no evidence of wage differences between black and white workers who believe they face discrimination (row 7) for each of our measures of discrimination (that is, W bdis 5 W dis w ). However, among workers who do not report exposure to discrimination (row 1), wages for black workers are 11.5 to 19 percent lower than for whites W nodis 5 W wnodis. Thus, b the racial wage gap, which is well documented, appears to be confined to those workers who think they are treated fairly. Before proceeding, it is important to note that evidence from Coleman et al. reveal that black employees grossly underestimate the degree to which they are subjected to discrimination while white employees vastly overestimate the degree to

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Table 9.3A

The impact of race and perceived workplace discrimination on wages for males: summary table

Variables

Model 1 (n = 968)

Black (b) nodis (1) wbnodis 2 ww (2) PerDisc (g)

−0.287*** −0.154*** −0.164*** −0.109*** −0.134*** (0.036) (0.031) (0.030) (0.032) (0.031) −0.187* −0.154* −0.169** −0.142* −0.168** (0.103) (0.084) (0.082) (0.082) (0.081) 0.262** 0.158 0.167* 0.143 0.178* (0.119) (0.097) (0.095) (0.094) (0.094)

nodis wdis w 2 ww

(3) Black*PerDisc (Y) F-statistic for impact on wages (4) wb 2 ww (b 1 y [ PerDisc ]) (5) wdis 2 wnodis (g 1 y [ Black ]) nodis (6) wdis b 2 ww ( b 1 g 1 y) dis (7) wdis b 2 ww ( b 1 y) nodis (8) wdis b 2 wb ( g 1 y) nodis (9) wdis w 2 wb (b 2 g) F-statistic for the equation Adjusted R-squared Controls for: Human capital Demographics Workplace characteristics Family and neighborhood Occupation

Model 2 (n = 960)

Model 3 (n = 948)

−13.66*** −10.11*** −12.60*** [0.000] [0.002] [0.000] −0.05 0.00 0.00 [0.827] [0.968] [0.978] 1.64 0.01 −0.00 [0.201] [0.932] [0.961] −0.93 0.00 0.00 [0.335] [0.996] [0.954] −22.69*** 31.41*** 29.41*** [0.000] [0.000] [0.000] 0.06 0.39 0.41 yes yes

yes yes yes

Model 4 (n = 948)

Model 5 (n = 921)

−5.04** [0.025] 0.14 [0.706] 0.00 [0.987] 0.16 [0.690] 20.75*** [0.000] 0.43

−6.86*** [0.009] 0.24 [0.621] 0.04 [0.835] 0.17 [0.677] 25.78*** [0.000] 0.43

yes yes yes yes

yes yes yes yes

Notes: Estimating equation is ln wi 5 a 1 b (Blacki) 1 g (PerDisci) 1 y (Black*PerDisci) 1 l (Xi) 1 mi. Dependent variable: ln wage rate. Coefficient estimates using OLS are reported and standard errors are shown in parentheses. Variables for each set of controls are described in Appendix 9A.1 Table 9A.3. F-statistics and their associated p-values, shown in square brackets, are reported for tests of differences in the wage return for dark skinned and light skinned blacks. *** Statistically significant at the 99% level, 95% level and 90% level identified by ***, ** and *, respectively. Reference group is white and do not perceive discrimination. Per Disc = 1 if answer yes to ‘During the past year were you discriminated against at your work because of your race?’ Source:

Multi City Survey of Urban Inequality (MCSUI).

Perceptions of discrimination: can we infer a happiness gradient?

Table 9.3B

217

The impact of race and perceived promotion discrimination on wages for males: summary table

Variables

Model 1 (n = 968)

Black (b) nodis (1) wbnodis 2 ww (2) PerDisc (g)

−0.289*** −0.162*** −0.170*** −0.116*** −0.137*** (0.036) (0.031) (0.031) (0.033) (0.031) 0.028 −0.104 −0.112 −0.093 −0.114 (0.089) (0.073) (0.072) (0.071) (0.070) 0.087 0.143* 0.139 0.128 0.141* (0.105) (0.086) (0.085) (0.084) (0.083)

nodis wdis w 2 ww

(3) Black*PerDisc (Y) F-statistic for impact on wages (4) wb 2 ww (b 1 y [ PerDisc ]) (5) wdis 2 wnodis (g 1 y [ Black ]) nodis (6) wdis b 2 ww ( b 1 g 1 y) dis (7) wdis b 2 ww ( b 1 y) nodis (8) wdis b 2 wb ( g 1 y) (9) wwdis 2 wnodis b (b 2 g) F-statistic for the equation Adjusted R-squared Controls for: Human capital Demographics Workplace characteristics Family and neighborhood Occupation

−10.46*** [0.001] −4.13** [0.042] 4.28** [0.039] −12.16*** [0.001] −22.50*** [0.000] 0.06

Model 2 (n = 960)

Model 3 (n = 948)

−7.55*** −10.56*** [0.006] [0.001] −0.05 −0.15 [0.821] [0.703] 0.74 0.35 [0.338] [0.557] −0.60 −0.60 [0.439] [0.439] 31.36*** 29.30*** [0.000] [0.000] 0.39 0.41 yes yes

yes yes yes

Model 4 (n = 948)

−3.16* [0.076] 0.02 [0.882] 0.59 [0.443] −0.10 [0.755] 20.72*** [0.000] 0.43 yes yes yes yes

Model 5 (n = 921)

−6.24** [0.013] 0.00 [0.956] 0.35 [0.557] −0.09 [0.759] 25.70*** [0.000] 0.43 yes yes yes yes

Notes: Estimating equation is ln wi 5 a 1 b (Blacki) 1 g (PerDisci) 1 y (Black*PerDisci) 1 l (Xi) 1 mi. Dependent variable: ln wage rate. Coefficient estimates using OLS are reported and standard errors are shown in parentheses. Variables for each set of controls are described in Appendix 9A.1 Table 9A.3. F-statistics and their associated p-values, shown in square brackets, are reported for tests of differences in the wage return for dark skinned and light skinned blacks. *** Statistically significant at the 99% level, 95% level and 90% level identified by ***, ** and *, respectively. Reference group is white and do not perceive discrimination. Per Disc = 1 if answer yes to ‘Have you ever felt at any time in the past that others at your place of employment got promotions or pay raises faster than you did because of your race?’ Source:

Multi City Survey of Urban Inequality (MCSUI).

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Table 9.3C

The impact of race and perceived hiring discrimination on wages for males: summary table

Variables

Model 1 (n = 968)

Model 2 (n = 960)

Black (b) nodis (1) wbnodis 2 ww (2) PerDisc (g)

−0.304*** (0.037) −0.088 (0.077) 0.202** (0.093)

−0.180*** −0.189*** −0.136*** (0.032) (0.032) (0.034) −0.087 −0.093 −0.090 (0.063) (0.062) (0.061) 0.171** 0.172** 0.176** (0.076) (0.075) (0.074)

−0.151*** (0.032) −0.066 (0.062) 0.134* (0.075)

−5.01** [0.025] −0.02 [0.898] 3.27* [0.071] −1.96 [0.162] 31.58*** [0.000] 0.39

−6.80*** [0.009] −0.07 [0.797] 2.90* [0.089] −2.17 [0.141] 29.50*** [0.000] 0.41

−1.32 [0.251] 0.32 [0.570] 3.54* [0.060] −0.51 [0.476] 20.91*** [0.000] 0.43

−3.81* [0.051] −0.06 [0.805] 2.20 [0.138] −1.70 [0.192] 25.73*** [0.000] 0.43

yes yes

yes yes yes

yes yes yes yes

yes yes yes

nodis wdis w 2 ww

(3) Black*PerDisc (y) F-statistic for impact on wages (4) wb 2 ww (b 1 y [ PerDisc ]) (5) wdis 2 wnodis (g 1 y [ Black ]) nodis (6) wdis b 2 ww ( b 1 g 1 y) dis (7) wdis b 2 ww ( b 1 y) nodis (8) wdis b 2 wb ( g 1 y) nodis (9) wdis w 2 wb (b 2 g) F-statistic for the equation Adjusted R-squared Controls for: Human capital Demographics Workplace characteristics Family and neighborhood Occupation

−14.30*** [0.000] −1.42 [0.234] 4.69** [0.031] −7.58*** [0.006] 23.07*** [0.000] 0.06

Model 3 (n = 948)

Model 4 (n = 948)

Model 5 (n = 921)

yes

Notes: Estimating equation is ln wi 5 a 1 b (Blacki) 1 g (PerDisci) 1 y (Black*PerDisci) 1 l (Xi) 1 mi. Dependent variable: ln wage rate. Coefficient estimates using OLS are reported and standard errors are shown in parentheses. Variables for each set of controls are described in Appendix 9A.1 Table 9A.3. F-statistics and their associated p-values, shown in square brackets, are reported for tests of differences in the wage return for dark skinned and light skinned blacks. *** Statistically significant at the 99% level, 95% level and 90% level identified by ***, ** and *, respectively. Reference group is white and do not perceive discrimination. Per Disc = 1 if answer yes to ‘Have you ever felt at any time in the past that you were refused a job because of your race?’ Source:

Multi City Survey of Urban Inequality (MCSUI).

Perceptions of discrimination: can we infer a happiness gradient?

219

which they are subjected to discrimination. We assume that white workers who believe they are treated fairly are the reference group for black workers when answering questions about exposure to discrimination. We now compare the wages of blacks who believe they are treated fairly (Group 1), and those who feel they face discrimination (Group 2), against the reference group and each other to shed light on how blacks who believe they face discrimination respond. 9.4.2 Evidence on the Waiting, Shirking, and Notification Hypotheses; White Workers Who Do Not Face Discrimination as the Reference Group We find no significant wage difference between black workers who believe they face discrimination and those who think they are treated fairly (row 8) for workplace and promotion discrimination, which is consistent with both the shirking and waiting hypotheses. But, we also find that blacks who believe they face promotion or workplace discrimination (row 6) and those think they are treated fairly (row 1) earn significantly lower wages than whites who do not believe they face discrimination, both of which are predicted by the shirking response to perceived discrimination. Thus, the evidence points toward a downward adjustment of effort on the part of black workers who believe they are discriminated against so that their contribution to the firm’s revenue corresponds, rather than exceeds, their hourly pay. A striking finding is that black workers who believe they are discriminated against earn wages that are about 8 percent higher than black employees who think they are not exposed to discrimination, and this difference is statistically significant. This outcome is predicted by the notification response or extraordinary effort to overcome the adverse stereotypes that the workers think they face. The notification strategy also predicts that white workers will earn more than black workers who believe they are treated fairly, and we find that as well. However, white workers earn substantially more than the black workers who identify themselves as facing hiring discrimination. This later finding suggests that although employers seem to recognize the greater effort and productivity of the workers who believe they face discrimination, they still do not think they are as productive as white workers, or they are slowly adjusting the wages of black workers who adopt the notification strategy. 9.4.3

Is There a Wage Hierarchy?

If relative wages influence happiness, then a wage gradient or hierarchy is consistent with a happiness gradient. Our estimate reveal that W dis w

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is less than W wnodis by 16–19 percent (row 1) based on Model 3 for the various forms of perceived discrimination. As noted earlier, we also find that blacks who believe they face discrimination have significantly lower wages, on the order of 16 percent, than white workers who believe they nodis do not face discrimination (row 6, W dis ). In addition, we find b 2 Ww statistically equivalent wages for white workers who think they are treated unfairly and black workers who believe they are treated fairly (row 9, nodis W dis ). Thus, we find evidence of a wage hierarchy where whites w 5 Wb who sense they are treated fairly earn more than whites who believe they are discriminated against and black workers, regardless of their view of how they are treated (unless the perceived source of discrimination is dis hiring); W wnodis . W nodis < W dis b w < W b . Thus, it is likely that the level of happiness is greater for whites who believe they are treated fairly, and happiness is roughly equivalent for other black and white workers.

9.5

CONCLUDING REMARKS

There is a substantial literature that finds a linkage between happiness and relative economic well-being as measured by earnings or wages. There is also a well-documented racial gap in wages. One explanation for this is disparate treatment or discrimination. Many black workers report perceiving that they face workplace discrimination in general and with respect to specific events such as hiring and promotion. This chapter explores how such workers respond to these feelings, under the assumption that perceived exposure to discrimination causes psychological discomfort that workers seek to eliminate. We identify three alternative strategies for attaining psychological equilibrium when facing discrimination – waiting, shirking and notification – each of which generates different predictions for intra-racial and inter-racial wage differences. Using data drawn from the MCSUI, which contains information on perceptions of discrimination, we derive estimates of the relative wage effects of perceived discrimination to shed light on which hypotheses are consistent with the data. We find evidence of a wage hierarchy with whites workers who believe they are treated fairly at the top and all other workers falling behind by an equivalent amount. Our evidence suggests that when confronted with hiring discrimination, black workers appear to give greater effort to overcome this hurdle, as predicted by the notification hypothesis. However, when black workers sense that they face promotion or workplace discrimination, the evidence is consistent with their reducing effort to bring their output level down, and hence in line with their pay level. A number of questions remain to be explored including: Are there

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systematic differences in the characteristics of those who report believing they face discrimination and those who believe they are treated fairly? Does the skin shade of blacks who believe they are subject to discrimination, or the amount of time these individuals have spent with their current employer, influence the strategy they adopt to reach psychological balance?

NOTES *

1.

2.

3.

4.

5. 6. 7. 8. 9.

10.

This chapter is part of an on-going reserch effort involving the author, William Darity Jr. (Arts & Sciences Professor of Public Policy Studies and Professor of African American Studies and Economics at Duke University), and Darrick Hamilton (Assistant Professor at Milano – The New School for Management and Urban Policy, The New School). However, smaller wage differences between black and white workers, on the order of 7 percent, have been reported by Altonji and Blank (1999) and Neal and Johnson (1996) when only pre-market controls and the Air Force Qualifying Test (AFQT) are included as a wage regressor. Economists previously have used cognitive dissonance theory to explain economic development (Hirschman, 1965), the accumulation of debt (Maital, 1982), job choice over safe and hazardous employment (Akerlof and Dickens, 1982) and labor supply (Goldsmith et al. 2004). Akerlof and Dickens (1982) and Goldsmith et al. (2004) formally merge neoclassical theory and cognitive dissonance theory rather than present cognitive dissonance theory as an alternative explanation for behavior. See Earl (1992) for a review of the literature in which economists make use of cognitive dissonance theory, and Earl and Wicklund (1999) for a brief discussion of rational decision making and cognitive dissonance. There is a substantial body of empirical research showing that people who behave in different ways also vary predictably in their attitudes, which are thoughts or cognitions. For a review of the empirical literature on the relationship between attitudes and behavior, see Ajzen and Fishbein (1980). Another form of statistical discrimination is when perceived group characteristics, held by an employer, are applied to an individual. Thus, if an employer believes that people with poorer quality schooling make less satisfactory workers, and that blacks on average possess inferior schooling, then they may judge a black worker on the basis of this negative racial stereotype, S, rather than their own background – instead of putting forth the time and effort to accurately assess the quality of their schooling. See Fiske and Ruscher (1993) for a review of the literature in social psychology on negative stereotyping and minority group status. According to Akerlof workers have an impulse to increase effort due to the pleasure associated with being overpaid. Psychologist Brehm (1966) describes such a behavioral alteration as reactance. All Detroit and Atlanta respondents were interviewed in 1992 and 1993 respectively, while participants residing in Boston and Los Angeles were interviewed in either 1993 or 1994. A concern is whether our sub-sample of employed persons who meet our restrictions differs markedly from the sub-sample of persons capable of working. Comparison of the means, for those variables that do not describe features of work, reveal little difference between those capable of work and those actually employed (table available upon request). Beginning with Model 3 the vector X contains city indicators for Los Angeles and

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REFERENCES Akerlof, George and W.T. Dickens (1982), ‘The economic consequences of cognitive dissonance’, American Economic Review, 72 (3), 307–19. Altonji, Joseph G. and Rebecca Blank (1999), ‘Race and gender in the labor market’, in Orley Ashenfelter and David Card (eds), Handbook of Labor Economics, Vol. 3A, Amsterdam: North Holland, pp. 3143–260. Ajzen, I. and M. Fishbein (1980), Understanding Attitudes and Predicting Social Behavior, New Jersey: Prentice-Hall. Arrow, Ken (1973), ‘The theory of discrimination’, in O. Ashenfelter and A. Rees (eds), Discrimination in Labor Markets, Princeton, NJ: Princeton University Press, pp. 3–33. Brehm, J.W. (1966), A Theory of Psychological Reactance, New York: Academic Press. Carver, Charles S. and Michael F. Scheier (1981), Attention and Self-Regulation: A Control-Theory Approach to Human Behavior, New York: Springer-Verlag. Coate, S. and Glen C. Loury (1993), ‘Will affirmative-action policies eliminate negative stereotypes?’, American Economic Review, 83 (5), 1220–40. Coleman, Major, William Darity Jr and Rhonda Sharpe (2008), ‘Are reports of discrimination valid? Considering the moral hazard effect’, American Journal of Economics and Sociology, 67 (2), 149–76. Couch, Kenneth and Mary C. Daly (2002), ‘Black-white wage inequality in the 1990s: a decade of progress’, Economic Inquiry, 40 (1), 31–41. Darity, William A., and Patrick L. Mason (1998), ‘Evidence on discrimination in employment: codes of color, codes of gender’, Journal of Economic Perspectives, 12 (2), 63–90. Earl, Peter E. (1992), ‘On the complementarity of economic applications of cognitive dissonance theory and personal construct psychology’, in S. Lea, P. Webley and B. Young (eds), New Directions in Economic Psychology, Brookfield, VT: Edward Elgar Publishing, pp. 49–65. Earl, Peter E. and Robert A. Wicklund (1999), ‘Cognitive dissonance’, in Peter E. Earl and Simon Kemp (eds), The Elgar Companion to Consumer Research and Economic Psychology, Cheltenham: Edward Elgar Publishing, pp. 81–8. Farmer, Amy and Dek Terrell (1996), ‘Discrimination, Bayesian updating of employer beliefs, and human capital accumulation’, Economic Inquiry, 34, 204–19. Festinger, Leon (1957), A Theory of Cognitive Dissonance, Palo Alto, CA: Stanford University Press. Fiske, Susan T. and Janet B. Ruscher (1993), ‘Negative interdependence and prejudice: whence the affect?’, in Diane M. Mackie and David Lewis Hamilton (eds), Affect, Cognition, and Stereotyping: Interactive Processes in Group Perception, San Diego, CA: Academic Press, pp. 239–68. Fiske, Susan T., Amy Cuddy, Peter Glick and Jun Xu (2002), ‘A model of (often mixed) stereotype content: competence and warmth respectively follow from

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perceived status and competition’, Journal of Personality & Social Psychology, 82, 878–902. Goldsmith, Arthur H., Stanley Sedo, William Darity Jr and Darrick Hamilton (2004), ‘The labor supply consequences of perceptions of employer discrimination during job search and on-the-job: integrating neoclassical theory and cognitive dissonance?’, Journal of Economic Psychology, 25 (1), 15–39. Goldsmith, Arthur H., Darrick Hamilton and William Darity Jr (2006), ‘Does a foot-in-the-door matter? White-nonwhite differences in the wage return to tenure and prior workplace experience’, Southern Economics Journal. Goldsmith, Arthur H., Darrick Hamilton and William Darity, Jr (2007), ‘From dark to light: skin color and wages among African-Americans’, Journal of Human Resources, XLII (4), 701–38. Hallock, Kevin, F., Wallace Hendricks and Emer Broadbent (1998), ‘Discrimination by gender and disability status: do worker perceptions match statistical measures?’, Southern Economic Journal, 65 (2), 245–63. Hirschman, A.O. (1965), ‘Obstacles to development: a classification and a quasivanishing act’, Economic Development and Cultural Change, 13, 385–93. Kuhn, Peter J. (1987), ‘Sex discrimination in labor markets: the role of statistical evidence’, American Economic Review, 77 (4), 567–83. Lundberg, S.J. and R. Startz (1983), ‘Private discrimination and social intervention in competitive labor markets’, American Economic Review, 73 (3), 340–7. Maital, S. (1982), Minds, Markets and Money: Psychological Foundations of Economic Behavior, New York: Basic Books. Mason, Patrick L. (1997), ‘Race, culture, and skill: interracial wage differences among African Americans, Latinos, and Whites’, Review of Black Political Economy, 25 (3), 5–39. Neal, Derek A. and William R. Johnson (1996), ‘The role of premarket factors in black–white wage differences’, The Journal of Political Economy, 104 (5), 869–95. Neumark, David, and Michele McLennan (1995), ‘Sex discrimination and women’s labor market outcomes’, Journal of Human Resources, 30 (4), 713–40. Shapiro, Carl and Joseph E. Stiglitz (1984), ‘Equilibrium unemployment as a worker discipline device’, American Economic Review, 74 (3), 433–44.

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APPENDIX: 9A.1 Table 9A.1

Definition of variables

Variables

Variable Definitions

Variables

Variable Definitions

W

Respondent’s hourly wage at survey date

Disability

White

1 if respondent is white, 0 otherwise

Foreign resident at 16 years of age

Workplace discrimination

1 if respondent believes they faced workplace discrimination, 0 otherwise 1 if respondent believes they faced promotion discrimination, 0 otherwise 1 if respondent believes they faced hiring discrimination, 0 otherwise Respondent’s age at survey date

Los Angeles

1 if respondent has a work limiting health condition, 0 otherwise 1 if respondent was primarily a foreign resident before 16 years of age, 0 otherwise 1 if respondent resides in Los Angeles, 0 otherwise

1 if respondent is younger than 35 years old, 0 otherwise Years of schooling completed at survey date Number of years employed by current employer at survey date

Work part-time

Promotion discrimination

Hiring discrimination

Age

Younger than 35

Schooling

Tenure

Atlanta

1 if respondent resides in Atlanta, 0 otherwise

Boston

1 if respondent resides in Boston, 0 otherwise

Union

1 if respondent is a union member, 0 otherwise 1 if respondent works part-time, 0 otherwise

Firm size

Mother education

Number of workers at respondent’s firm per 1000 workers 1 if respondent’s mother completed at least 12 years of formal schooling, 0 otherwise

Perceptions of discrimination: can we infer a happiness gradient?

Table 9A.1

225

(continued)

Variables

Variable Definitions

Variables

Variable Definitions

H.S. drop out

1 if respondent failed to complete high school, 0 otherwise

Father education

High school

1 if respondent’s highest level of schooling is completion of high school, 0 otherwise 1 if respondent’s highest level of schooling is completion of community college, 0 otherwise 1 if respondents highest level of schooling was attending college, 0 otherwise 1 if respondent completed college school, 0 otherwise

Both parents raised

1 if respondent’s father completed at least 12 years of formal schooling, 0 otherwise 1 if lived with mother and father to age 16, 0 otherwise

Community college

Attend college

College

< 35 & Ave. H.S. grade ≤ C

No. H.S. by 19 years of age

Self-esteem

1 if respondent is <35 and average high school grade is C or poorer or never attended H.S., 0 otherwise 1 if respondent completed high school by 19, 0 otherwise Rosenberg selfesteem score. Scores range in ascending order from 0 to 4

Mother Raised

1 if lived with mother to age 16, 0 otherwise

Father raised

1 if lived with father to age 16, 0 otherwise

Grandparent raised

1 if lived with grandparent(s), not parents, to age 16, 0 otherwise 1 if lived with someone other than parent(s) or grandparent(s), to age 16, 0 otherwise

Other raised

Religion attendance

Welfare as a youth

1 if respondent attended church at least once a month growing up, 0 otherwise 1 if respondent’s family was on welfare at some point up to age 16, 0 otherwise

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Table 9A.1

(continued)

Variables

Variable Definitions

Variables

Variable Definitions

Married

1 if respondent is married or living with a partner, 0 otherwise

Jail as a youth

Number of dependents

Number of dependents in the household

Public housing

Good police

1 if respondent believes police services in current neighborhood are good, 0 otherwise 1 if respondent believes public schools in current neighborhood are good, 0 otherwise 1 if respondent believes level of crime is low in the current neighborhood, 0 otherwise 1 if respondent supervises other employees, 0 otherwise 1 if respondent is in a managerial or professional occupation, 0 otherwise 1 if respondent is in a precision production, craft or repair occupation, 0 otherwise

Services

1 if respondent has ever been incarcerated or attended reform school, 0 otherwise 1 if respondent currently lives in public housing, 0 otherwise 1 if respondent is in a service occupation, 0 otherwise

Good schools

Low crime

Supervise others

Manager or professional

Production

Source:

Craft

1 if respondent is in a craft occupation, 0 otherwise

Laborers

1 if respondent is in a laborer occupation, 0 otherwise

Government

1 if respondent is a public employee, 0 otherwise

1994

1 if respondent was interviewed in 1994, 0 otherwise

Multi City Survey of Urban Inequality (MCSUI).

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Table 9A.2

227

Summary of findings: expected wage impact when black workers in Group 2 believe they face statistical discrimination Intra-group Wages

Strategy for attaining psychological equilibrium Waiting Shirking Notification

Workplace discrimination Promotion discrimination Hiring discrimination Hiring discrimination: median

(W) 1b vs (W) 2b

Inter-group Wages (W) 1b vs (W) w

(W) 2b vs (W) w

(W) 1b 5 (W) 2b (W) 1b 5 (W) w (W) 2b 5 (W) w 1 2 1 (W ) b 5 (W ) b (W ) b , (W ) w (W) 2b , (W) w (W) 1b , (W) 2b (W) 1b , (W) w (W) 2b . (W) w Panel A Reference Group: Whites Who Do Not Believe They Face Discrimination Row 8

Row 1

Row 6

=(shirk, wait)

-(shirk, notification)

-(shirk)

=(shirk, wait)

-(shirk, notification)

-(shirk)

+(notification) +(notification)

-(notification, shirk) -(notification, shirk)

-(shirk) -(shirk)

PART III

Happiness and politics

10.

Politics and happiness: an empirical ledger Alexander C. Pacek

Does politics affect human happiness, and do shifts in human happiness have explicit political consequences in turn? From the onset of intellectual history there has been no dearth of opinion in support of these interrelated questions. Aristotle made it abundantly clear that the development of moral character and virtue was the key to human happiness, and that the state had a paramount role to play in this development. For Aquinas, writing in the Summa Theologiae, the state was to pursue the enhancement of both spiritual and earthly happiness, stating ‘law must attend to the ordering of individual things in such a way as to secure the common happiness of all’. Thomas Jefferson famously wrote to the general Thaddeus Kosciusko that ‘The freedom and happiness of man . . . are the sole objects of all legitimate government.’ The Declaration of Independence’s author further remarked that ‘The only orthodox object . . . of government is to secure the greatest degree of happiness possible to the general mass of those associated with it.’ For Bentham, the state had an obligation to nurture happiness by not allowing people to suffer needlessly, by encouraging abundance and by ensuring a basic equality of means. While these debates continued for centuries, they remained debates. However the advent of a large and growing body of literature on the empirical study of human happiness shifted the discourse from presumption and speculation to scientific inquiry, aided by ever more sophisticated measurement tools (for extensive reviews, see, Diener et al., 1999; Veenhoven, 1996). While invaluable, the lack of attention to politics, explicitly, was striking; across little more then 3000 empirical works on the subject of human happiness, scholars paid little attention to the political determinants of subjective well-being across and within nations, and even less attention to the political consequences. As Radcliff (2001) observed, the three main theoretical groupings in the social science approach to human happiness – comparison, livability and trait theory – evinced little evidence that politics per se mattered. In light of the philosophical 231

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and normative debates across the span of written human history, this discrepancy was to say the least odd. A careful perusal of the more recent scholarly literature on the empirical study of human happiness reveals, however, that scholars have focused ever more closely on the linkages between specifically political factors and subjective well-being across the globe. As this chapter argues, what emerges from this is not consensus, but a series of continuing debates about just how precisely politics affects happiness and life satisfaction, and what, if any, the consequences of differential levels of happiness and life satisfaction are for politics. I focus on five specific areas receiving the most scholarly attention, and spurring the most contentious debates: (1) the relationship between democracy and happiness; (2) the linkages between social capital, civic engagement and happiness; (3) the impact specific political actors have on happiness; (4) the role of government itself in enhancing or hindering happiness; and (5) the debate over happiness as a policy goal of government. Covering every piece of empirical research on politics and happiness in detail is well beyond the scope of this chapter. Instead, I hope to underscore the more salient debates that highlight the questions driving this research, and at least some of the questions left unanswered as well. We can define progress here not in terms of unassailable conclusions to the questions of politics and happiness, but rather in a renewed and expanding interest in pursuing these debates further with ever more sophisticated research tools and more useful data. Despite the tardiness of the endeavor, there is little doubt that empirical research into political determinants and consequences of human happiness is proceeding apace, generating new interest, and creating newer and more venues for scholarly inquiry.

10.1

DEMOCRACY AND HAPPINESS

The relationship between democracy and subjective well-being has been explored in some depth, and at first glance might appear to be a straightforward one: the establishment and maintenance of democratic institutions fosters well-being. At the most basic level of argument, people in democratic societies exhibit greater levels of happiness then those in authoritarian societies (Diener et al., 1995; Diener and Suh, 1997; Headey and Wearing, 1988; Inglehart, 1990, 1999, 2000, 2006). As Inglehart and Klingemann muse tongue in cheek, ‘adopt democratic institutions and live happily ever after’ (2000, p. 179). Extensive investigation carried out by researchers suggests, however, that the links are not quite as obvious as one might surmise (Inglehart, 1990, 1999, 2000, 2006; Inglehart and

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Klingemann, 2000). Inglehart (1990) and Inglehart and Klingemann (2000) posit that decades of living under democratic institutions should presumably produce greater life satisfaction. The move from authoritarianism and the introduction of basic rights and freedoms, government accountability and greater voluntary political involvement on citizens’ part all would seem to generate increases in well-being. And certainly the authors demonstrate a powerful and positive association has existed for some time between the stability of democratic institutions and life satisfaction, with correlations ranging from 0.78 to 0.85 testifying to this (Inglehart, 1990, p. 1217; Inglehart and Klingemann, 2000, p. 179). Yet the causal direction might also move the other way. Inglehart and Klingemann note that sharp declines in subjective well-being in Belgium and the Soviet Union at the end of its lifespan preceded rather then followed major constitutional changes (2000, p. 177). They further point to the linear, and often precipitous, decline in life satisfaction across the post-communist world following the establishment of democratic institutions, and, conversely, the rising levels of subjective well-being in communist China as the regime there continues to stymie political reforms (ibid., p. 179). In a more detailed analysis of the causal question, Inglehart and Welzel (2005) demonstrated that economic growth and development sharply mitigate the effect of democracy on life satisfaction, but that life satisfaction indeed shows a strong positive effect on democratic stability. Inglehart (2006) examines in some detail the case of the post-communist world, charting how the establishment of democratic institutions did little to enhance subjective well-being amidst a sea of turmoil and problems. Moreover, increases in a country’s democratic rating (Russia from 1981–95, Romania after 2006, Hungary after 1981) were not matched by concomitant increases in life satisfaction. Evidence from Latin America and South Africa was more mixed, which itself calls into question the democracy → happiness hypothesis (Graham and Pettinato, 2001; Moller, 2001). Thus, the consensus among many of these scholars to date is, as Inglehart and Klingemann surmise, that ‘democracy is a good thing, and it probably makes some contribution to human happiness, but it does not seem to have nearly as much impact as other aspects of people’s experiences’ (2000, p. 180). Yet scholars continue to disagree over this, especially when specific aspects of the democratic process are considered rather then broad and general rankings of a particular country’s status as a functioning democracy. Certainly the argument that political participation per se might influence well-being is by no means recent, dating back to Aristotle. The line of reasoning suggests that political participation can have a range of effects on the individual – providing individuals with a sense of

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self-worth and autonomy, increasing knowledge, competence, awareness and so on – all of which work to foster a heightened sense of satisfaction. Yet few empirical studies have tested this proposition, and the question of causal direction looms large. Such is the case with Tavits’s (2007) study using survey data from Europe that finds voters are significantly happier then non-voters, regardless of their choice. Frey and Stutzer’s (2000a) influential piece illustrates this approach nicely, as the authors focus on the salience of ‘direct democracy’, for example, the process by which citizens decide on political issues via initiatives and referenda. As the authors argue, direct democracy gives the power to ‘check and challenge the political class’ to citizens themselves, and can be expected to lead to ‘political decisions more in line with voters’ preferences’ than in representative democracy alone (Frey and Stutzer, 2000a, p. 81). This in turn, simply, should result in a higher level of subjective well-being for citizens. Through an analysis of survey data of 6000 citizens across Switzerland’s 26 cantons, the authors find that such measures as direct democratic rights and citizens’ meetings exert a powerful and positive effect on life satisfaction irrespective of levels of wealth and education (ibid., pp. 87–9).1 Two additional findings of interest stand out: foreign residents who lack the same participatory benefits also demonstrate lower levels of subjective well-being even where direct democracy is more prevalent (ibid., pp. 89–90). In addition, the procedural as well as the outcome utility of direct democracy is shown to positively affect life satisfaction (ibid.). The effect of procedural utility on happiness is further confirmed in additional empirical analysis (Frey and Stutzer, 2000b; Stutzer and Frey, 2003). The clear implication here is that the very act of participating in a democratic process, irrespective of the outcome, boosts levels of subjective well-being. This ties into the larger issue of the quality of democracy, rather then whether a laundry list of democratic institutions is sufficient to increase individual or societal happiness. Further empirical work corroborated these findings (Frey and Stutzer, 2002). The cultural determinism argument posited by some scholars (Inglehart, 1990; Inkeles, 1997) is used, however, to counter these findings. In a follow-up piece Dorn et al. (2008) soundly reject the Frey and Stutzer thesis, contending instead that once cultural attributes of regions are controlled for, the effect of direct democracy essentially washes out. Specifically they link the development of direct democracy in Switzerland to the Germanspeaking areas, noting that German-speaking countries typically register higher levels of subjective well-being than Romance-speaking countries. In their re-estimation of Frey and Stutzer’s model, the authors control for two aspects of culture, cantonal language and religious affiliation. While the coefficient for direct democracy is positive and significant without these

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235

two controls, the addition of them dramatically reduces the significance of the main variable of interest (Dorn et al., 2008, p. 237). The authors cautiously conclude that at least weighed against more powerful determinants, direct democracy might not have a measureable effect on life satisfaction. While the final verdict on these studies remains undecided, they do move the discussion in the productive direction of emphasizing specific, tangible aspects of the democratic process. In this regard, the surface has barely been scratched. One relatively recent development that spurred additional scholarly interest in the impact of democracy was the tumultuous transition across the post-communist and, to a lesser extent, other post-authoritarian systems. Debates about the economic costs and benefits of authoritarian versus democratic regimes aside, one might easily surmise that the replacement of an oppressive regime with a more open and benign one would precipitate significant increases in happiness. Two salient questions this line of inquiry focuses on are: (1) is this supposition correct? and (2) what is the explanatory power of political considerations when the social and economic consequences of post-authoritarian transitions are accounted for? Inglehart (2006) addresses both these questions, finding that across the post-communist world the transition to democracy was as likely to result in declines in overall happiness as improvements. Moreover, recent deterioration in elements of democracy in Russia appears to have little to no impact on levels of life satisfaction, which actually increased during this period (1995–2006). Veenhoven (2001) indirectly addresses the second question, asking ‘Are the Russians as unhappy as they say are?’, a response to numerous polls showing an unprecedented decline in average mean happiness levels in Russia since 1990. While it might seem a stretch to attribute this drop in subjective well-being to nostalgia for the communist state, Veenhoven does find that the near-catastrophic economic conditions that prevailed during the 1990s after the initial wave of market reforms cannot alone account for this situation (Veenhoven, 2001, p. 115). Rather, a general dissatisfaction with the transition as a whole, including the political aspects, seems to resonate with populations across widely varying economic circumstances. Yet the article does not directly test the impact of political conditions. Abbot and Sapsford (2006) do test the impact of political transition directly in Russia and Ukraine. In a large multivariate analysis they include several items that tap perception of the political situation in each country, including retrospective evaluations of the communist regime, present day assessments of the current regime, government performance and provision of services, and trust in the new regime’s institutions. In both countries these variables display a significant and positive relationship

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with happiness (Abbott and Sapsford, 2006, pp. 264–7, 270–1). Again the authors’ emphasize that even where material conditions are as problematic as in this part of the world (or at least were during much the 1990s), economic conditions alone are insufficient to account for varying levels of happiness and life satisfaction. Empirical research on post-communist East European countries finds somewhat stronger evidence that attributes of transitional democracy do appear to bolster levels of happiness, controlling for standard economic variables. Hayo’s (2007) cross-national study of East Europe, using the New Democracies Barometer series during the early 1990s, finds, in keeping with many other studies, much lower levels of overall life satisfaction in East Europe compared to West Europe. Using indicators from the European Bank for Reconstruction and Development on the degree of civil liberties and of political rights, the author finds both positively associated with national happiness levels, with Pearson’s correlation coefficients of −0.54 and −0.34, respectively (Hayo, 2007, p. 215). Other post-authoritarian systems have been scrutinized in this regard. Work by Valerie Moller (2001) on South Africa tracks rather volatile fluctuations in life satisfaction among all groups from the apartheid to post-apartheid era. The promise of a better society embodied in the initial 1994 elections appears to have had a direct impact on happiness levels of the majority black population, and a concomitant downturn in happiness levels among minority whites (Moller, 2001, p. 37). The author notes, however, that the dramatic rise in happiness attributed to the country’s first democratic elections may be unprecedented among post-authoritarian countries, casting further doubt on the salience of elections per se as direct determinants of well-being (ibid., 39). In their study of post-authoritarian Latin America Graham and Pettinato (2002) find that happier people are more likely to have pro-market and pro-democratic attitudes, again irrespective of key economic controls. Both attitudinal measures exert significant and positive effects on happiness in Latin America and Russia, which the authors include as a reference category (Graham and Pettinato, 2002, p. 257). While few precise conclusions can be drawn concerning the relationship between democratic attributes and happiness in the postauthoritarian world, there is little doubt that this represents one of the more potentially fruitful venues for exploring the impact of politics on life satisfaction. There is of course the other side of the coin; what if any impact does happiness/life satisfaction have on democracy? Here the evidence seems less tenuous where this causal direction is concerned. The argument that high levels of happiness or life satisfaction might be beneficial to the longterm health of democracy is reasonably straightforward; less discontent

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translates into less ‘cynical withdrawal’ at best, less system destabilizing activity at worst. If people feel that their life in general has been going well, they are more likely to legitimize and support the system in charge. For democratic regimes that can scarcely rely on coercion, this is especially salient. Many of the traits that have a demonstrated association with subjective well-being – personal and institutional trust, tolerance for others, ‘social capital’ and so on are also critical to democratic maintenance. Testing this thesis, Inglehart and Welzel (2005) and Ingelhart (1990, 2006) find compelling evidence that democratic institutions are far more likely to thrive in societies marked by high levels of life satisfaction, a national ‘trait’ with its roots in cultural determinants. In transitional societies, however, this relationship may be more nuanced. Finifter and Mickiewicz (1992) found that in the waning days of the Soviet Union, higher life satisfaction was associated with a decreased desire for change, democratic or otherwise, but an increased desire for individual versus state-managed solutions to social welfare (Finifter and Mickiewicz, 1992, p. 869). Empirical happiness research will no doubt witness a further expansion in sophisticated research exploring the causal question of democracy (and specific democratic features) relationship with happiness, both in established and transitional democracies. That there is a link is beyond scholarly dispute. However, many more questions have been raised that warrant attention and answers.

10.2

SOCIAL CAPITAL AND HAPPINESS: THE ROLE OF TRUST AND CIVIC ENGAGEMENT

‘Social capital’ is a concept encompassing business, economics, organizational behavior, public health, sociology, psychology and politics. Since the early 1990s, it has generated considerable scholarly attention regarding its political determinants and consequences, following the publication of Robert Putnam’s seminal work, Making Democracy Work in 1993. Putnam’s exhaustive analysis of the disparities in ‘civic community’ and government performance between the regions of Italy provided compelling evidence that measurable differences in various indicators of social capital had profound influences on governance, and citizens’ perceptions of that governance. Later work expanded on the range of political consequences to longitudinal shifts in voter participation, attitudes toward elements of democracy and public policy initiatives (Putnam, 2000). While scholars often disagreed over what precisely constituted social capital, there was little dissensus as to whether the concept was of significant relevance for politics.

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It is not surprising, therefore, that empirical studies on subjective well-being have zeroed in on its applicability. The logic for social capital positively affecting happiness is straightforward; social capital is posited to lead to a better functioning society both economically and politically, and societies with high levels of social capital may provide individuals with self-confidence and social support (Gundelach and Kreiner, 2004, p. 379). Putnam (1993) argued that social capital reduces the transaction costs in society, which in turn affects economic exchanges and public institutions. In as many and perhaps more ways, social capital presents even more challenges than the nuanced term ‘democracy’ for researchers. As Miller and Buys (2008) note, ‘There is no universal definition of social capital, with theorists variously conceiving it as an attribute of the community (Putnam, 2000), institutional/organizational structures (Coleman, 1988), and as a resource (Bourdieu, 1986) . . . the lack of conceptual clarity means that the definition and indicators of social capital differ substantially from study to study (p. 16)’. While scholars conceptualizing social capital emphasize some components over others, common themes repeat: interlocking networks of relationships (Fukuyama, 1995; Putnam, 1993, 2000; Woolcock, 1998), reciprocity (Reno et al., 1993; Taylor, 1982), trust (Fukuyama, 1995; Putnam, 1993, 2000) and social norms (Coleman, 1988; Putnam, 1993, 2000; Bjornskov 2003). Further clouding efforts to model the effect of social capital are the myriad coding schemes brought to bear by researchers.2 Empirical studies on happiness, however, largely have in common the central finding that levels of social capital do indeed affect subjective well-being, largely in a positive direction (Brehm and Rahn, 1997; Bruni and Stanca, 2006; Helliwell, 2003, 2006; Helliwell and Putnam 2004). Putnam’s (2000) extensive analysis on the USA suggests several mechanisms by which social capital enhances well-being. Social capital associates strongly with education progress measured by child development and performance, spurred by high levels of civic engagement among parents and educators, community officials (Putnam, 2000, pp. 301–2). In turn, such progress lowers the likelihood of school violence; heightened feelings of safety certainly have been shown to improve perceived happiness. Social capital can, in addition, positively affect economic prosperity and, hence, life satisfaction, although Putnam cautions there may be deleterious consequences if tight bonds of trust restrict growth and mobility (ibid., p. 322). Perhaps the strongest effect is that associated with social capital’s impact on mental and physical health, which both affect subjective well-being powerfully. Simply put, good health makes us happy, while social connectiveness keeps individuals less isolated and better supported, and thus happier. Putnam notes and illustrates that average levels of happiness rise

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markedly with increased civic connectedness measured by participation in voluntary organizations (ibid., p. 334). Other studies confirm Putnam’s longitudinal findings. Bartolini et al. (2007) assessed the extent that social capital trends may have played in declining levels of happiness observed in the USA from 1975–2004. The authors posit that various proxies for social capital play a critical role in an individual’s self-reported well-being during the period studied, and highlight the salience of an alternative explanation to primarily economic ones. Their social capital measures include reported trust in institutions such as organized labor, schools, Congress, the military, private businesses and other divisions of government. They also include measures of social connectiveness, trust in individuals and membership in organizations, as well as indicators of relational activities such as time spent watching television (Bartolini et al., pp. 4–6). The most explicitly political components of their measures are, quite naturally, the ones corresponding to confidence in government institutions. Compared to other components, these do not perform with a great degree of strength, although the association is clearly positive. The authors conclude that while ‘U.S. citizens who believe in the correct functioning and usefulness of U.S. institutions . . . are happier . . . confidence in institutions can explain, at most, only a small part of the happiness trend’ (ibid., p. 13). In both country-specific and cross-national empirical studies the pattern is one of mixed findings where some particular components of social capital perform better than others, and the more politically oriented of these (confidence/trust in institutions, tolerance, local political participation) likewise demonstrate mixed results (Hudson, 2006; Kroll, 2008). Miller and Buys’s (2008) study of Australia examining relatively small cross-sections found only two of seven social capital indicators (Value of Life, Feelings of Trust and Safety) were consistent predictors of happiness (Miller and Buys, 2008, p. 18). The study said nothing definitive about causal direction, however, as the authors noted (ibid., p. 19). Bjornskov’s (2006) large cross-national study of more than 80 countries similarly finds that only some components of social capital exert a significant effect on subjective well-being.

10.3

POLITICAL ACTORS AND HAPPINESS: POLITICAL PARTIES AND ORGANIZED LABOR

There is little doubt that through both direct and indirect means, key political actors leave their mark on human well-being. Social movements can

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engender a sense of solidarity about a particular cause among members, as the extensive resource mobilization literature has documented (Cress and Snow, 1996; Hirsch 2008; McCarthy and Zald, 1977). Moreover, mass movements, political parties and other political associations work to obtain tangible benefits not only for their members and constituents, but for society as a whole. Yet surprisingly, the direct links between their behavior and subjective well-being have been largely ignored. One of the very few empirical studies examining the role of political parties, albeit indirectly, is DiTella and MacCulloch’s (2005) analysis of OECD citizens from 1975–92. While the study is primarily focused on macroeconomic effects on individuals’ happiness, the authors model the relationship through the filter of political parties. Specifically, they examine the mitigating impact of individuals’ partisan leanings, as well as the partisan composition of governments in advanced industrial societies. Irrespective of income, citizens are found to be happier when the party they support is in power, regardless of the economic situation. As they observe and their findings confirm, ‘The effect of politics is large’ (DiTella and MacCulloch, 2005, pp. 367, 381). Certainly there has been a scholarly interest in labor unions as pathways to human well-being (Korpi and Shalev, 1979; Pfeffer and Davis-Blake, 1990; Levi 2003; Radcliff and Saiz 1998; Western, 1997). These and other scholars note organized labor’s role in a variety of mechanisms that might affect happiness, such as their role in promoting social reforms across a broad policy spectrum that affect incomes, working conditions and health insurance. More narrowly, labor unions clearly can and do change the conditions of the workplace through collective bargaining which in turn facilitates workers’ ability to redress grievances, and indeed, to have a real say in how workplaces are run (Radcliff, 2005; Sutton, 1990). The sense of solidarity evinced in social movements among members may also contribute to well-being. Labor unions may foster social connectedness, trust, fellowship and so on, and the impact of these on well-being is widely discussed in the literature on social capital (Lane, 2000; Putnam, 2000). In light of this, there are reasons to suggest that organized labor exerts a largely positive effect on human well-being. Once again, however, empirical research has lagged behind the scholarly assertions. Radcliff’s (2005) study on the developed Western democracies is notable for not only being one of the very few studies of this type, but also for its provocative findings. Using Eurobarometer data from 1972–95 for ten West European countries, Radcliff finds that union density (measured as a percentage of the labor force unionized) exerts a significant and positive effect on national mean life satisfaction over time (Radcliff, 2005, p. 518). Individual-level analysis on a broader sample of 17 advanced

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industrial democracies using pooled World Values Survey data confirms the previous finding, only here a measure of the respondent’s union membership is used along with the union density measure (ibid., p. 521). But perhaps the most salient finding is that organized labor has a statistically significant positive impact on life satisfaction for non-union members as well; the implication here being that unions are good for all, not just for members (ibid., p. 523). In many ways, this study opens the door for further empirical analyses on the impact specific political actors have on human well-being. What of the role of organized labor outside the established Western democracies, for example? What of the direct role of political parties, protest organizations, interest groups and social movements? Doubtless these potentially productive research areas will find renewed scholarly interest as more and better data to assess the various linkages become available.

10.4

GOVERNMENT AND HAPPINESS: SIZE, COMPOSITION AND QUALITY

While empirical research assessing the relationship between fundamental aspects of government and subjective well-being are relatively recent, the notion that ‘government matters’ is hardly new. Philosophically, the earliest debates focused on whether limited or expansive government was best suited to the pursuit of happiness on an individual or society’s behalf. For Aristotle, of course, the ‘state’ was an aggregate of friends and companions, and therefore had a critical role to play in advancing wellbeing (Barker, 1969, p. 3). The state is a creation of nature ‘originating in the bare needs of life, and continuing for the sake of a good life’ (ibid., pp. 4–5). Yet, scholars contend that Aristotle was quite explicit about the limits on the state’s capacity to fulfill the role of increasing happiness; as the structure and machinery of government grow ever larger and more complex, the extent to which the state can carry out this task proportionately decreases. Thus, relatively early on, the debate over government’s impact on human well-being was framed with respect to size. Later philosophers focused on the various means and tools by which government might accomplish this mission. Jeremy Bentham, who explicitly promulgated the notion that one of government’s principal goals was the increased happiness of the majority, placed his trust in constitutional provisions to achieve this. Writing in the early 1800s at a time of political upheaval, Bentham outlined a series of constitutional provisions – universal suffrage, annual parliaments, votes by ballot, equal rights for women and strict accountability of government representatives to the people – as all

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essential in the pursuit of societal happiness (Bentham, 1830). John Adams famous and oft-repeated quote that ‘the happiness of society is the end of all government’ illustrates that contesting views prevailed as seventeenth and eighteenth century thinkers debated whether government per se was even necessary to achieve individual or collective happiness. Few early thinkers predicted the scope and magnitude of neither government’s expansion from the late 1800s to the present, nor the ideological debates about what political direction was best suited to expanding and maintaining human well-being. The explosive growth in government programs, the welfare state, public sector employment and government’s overall share of the economy which occurred across the advanced industrial world and parts of the developing world reached its apex in the 1960s and 1970s, prompting scholarly interest in consequences for happiness. Various arguments suggest both positive and negative associations between government size and happiness (Bjornskov et al., 2006). Bjornskov et al. (2007) sum up the two main contending ones succinctly. If the central aim of government is maximizing societal welfare, then an expansive government might very well correspond to the desires of a majority of citizens. Simply put, the provision of public goods binds citizens positively to everexpanding government, which in turn leads to measurable increases in life satisfaction (Bjornskov et al., 2007, p. 269). Conversely, expansive government can be perceived as inefficient and self-serving, where the principal goal is self-interest of the many bureaucrats and staff who benefit from this expansion. Budgets grow, staffs increase, spending goes up and ever-increasing resources are required to sustain the process. Citizens feel increasingly frustrated and alienated from an increasingly unresponsive state, and perceive their preferences are not met. The result being that expansive government contributes only to everdecreasing life satisfaction (ibid.). On the basis of these two arguments, the authors posit both positive and negative associations with life satisfaction, and test these arguments using data from 74 countries, and relying on the most commonly utilized empirical source of survey data on life satisfaction, the various waves (1997–2001) of World Values Survey data. Controlling for a host of other associations – economic conditions, ideology, government effectiveness, political competition, social trust and so on – the authors find clearly and unambiguously that life satisfaction decreases with increased government spending (ibid., pp. 275, 277). This effect is mediated somewhat by government effectiveness, but only in countries where the state sector is already relatively small (ibid., p. 279). The authors conclude with a recommendation: governments interested in maximizing life satisfaction should limit their interventions in the economy (ibid., p. 287). The evidence presented in this study is particularly

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compelling with the inclusion of controls for political competition and democracy; neither have a mitigating effect on the relationship of interest. One might question, however, whether ‘spending’ per se is a necessarily sufficient indicator of government size, or at least of government’s broader impact on individual lives. The authors themselves admit that the broader implications regarding the impact of government spending on life satisfaction are decidedly mixed. Additional studies addressed this question with further empirical testing. Now specific aspects of the state apparatus were weighed and tested, one of the most notable attempts to alter fundamentally the means by which human well-being has been produced and distributed since the end of feudalism: the welfare state. Often considered synonymous with expansive government per se, the broad spectrum of government programs for the provision of goods and services to the poor, elderly, unemployed and other disadvantaged groups is seen by proponents as an integral means to improve human well-being. Indeed, as Veenhoven (2000a) notes, ‘this belief is one of the ideological foundations of the welfare state, and a major legitimation of resistance against reform’ (Veenhoven, 2000a, p. 92). Certainly the theoretical relationship between the welfare state and well-being has long been articulated and debated by scholars, who view its mitigating effects against the market as a basis for the allocation of well-being (Esping-Andersen, 1985, p. 129). Esping-Andersen’s contention that markets, whatever their benefits, serve to commodify workers is echoed in Lane’s recent musing that markets are ‘indifferent to the fate of individuals’ (Lane, 1978, p. 13). Conversely, the welfare state might be a structural euphemism for gross inefficiency and wastefulness that imposes its costs on the population, and therefore lowers the general level of happiness (Veenhoven, 2000a, pp. 112–19). In this view the state’s efforts at redistribution and provision fail because they actually reduce both the ‘quantity’ and ‘quality’ of well-being relative to markets. This is principally because they displace the church and family as sources of qualitatively superior support, and, more critically, because they encourage ‘collectivization’ with deleterious consequences for individual privacy, freedom and autonomy. Often a relationship is assumed without direct empirical testing; Gundlach and Kreiner (2004) opine in their study of eight advanced industrial countries that ‘traditional factors such as the type of welfare state . . . do not seem to play a central role in the level of happiness (Gundlach and Kreiner, 2004, p. 383). While empirical studies testing these two contending arguments offer decidedly mixed results, they also differ significantly in approach. A major study by Veenhoven (2000a) relies on raw expenditure data as a measure

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of welfare state effort, and a data set comprised of 40 countries pooled from both democracies and non-democracies. Using both zero-order and partial correlations, Veenhoven finds that the positive argument holds until a country’s overall level of wealth is controlled for; the results then wash out. This confirms earlier research on OECD countries alone by Veenhoven (1990) and Veenhoven and Ouweneel (1995) who found little to no correlation between spending, the age of welfare systems, social entitlements and life satisfaction. Contrary to his own expectation, Veenhoven concludes that there appears to be no link between the size of the welfare state and the level of well-being, and that living standards rather then welfare account for cross-national differences in happiness (Veenhoven, 2000a, p. 91). Further studies contested this conclusion however. Three articles by Radcliff (2001), and Pacek and Radcliff (2008a, b) adopt several approaches in addressing the question. In a cross-sectional study of 15 advanced industrial democracies, Radcliff (2001) brings to bear a data set which measures welfare effort through the concept of ‘decommodification’, outlined by Esping-Andersen (1990) in meticulous detail.3 In essence, decommodification reflects the quality as well as the quantity of social rights and entitlements, and moves the focus away from the mere presence of social assistance or insurance. Among other things, it reflects the extent that citizens are ‘emancipated’ from the market via government intervention, in the sense that they can freely opt out of work, when necessary, without risking their jobs, incomes or general welfare. Radcliff finds this summary index, along with certain ideological attributes of governments, exerts a beneficial effect on both national and individual levels of life satisfaction (Radcliff, 2001, pp. 943, 945). Importantly, the author finds that the association is not confined to low income groups in society, for example, the natural constituency for welfare state effort. While the effect is somewhat less pronounced, high income individuals similarly find their levels of life satisfaction positively associated with welfares state effort (ibid., p. 946). While both Veenhoven and Radcliff’s studies were largely cross-sectional in nature, two additional studies add a longitudinal component to the question under focus, as well as additional measures of welfare state effort. Pacek and Radcliff’s (2008a) study utilizes a pooled sample of strictly European Union countries from 1975–2002, and a second broader sample of advanced industrial democracies from 1981–2000. Utilizing a cross-national time-serial data set on decommodification covering 18 advanced industrial democracies from 1971–2002, the authors find that welfare state effort has a positive effect on national rates of life satisfaction. An additional measure of welfare effort, the ‘social wage’, similarly has a strong positive effect on life satisfaction.4 A second follow-up study

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by the same authors pools individual-level responses across 18 industrial democracies from 1981–2000 and found similar, if somewhat stronger associations (Pacek and Radcliff, 2008b, pp. 8, 10). Remarkably, the strength of the welfare effort variable was approximately twice that of unemployment, which has a long-established reputation as one of the strongest determinants of life satisfaction. Further confirmation still is provided by running additional models on ‘happiness’; while some scholars maintain ‘happiness’ and ‘life satisfaction’ can be used interchangeably (Veenhoven, 1994), others argue that they should be measured and analysed separately (Cummins, 1998). In this case welfare effort’s impact is positive and strong on both concepts. While these few studies by no means settle the debate, they provide powerful evidence that both the quantity and quality of the welfare state experiment is largely beneficial to human well-being. Few scholars would argue, however, that the welfare state evolved in an ideological vacuum; indeed, it is a central pillar of the social democratic model specifically, and the left more generally. Thus the question of what impact government composition or partisan direction has on subjective well-being becomes paramount as well. It has long been recognized that the ‘social democratic world’ described by Esping-Andersen is also the ‘happiest’ world (Diener et al. 1995; Inglehart, 1990; Veenhoven, 1995). While some scholars maintain this is due to specific cultural traits (Inglehart, 1990; Inkeles, 1997) or levels of development (Veenhoven, 2000b), others posit that the presence of an organized partisan left in government over the long term plays no small role in affecting well-being. This somewhat controversial point is taken up by Radcliff (2001) and Pacek and Radcliff (2008a) who test for whether the predominance of the left in government (at least in democratic societies) should result in greater or less well-being. The argument is straightforward: left parties and governments have long advocated, adopted and implemented ‘socialist regime attributes’ which include, among other things, core elements of the welfare state (Huber and Stephens, 2001). Although scholars debate the extent to which other parties such as Christian Democrats fulfill these roles, something of a consensus exists over leftist parties as advocates of social rights. The Radcliff and Pacek and Radcliff studies employ a measure of left party power, for example the cumulative share of cabinet seats left parties have shared over time less the cumulative right party share. In both studies left party control of government exerts a positive influence on life satisfaction (Pacek and Radcliff, 2008a, pp. 271, 272; Radcliff, 2001, pp. 943, 945, 946). While far from the last word, the implication here is that subjective well-being is affected meaningfully by the political choices of voters, and the governments they install in power.

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The manner in which government functions, regardless of ideological stripe, has also been pursued as a possible determinant of subjective wellbeing (Murray, 1988). In a series of papers Helliwell (2003) and Helliwell and Huang (2005) found that the relationship between the quality of government and subjective well-being was not only positive, but stronger than that between income and subjective well-being. Helliwell and Huang employed two composite measures, the first focusing on the operation of the democratic process (voice and political stability) and the second focusing on the delivery of government services and links to citizens (effectiveness, regulatory quality, rule of law and control of corruption). While they found the first index to be positively and the second to be negatively correlated with life satisfaction, this discrepancy was a result of different emphases on the part of citizens in richer versus poorer countries. In short, quality of government mattered relative to a country’s level of overall development with regard to the direction of the effect. Across the varying approaches and perspectives employed by these scholars, what stands out is the accumulation of evidence suggesting government per se does indeed matter to the subjective well-being of individuals and societies. That ‘good government’ matters is not especially surprising perhaps, but that interventionist government does is perhaps more controversial. All told, this sample of studies provides intriguing food for thought in the ancient and enduring debate about whether government, large or small, is an impediment or an ally in the pursuit of human happiness. Certainly the overwhelming focus on the advanced industrial democracies precludes an immediate resolution of this debate, and more refined measures of all aspects of government will reveal further insights.

10.5

HAPPINESS AS A PUBLIC POLICY ISSUE

Of all the areas of investigation concerning the links between politics and happiness, none have generated more contention then the notion that government has a role to play in ‘maximizing happiness’. Substantively and analytically, the salience of the topic is unmistakable. From Bentham to the present, influential voices argued that maximizing happiness was the ultimate policy goal of good governments. Yet until recently, the means to measure the happiness function empirically was beyond the scope of researchers and policy practitioners alike. With the refinement of statistical technique and the creation of ever-broader data sets, scholars and government officials now had the means to at least measure outcome, and this in turn accelerated the policy debate. Happiness scholar Richard Layard has been an influential voice in advising the New Labour government on

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policies designed to increase levels of happiness in the UK. In Layard’s view the position is clear and straightforward: the best society is the one where people are the happiest, and the best policy is the one that produces the greatest happiness (Layard, 2007). Layard’s focus is on improving specific areas of policy, most notably education curriculum, mental health, tax policy and social welfare programs. As far back as 1972, Bhutan’s King Jigme Singye Wangchuck coined the term ‘gross national happiness’ to emphasize a commitment to quality of life issues in that developing nation. Veenhoven’s (2004) appraisal of the philosophical debates over time leads him to conclude that not only can happiness be maximized in societies, but that it is indeed a worthwhile goal to pursue. At the same time, a chorus of voices opposed to the idea that government should, or even can, emphasize maximizing happiness as a policy concern has been raised. Scholars from across various fields propagated this line of reasoning in a number of ways. Kenneth Arrow (1950) argued simply, in mathematical terms, that aggregating individual preferences into one social good was virtually impossible. Buchanan and Tullock (1971) demonstrated the extent to which the interests of policy makers and citizens diverge, exacerbating the difficulty of implementing a ‘common good’ set of well-being enhancing policy goals. But research by Bruno Frey and Alois Stutzer (2007) makes perhaps the most compelling case against government attempting to maximize human happiness. The authors detail five arguments from various perspectives that preface their own position. The first, based on welfare economics, follows Arrow in emphasizing the difficulty in creating a social welfare function that ranks individual orderings of outcomes consistently (Frey and Stutzer, 2007, p. 6). The second, from happiness research itself, speaks with the findings of studies showing many changes in life circumstances have only short-lived effects on reported subjective well-being as people adapt to new situations. Moreover, people’s aspirations can change due to changes in life circumstances. The authors note one possible consequence of social welfare maximization in light of adaptation and aspiration possibilities: if taxation is used as a policy prescription, then people with high income aspirations might suffer from increases in the personal income tax (ibid., p. 8). A third objection cited derives from political economy, and specifically the possibly deleterious impact on individual autonomy from government interference (ibid., p. 9). Fourth, the possibility that respondents may systematically misrepresent their well-being status might lead to their ‘playing the system’ for perceived benefits (ibid., p. 11). And, finally, a libertarian perspective suggests simply that government action may not be necessary at all if a viable alternative route emphasizing the individual’s choices can be emphasized (ibid., p. 12).

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Frey and Stutzer do not, however, argue that maximizing happiness is not a valid policy concern. Rather, their proposition allows for government to be more responsive and accountable at the broadest possible level to people’s common interests and not block the fulfillment of individual preferences, even if other goals besides happiness are paramount. Instead of direct government intervention in the form of ‘corrective taxes’ or various social welfare policies, the authors suggest that governing institutions might better serve citizens by facilitating their search for what constitutes the ‘good life’ by their individual measures. In essence, the emphasis is on improving the quality of government itself rather than broadening the scope of government action. This position sits at the interstices of two perspectives discussed in this chapter. Research by Helliwell (2003) and Helliwell and Huang (2005) demonstrate the empirical links between indicators of government quality and responsiveness, and life satisfaction. Papers by Radcliff (2001) and Pacek and Radcliff (2008a, b), however, highlight the positive association between at least one set of government policy interventions and human happiness. It remains for further empirical analyses to untangle precisely what government’s position on maximizing happiness should be. Opinions vary as to what mechanisms might best be suited for this purpose (assuming one accepts the premise that government should attempt to maximize happiness after a fashion). Thomas Frank’s (1999) thought-provoking book points the intellectual finger at the phenomenon of ‘luxury fever’, the ever-expanding drive to consume conspicuously, as a major determinant of un-happiness in modern society. As individuals pursue incentives to increase their relative status, they get caught in the spiral of ever increasing wasteful consumption with few or diminished net gains in happiness. As a palliative to this ‘trap’, Frank prescribes a progressive consumption tax that would exempt all savings from taxation, and increase the cost of conspicuous consumption while freeing up resources to pursue ‘inconspicuous consumption’, for example, education, family life, environmental and various quality of life issues. The end result, ideally, would be a net gain in societal happiness overall. In a similar vein, Kasser (2002) attributes declines in life satisfaction to the growing culture of materialism, its links to insecurity and low selfesteem and hence to unhappiness. Materialism conflicts with a wide range of values relevant to community and family relationships, and as individuals pursue materialistic goals to the exclusion of others, these bonds become increasingly frayed; other people are treated like objects, relationships are threatened and alienation results. Kasser further emphasizes that people who have strong materialist values have a negative impact on the health and happiness of others as empathy is sacrificed and relationships become

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shallow and superficial. While the burden for breaking out of this view is shared among individuals, families and societies, Kasser does suggest ways government might help as well. Foremost are government regulatory mechanisms aimed at, among other things, television advertising for its alleged pernicious effect on materialist pursuits. Advertising ‘free zones’ would be created at schools and along transportation routes, and aimed at children especially for their heightened vulnerability. Kasser also encourages more government policies aimed at enhancing the overall security of citizens, a view promulgated similarly by Layard (2005). Layard’s own pro-government intervention approach focuses on the possible pathways a ‘policy maker’s ideal world’ might manifest in raising the happiness of citizens. Simply put, economic policy would aim for income increases and security, family policy would aim at strengthening family bonds, and community policy would aim at enhancing the bonds of citizens within and across their communities (Layard, 2006, p. C32). Yet the author is quick to admit that reality rarely behaves as neatly as envisioned in this scheme. Further research explores whether government policy action indeed can make a difference in maximizing happiness. Here the analytical jury remains very much in contention. Veenhoven (1992) examines the proposition that government action aimed at reducing social inequality might concomitantly reduce disparities in happiness across individuals. The proposition is predicated on the positive argument that only the state has the necessary power to collect and redistribute the resources necessary to achieve this, and countered by the contention that such intervention might create new inequality and redistribute inefficiently (Veenhoven, 1992, pp. 2–3). Using data on 22 advanced industrial countries, Veenhoven finds that while welfare state effort leads to reductions in income inequality, this in turn does not lead to reductions in life satisfaction inequality, and thus calls into question the extent that government can truly effect changes in attitudinal characteristics that are dependent on non-fiscal links, such as social support networks. This pessimistic finding on a rather limited set of policy indicators does not, however, prevent Veenhoven from later noting that ‘Findings suggest that happiness can be advanced systematically. Public policy can create conditions that appear conducive to happiness such as freedom, while therapy and education can foster personal conditions such as independence’ (Veenhoven, 2004, p. 11). Veenhoven’s own findings here confirm the pessimistic judgment on income equality policies as an instrument for raising happiness, but deviate optimistically in policy areas such as education, citizenship and ‘quality of government’ (ibid., p. 19). In this regard, Veenhoven’s findings confirm, at least in part, the prescription counseled by Frey and Stutzer (2007) that government can

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assist in maximizing happiness provided it does so with a ‘light hand’, and as uninterventionist as possible. Debate over what mechanisms and how to use them is likely to continue, however, especially when the issue of taxation is raised. Grounded in the now-familiar debates about the impact of raising incomes and reducing inequality on levels of subjective well-being, the discourse over taxation follows a familiar path. Thomas Griffith (2004) notes the diminishing return of upward income adjustment argument so prevalent in much happiness research, and espouses progressive taxation as a means to bolster the impact of relative versus absolute income on happiness. His own data bear out the possible effect this might have (Griffith, 2004, pp. 1377–80). Despite the logic at hand, the author notes the paradox of opposition to progressive taxation; in essence, policy makers confront the dilemma poised by citizens preferring an action that will make them less happy if achieved. Kornhauser (2004) notes this anti-tax opposition and suggests another pathway for government policy: education. Specifically, education to increase public awareness of the connection between taxes and government, and to increase awareness of the details of progressive taxation which are often buried in the rhetorical policy debates. In the end, perhaps where we are left in this enduring debate, is a struggle to better define the balance between direct and indirect government intervention on behalf of individual happiness, and a concomitant challenge to better measure the impact such direct and indirect policy initiatives have on happiness. While the tools to do this certainly exist as the byproduct of decades of scientific advancement in defining and measuring human happiness, their application in the service of policy analysts and scholars remains underutilized. In this respect, as with the preceding areas of inquiry discussed in this chapter, the opportunities for new and more precise breakthroughs are numerous.

NOTES 1. The measure of direct democracy used is a composite index developed by Frey and Stutzer (2000a) comprised of an unweighted average of four sub-indices, of which each assesses the degree of citizen empowerment through a specific institution of direct democracy. These include: (1) constitutional initiatives; (2) statutory initiatives; (3) referenda on cantonal laws and statutes; and (4) referenda on single expenditure projects. Dorn et al. (2008) question whether this index measures merely the availability of such institutions rather then their effective use. 2. Robert Putnam’s (2000) social capital index utilizes 14 sub-indicators, some from individual surveys and some from aggregate data. The sub-indicators conform to the components of social capital: formal membership and participation in informal networks, social trust and ‘organized altruism’. Onyx and Bullen’s (2000) study created an index

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of eight elements of social capital: participation in local community, social agency and proactivity, feelings of trust and safety, neighborhood connections, family and friends’ connections, tolerance of diversity, value of life and work connections. 3. The details of this operationalization are not readily summarized. Perhaps the most succinct description is offered by Messner and Rosenfeld 1997 (p. 1399): the index ‘encompasses three primary dimensions of the underlying concept: the ease of access to welfare benefits, their income-replacement values, and the expansiveness of coverage across different statuses and circumstances. A complex scoring system is used to assess [the amount of decommodification provided by] the three most important social welfare programs: pensions, sickness benefits, and unemployment compensation. The scoring system reflects the “prohibitiveness” of conditions for eligibility [for example, means testing], the distinctiveness of and duration of entitlements [for example, maximum duration of benefits], and the degree to which benefits replace normal levels of earnings. The indices for these three types of . . . programs are then aggregated into a combined [additive] index.’ 4. The measure is defined as ‘the average of the gross unemployment benefit replacement rate for two earnings levels [median-income and the 67th percentile of the income distribution], three family situations, and three durations of unemployment’. See http://www. oecd.org/dataoecd/25/31/34008592.xls, last accessed 2005.

REFERENCES Abbot, Pamela and Roger Sapsford (2006), ‘Life-satisfaction in post-Soviet Russia and Ukraine’, Journal of Happiness Studies, 7, 251–87. Arrow, Kenneth (1950), ‘A difficulty in the concept of social welfare’, Journal of Political Economy, 58 (4), 328–46. Barker, Ernest (ed.) (1969), The Politics of Aristotle, Oxford: Oxford University Press. Bartolini, S., E. Bilancini and M. Pugno (2007), ‘Did the decline in social capital decrease America’s happiness? A relational explanation of the happiness paradox?’ Working Paper, No. 513, Department of Economics, University of Siena. Bentham, Jeremy (1830), The Constitutional Code, London: Bowring. Bjornskov Christian (2003), ‘The happy few: cross-country evidence on social capital and life satisfaction’, Kyklos, 56 (1), 3–16. Bjornskov, Christian (2006), ‘The multiple facets of social capital’, European Journal of Political Economy, 22, 2–40. Bjornskov, Christian, Axel Dreher and Justina A.V. Fischer (2008), ‘On decentralization and life satisfaction’, Economics Letters, 99 147–51. Bjornskov, Christian, Axel Dreher and Justina A.V. Fischer (2007), ‘The bigger the better? Evidence of the effect of government size on life satisfaction around the world’, Public Choice, 127 (3), 267–92. Bourdieu, P. (1986), ‘The forms of capital’, in J.G. Richardson (ed.), Handbook of Theory and Research for the Sociology of Education, New York: Greenwood Press, pp. 241–58. Brehm, John and Wendy Rahn (1997), ‘Individual-level evidence for the causes and consequence of social capital’, American Journal of Political Science, 41 (3), 999–1023. Bruni, Luigini and Luca Stanca (2006), ‘Income aspirations, television, and happiness: evidence from the World Values Surveys’, Kyklos, 59 (2), 209–25. Buchanan, James and Gordon Tullock (1971), The Calculus of Consent: Logical

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Foundations of Constitutional Democracy, Ann Arbor, MI: University of Michigan Press. Coleman, J. (1988), ‘Social capital in the creation of human capital’, American Journal of Sociology, 94, 95–120. Cress, Daniel and David Snow (1996), ‘Mobilization at the margins: resources, benefactors, and viability of homeless social movement organizations’, American Sociological Review, 61, 1089–109. Cummins, R.A. (1998), ‘The second approximation to an international standard for life satisfaction’, Social Indicators Research, 43, 307–34. Diener, Ed and E.M. Suh (1997), ‘Measuring quality of life: economic, social, and subjective indicators’, Social Indicators Research, 40 (1–2), 189–216. Diener, E., E.M. Suh, R.E. Lucas, and H.L. Smith (1999), ‘Subjective well-being: three decades of progress’, Psychological Bulletin, 125, 276–302. Diener, Ed, Carol Diener and Marissa Diener (1995), ‘Factors predicting the subjective well-being of nations’ Journal of Personality and Social Psychology, 69, 851–64. DiTella, Rafael and Robert MacCulloch (2005), ‘Partisan social happiness’, Review of Economic Studies, 72, 367–93. Dorn, David, Justina Fischer, Gebhard Kirchgasser and Alfonso Sousa-Poza (2008), ‘Direct democracy and life-satisfaction revisited: new evidence for Switzerland’, Journal of Happiness Studies, 9, 227–55. Esping-Andersen, Gosta (1985), Politics Against Markets, Princeton, NJ: Princeton University Press. Esping-Andersen, Gosta (1990), The Three Worlds of Welfare Capitalism, Princeton, NJ: Princeton University Press. Finifter, Ada and Ellen Mickiewicz (1992), ‘Redefining the political system of the USSR: mass support for political change’, American Political Science Review, 86 (4), 857–74. Frank, Robert (1999), Luxury Fever: Money and Happiness in an Era of Excess, Princeton, NJ: Princeton University Press. Frey, Bruno and Alois Stutzer (2000a), ‘Happiness prospers in democracy’, Journal of Happiness Studies, 1, 79–102. Frey, Bruno and Alois Stutzer (2000b), ‘Happiness, economy, and institutions’, The Economic Journal, 110, 918–38. Frey, Bruno and Alois Stutzer (2002), ‘Happiness and economics: how the economy and institutions affect human well being’, Princeton, NJ: Princeton University Press. Frey, Bruno and Alois Stutzer (2007), ‘Should national happiness be maximized?’, Working Paper Series ISSN 1424–0459, Institute for Empirical Research in Economics, Zurich, Switzerland. Fukuyama, F. (1995), Trust: The Social Virtues and the Creation of Prosperity, New York: The Free Press. Graham, Carol and Stefano Pettinato (2002a), ‘Happiness, markets, and democracy: Latin America in comparative perspective’, Journal of Happiness Studies, 2, 237–68. Graham, Carol and Stefano Pettinato (2002b), Happiness and Hardship: Opportunity and Insecurity in New Market Economies, Washington, DC: The Brookings Institution. Griffith, Thomas (2004), ‘Progressive taxation and happiness’, Boston College Law Review, 45 (5), 1363–98.

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Gundelach, Peter and Svend Kreiner (2004), ‘Happiness and life satisfaction in advanced industrial countries’, Cross-Cultural Research, 38 (4), 359–86. Hayo, Bernd (2007), ‘Happiness in transition: an empirical study on Eastern Europe’, Economic Systems, 31, 204–21. Headey, Bruce and A. Wearing (1988), ‘The sense of relative superiority to wellbeing’, Social Indicators Research, 20, 497–518. Helliwell, John F. (2003), ‘How’s life? Combining individual and national variables to explain subjective well-being’, Economic Modeling, 20, 331–60 (also INBER Working Paper No. 9065, 2002). Helliwell, John F. (2006), ‘Well-being, social capital, and public policy: what’s new?’, The Economic Journal, 116, C34–C45. Helliwell, John F. and Robert Putnam (2004), ‘The social context of well-being’, Philosophical Transactions of the Royal Society of London, 359, 1435–46. Helliwell, John F. and Haifang Huang (2008), ‘How’s your government? International evidence linking good government and well-being’, British Journal of Political Science, 38 (4), 596–619. Hirsch, Eric (2008), ‘The creation of political solidarity in social movement organizations’, Sociological Quarterly, 27 (3), 373–87. Huber, Evelyne and John Stephens (2001), Crisis and Development in the Welfare State: Parties and Policies in Global Markets, Chicago, IL: University of Chicago Press. Hudson, John (2006), ‘Institutional trust and subjective well-being across the EU’, Kyklos, 59 (1), 43–62. Inglehart, Ronald (1990), Culture Shift in Advanced Industrial Democracies, Princeton, NJ: Princeton University Press. Inglehart, Ronald (1999), ‘Postmodernization brings declining respect for authority, but rising support for democracy’, in Pippa Norris (ed.), Critical Citizens: Global Support for Democratic Government, Oxford: Oxford University Press, pp. 236–56. Inglehart, Ronald (2000), ‘Globalization and postmodern values’, Washington Quarterly, 23 (1), 215–28. Inglehart, Ronald (2006), ‘Democracy and happiness’, Paper presented at the conference New Directions in the Study of Happiness, South Bend, Indianapolis, October. Inglehart, Ronald and Hans-Dieter Klingemann (2000), ‘Genes, culture, democracy, and happiness’, in E. Diener and E.M. Suh (eds), Culture and Subjective Well-Being, Cambridge and London: MIT Press, pp. 165–83. Inglehart, Ronald and Christian Welzel (2005), Modernization and Cultural Change and Democracy, New York and Cambridge: Cambridge University Press. Inkeles, Alex (1997), National Character: A Psycho-social Perspective, New York: Transaction Publishers. Kasser, Tim (2002), The High Price of Materialism, Cambridge, MA: MIT Press. Kornhauser, Marjorie (2004), ‘Educating ourselves toward a progressive (and happier) tax: a commentary on Griffith’s “Progressive Taxation and Happiness”’, Boston College Law Review, 45 (5), 1399–412. Korpi, Walter and Michael Shalev (1979), ‘Strikes, industrial relations and class conflict in capitalist societies’, British Journal of Sociology, 30, 164–87. Kroll, Christian (2008), Social Capital and the Happiness of Nations: The Importance of Trust and Networks for Life Satisfaction in a Cross-national Perspective, New York: Peter Lang Publishers.

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Lane, Robert E. (1978), ‘Autonomy, futility, felicity’, Journal of Politics, 40, 1–24. Lane, Robert E. (2000), The Loss of Happiness in Market Democracies, New Haven, CT: Yale University Press. Layard, Richard (2005), Happiness: Lessons from a New Science, New York: Penguin Press. Layard, Richard (2006), ‘Happiness and public policy: a challenge to the profession’, The Economic Journal, 116, C24–C33. Layard, Richard (2007), ‘Setting happiness as a national goal’, The Futurist, 41 (4). Levi, M. (2003), ‘Organizing power: the prospects for an American labor movement’, Perspectives on Politics, 1, 45–68 McCarthy, John D. and Meyer N. Zald (1977), ‘Resource mobilization and social movements’, American Journal of Sociology, 82, 1212–39. Messner, S.F. and R. Rosenfeld (1997), ‘Political restraint of the market and levels of criminal homicide: a cross-national application of institutional-anomie theory’, Social Forces, 75, 1393–1416. Miller, Evonne and Laurie Buys (2008), ‘Does social capital predict happiness, health, and life satisfaction in an urban Australian community?’, Kotuitui: New Zealand Journal of Social Sciences Online, 3, 15–20. Moller, Valerie (2001), ‘Happiness trends under democracy: where will the new South African set-level come to rest?’ Journal of Happiness Studies, 2, 33–53. Murray, Charles (1988), In Pursuit of Happiness and Good Government, New York: Simon & Schuster. Onyx, Jenny and Paul Bullen (2000), ‘Measuring social capital in five communities’, Journal of Applied Behavioral Science, 36 (1), 23–42. Pacek, Alexander and Benjamin Radcliff (2008a), ‘Assessing the welfare state: the politics of happiness’, Perspectives on Politics, 6 (2), 267–77. Pacek, Alexander and Benjamin Radcliff (2008b), ‘Welfare policy and subjective well-being across nations: an individual-level assessment’, Social Indicators Research, 89 179–91. Pfeffer, Jeffrey and Alison Davis-Blake (1990), ‘Unions and job satisfaction’, Work and Occupations, 17 (3), 259–84. Putnam, Robert (1993), Making Democracy Work: Civic Traditions in Modern Italy, Princeton, NJ: Princeton University Press. Putnam, Robert (2000), Bowling Alone: The Collapse and Revival of American Community, New York: Simon & Schuster. Radcliff, Benjamin (2001), ‘Politics, markets, and life satisfaction: the political economy of human happiness’, American Political Science Review, 95 (4), 939–62. Radcliff, Benjamin (2005), ‘Class organization and subjective well-being: a crossnational analysis’, Social Forces, 84 (1), 514–30. Radcliff, Benjamin and Martin Saiz (1998), ‘Labor organization and public policy in the American states’, Journal of Politics, 60, 113–25. Reno, R., R. Cialdini and C. Kallgren (1993), ‘The transsituational influence of social norms’, Journal of Personality and Social Psychology, 64 (1), 104–12. Stutzer, Alois and Bruno Frey (2003), ‘Institutions matter for procedural utility: an economic study of the impact of political participation possibilities’, in R. Mudambi and G. Sobbrio (eds), Economic Welfare, International Business, and Global Institutional Change, Cheltenham, UK and Northampton, MA, USA: Edward Elgar Publishing, pp. 81–99.

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Sutton, John (1990), ‘Bureaucrats and entrepreneurs: institutional responses to deviant children in the United States’, American Journal of Sociology, 95 (6), 1367–400. Tavits, Margit (2007), ‘Policy shifts and political competition: contrasting effects in pragmatic and principled issue domains’, American Journal of Political Science, 51 (1), 151–65. Taylor, M. (1982), Community, Anarchy and Liberty, Cambridge: Cambridge University Press. Veenhoven, Ruut (1990), ‘Inequality in happiness. Inequality in countries compared between countries’, Paper presented at the 12th Work Congress of Sociology, Madrid, Spain, July. Veenhoven, Ruut (1992), ‘Social equality and state-welfare-effort’, Paper presented at the International Sociological Conference Towards the Good Society. Applying the Social Sciences, Rotterdam, the Netherlands, June. Veenhoven, Ruut (1994), ‘Is happiness a trait? Tests of the theory that a better society does not make people any happier’, Social Indicators Research, 33, 101–60. Veenhoven, Ruut (1996), ‘Developments in satisfaction research’, Social Indicators Research, 37 (1), 1–46. Veenhoven, Ruut (2000b), ‘Freedom and happiness: a comparative study in fortyfour nations in the early 1990s’, in E. Diener and E.M. Suh (eds), Culture and Subjective Well-Being, Cambridge, MA: MIT Press, pp. 257–88. Veenhoven, Ruut (2000a), ‘Well being in the welfare state: level not higher, distribution not equitable’, Journal of Comparative Policy Analysis, 2, 91–125. Veenhoven, Ruut (2001), ‘Are the Russians as unhappy as they say they are?’ Journal of Happiness Studies, 2, 111–36. Veenhoven, Ruut (2002), ‘Why social policy needs subjective indicators’, Social Indicators Research, 58, 33–45. Veenhoven, Ruut (2004), ‘Happiness as an aim in public policy: the greatest happiness principle’, in Alex Linley and Stephen Joseph (eds), Positive Psychology in Practice, Hoboken, NJ: John Wiley and Sons, Inc, pp. 658–78. Veenhoven, Ruut and P. Ouweneel (1995), ‘Livability of the welfare state: appreciation of life and length of life in nations varying in state welfare effort’, Social Indicators Research, 36, 1–14. Woolcock, M. (1998), ‘Social capital and economic development: toward a theoretical synthesis and policy framework’, Theory and Society, 27, 151–208. Western, Bruce (1997), Between Class and Market, Princeton, NJ: Princeton University Press.

11.

Democracy and happiness: what causes what? Ronald Inglehart

Throughout the two decades before the explosion of democracy that occurred around 1990, reported happiness levels showed strong linkages with all of the widely accepted measures of democracy. The national level correlations between happiness and the Freedom House political rights and civil liberties scores were in the 0.7 to 0.8 range – a remarkably strong linkage that could be interpreted to mean that over half of the total variation in a society’s level of happiness could be attributed to its level of democracy; or conversely, it could mean that a society’s level of democracy largely reflected its happiness level. Correlation is not causation, and this linkage could reflect any of the following things: (1) living under democratic institutions makes people much happier than living under authoritarian institutions; or (2) high levels of subjective well-being are conducive to democratic institutions; or (3) the correlation could be spurious, due to the fact that both subjective well-being and democracy are strongly correlated with some other variable such as high levels of economic development. Solving this puzzle has far-reaching implications. If the linkage is not spurious and democracy makes people happy, this provides a strong additional argument on behalf of democracy; while if high levels of happiness are conducive to democracy, this can lead to a better understanding of how democracy emerges and flourishes. Using World Values Survey data on happiness levels from 1981 to 2006, and the Freedom House measures of democracy levels from 1972 to 2005, this chapter analyses the relationships between happiness and democracy in order to determine what is causing what. Though the political culture literature has long argued that interpersonal trust and tolerance play an important role in the emergence and flourishing of democratic institutions, it has largely neglected the role of human happiness. But it is logical to expect that high levels of happiness would be linked with democracy. Political economy research demonstrates that if the economic cycle has been going well, support for the incumbents increases. 256

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257

Support for a democratic regime reflects much deeper long-term processes. If, in the long run, people feel that their life as a whole has been good under a given regime, it produces legitimacy and diffuse support for that regime. High levels of subjective well-being can also help stabilize authoritarian regimes, of course. Thus, China has experienced high levels of economic growth throughout the past two decades, and her public shows much higher levels of subjective well-being than the ex-communist regimes of Eastern Europe. This almost certainly helps legitimate China’s one-party communist regime – in the short run. But in the long run economic growth tends to bring cultural changes through which the public gradually places increasing importance on autonomy and self-expression – which eventually gives rise to demands for a more liberal political order (Inglehart and Welzel, 2005). Legitimacy is helpful to any regime, but authoritarian systems can survive through coercion; democratic regimes must have mass support or they can be voted out of existence like the Weimar republic. Thus, societies with happy publics are far more likely to survive as democracies than those with unhappy publics. Moreover, high levels of subjective well-being are linked with trust, tolerance and emphasis on self-expression that is conducive to the emergence and survival of democracy. Accordingly, a remarkably strong relationship existed between democracy and the self-reported happiness levels of given publics throughout the period before the explosion of democracy that occurred around 1990. Figure 11.1 shows this relationship among the 39 countries for which we have long-term survey data.1 As this figure demonstrates, happiness and democracy were strongly linked in the 1980s: the correlation between the two is r 5 0.81, and although we do not have survey data from the 1970s, the happiness levels of given societies tend to be relatively stable, and the levels shown here show almost equally strong relationships with the same countries’ Freedom House scores throughout the period from 1972 to 1987. This confirms previous findings that happiness is closely correlated with democracy (Frey and Stutzer, 2000, 2002; Inglehart, 1990). Both democracy and human happiness vary a great deal from one society to another. The societies examined here range from long-established liberal democracies such as Britain, Sweden, Denmark, USA and Canada, to countries that were extremely authoritarian in 1981 to 1986, such as China, Russia and Bulgaria.2 Happiness levels also vary greatly. The happiness levels used here could theoretically range from 0.00 (if everyone in the society said they were ‘extremely unhappy’) to 3.00 (if everyone said they were ‘very happy’). To provide some concrete illustrations: in Ireland (with a mean score of 2.36) fully 41 percent of the public described themselves as ‘very happy’, while in Belarus (with a mean score of 1.46), only 5 percent described themselves as ‘very happy’.

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Happiness, economics and politics 80

Sweden Ireland Norway Britain United Canada States Australia Denmark Netherlands

Japan West Germany Spain

70

Italy

Freedom House Scores, 1981–86

60

France

Finland India

50 Brazil Argentina

Mexico

40 Turkey Nigeria

30 S. Korea

20

Hungary Slovenia China

10 Lithuania Belarus Bulgaria Latvia

0 1.25

1.35

1.45

Estonia Romania Slovakia

1.55

Czech

Poland South Africa Chile East Germany

Ukraine Russia

1.65

1.75

1.85

1.95

2.05

2.15

2.25

2.35

2.45

Mean Happiness Score 1981–90 (r = 0.81) Source:

Values Surveys, 1981–90 and Freedom House scores, 1981–86.

Figure 11.1

The linkage between happiness and democracy before the third wave of democratization

One way to explain the strong linkage shown here between happiness and democracy would be to assume that democracy makes people happy. This interpretation is appealing and suggests that we have a quick fix for most of the world’s problems: adopt a democratic constitution and live happily ever after. Unfortunately, the experience of most of the Soviet successor states does not support this interpretation. Since their dramatic move toward democracy in 1991, their people have not become happier: for the most part, they moved in exactly the opposite direction with the sharp decline of their economy and society, as we will see.

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Nevertheless, we believe that in the long run a climate of free choice is conducive to happiness. Given individuals may not be conscious of the linkage between free choice and happiness, but those who feel they have relatively high levels of control and choice over how their lives turn out consistently report higher levels of life satisfaction than those who don’t. Free choice tends to make people happier. This is a driving force in the process of human development: rising emphasis on free choice favors democracy – the institutions that maximize human freedom. But democratic institutions are by no means the only factor shaping human happiness. Protracted periods of economic growth seem to be conducive to rising levels of happiness, and severe economic decline can have the opposite effect. Similarly, the breakdown of the social and political order that accompanied the collapse of communism in many societies was linked with declining levels of happiness, despite the sharp, sudden increase in political rights and civil liberties that occurred at the same time. We suspect that democratic institutions do contribute to human happiness to an appreciable extent, but the causal linkage seems to work much more strongly in the opposite direction, with democratic institutions being much more likely to flourish in a social climate characterized by high levels of subjective well-being – which are linked with high levels of trust, tolerance and emphasis on self-expression, constituting a syndrome of ‘self-expression values’ (Inglehart and Welzel, 2005). Thus Inglehart and Welzel (2005, chapter 8) examine why economic development goes with democracy, hypothesizing that cultural changes provide the link between development and democratization. They first test the impact of self-expression values at Time 1 on subsequent levels of democracy at Time 2. They find that a society’s mean score on the survival/self-expression dimension is by far the most powerful influence on its subsequent level of democracy. Although economic development is at the root of this causal sequence, it is important mainly in so far as it contributes to the emergence of self-expression values. They then test the reverse causal model: that democratic institutions cause a shift from survival values to self-expression values. Since these values show a 0.83 correlation with democracy, if one used democracy alone as a predictor of these values, it would ‘explain’ most of the variance. But when economic development is also included in the regression, democratic institutions explain only an additional 2 percent of the variance in self-expression values, beyond what was explained by economic development and religious heritage. Culture seems to shape democracy far more than democracy shapes culture. Despite the strong correlation between happiness and democracy, democratization does not automatically bring higher levels of democracy.

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8 7 Happiness 6 5

Democracy

4 3 2 1 0 1981

1990

1995

2000

2006

Note: Democracy is measured by the two Freedom House scales, which range from 1 to 7; their sum ranges from 2 to 14 but since high scores indicate low democracy, their polarity is reversed by subtracting them from 14, producing a scale that ranges from 0 to 12. Happiness is measured on a scale that ranges from 1 to 4, but since high scores indicate low happiness, polarity is reversed by subtracting from 4, producing a scale that ranges from 0 to 3. This score is then multiplied by 4 to produce a scale that ranges from 0 to 12 – giving both happiness and democracy the same 0–12 range. The 1981 happiness score is from a survey in Tambov oblast, which parallels the Russian republic rather closely.

Figure 11.2

Happiness and democracy in Russia, 1981–2006

As Figure 11.2 demonstrates, in 1981 the Russian public already showed relatively low levels of happiness by international standards.3 A low level of happiness preceded the collapse of communism – and, we suspect, contributed to it. Happiness level fell to an even lower level in Russia in 1990, and continued to fall in 1995 and 2000, despite the dramatic shift toward democracy that took place from 1981 to 1995. The severe economic decline that took place during this era (with real income declining to about 40 percent of its 1980 level), together with the collapse of the Soviet Union in 1991 and the accompanying collapse of the social order and the communist belief system, brought severe malaise to the Russian people: by 1995, a majority of them described themselves as unhappy and dissatisfied with their lives as a whole. Despite the marked increase in personal and political freedom that took place during this era, human happiness declined. Conversely, although political rights and civil liberties declined sharply from 1995 to 2006, happiness levels rose in 2006 as a partial economic recovery occurred, stimulated by rising gas and oil prices. Rising levels of

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democracy do not necessarily go with higher levels of happiness – the two can even move in opposite directions. Despite this evidence, we believe that democracy is conducive to human happiness – but clearly, it is only part of the story. The democracy and happiness scores have been transformed to have the same scale (ranging from 0 to 12) on Figure 11.2, to make the amplitude of their changes comparable. As this figure demonstrates, happiness levels are relatively stable, even in the face of dramatic societal changes. While a country’s scores on the Freedom House political rights and civil liberties scales can change dramatically from one year to the next – with Russia jumping by fully seven points out of a possible 12 from 1981 to 1995 – the Russian public’s happiness levels varied by less than one point on the scale during the same time period. As earlier analyses already indicated, relatively high or low levels of happiness and overall life satisfaction are relatively stable characteristics of given societies (Inglehart, 1990, pp. 25–8) – and they are strongly correlated with both per capita GNP and with democracy (ibid., pp. 31–44). They can and do change over time – economic, social and political developments seem to have an impact – but they tend to change rather slowly. A public’s assessment that their lives as a whole are going well or badly seems to be a deep-rooted orientation. Figures 11.3, 11.4 and 11.5 show how levels of happiness and democracy evolved in three more ex-communist societies for which we have survey data covering at least 15 years. Hungary was the only other communist country in which we were able to carry out a survey in 1981. It showed a happiness level then that was well below that of any stable democracy (and in the bottom quartile for the world as a whole) but significantly higher than that of Russia. This already low level declined further in 1990 when communism collapsed, and then made a modest recovery, perhaps linked with the fact that Hungary made a relatively smooth transition to democracy and a market economy. We do not have 1981 data for Romania or Slovenia, but – like all of the ex-communist countries without exception – they showed relatively low levels of subjective well-being in the first available survey in 1990. Fully 28 of the 30 lowest levels of happiness registered in the more than 200 surveys carried out by the World Values Survey, are found in ex-communist countries (the two remaining cases occur in the surveys carried out in Iraq in 2004 and 2006). Pervasive malaise characterized the European communist societies and, we believe, contributed to their collapse. Democratization occurred later in Romania than in Hungary, with Romania moving into Freedom House’s ‘free’ category only by 2000. Happiness declined from 1990 to 2000 and rose slightly in 2006 but remained below her earliest level. As of 2006, a huge increase in Romania’s level of democracy – rising

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14 12 Democracy

10 8

Happiness

6 4 2 0 1981

Figure 11.3

1990

1995

2000

2006

Happiness and democracy in Hungary, 1981–2006

12 10 Democracy 8 6

Happiness

4 2 0 1981

Figure 11.4

1990

1995

2000

2006

Happiness and democracy in Romania, 1981–2006

9 points on a scale having a maximum of 12 – has not brought a significant increase in happiness. Slovenia shows a more positive picture. A dramatic increase in her level of democracy (rising 8 points on the 12-point maximum) has been accompanied by a modest but steady rise in happiness levels. But it seems unlikely that this increase is due to democratization alone, for Slovenia

Democracy and happiness: what causes what?

263

14 12

Democracy

10 Happiness

8 6 4 2 0 1981

Figure 11.5

1990

1995

2000

2006

Happiness and democracy in Slovenia, 1981–2006

had impressive economic growth during this period, and is now the only ex-communist country that has risen into the World Bank’s ‘high income’ category; moreover, Slovenia’s political situation has become substantially more stable than that of many other ex-communist countries, with her entry into both the European Union and NATO. In another part of the world, both Mexico and Argentina made transitions to democracy in recent years, and we have relatively extensive time series data on their happiness levels. Mexico displays a pattern in which happiness and democracy levels move in tandem, with both variables showing a significant increase in 2000, the year in which one-party rule by the PRI (Institutional Revolutionary Party) finally ended through free elections. Although the evidence in Figure 11.6 does not control for other factors, it is certainly consistent with the belief that democratization contributes to rising levels of human happiness. Argentina’s transition to democracy took place earlier than the one in Mexico, but the evidence shown in Figure 11.7 is also consistent with the idea that democratization contributes to happiness: a dramatic shift toward democracy occurred between 1981 and 1990, accompanied by a modest rise in happiness. We have long-term evidence from two other societies that experienced a transition to democracy since 1981: South Africa and South Korea. In both cases happiness levels experienced a modest rise after the transition, although the change on the happiness scale was much smaller than the change on the democracy scale, as Figures 11.8 and 11.9 demonstrate: while democracy scores rose by 8 points in both countries, the happiness

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12 10 Happiness 8 Democracy 6 4 2

0 1981

Figure 11.6

1990

1995

2000

2006

Happiness and democracy in Mexico, 1981–2006

12 Democracy

10 8

Happiness

6 4 2 0 1981

Figure 11.7

1990

1995

2000

2006

Happiness and democracy in Argentina, 1981–2006

levels rose by less than 1 point on a scale having the same range as the democracy scale. Data are also available from a number of societies that did not experience recent transitions to democracy but they reveal little about the relationship between happiness and democracy because neither variable

Democracy and happiness: what causes what?

265

12 Democracy

10 8

Happiness 6 4 2 0 1981

Figure 11.8

1990

1995

2000

2006

Happiness and democracy in South Africa, 1981–2006

12 10 Democracy 8 Happiness 6 4 2 0 1981

Figure 11.9

1990

1995

2000

2006

Happiness and democracy in South Korea, 1981–2006

shows much movement. With Sweden and the USA, for example, the pattern shows two almost parallel lines, with democracy remaining constant at point 12 (the top of the scale) and happiness fluctuating at a level slightly above point 9. The evidence we have reviewed up to this point suggests that democracy

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Table 11.1

Predicting levels of happiness in 2000

Independent Variables

Model 1

Real GDP per capita, 0.006 1995 (in $1000 US) (0.008) Sum of Freedom House 0.004 scores, 1991–96 (0.003) Mean score on 0.673*** materialist/post(0.207) materialist values, 1995 Average annual growth 0.032*** rate, 1990–2000 (0.009) Adjusted R-squared 0.554 Number of countries 43

Model 2

Model 3

Model 4

Model 5

_____

_____

_____

_____

0.003 (0.002) 0.767*** (0.168)

_____

_____

_____

0.612***

_____

0.753*** (0.138)

0.034*** (0.009) 0.547 43

0.048*** (0.011) 0.318 43

____

0.032*** (0.009) 0.558 43

0.395 44

Note: The table shows standardized regression coefficients, with the unstandardized coefficients in parentheses. Dependent variable: happiness level, 2000. Significance levels: * p ≤ 0.05; ** p ≤ 0.01; ***p< 0.001. Source:

World Values Surveys (2000).

may be conducive to human happiness, but its immediate impact seems to be rather modest – and transitions to democracy can even be linked with declining levels of happiness. Additional factors seem to be involved. In order to test the relative impact of democracy and other likely factors, we carried out multiple regression analysis. Table 11.1 shows the results of an analysis in which the dependent variable is a society’s level of happiness in 2000 – a decade after the explosion of democracy around 1990. These predictors were selected after an initial screening of additional variables that theoretically might be involved. Among the independent variables, we used the society’s level of democracy as measured by the sum of its Freedom House scores in 1991–96. This provides a measure of democracy at a time before that of the dependent variable (in keeping with the fact that causes precede effects), but after the explosion of democracy. Additional predictors include two economic indicators: (1) the society’s level of economic development, as indicated by its per capita GNP in 1995; and (2) the society’s annual growth rate during the decade preceding the time at which happiness is measured. Finally, we also use the society’s level of post-materialist values, as an indicator of the extent to which the society emphasizes self-expression and free choice, in keeping with the human development thesis which holds that free choice is conducive to human happiness (Inglehart and Welzel, 2005). As we have noted, happiness and free choice are closely linked in the syndrome of self-expression values

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– but for present purposes, we want to examine the impact that emphasis on free choice has on happiness, controlling for other factors. In Model 1 of this analysis these five independent variables explain more than 55 percent of the cross-national variance in happiness. Although per capita GNP has a strong and significant zero-order correlation with happiness (r 5 0.52), its impact disappears when we include the other variables in this analysis. But a country’s economic growth rate during the decade preceding the time when happiness was measured does show an impact on its happiness level that is significant at the 0.001 level. In keeping with the aspiration-adjustment model (Campbell et al., 1976; Inglehart, 1990), improving or deteriorating economic conditions seem to have more impact on a society’s happiness level than does its absolute level of wealth. When we drop per capita GNP from the regression equation (Model 2), the remaining variables explain fully as much of the variance in happiness as did Model 1. And despite the remarkably strong correlation that existed between democracy and happiness before the explosion of democracy around 1990 (see Figure 11.1), a society’s level of democracy in 1991–96 had only a modest impact on its subsequent level of happiness. As Model 3 demonstrates, when we drop the Freedom House measures of democracy from our analysis, the amount of explained variance falls only slightly, from 55.8 percent to 54.7 percent. If a society’s level of happiness were mainly determined by its level of democracy, then the explosion of democracy around 1990 would have been followed by sharp increases in the happiness levels of the societies that democratized. This did not happen, as Figures 11.2 to 11.9 indicate. As a result, the previously strong correlation between happiness and democracy suddenly became much weaker, falling from the 0.8 level around 1980 to less than 0.3 in 1995. Apparently, democracy does have some impact on a society’s happiness level, but it is by no means the sole determining factor. On the other hand, both economic growth and post-materialist values seem to have strong impacts on a society’s relative happiness level. Together, they explain almost 55 percent of the variation. As Model 4 indicates, when we drop materialist/post-materialist values from the equation, the explained variance falls from about 55 percent to about 32 percent; and when we drop economic growth from the equation but retain materialist/post-materialist values (see Model 5), the explained variance falls from 55 percent to 40 percent. Living in an environment of economic and psychological security seems to have a powerful impact on a society’s happiness level. The fact that both of these attributes tend to go with high levels of economic development largely explains the strong zero-order correlation between GNP per capita and happiness. Inglehart et al. (2008) analyse the causes of changes in societies’ levels

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Table 11.2

Predicting shifts in happiness levels, 1981–2000

Independent Variables Average annual growth in GNP, 1990–2000 Change in support for gender equality in jobs, 1981–2000 Sum, Freedom House scores, 1991–96 Change in tolerance of homosexuality, 1981–2000 Adjusted R-squared Number of countries

Model 1

Model 2

Model 3

Model 4

Model 5

0.009 (0.008) 0.211* (0.104)

_____

_____

_____

_____

0.178 (0.098)

_____

0.113 (0.096)

_____

0.004* (0.002) 0.070* (0.028)

0.004* (0.002) 0.073* (0.027)

0.003 (0.002) 0.060* (0.027)

_____

_____

0.049 (0.026)

0.045 (0.026)

0.140 38

0.140 38

0.084 38

0.061 38

0.052 38

Note: The table shows standardized regression coefficients, with the unstandardized coefficients in parentheses. Dependent variable: shifts in happiness levels, 1981–2000. Significance levels: * p ≤ 0.05; ** p ≤ 0.01. Source:

1999–2001 World Values Surveys (1981–2000).

of subjective well-being from 1981 to 2006. A similar analysis is provided in Table 11.2. They find that under extreme conditions a society’s levels of happiness and life satisfaction can show lasting changes, as happened with the collapse of the Soviet economy and its social, political and belief systems. Socio-economic changes can lastingly reshape the subjective wellbeing levels of entire societies. Sharp declines in subjective well-being occur rarely, but when they do they can have serious consequences. Though the collapse of the Soviet Union in 1991 had its own negative effects, it was preceded by declining subjective well-being. Similarly, the breakup of the Belgian state in the 1980s and its reorganization into a federation based on ethnic cleavages was preceded by a sharp decline in subjective well-being (Inglehart and Klingemann, 2000). These findings are consistent with the interpretation that economic factors have a strong impact on subjective well-being in low income countries – but that at higher levels of development, evolutionary cultural changes occur in which people place increasing emphasis on self-expression and free choice, leading them to increasingly emphasize strategies that maximize free choice and happiness (Inglehart and Welzel, 2005). In recent years economic growth, democratization and these changing cultural strategies actually seem to have raised happiness levels in much of the world. The evidence indicates that these factors were conducive to happiness mainly through their common tendency to increase free choice

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in the economic, social and political realms. A path analysis of this causal sequence carried out by Inglehart et al. (2008) indicates that during the years since 1981 democratization, rising social tolerance and economic development all contributed to a growing sense of free choice, and thus to rising levels of happiness.

CONCLUSION Democratization does not necessarily bring happiness. In many excommunist societies democratization was accompanied by social and economic collapse – and far from bringing rising happiness, democratization was followed by sharply falling levels of happiness. In other countries, such as Mexico, where democratization was accompanied by normal social and economic conditions, it was followed by rising happiness. Although democracy does not determine a society’s level of subjective well-being, other things being equal, democracy does contribute to happiness. But the causal flow seems stronger in the opposite direction. Multivariate analysis indicates that both economic growth and changing values have strong impacts on a society’s relative happiness level. Living in an environment of economic and psychological security seems to have a powerful impact on a society’s happiness level – constituting a syndrome that is conducive to democracy. The citizens of democracies are substantially happier than those of autocracies. In part, this reflects the fact that democracy is conducive to happiness – but it is even more strongly linked with the fact that a syndrome of tolerance, trust, activism and subjective well-being is conducive to democracy.

NOTES 1. In order to carry out time series analysis, these analyses are based only on those countries for which we have data covering at least 15 years. We use the earliest available measure of happiness levels for the countries shown in Figure 11.1; for 22 countries the data are from the 1981 World Values Survey, and for 17 countries the data are from the 1990 World Values Survey. 2. The vertical axis on Figure 11.1 is based on the sum of each country’s Freedom House scores for 1981 to 1986, which run from 2 to 14, with high scores reflecting low levels of democracy. In order to reverse this polarity, each country’s score was subtracted from 14, producing scores ranging from 0 to 12 for any given year, and a maximum score of 72 for the six-year period. The original happiness scores ranged from 1 to 4, with high scores indicating low levels of happiness; their polarity was also reversed, by subtracting each country’s mean score from 4, to produce scores ranging from 0 to a theoretical maximum of 3, which would be obtained if everyone described themselves as ‘very happy’. Accordingly, on Figure 11.1, high scores indicate high levels of happiness and democracy.

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3. It was not possible to carry out a survey of the entire Russian republic in 1981, but we did survey Tambov oblast, which our Russian colleagues selected as a region that was representative of Russia as a whole. The assumption that it is gains support from the fact that in 1995, when we surveyed both Tambov oblast and Russia as a whole, they did show similar levels of happiness and other variables.

REFERENCES Campbell, Angus, Philip E. Converse and Willard L. Rodgers (1976), The Quality of Life, New York: Sage. Frey, Bruno S. and Alois Stutzer (2000), ‘Happiness, economy and institutions’, The Economic Journal, 110 (466), October 918–38. Frey, Bruno S. and Alois Stutzer (2002), Happiness and Economics: How the Economy and Institutions Affect Human Well-being, Princeton, NJ: Princeton University Press. Inglehart, Ronald (1990), Culture Shift in Advanced Industrial Society, Princeton, NJ: Princeton University Press. Inglehart, Ronald and Hans-Dieter Klingemann (2000), ‘Genes, culture, democracy and happiness’, in Ed Diener and Eunkook Suh (eds), Subjective WellBeing Across Cultures, Cambridge, MA: MIT Press, pp. 165–83. Inglehart, Ronald and Christian Welzel (2005), Modernization, Cultural Change and Democracy, New York and Cambridge: Cambridge University Press. Inglehart, Ronald, Roberto Foa, Christopher Peterson and Christian Welzel (2008), ‘Development, freedom and rising happiness’, Perspectives on Psychological Science, 3 (4), 264–85.

12.

The causal link between happiness and democratic welfare regimes Charlotte Ridge, Tom Rice and Matthew Cherry

In a recent article Radcliff (2001) provides substantial empirical support for an important and ideologically charged thesis: social democratic welfare regimes make people happier. He reaches this conclusion after an exhaustive examination of both aggregate- and individual-level data across 15 industrialized democracies in the latter decades of the twentieth century. Subsequent cross-national work supports the finding (Pacek, 2006; Pacek and Radcliff, 2008) and new research on the US states shows that people tend to be happier in states with more liberal governments and policies (Alvarez-Diaz et al., 2006). Clearly, this work is potent and controversial. Not only does it claim that life is better under one type of government than others, it makes the claim with respect to human happiness, perhaps the most meaningful measure of a good society. Given the significance of the thesis, it is especially important to test it thoroughly. The research to date has done a fine job of statistically linking happiness to left-leaning regimes and distributive social welfare policies. These empirical associations are certainly strong evidence in support of the thesis, but they may not be the final say on the matter. We contend that the proponents of the thesis may have been too quick to equate correlation as causation. In this chapter, we take a step back and start from the position that the causal direction of the statistical link between happiness and politics may run either way, or even be spurious. After briefly outlining the causal possibilities, we make use of two complementary data sets to put the competing hypotheses to a series of tests.

12.1

THE THEORETICAL CONNECTIONS

There are three ways that politics and happiness might be linked. The theory that has driven the recent work in this area holds that politics influences happiness. Proponents maintain that the ‘economic insecurity 271

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and personal loss of autonomy that accompany market economies’ cause unhappiness (Radcliff, 2001, p. 941). Social democratic welfare regimes, so the argument goes, help minimize this unhappiness by putting in place programs, such as unemployment and disability benefits, that protect people against the worst effects of market economies. In one way or another, this position is expressed in the work of Marx, Polanyi (1944), Lindblom (1977), Lane (1978) and many others. Put in terms of a simple model, the position can be expressed as: Politics → Happiness

(Theory 1)

One alternative to this theory is that the causal path is reversed: that happiness leads to politics. More specifically, this counter premise contends that happier people are more likely than less happy people to embrace social democratic welfare regimes and policies. Although this line of thinking has not been explored in the literature, it has intuitive appeal. At its core this reasoning rests on the plausible assumption that happy people are less insular and more open to sharing resources to help others. We know, for example, that happiness is correlated with charitable giving and voluntarism (Thoits and Hewitt, 2001). If we extend this to politics, it seems plausible that happy people would be more willing to support social programs and social democratic welfare regimes. This theory is expressed as: Happiness → Politics

(Theory 2)

A third alternative is that the positive relationship between politics and happiness is spurious. According to this view, some other force is influencing both politics and happiness. Culture is a likely ‘other’ force. There are well-developed literatures linking culture to politics (see, for example, Elazar, 1966; Formisano, 2001; Inglehart, 1988) and happiness (see Diener and Suh, 2000; Inglehart, 1997; Inkeles, 1997; Rice and Steele, 2004). Particularly prominent in recent years has been work on the influence that a specific form of culture, social capital, has on politics and happiness. Scholars have defined social capital in a myriad of ways, but a central feature to most definitions is the notion of generalized trust. This type of trust extends beyond family and friends, and it facilitates collaboration for mutual gain in society. Putnam (1993, 2000) and others argue that societies high in interpersonal trust tend to have more social welfare policies. Helliwell (2001, 2005) contends that societies high in trust tend to be happier. If these scholars are correct, it is quite possible that the positive correlation between politics and happiness is, indeed, spurious. Instead of

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social democratic welfare governments and policies causing happiness or the other way around, both would be the product social capital. Expressed in model form, this theory is: Culture → Happiness Culture → Politics Politics ≠ Happiness

(Theory 3)

Sorting out which of these theories is correct is more than an interesting academic exercise. Happiness, politics and social capital matter. If Theory 1 is correct it means that human happiness is best achieved under social democratic welfare regimes and their policies. If Theory 2 is correct it means that human happiness influences the likelihood of adopting social democratic welfare regimes and their policies. And if Theory 3 is correct it means that social capital promotes human happiness and social democratic welfare regimes. Clearly, these theories speak to very big issues and they offer very different messages.

12.2

THE DATA NEEDS AND VARIABLE CONSTRUCTION

Sorting out which theory is correct requires data over time. Without these data, all we can know for certain is correlation, not causation. Take, for example, happiness and politics. As noted earlier, Radcliff (2001) and others use data collected at roughly the same point in time to show that happiness is correlated with liberal regimes and policies. They surmise from these correlations that politics drives happiness (Theory 1), yet the data also support the notion that happiness drives politics (Theory 2) and the notion that both politics and happiness are caused by culture (Theory 3). As long as the data are from the same point in time, it is difficult to determine the causal link behind the correlations. What is needed are data at two points in time so that we can be certain that the measures from the earlier point in time could not have been caused by the measures at the later point in time. Let us consider our data needs more precisely. Our measures of politics will have to be collected at the national level because social democratic welfare regimes and redistributive policies are national-level factors. Given that these measures will be national level, it makes sense to also develop national-level measures of happiness and social capital. Ideally, we would have national-level measures of happiness and social capital that predate the post-World War II emergence of social democratic welfare regimes

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and significant redistributive policies. If these early measures of happiness and social capital at the national level correlate with national politics in the modern era, it would be very powerful evidence against Theory 1 that politics influences happiness. After all, post-World War II governments and policies could not have influenced pre-World War II levels of happiness and social capital. Our data needs, then, include pre-World War II levels of happiness and social capital. Fortunately, many of our contemporary data needs can be met by using Radcliff’s (2001) national-level measures of politics and happiness. As noted earlier, he examines the link between these two factors for 15 industrialized nations. We need to add to these data a contemporary national-level measure of social capital and pre-World War II nationallevel measures of happiness and social capital. The contemporary measure of social capital is easy to construct by aggregating widely available survey responses by nation. The historical national-level measures of happiness and social capital are another matter altogether. For many of our nations, there were no surveys conducted before World War II that included happiness and social capital questions. It might seem, then, that we will be forced to search for imperfect contextual measures of these two factors. However, we can draw on the work of Rice and Feldman (1997) to use contemporary survey data to derive nineteenth-century estimates of the relative levels of happiness and social capital in most of the nations in Radcliff’s (2001) sample. We now turn to the construction of our measures. 12.2.1

Measures of Politics

Radcliff used three measures of politics to assess the extent to which social democratic welfare regimes and their policies correlated with happiness. The first of these measures examines the degree to which governments shield citizens against market dependence. Originally devised by EspingAndersen (1990), it consists of three variables that gauge ‘how much a national system embodies elements of his three ideal types of welfare regime: Liberal, Conservative, and Socialist’ (Radcliff, 2001, p. 942). For our purposes, the key hypothesis is that happiness should be positively related to the socialist score. This variable, which we term socialist, ranges in value from 0 for the least socialist to 8 for the most socialist. The second politics variable, called decommodification, is an index that assesses the degree to which citizens ‘can uphold a socially acceptable standard of living independent of market participation’, and it, too, was created by Esping-Andersen (1990, p. 37). Information about the scope of pensions, income maintenance and unemployment benefits was used to calculate the index. Higher scores indicate greater decommodification, so happiness

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should be positively related to this variable. The scores range from 13.8 to 39.1. The third political variable, which we term left dominance, consists of data from Huber et al. (1997) on the ‘cumulative portion of leftist cabinet seats less the cumulative portion of rightist seats’ from 1950 to 1990 (Radcliff, 2001, p. 942). Country-level scores on this variable range from −44.11 to 36.50 and it should be positively related to happiness. 12.2.2

Measures of Happiness

For a dependent variable, Radcliff (2001) uses mean happiness scores for 15 industrial democracies derived from the 1990 wave of the World Values Survey (WVS). Each country’s score is calculated using responses to the question: ‘All things considered, how satisfied are you with your life now?’ Response categories range from 1 (dissatisfied) to 10 (satisfied), and country-level means ranged from 6.53 (Japan) to 8.16 (Denmark). It is important to mention that the early version of the WVS data used by Radcliff contained a serious coding error for Austria that was fixed in later releases. Once corrected, the mean Austrian happiness score increases from 6.51 to 7.87. This variable, with the correct Austrian mean, serves as our measure of contemporary happiness levels in the nations. Our pre-World War II measure of national happiness levels comes from a recent study by Rice and Steele (2004) that employs methodology developed by Rice and Feldman (1997). The data used to construct the measure are from the General Social Surveys (GSS), a widely respected series of random sample surveys of US citizens that have been conducted almost annually since the early 1970s. Most of the annual surveys have included the question: ‘Taken all together, how would you say things are these days — would you say you are very happy, pretty happy, or not too happy?’ For their analysis, Rice and Steele (2004) code the ‘not too happy’ responses as a 1, the ‘pretty happy’ responses as a 2 and the ‘very happy’ responses as a 3. The GSS also includes a question that asks the respondents: ‘From what countries or part of the world did your ancestors come?’ Rice and Steele (2004) use these data to calculate the aggregate happiness levels of Americans from different ancestral groups. Before doing so, however, they excluded from their analysis all of the respondents who were not born in the USA and all of the respondents who named more than one nation of primary origin. With these interviewees omitted, they calculated the mean happiness level for each of the ancestral groups; that is, they separated the GSS data by the respondents’ self-reported country of national origin and computed the mean happiness level for each of these groups. Thus, they ended up with mean happiness levels for Americans of French ancestral

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background, Italian ancestral background and so on. These means, they argue, are serviceable proxies for the relative happiness levels of citizens from the home countries many generations ago. As evidence, they show that the GSS ancestral happiness means are strongly correlated with the happiness means of contemporary citizens from those countries derived from the WVS data. This suggests that relative happiness levels of national populations remain about the same across generations and that the GSS ancestral means are approximations for the relative happiness levels of people from the home countries years ago. Rice and Steele (2004) calculated GSS happiness means for the ancestors from all of the countries in Radcliff’s (2001) sample except Belgium and Japan. We were able to add Japan to the sample by using the Rice and Steele (2004) methodology to compute the happiness mean for American-born GSS respondents who claimed to have ancestors primarily from that country. For Belgium, however, this process yielded only 19 respondents who claimed primary ancestral ties to that nation. With a sample size this small the mean happiness score is likely to be biased. To check for this possibility we calculated the z-scores for the mean happiness values for the 15 nations. The z-score for the Belgium mean as 3.00 is an obvious outlier (all of the other ancestral group z-scores were within 1.20 standard deviations of the mean). Thus, we dropped Belgium from our sample. We use the GSS ancestral group happiness means for the remaining 14 nations as our pre-World War II surrogate measure for mean happiness levels in these nations. In reality, these means probably measure home country happiness levels back much further than World War II because the vast majority of Americans can trace their American ancestors back many generations. The means range from 2.18 for people of Austrian origin to 2.30 for Swedish origin. 12.2.3

Measures of Social Capital

The WVS includes the following widely used generalized trust question: ‘Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people?’ For our measure of social capital in the nations today we use the percentage of people in each nation who say that people can be trusted as reported by Inglehart (1997, p. 359). The percentages run from 23 percent in France to 66 percent in Sweden. We created our pre-World War II measure of social capital by employing the same technique that Rice and Steele (2004) used to create our historical measure of happiness. In this case we calculated the mean trust level for the American-born GSS respondents who claimed primary ancestry to one nation. For this procedure, the ‘most people can be trusted’ responses were coded as a 1 and the ‘must be careful in dealing with people’ responses

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were coded as a 2. The mean values ranged from 1.39 for people of Italian ancestry to 1.60 for people of Norwegian ancestry. These values correlate at 0.47 (p , 0.05) with the WVS national trust values, suggesting that trust, like happiness, is, to a certain degree, passed on from generation to generation. It also suggests that our GSS trust means are serviceable proxies for relative trust levels in our sample nations prior to World War II.

12.4

FINDINGS: CAUSAL POTPOURRI

The variables are now in place for a test of the causal linkages between happiness, social democratic welfare regimes and social capital. We begin by looking exclusively at the relationships between the three political variables and the two happiness variables. Table 12.1 reports the bivariate correlations between these variables and the coefficients show that the political variables are as closely correlated with the historical measure of happiness as they are to the contemporary measure of happiness. The historical measure of happiness is significantly linked to socialist and decommodification, and the contemporary measure is significantly linked to socialist and left dominance. These findings certainly raise doubts about the prevailing wisdom that social democratic welfare regimes lead to higher levels of aggregate citizen happiness than other types of regimes. After all, how can welfare regimes drive happiness if national happiness levels that predate the rise of welfare regimes are significantly related to two of the contemporary welfare regime measures? It is true that two of the three political variables are also significantly related to contemporary happiness, but in light of the strong correlations with the historical happiness measures, the causal direction of these relationships may well run from happiness to politics rather than the other way around. In terms of the theories guiding our research, Table 12.1 provides more support for Theory 2 than Theory 1. Now let us add social capital to the mix. To do this we generate three Table 12.1

Bivariate correlations between happiness and politics Socialist

Contemporary happiness Historical happiness Note:

Decommodification

Left Dominance

0.45*

0.25

0.64**

0.72**

0.45*

0.33

N = 14; * = significant at 0.05; ** = significant at 0.01.

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Socialistt

Happyt Social Capitalt

Happyt–1

Social Capitalt–1 Figure 12.1

Path analysis model

path analysis models, one for each of the political variables. The models assume that every endogenous variable is the product of all prior endogenous and exogenous variables. Social capitalt-1 is the only exogenous variable and the endogenous variables in order of presumed causality are happyt-1, social capitalt, the political variables (socialistt, decommodificationt and left dominancet) and happyt. Figure 12.1 displays the presumed paths. In formal terms, the equations in the path models are: Happyt−1 5 b11social capitalt−1 1 e1

(12.1)

Social capitalt 5 b21social capitalt−1 1 b22happyt-1 1 e2

(12.2)

Politicst 5 b31social capitalt−1 1 b32happyt−1 1 b33social capitalt 1 e3 (12.3) Happyt 5 b41social capitalt−1 1 b42happyt-1 1 b43social capitalt 1 b44politicst 1 e4.

(12.4)

We set a lenient minimum significance level for the paths of p . 0.15 because there are only 14 cases. As the equations were being generated, all

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Happyt 0.64 Socialistt 0.30

Social Capitalt

0.43 0.44 Happyt–1 0.39

0.33

0.32 Social Capitalt–1

Figure 12.2

Path analysis with socialistt

statistically insignificant paths were omitted and the equations were rerun until only significant paths remain. Figure 12.2 displays the path coefficients (standardized coefficients) for the model with the socialist variable as the political term. Only a single variable, the contemporary social capital variable (social capitalt), has a direct significant impact on contemporary happiness (happyt). The same is true in Figure 12.3, where contemporary social capital is again the only variable to have a direct significant impact on contemporary happiness. In these two path models, then, the political variables, socialistt and decommodificationt, have no influence on contemporary happiness controlling for social capital, clear evidence against Theory 1. The theory does pick up some support in Figure 12.4, where the left dominance variable is significantly related to contemporary happiness (as is the contemporary social capital variable, again). On balance, however, Theory 1 fares poorly in the path models. The socialist and decommodification variables, the two political terms that most directly measure the policies that protect people from the downsides of market dependence, fail to influence happiness, while the only political variable to reach significance, left dominance, measures party control of government more than policy outputs. Do Theories 2 or 3 fare any better in the path models? There is certainly not much support for Theory 2 in the contemporary part of the models. If causality runs from happiness to politics, as speculated in Theory 2, we

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Happyt 0.64

Decommodificationt 0.54

Social Capitalt

0.28 0.44

Happyt–1

0.33

0.32

Social Capitalt–1

Figure 12.3

Path analysis with decommodificationt Happyt 0.41

0.41

Left Dominancet 0.63

Social Capitalt 0.44

Happyt–1 0.35

0.33

0.32 Social Capitalt–1

Figure 12.4

Path analysis with left dominancet

should see significant links between contemporary happiness and the three political variables. But, as already noted, the only path between these variables that is significant is in Figure 12.4. The theory does find somewhat more support when we bring the historical portion of the models into play. The historical measure of happiness (happyt-1) is linked significantly

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to two of the political variables, socialist and decommodification. There is no mistaking causality here because the historical measure of happiness comes from the American-born GSS respondents, whose happiness is not influenced by the contemporary welfare politics of their ancestral homeland. Thus, two of the three models provide solid evidence in favor of Theory 2. Theory 3 also finds support in the path models. In the contemporary portion of all three of the models social capital is significantly related to happiness and politics, just as Theory 3 predicts. Moreover, once we control for social capital, the only political variable significantly linked to contemporary happiness is left dominance. The links between the other two political variables and happiness are insignificant, also as Theory 3 predicts. It is possible, of course, that the causal order of the contemporary variables in the models runs the other way. Perhaps contemporary happiness and politics influence social capital. This seems unlikely, however, given substantial work that shows that societal levels of social capital change very slowly (Putnam, 1993, 2000; Rice and Arnett, 2001; Rice and Feldman, 1997). The historical variables in the path models also provided limited support for Theory 3. The historical measure of social capital (social capitalt-1) is linked significantly to two of the political variables, suggesting that contemporary welfare state politics is influenced by prior levels of social capital (as calculated from the American-born GSS respondents). There is no evidence that historical levels of social capital directly influence contemporary levels of happiness, but in all three models historical social capital influences contemporary social capital, which, in turn, is significantly linked to both contemporary happiness and politics. This suggests that historical social capital indirectly influences happiness and politics though contemporary social capital, a result entirely consistent with Theory 3.

12.5

DISCUSSION

Looked at in total, our modest analysis finds some evidence in favor of the notion that politics influences happiness (Theory 1), somewhat more evidence that politics influences happiness (Theory 2), and still more that both happiness and politics may be the product of culture (Theory 3). The results, then, do not do much to help sort out the causal connection between happiness, politics and culture. Instead, they muddy the water – which, in our view, is a good reason for having conducted the study. The confusion calls into question the prevailing view that social democratic

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welfare regimes and their policies make people happy. Perhaps the view is correct, but at the very least, our findings suggest that more work needs to be done to be sure. We did a bit more work with the data at hand. In several additional tests we reran the path models in Figures 12.2, 12.3, and 12.4 using a dependent variable generated from a different WVS county-level happiness question. The question asked directly about ‘happiness’ instead of ‘life satisfaction’. The results were again mixed, with evidence for all three theories. For a final series of tests we attached the values of the aggregated variables in the path models (politicst, happyt-1 and social capitalt-1) to the appropriate respondents in the WVS survey. So, for example, we attached the decommodification score for France to all of the French respondents. Using the individual-level happiness questions as the dependent variables (happiness and life satisfaction) we generated a series of regression models, each with a different political variable as one of the independent variables. The other independent variables included the historical measures of happiness and social capital, the contemporary measure of social capital (trust at the individual level), and a long list of controls, such as age, gender, national unemployment rates and church attendance (we were able to include most of the controls as Radcliff (2001) used in a similar analysis). Once again, the results were mixed. The political variables perform well in the models with the life satisfaction question as the dependent variable, evidence for Theories 1 and 2. However, when the happy question is the dependent variable, the political variables perform poorly. The historical social capital variable is significant in some models, but not others, providing limited support for Theory 3. If we want to muddy the waters even further we can look to a recent paper by Helliwell (2005) that reports that national happiness levels are related to several government characteristics, none of which are the redistributive polices that mark social democratic welfare regimes. He finds that government stability, the rule of law, regulatory quality and several other characteristics lead to happy citizens, but not redistributive programs. This suggests that future tests of a link between social welfare policies and happiness should control for a whole host of other government characteristics, many of which are probably correlated with welfare policies (for example, social democratic welfare regimes tend to stable governments, rule of law and so on). Helliwell’s work raises the possibility that it is not the redistributive policies of social democratic welfare regimes that lead to happiness, but other characteristics of their governments (some of which they share with other types of governments). The point is that there is good reason to be uncertain about the causal connection between social democratic welfare regimes and happiness. By

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drawing attention to the uncertainty, we are not trying to discourage work in this area. Sorting out the causal connection between happiness and politics is important. If, on the one hand, the distributive policies most often associated with democratic social welfare regimes really do lead to greater human happiness, then this is a powerful reason to embrace and encourage these regimes. If, on the other hand, happiness leads to social welfare regimes, then advocates of this type of government would do well to promote happiness. And if happiness and social welfare regimes are a product of certain cultural characteristics, then proponents of happiness and social welfare regimes should focus on promoting these characteristics (we suggest that one characteristic might be social capital). The point is that happiness and regime type are very important. We all strive for happiness and we hotly debate, and even go to war over, the question of the best form of government. Sorting out the relationship between these two variables would seem to have important real-world ramifications. We want to stress again that the proponents of the thesis that social democratic welfare regimes and their polices lead to happy citizens may be right. They have conducted some very creative and rigorous empirical tests that show results consistent with the thesis. The work is excellent as far as it goes, but it does not test for the causal direction of the relationship or the possibility that the relationship is spurious. It is simply assumed that the causality runs from regime type to happiness. Until causality is sorted out, it is premature to claim that democratic social welfare regimes and their policies lead to higher levels of human happiness.

REFERENCES Alvarez-Diaz, A., L. Gonzalez and B. Radcliff (2006), ‘The politics of happiness: on the political determinants of quality of life in the American States’, Working Paper, Department of Political Science, University of Notre Dame. Diener, Ed and Eunkook M. Suh (eds) (2000), Culture and Subjective Well-Being, Cambridge, MA: MIT Press. Elazar, Daniel (1966), American Federalism: A View from the States, New York: Thomas Y. Crowell. Esping-Andersen, Gøsta (1990), The Three Worlds of Welfare Capitalism, Princeton, NJ: Princeton University Press. Formisano, Ronald P. (2001), ‘The concept of political culture’, Journal of Interdisciplinary History, 31 (3), 393–426. Helliwell, J.F. (ed.) (2001), ‘The contribution of human and social capital to sustained economic growth and well-being’, in J. Heliwell (ed.), The Contribution Of Human And Social Capital to Sustained Economic Growth And Well-Being, Hull, Canada: Organization for Economic Co-operation and Development, pp. 425–60.

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Helliwell, J.F. (2005), ‘Well-being, social capital and public policy: what’s new?’, NBER Working Paper No. 11807, available at SSRN: http://ssrn.com/ abstract5875683. Huber, Evelyne, Charles Ragin and John D. Stephens (1997), ‘Comparative welfare states dataset’, Northwestern University and University of North Carolina, http://www.unc.edu/~jdsteph (accessed 10 April 1998). Inglehart, Ronald (1988), ‘The renaissance of political culture’, American Political Science Review, 82 (4), 1203–30. Inglehart, Ronald (1997), Modernization and Postmodernization, Princeton, NJ: Princeton University Press. Inkeles, Alex (1997), National Character, New Brunswick, NJ: Transaction. Lane, Robert (1978), ‘Autonomy, felicity, futility’, The Journal of Politics, 40 (1), 1–24. Lindblom, Charles (1977), Politics and Markets, New York: Basic Books. Pacek, Alexander, (2006), ‘Globalization and subjective well-being: a crossnational analysis’, New Directions in the Study of Happiness Workshop, University of Notre Dame, 22–24 October. Pacek, Alexander and Benjamin Radcliff (2008), ‘Assessing the welfare state: the politics of happiness,’ PS: Perspectives on Politics, 6 (2), 267–78. Polanyi, Karl (1944), The Great Transformation, New York: Rinehart. Putnam, Robert (1993), Making Democracy Work, Princeton, NJ: Princeton University Press. Putnam, Robert (2000), Bowling Alone, New York: Simon & Schuster. Radcliff, Benjamin (2001), ‘Politics, markets, and life satisfaction: the political economy of human happiness’, American Political Science Review, 95 (4), 939–52. Rice, Tom and Marshall Arnett (2001), ‘Civic culture and socioeconomic development in United States: a view from the states 1880s–1990s’, The Social Science Journal, 38 (1), 39–51. Rice, Tom and Jan Feldman (1997), ‘Civic culture and democracy from Europe to America’, The Journal of Politics, 59 (4), 1143–72. Rice, Tom and Brent Steele (2004), ‘Subjective well-being and culture across time and space’, Journal of Cross-Cultural Psychology, 35 (6), 633–47. Thoits, Peggy A. and Lyndi N. Hewitt (2001), ‘Volunteer work and well-being’, Journal of Health and Social Behavior, 42 (2),115–31.

13.

Labor organization and the quality of life in the American states Suzanne M. Coshow and Benjamin Radcliff

Recent decades have witnessed the emergence of an extensive social scientific literature on the socio-political determinants of life satisfaction. With the refinement of the tools necessary to measure with reasonable reliability and validity how satisfied people are with their lives, it has become possible to test theoretically derived hypotheses about the observable factors that tend to make people more satisfied in some societies than others. In sum, we are capable of measuring subjective quality of life in a rigorous fashion, theorizing about the real-world conditions that determine such differences, and testing the resulting empirical predictions (for reviews, see Diener and Suh, 2000; Frey and Stutzer, 2002; Veenhoven, 1997). While extensive scholarly attention has been devoted to questions about how cultural, economic and political conditions determine differences in life satisfaction in affluent democratic countries, the literature has conspicuously failed to consider that such nations also have market economies. While the market doubtless contributes to human well-being in a variety of ways, it must also be recognized that market societies remain class societies. Simply put, modern capitalist democracies remain characterized by class and thus class conflict. This conflict is in part over the direction of public policy, but is also manifest within labor markets. The principal mechanism by which workers compete in these conflicts is, of course, through the institution of the labor union. The organization of labor is not only generally agreed to be an important phenomenon by social theorists of all persuasions, but large empirical literatures in sociology, economics and political science document how differences in the extent of organization across countries affect a multitude of social outcomes. In this chapter, we attempt to assess how the organization of workers affects differences in satisfaction with life in the USA. In particular, we seek to determine if the huge differences in labor union density across the American states predict the level of life satisfaction across the states. 285

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LABOR ORGANIZATION AND LIFE SATISFACTION

Unionization contributes to subjective well-being through a variety of mechanisms. Some are direct, in the sense that they affect organized workers as individuals per se; in this way, a society has greater average satisfaction as union density increases because the benefits of organization apply to a larger share of society’s members. Others are indirect, affecting both the organized and unorganized; aggregate levels of well-being thus increase with density because greater organization alters social arrangements such that they better contribute to a generalized improvement in living conditions. All are ultimately political in that union density itself is universally agreed to be substantially (though of course not entirely) determined by governmental policy (for example, Western, 1997). 13.1.1

Direct Effects

While it is often argued that the main sources of satisfaction come from outside work (for example, Lane, 2000), it remains the case that work is one of, and perhaps the, central focuses of most people’s lives (for example, Seeman and Anderson, 1983). The workplace is certainly one in which labor market participants spend a large portion of their waking lives. To the extent that the work experience is an agreeable one, people surely ought to be more satisfied over all. Empirical evidence confirms that intuition: job satisfaction is one of the most important determinants of overall life satisfaction (for example, Argyle, 2001; see Sousa-Poza, 2000 for a discussion). Belonging to a labor union may tend, in turn, to increase job satisfaction (for example, Pfeffer and Davis-Blake, 1990).1 The mechanisms are many, but the core relationships are clear enough: job security, and a good work environment, nurture satisfaction with one’s job (for example, Sousa-Poza, 2000). Unions, of course, tend to increase the production of those goods. Through collective bargaining the way in which the workplace is organized and governed is negotiated, with results that are more likely to be consistent with the preferences of workers. Job security is similarly increased through contracts that provide protection from arbitrary dismissal. Members may also feel empowered by the existence of grievance procedures that give one the ability to appeal decisions made by employers. In all of these ways labor unions facilitate the creation of a workplace that functions through ‘due process’, with felicitous consequences (see Sutton, 1990). If unions contribute to job satisfaction, and if job satisfaction contributes to life satisfaction, then union members should demonstrate higher life satisfaction.

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A closely related argument relates to the fact that unions may help reduce alienation by giving individuals a collective say in how the enterprise at which they work is managed. Individuals who are less alienated are in turn likely to be more satisfied with their jobs and, thus, their lives. Alienating work imposes psychological costs on individuals that contribute to depression (for example, Erikson, 1986), job dissatisfaction (for a review, see Greenberg and Grunberg, 1995) and a general decline in life satisfaction (Loscocco and Spitze, 1990). Similarly, it is widely agreed that autonomy on the job is vital for well-being. As Kohn et al. (1990, p. 964) put it, ‘occupational self-direction . . . affects values, orientations, and cognitive functioning’ in exactly the way one would imagine: those who lack self-direction are more prone to psychological ‘distress’ (for example, anxiety, lack of self-confidence). To be sure, alienation and especially autonomy are largely determined by occupation, but there are reasons to expect those represented by unions to evidence these pathologies to a lesser degree for any given type of occupation. While the union workplace may, of course, actually reduce autonomy in the abstract (given that union rules are indeed more rules that must be adhered to), unions are also contextually more supportive of selfdetermination in two respects. First, they establish a degree of autonomy for their members though collective bargaining at a level that is almost by definition higher than in non-union workplaces. Workers thus rightly interpret autonomy as something collectively achieved, that is, as a benefit of organization (for example, Edwards, 1979). Further, as Fenwick and Olson (1986) observe, the experience of union membership fosters cognitive changes that encourage exactly the workplace participation that unionization allows, which may in turn foster more self-direction. To the extent that unions lessen alienation, then, we should again see a positive relationship between membership and well-being, net of other factors. Unions may also contribute to well-being through their effect on another variant of connectedness. A large literature in social psychology has demonstrated that individuals are afforded some protection against the deleterious consequences of stress, and especially job related stress, through social support networks (Cohen and Wills, 1985). Work, even enjoyable work, can be a major source of stress, particularly when performance affects one’s livelihood. While support from all quarters is surely helpful, evidence suggests that buffering is most effective when the source of support is from the same domain as the source of stress. Work-related stress, then, is best buffered by having sources of emotional support at work (for example, Jackson, 1992). Common sense would suggest that unions may facilitate such support, in that they help build not only connections, but a sense of solidarity among coworkers. Indeed, Uehara

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(1990) goes so far as to specify ‘solidarity’ as a critical agent in effective social support networks. By nurturing solidarity, unions may thus provide an ideal context in which to find the type of social support that helps insulate against work-related stress. There are few rigorous empirical studies of the general role of unions, social connection and stress, but the extant literature does offer some evidence suggesting that unions facilitate both general social support (for example, Lowe and Horthcott, 1988) and protection against job-related stress per se (for example, Brenner, 1987). The evidence in regard to the effect of job stress on life satisfaction is clearer still. Loscocco and Spitze (1990) demonstrate that precisely the negative consequences for satisfaction that one would expect do in fact obtain. Unions may thus again contribute to higher quality of life among their members.2 The arguments above bring us to social capital (for example, Putnam, 1993, 2000). At its core, ‘social capital refers to connections among individuals – social networks and the norms of reciprocity and trustworthiness that arise from them’ (Putnam, 2000, p. 19). Generalizing slightly, the implicit idea at its most simple is that social networks facilitate positive psychological and cognitive changes in individuals that not only are politically desirable but which are conducive to greater personal well-being (Putnam, 2000, pp. 333–4). The literature, indeed, is unanimous in suggesting that social connectedness fosters greater subjective well-being. This argument is made most persuasively by Robert Lane (1978, 2000), who places the blame for declining levels of subjective well-being in the USA and Western Europe on a growing ‘famine’ of ‘interpersonal relationships’ (Lane, 2000, p. 9). A variety of other studies have documented the importance of social connection (for example, Myers and Diener, 1995; Veenhoven, 1996). That unions as organizations facilitate the building of social networks requires no elaboration. That they are likely as fraternal organizations to foster norms of reciprocity and solidarity is equally clear. We have already noted the positive effect of union membership on social connections in the workplace. We thus have reasons to hypothesize further that union members, given that they tend to enjoy their jobs more and to suffer from less work-related stress, to say nothing of having more social connections (and indeed more social capital), are likely to be better able to build and maintain intimate and rewarding relationships. Labor organization can thus affect the quantity and quality of personal connections between human beings, which in turn surely contribute to subjective well-being (for example, Lane, 2000). To the extent that social capital and social connectedness contribute to a better quality of life, we consequently return again to the hypothesis that labor organization promotes well-being.

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Societal Effects

The social level of unionization should also contribute to people in general, rather than just union members, enjoying better lives. There are two mechanisms, neither of which require extensive elaboration. One is a simple contagion effect: if one’s own subjective well-being is to some extent determined by interactions with others, such that we are likely to be more satisfied ourselves the more we interact with other satisfied people, then people in states with a higher proportion of more satisfied than otherwise union members are likely to be more satisfied, on average, than those in states with fewer proportional union members. This effect will be most apparent in the intimate relationships discussed above, but the logic extends to all forms of social interaction. A more immediate argument relates to the political consequences of having a strong labor movement. One of the best-documented relationships in social science is that between the strength of organized labor and the generous social democratic welfare states that union movements tend to ideologically favor (for insightful discussions, see Hicks, 1999; Huber and Stephens, 2001). This, of course, suggests that unions will contribute to satisfaction with life to the extent that the welfare state promotes subjective well-being.

13.2

ANALYSIS

To address the questions posed above requires survey data that meets two substantive criteria: it has enough cases to examine the effects of a state’s level of union density, and it includes an appropriate measure of satisfaction with life. The DDB Life Style Survey, the use of which in social science was popularized by Putnam (2000), meets those criteria. It contains a total of more than 40 000 respondents distributed over the 48 continental states, polled in yearly intervals from 1983 to 1998. It also contains a life satisfaction question which matches closely that used in the World Values Study, the Eurobarometer and other data sets conventionally used in the literature: ‘I am very satisfied with the way things are going in my life these days’ with the respondent offered six response categories representing increasing levels of agreement with the statement. We analyse these data in two ways. First, we simply take the satisfaction item noted above as our dependent variable, modeling it as a function of both individual- and state-level factors. Second, we analyse the mean value of life satisfaction for each state. In the first approach the unit of analysis is the individual; in the latter it is the state mean.3

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Our basic hypothesis is, of course, that life satisfaction should vary directly with the level of labor union density. Our principal independent variable is thus the percentage of the workforce organized, using the standard data collection maintained by Barry Hirsch and David Macpherson (2003).4 13.2.1

Individual-level Data

To separate the effects of unionization from other factors, we must first specify an appropriate set of control variables. We begin with the standard battery of demographic items identified by prior research (for example, Radcliff, 2001): respondent’s education, employment status, income and satisfaction with income, gender, dummies for African-Americans and those of other races (leaving non-Hispanic whites as the reference category), age and age-squared (to account for the curvilinear relationship between age and satisfaction), dummies for those widowed, divorced or married (leaving single as the reference category) and church attendance. We also add a measure of the respondent’s self-reported health given the strong correlation between such and subjective well-being (for example, Frey and Stutzer, 2002).5 The above variables account for the individual-level factors. We also include a set of controls for aggregate level conditions. To account for a state’s level of economic development, we include state per capita personal income. We also include three sociological variables that might reasonably be thought not only to affect perceived quality of life, but also be collinear with the political variables we discuss presently: the size of the state population (measured in thousands of persons), its level of urbanization (in 1990, as a percentage of population) and its racial diversity (using the ratio of minority to white population as suggested by Hero and Tolbert, 1996). Two other contextual factors identified earlier remain to be considered. One of these, social capital, lends itself to an easy and obvious operationalization: Putnam’s (2000) state-level ‘Comprehensive Social Capital Index’.6 It is a composite of 14 items including topics of trust, sociability, volunteerism, engagement in public affairs and community life; higher values indicate more social capital. The other, culture, is not so easily dispatched. While students of American politics are familiar with the idea of political culture (for example, Elazar, 1984), the cross-national literature on life satisfaction has focused on a much wider, sociological interpretation of culture. This strand of the literature is perhaps best exemplified by Inglehart (1990), who conceives of variation across nations in levels of satisfaction with life as reflecting accumulated national experiences, absorbed in pre-adult socialization, that form a ‘national character’. In this view culture becomes the national equivalent of a relatively fixed personality, affecting the overall level of

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satisfaction in a country in precisely the same way that human individuals have personalities (or ‘set-points’) that predispose them toward a given level of happiness. Thus, culture is typically controlled for in the obvious fashion: by fitting dummy variables for sets of nations thought to share similar cultures (for example, Latin America, Scandinavia).7 We adopt this approach by including dummies for each of the nine conventionally used regions of the USA, excepting a reference category.8 It should be noted that this approach is almost the most econometrically powerful method for isolating the variables of interest from unmodeled regional effects, whether attributable to culture or other factors. By fitting separate intercepts for each relatively homogenous region, we account for all long-term, structural conditions that may cause the level of satisfaction to vary geographically.9 Finally, we include the year to account for possible secular trends in satisfaction over time. This precaution is especially recommended in light of evidence that levels of subjective well-being have been declining in the industrial world and in the USA in particular (Lane, 2000). Estimation is done with Huber-White robust standard errors, correcting for the pooled structure of the data (that is, state-clustered). This procedure yields estimates that are robust to both between-state heteroscedasticity and within-state correlation (that is, robust to error terms being neither identically distributed nor independent). The dummy variables, as noted previously, further control for the pooled structure of the data. Having discussed operationalizations and models, we can now analyse the main empirical results. In the first column of Table 13.1 presents the basic estimates for the individual-level analysis. As is apparent, the density variable is positive and significant, suggesting, as predicted, that individuals are more satisfied with the quality of their lives as union density increases.10 To interpret the magnitude of the unionization effect, we compare the predicted change in satisfaction when moving from the lowest to the highest observed values of density in the sample. This suggests an expected increase of satisfaction of that equivalent to the effect of marriage, widely regarded as one of the most important and consistent correlates of happiness. Clearly, then, unionization has an impact on quality of life that is significant in substantive rather than merely statistical terms. We considered the possibility that the effect of unionization might vary with income, such that the more wealthy benefit less from unionization than others. This proves not to be the case, as the interaction term between the two variables is utterly lacking in statistical significance, as documented in the second column of Table 13.1. This result is important, in that it suggests that the positive effects of unionization on well-being apply to everyone in society, rich and poor alike.

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Table 13.1

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Individual-level analysis Base Results

Union Variables Density Density * Income

With Income Interaction

0.005*** (0.002) n/a

0.007*** (0.003) 0.000 (0.000)

0.078*** (0.002) 0.012** (0.006) −0.434*** (0.042) 0.076*** (0.014) −0.375*** (0.034) −0.040** (0.019) −0.056*** (0.003) 0.001*** (0.000) 0.043 (0.042) −0.136*** (0.041) 0.198*** (0.031) 0.043*** (0.003) 0.211*** (0.005)

0.083*** (0.005) 0.012** (0.006) −0.434*** (0.042) 0.075*** (0.14) −0.374*** (0.034) −0.040** (0.020) −0.056*** (0.003) 0.001*** (0.000) 0.043 (0.042) −0.136*** (0.041) 0.198*** (0.031) 0.043*** (0.031) 0.211*** (0.005)

−0.000 (0.000) −0.000** (0.000) −0.016*** (0.003) −0.086* (0.062) −0.127*** (0.023) −0.040** (0.018) −0.061** (0.028) 0.027 (0.033) −0.009 (0.039) 0.002 (0.027) 0.007 (0.045) 0.084 (0.114) 0.042* (0.026) −0.000 (0.001)

−0.000 (0.000) −0.000** (0.000) −0.016*** (0.003) −0.086* (0.062) −0.126*** (0.023) −0.040** (0.019) −0.061** (0.028) 0.026 (0.034) −0.009 (0.040) 0.001 (0.027) 0.006 (0.045) 0.088 (0.114) 0.042* (0.026) −0.000 (0.001)

Individual-level Factors Income Education Respondent unemployed Sex African-American Other non-white Age Age squared Widowed Divorced Married Church attendance Health of respondent State-level Variables State income State population Year New England Mid Atlantic East-North Central West-North Central South Atlantic East South-Central West South-Central Mountain Racial diversity Social capital Urbanization Constant Observations R-squared

35.403*** (5.323) 48440 0.1309

35.467** (5.324) 48440 0.1309

Note: Dependent variable is life satisfaction. Entries are unstandarized regression coefficients (state-clustered robust standard errors in parentheses). * significant at 0.10, **significant at 0.05 level, *** significant at 0.01 level.

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Table 13.2

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Aggregate analysis Results

Union density State population State income Racial diversity Social capital Urbanization New England Mid Atlantic East-North Central West-North Central South Atlantic East South-Central West South-Central Mountain Constant Observations R-squared

0.006** (0.003) −0.000 (0.000) −0.000 (0.000) 0.336** (0.142) 0.065*** (0.027) 0.001 (0.001) 0.084* (0.061) −0.103** (0.056) 0.014 (0.049) 0.004 (0.057) 0.042 (0.064) 0.013 (0.072) −0.033 (0.068) 0.043 (0.060) 3.869*** (0.117) 48 0.4957

Note: Dependent variable is mean Life Satisfaction by state. Entries are unstandardized regression coefficients (standard errors in parentheses). * significant at 0.10, **significant at 0.05 level, *** significant at 0.01 level.

13.2.2

Aggregate Analysis

Turning to the second estimation approach discussed earlier, we regress a state’s mean level of satisfaction on the aggregate level of the independent variables discussed above. As is apparent in Table 13.2, the results are very similar to those obtained before, with the union variable being significant and of the correct sign. The substantive implication is thus that the state’s average level of satisfaction varies directly with the degree to which the state’s labor force is unionized.11

13.3

DISCUSSION

The principal empirical conclusions emerging from the analysis may be summarized easily: life satisfaction varies directly with union density. This conclusion obtains when controlling for aggregate economic conditions and (through the regional dummy variables) other long-term, relatively fixed state-level characteristics which might plausibly be thought to play

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a role. In sum, labor organization, whatever other consequences it may produce, does contribute to quality of life. This conclusion would appear to be of some moment. It implies, most obviously, that the institution of the labor union is one with important felicitous social consequences. This point is especially important given that the organization of workers has ever been an ideologically contested practice in market economies. This political ambivalence afforded labor movements is mirrored in the academic treatment of labor organization within the social sciences. As is typically the case for other ideologically relevant – and thus truly important – social institutions, unionization has been a scholarly as well as a politically divisive concept. The vast empirical and theoretical research on labor organization in the social sciences has often (though by no means always) had a latent (and often no doubt unintended) tendency to provide an empirical answer to the ideological debate over unionization. While seldom expressed in so stark or explicit terms, it would be only a slight exaggeration to contend that economists, sociologists and political scientists have been involved in an implicit argument over the issue of whether unions are, in the end, good or bad. To be sure, the explicit focus of research has always been – and appropriately so – limited to ascertaining what the consequences of unionization were for particular, tangible phenomena, such as economic growth, unemployment, productivity, inflation, interest group activity, electoral participation, political sophistication or social stratification. These are, of course, all vitally important questions, and ones that this chapter in no way informs. Thus, while the analysis offered above tells us nothing about the possible impact of labor organization on, say, economic performance, it does imply that unions make a net positive contribution to quality of life. Thus, whatever deleterious or ambiguous consequences unions may well have for specific economic or social problems, they do appear to make a positive contribution to the degree that people find their lives rewarding. This hardly settles the ideological debate about the desirability of unionization, but it surely suggests at least one undeniably important dimension in which the consequences of organization are commendatory by any evaluative standard. The analysis also speaks more specifically to the literature on subjective well-being by highlighting a conspicuous oversight in the field: the failure to take seriously the importance of social class. While the effect of income on satisfaction has been extensively examined (for example, Schyns, 2002), no study has to our knowledge hitherto explicitly considered the fact that citizens in market economies are not merely characterized by more or less income: they are also differentiated by the position they hold in the class structure inherent in capitalism. For the vast majority of wage and salary

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workers, the quality of that position is in turn partially determined by whether they are members of a union that both represents their interests and, through its organizational characteristics, provides psychological and emotional support mechanisms. At the collective level, the state level of unionization has potentially profound effects on all market participants, rich and poor alike, for the reasons discussed previously. We know a great deal about all manner of social, cultural, demographic, economic and political factors that tend to influence life satisfaction across nations. The analysis offered here suggests not merely that we add labor organization to that list, but that we give more serious attention to the classanalytic perspective when theorizing about the determinants of subjective appraisal of life.

NOTES 1.

2.

An interesting paradox in the earlier literature arose from evidence suggesting that union members are more dissatisfied than non-members, but also that they are much less likely to quit than non-members (for example, Freeman and Medoff, 1984). This seeming contradiction was resolved by applying the ‘voice hypothesis’, such that unionization allows members to complain about their working conditions precisely because they are in a position to ameliorate them through collective action. Workers thus sought to improve their working conditions rather than ‘exit’ because they could – and, presumably, because they valued the job enough to try. There is also an endogenity problem that Pfeffer and Davis-Blake (1990) successfully account for. The issue is nicely expressed by Clark (1996, p. 202): ‘if unions address worker dissatisfaction, the more dissatisfied workers will be the most attracted by union membership’, so that union shops will emerge in those industries, and under those employers, that create the most initial dissatisfaction. When controlling for this effect, Pfeffer and Davis-Blake demonstrate that ‘unionization has a significant positive effect on [job] satisfaction’. Similar evidence is provided by Bender and Sloane (1998). Unions may also contribute to the well-being of their members, and perhaps to society at large, through their capacity (in varying degrees) as participatory institutions. It is often argued that participating in organizations such as unions tends to teach individuals cognitive and social skills. People learn how to communicate with each other, as well as to analyse and solve problems better. Evidence also suggests that belonging to an organization helps individuals understand their preferences and interests more clearly. The participatory or developmental strand of democratic theory encourages worker participation and involvement in decision making in the workplace because such participation is believed capable of creating better citizens – citizens who are more sophisticated, more knowledgeable, more tolerant and more civic minded (for example, Pateman, 1970). An extensive body of analysis generally supports the empirical veracity of this presumption (for a review, see Radcliff and Wingenbach, 2000). Thus, if participation in organizations contributes to human development, and if being a union member implies at least some degree of participation in the organization, then more union membership should mean more developed citizens. If we are willing to accept that more developed humans will tend to be more satisfied humans, then union membership should contribute to satisfaction in this way. Further, while they do not frame their argument in a developmental framework, Frey and Stutzer (2002) do demonstrate that institutional settings that foster greater democratic participation produce greater

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4. 5.

6. 7.

8.

9. 10.

11.

Happiness, economics and politics levels of subjective well-being. If so, then unions should similarly contribute, at least to the extent that they offer participatory opportunities. It would be ideal if the data contained a variable for individual-level union membership, but they do not. Hence, we are of necessity limited to focusing on union density only. While this is in fact the main theoretical variable of interest, it would ideally be preferable to have the individual-level indicator, so as to be able to separate the effects of an individual membership and density (Radcliff, 2001). The data come from their comprehensive collection at http://www.unionstats.com (accessed 2 May 2009), Income is measured in 15 categories in ascending order; education is the highest level of education completed in six categories with higher values representing higher attainment; employment status is a dummy coded 1 if the respondent is unemployed and ø otherwise; gender is coded 1 for females, 2 for males; church attendance is the frequency with which the respondent attends ‘a church or other place of worship’ in seven ascending categories; income satisfaction is from the survey question ascertaining the level of agreement with the statement: ‘Our family income is high enough to satisfy nearly all our important desires’; personal health is the survey item: ‘I am in very good physical condition’ with six response categories with higher values indicating greater agreement. The components making up this index are described in Putnam (2000, ch. 16) and taken from the ‘Bowling Alone’ website http://www.bowlingalone.com/data.php3 (accessed 15 January 2006). Others have sought to connect international differences in satisfaction with variation not in ideographic national cultures, but with particular cultural characteristics. By far the most successful of the latter is the effort to show that the fundamental dimension of importance is that between ‘individualistic’ as opposed to ‘collectivist’ a country is in its value orientations (for example, Diener et al., 1995; Radcliff, 2001; Schyns, 1998; Veenhoven, 1996, 1997). The basic distinction is between the prevalence of cultural norms that encourage citizens to define themselves as either essentially autonomous individuals or as members of nested superorindate groups (for example, family, religion, ethnicity, region, nation and so on). In collectivist cultures individual freedom is subordinated to the customs, practices and perhaps needs of the reference group, with consequently greater emphasis on conformity and obedience to authority, and thus less freedom for individuals to lead lives that maximize their own personal satisfaction. The amount of ‘collectivism’ of culture is surely not likely to show great variation across the American states. In any event, we are aware of no subnational measure of this concept, and presume it would, in any event, be adequately captured by the region dummies. The regions (using the standard Census Bureau classification) are New England, the Mid Atlantic, the East-North Central, the West North-Central, the South Atlantic, the East South-Central, the West South-Central, Mountain and Pacific. In the analysis that follows the Pacific (California, Oregon and Washington) is the excluded reference category. Note also that, as Hero and Tolbert (1996) discuss, their diversity measure may itself also be considered as a measure of political culture, to the extent that the concept is of interest in this context. Note that this result is unchanged when including as an additional control the per capita level of welfare spending in the given state, demonstrating thus that the effect of unionization is not an artifact of failing to consider the state’s effort at redistribution, which in turn should vary with the strength of the labor movement. We report the OLS results for the full model. As there are a fairly large number of independent variables, however, and as several of them are completely lacking in statistical significance, we re-estimated the results when omitting the variables with t-values less than unity in absolute values. The results are much as one would expect: the unionization variable remains about the same in magnitude but has its standard error substantially reduced. We also estimated both equations using robust standard errors to protect against any potential heteroscedasticity, but results are again unchanged.

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REFERENCES Argyle, Michael (2001), The Psychology of Happiness, 2nd edn, London: Methuen. Bender, Keith and Peter Sloane (1998), ‘Job satisfaction, trade unions, and exitvoice revisited’, Industrial and Labor Relations Review, 51 (2), 222–40. Brenner, M. Harvey (1987), ‘Relation of economic change to Swedish health and social well being’, Social Science and Medicine, 25,183–95. Cohen, Sheldon and Thomas Ashby Wills (1985), ‘Stress, social support, and the buffering hypothesis’, Psychological Bulletin, 98, 310–57. Clark, Andrew (1996), ‘Job satisfaction in Britain’, British Journal of Industrial Relations, 34, June, 189–217. Diener, Ed and Eunkook Suh (2000), ‘Measuring subjective well-being to compare the quality of life of cultures’, in Ed Diener and Eunkook Suh (eds), Culture and Subjective Well-being, Cambridge, MA: MIT Press, pp. 3–12. Diener, Ed, Marissa Diener and Carol Diener (1995), ‘Factors predicting the subjective well-being of nations’, Journal of Personality and Social Psychology, 69, May, 851–64. Edwards, Richard (1979), Contested Terrain, New York: Basic Books. Elazar, Daniel (1984), American Federalism: A View From the States, New York: Thomas Crowell. Erikson, Kai (1986), ‘On work and alienation’, American Sociological Review, 51 (1), 1–8. Fenwick, Rudy and Jon Olson (1986), ‘Support for worker participation’, American Sociological Review, 41 (4), 505–22. Freeman, Richard B. and James L. Medoff (1984), What Do Unions Do?, New York: Basic Books. Frey, Bruno S. and Alois Stutzer (2002), Happiness and Economics, Princeton, NJ: Princeton University Press. Greenberg, Edward and Leon Grunberg (1995), ‘Work alienation and problem alcohol behavior’, Journal of Health and Social Behavior, 36, March, 83–102. Hero, Rodney and Caroline J. Tolbert (1996), ‘A racial/ethnic diversity interpretation of politics and policy in the states of the U.S.’, American Journal of Political Science, 40 (3), 851–72. Hicks, Alexander (1999), Social Democracy and Welfare Capitalism, Ithaca, NY: Cornell University Press. Hirsch, Barry T. and David A. Macpherson (2003), ‘Union membership and coverage database from the current population survey: note’, Industrial and Labor Relations Review, 56 (2), January, 349–54. Huber, Evelyne and John D. Stephens (2001), Development and Crisis of the Welfare State: Parties and Policies in Global Markets, Chicago, IL: University of Chicago Press. Inglehart, Ronald (1990), Culture Shift in Advanced Industrial Society, Princeton, NJ: Princeton University Press. Jackson, Pamela (1992), ‘Specifying the buffering hypothesis: support, strain, and depression’, Social Psychology Quarterly, 55 (4), 363–78. Kohn, Melvin, Atsushi Naoi, Carrie Schoenbach, Carmi Schooler and Kazimierz M. Slomczynski (1990), ‘Position in the class structure and psychological functioning in the United States, Japan, and Poland’, American Journal of Sociology, 95 (4), 964–1008.

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Lane, Robert (1978), ‘Autonomy, felicity, futility’, Journal of Politics, 40, Winter, 1–24. Lane, Robert (2000), The Loss of Happiness in Market Democracies, New Haven, CT: Yale University Press. Loscocco, Karyn and Glenna Spitze (1990), ‘Working conditions, social support, and the well-being of female and male factory workers’, Journal of Health and Social Behavior, 31 (4), 313–27. Lowe, Graham S. and Herbert C. Horthcott (1988), ‘The impact of working conditions, social roles, and personal characteristics on gender differences in distress’, Work and Occupations, 15, 55–77. Myers, David and Ed Diener (1995), ‘Who is happy?’, Psychological Science, 6, January, 10–19. Patmen, Carole (1970), Participation and Democratic Theory, Cambridge: Cambridge University Press. Pfeffer, Jeffrey and Alison Davis-Blake (1990), ‘Unions and job satisfaction’, Work and Occupations, 17 (3), 259–84. Putnam, Robert (1993), Making Democracy Work, Princeton, NJ: Princeton University Press. Putnam, Robert (2000), Bowling Alone, New York: Simon & Schuster. Radcliff, Benjamin (2001), ‘Politics, markets, and life satisfaction’, American Political Science Review, 95 (4), 939–52. Radcliff, Benjamin (2005), ‘Class organization and subjective well-being: a crossnational analysis’, Social Forces, 84 (1), 513–30. Radcliff, Benjamin and Ed Wingenbach (2000), ‘Preference aggregation, functional pathologies, and participation: a social choice defense of participatory democracy’, Journal of Politics, 62, 977–98. Schyns, Peggy (1998), ‘Cross national differences in happiness’, Social Indicators Research, 43, February, 3–26. Schyns, Peggy (2002), ‘The wealth of nations, individual income and life satisfaction in 42 countries’, Social Indicators Research, 60, 5–40. Seeman, Melvin and Carolyn S. Anderson (1983), ‘Alienation and alcohol: the role of work, mastery, and community in drinking behavior’, American Sociological Review, 48 (1), 60–77. Sousa-Poza, Alfonso (2000), ‘Well-being at work’, Journal of Socio-Economics, 29 (6), 517–39. Sutton, John (1990), ‘Bureaucrats and entrepreneurs: institutional responses to deviant children in the United States’, American Journal of Sociology, 95 (6), 1367–400. Uehara, Edwina (1990), ‘Dual exchange theory, social networks, and informal social support’, American Journal of Sociology, 96 (3), 521–57. Veenhoven, Ruut (1996), ‘Developments in satisfaction research’, Social Indicators Research, 37, January, 1–46. Veenhoven, Ruut (1997), ‘Quality of life in individualistic society’, in Mart-Jan de Jong and Anton C. Zijderveld (eds), The Gift of Society, Nijker, the Netherlands: Enzo Press, pp. 149–70. Western, Bruce (1997), Between Class and Market, Princeton, NJ: Princeton University Press.

PART IV

What is to be done?

14.

Should national happiness be maximized? Bruno S. Frey and Alois Stutzer1

14.1

INTRODUCTION

Cross-disciplinary ‘happiness research’ has attracted great attention within the social sciences as well as in the general public. This is reflected in a massive increase of scholarly work on people’s subjective well-being and frequent featuring of happiness research in blogs, in the media, as well as in publications of think tanks.2 A case in point is the empirical study of happiness in economics. Within ten years many insights about the determinants of individual well-being were attained (for surveys, see Di Tella and MacCulloch, 2006; Frey, 2008; Frey and Stutzer, 2002a, b; Layard, 2005; van Praag and Ferrer-iCarbonell, 2004). Moreover, the separation of traditional decision utility from experienced utility as reflected in subjective well-being challenges the orthodoxy of the revealed preference approach in economics (Kahneman et al., 1997; Stutzer and Frey, 2007). Individuals’ ex post evaluation of their experiences now allows us to directly study problems of self-control and utility misprediction (Frey and Stutzer, 2008; Kahneman and Thaler, 2006; Stutzer, this volume). We plead guilty for being euphoric about the advances in happiness research. In addition to seeking to explain the determinants and consequences of happiness, a big effort has been made to derive implications for policy. We argue that it is tempting to apply happiness research in a technocratic way. This is best visible in the idea of maximizing aggregate happiness as a social welfare function. This is, however, a mistaken direction to go in. It neglects the insights from political economics and fails to reflect the rich insights from happiness research. The next section discusses the advances in measurement enabling empirical happiness research. Section 14.3 sketches how the idea of maximizing social welfare has been taken up in happiness research. The following two sections discuss two major sets of objections against this approach, the first based on classical welfare economics, the second based on happiness 301

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research itself. Section 14.6 deals with the fundamental objections from political economy to happiness maximization. The problem of incentive distortions induced by the happiness maximization approach is discussed in Section 14.7. An alternative approach to use the insights of happiness research for policy is developed in Section 14.8, and Section 14.9 concludes.

14.2

HAPPINESS CAN BE USEFULLY MEASURED

Many social scientists, and in particular economists, have traditionally been most skeptical about direct measures of individual well-being or utility. They are taken to be private experiences felt in many different ways that can neither be summed up, expressed on a scale, nor be compared between individuals. Economic analysis therefore derives utility indirectly by looking at revealed behavior rather than at direct statements by the individuals of their state of utility. The situation has recently changed dramatically. Great advances have been made in measuring happiness (see also Veenhoven, this volume). There is now a widespread consensus among scholars dealing with these issues that experienced utility and individual welfare can be measured with some accuracy (for example, Diener, 2005; Kahneman and Krueger, 2006; Kahneman et al., 1999). One indicator that such measurements credibly capture important aspects of well-being is shown by the fact that they correlate with behavior and aspects generally associated with happiness. Reliability studies have found that reported subjective well-being is moderately stable and sensitive to changing life circumstances (for example, Ehrhardt et al., 2000; Schimmack and Oishi, 2005). Consistency tests reveal that happy people are more often smiling during social interactions (Fernández-Dols and Ruiz-Belda, 1995), are rated as happy by friends and family members (for example, Lepper, 1998; Sandvik et al., 1993), as well as by spouses (Costa and McCrae, 1988), express more frequent expressions of positive emotions, are more optimistic, are more sociable and extrovert, and enjoy better sleep (Frey and Stutzer, 2002a, p. 33). Happy persons are also less likely to commit suicide (Helliwell, 2007; Koivumaa Honkanen et al., 2001). There is no single, overriding concept that motivates all individual behavior and registers all experiences, feelings and judgments; the following conceptions of individual well-being can be distinguished (Diener, 2005): ●

Subjective well-being referring to different types of positive and negative evaluations made by people regarding their lives.

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Positive and negative affect denoting pleasant and unpleasant moods and emotions, respectively, such as joy and sadness. Happiness has been used in many different meanings. It often refers to the balance between short-term positive and negative emotions. Life satisfaction refers to how an individual evaluates their life taken as a whole and is a broad, reflective appraisal the person makes of their life. Quality of life designates the degree to which a person’s life is desirable rather than undesirable, and is often connected to external components such as the natural environment. It is often expressed as ‘objective’ in contrast to subjective well-being.

In our analysis we do not in general distinguish between these concepts but simply use the term ‘happiness’. Distinctions between the various concepts are only made when it comes to particular measurements and when it is alluded to empirical studies. There are five prominent measures of individual well-being. 14.2.1

Asking People: Global Evaluations of Individual Life Satisfaction

This approach seeks to capture happiness by asking a representative sample of individuals about their overall satisfaction with the life they lead. A prominent example of a single-item question on a three-point scale is in the General Social Surveys (Davis et al., 2001). It asks the question: ‘Taken all together, how would you say things are these days – would you say that you are very happy, pretty happy, or not too happy?’ Life satisfaction is assessed on a scale from 1 (dissatisfied) to 10 (satisfied) in the World Values Surveys (Inglehart et al., 2000). People answer the question: ‘All things considered, how satisfied are you with your life as a whole these days?’ The Eurobarometer Surveys, covering all members of the European Union, ask a similar question: ‘On the whole, are you very satisfied, fairly satisfied, not very satisfied, or not at all satisfied with the life you lead?’ Among the multiple-item approaches, the most prominent is the ‘Satisfaction with life scale’ (Diener et al., 1985), composed of five questions, rated on a scale from 1 to 7 (see the survey about various measures of subjective well-being by Andrews and Robinson, 1991). Despite the favorable evaluation of direct measures of individual wellbeing, as subjective survey data are based on individuals’ judgments, they are prone to many biases. Reported subjective well-being is, for example, expected to depend on the order of questions, the wording of question, scales applied, actual mood and the selection of information processed (Schwarz and Strack, 1999). The relevance of these errors, however,

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depends on the intended usage of the data. Often, the main use of happiness measures is not to compare levels in an absolute sense between single individuals. Research rather seeks to identify the determinants of happiness. For that purpose, it is often neither necessary to assume that reported subjective well-being is cardinally measurable nor that it is interpersonally comparable. Almost all of the empirical work so far undertaken in happiness research in economics has been based on representative, large-scale sampling of individuals’ global evaluations of their life satisfaction. The great advantage of this measurement approach is its good performance compared to its cost, as well as its availability for a large number of countries and periods. Thus, for example, the surveys on life satisfaction contained in the World Values Surveys today cover 80 countries representing over 80 percent of the world’s population over four periods. 14.2.2

Experience Sampling Method

This approach collects information on individuals’ experiences in real time in their natural environments (Csikszentmihalyi and Hunter, 2003; Scollon et al., 2003). A representative selection of individuals are supplied with a beeper or a hand held computer asking them at random instances of time to immediately answer a battery of questions with regard to momentary positive and negative affects in that particular moment. Respondents are also asked to state the intensity of their feelings. This electronic diary seeks to practically apply Edgeworth’s (1881) old idea of capturing utility by a ‘hedonimeter’ capturing immediate experience. Happiness can then be calculated by the aggregation of these instantaneous statements of affect. This method has so far not been applied on any large scale. It is more costly than representative surveys of global evaluations of life satisfaction. 14.2.3

Day Reconstruction Method

The Day Reconstruction Method of measuring happiness is a special variant of experience sampling (Kahneman et al., 2004a). Respondents are asked to reconstruct the previous day by filling out a structured questionnaire. The respondents first recall the activities undertaken the previous day into working memory by producing a sequence of episodes. They then describe each episode in detail by identifying when, what, where and with whom the episode took place. The respondents then rate these episodes in terms of positive affect (happy, warm/friendly, enjoying myself) or negative affect (frustrated/annoyed, depressed/blue, hassled/pushed

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around, angry/hostile, worried/anxious, criticized/put down). Moreover, the feeling of being competent, impatient for the episode to end or tired is also asked. The Day Reconstruction Method allows more refined measures of happiness than is the case with representative surveys confined to one question. By carefully splitting up the past day into episodes, the respondents are induced to think carefully about how they felt during each time period. They are less prone to distortions of memory known to be especially severe in the recall of affect (Robinson and Clore, 2002). However, the weighing of episodes that matter for people’s overall evaluation of their life is determined by the researcher according to some aggregation rules and not by the subjects themselves. The Day Reconstruction Method is new and has so far been empirically used only on an experimental basis. It must be left to the future to what extent, and for which specific issues, happiness researchers will rely on this measurement approach. It is moreover open to what extent individuals are able and willing to correctly remember the emotions in past episodes (though they are quite recent). 14.2.4

The U-Index

In the measures so far discussed there is no guarantee that the scales used map the corresponding feelings into numbers representing cardinal values that can be compared across people. The question is whether the answer of ‘very satisfied’ is really worth twice the value of the answer ‘not satisfied’. Kahneman and Krueger (2006) propose the U-Index (for ‘unpleasant’) based on the Day Reconstruction Method to avoid this cardinality concern. The U-Index is defined as the fraction of time per day that an individual spends in an unpleasant state. An episode is unpleasant if the most intense feeling the individual experiences in that episode is a negative one. The U-Index relies on the observation that the dominant emotional state of most of the people during most of the time is positive. Hence any episode when a negative feeling occurs is a significant occurrence. It is thus assumed that a dominant negative emotion colors an entire episode. Obviously, this is a special assumption focusing on a particular, unpleasant state of mind while positive experiences are disregarded. 14.2.5

Brain Imaging

A quite different measuring approach to approximate utility in a quantitative way consists in scanning individuals’ brain activities. It relies on functional magnetic resonance imaging (fMRI) which tracks blood flow

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in the brain using changes in magnetic properties due to blood oxygenation (on neuroeconomics, see Camerer et al., 2005; Fehr et al., 2005; Zak, 2004). Happy persons reveal a characteristic pattern of electrocortical activity. They exhibit greater activity in the left than in the right prefrontal cortex (Davidson, 2003; Pugno, 2004). This prefrontal cortical asymmetry between more or less happy people further correlates behavioral activation (rather than inhibition), and even with antibody response to influenza vaccine (Urry et al., 2004). It is important to note, however, that the quality of physiological measures depends on the quality of self-reported measures of well-being with which they were originally calibrated. For many tasks self-reported measures of life satisfaction have proved to perform in a satisfactory way especially for the issues economists are mostly interested in. It is so far the best empirical approximation available to the concept of individual welfare used in economic theory. The measurement of happiness has proved to yield useful insights to better understand the economy and society. On the macro level it is increasingly accepted as a complement to the long-established measures of national income, thus following the lead of the social indicators approach and of the capabilities approach.3 The UK and Australia as well as some other countries are committed to producing national measures of wellbeing, and already back in the 1970s the Kingdom of Bhutan proclaimed that it wants to maximize Gross National Happiness rather than Gross National Income (Ura and Galay, 2004). On the scientific side, a group of 50 well-known scholars promotes the idea of ‘National indicators of subjective well-being and ill-being’ (Diener, 2005). We also signed the guidelines because we find it important that measures of subjective wellbeing are further introduced and improved to get a better understanding of individual welfare. At the micro level the measurement of happiness allows us a more direct welfare analysis than in standard welfare economics, and therefore is a useful complement. The exclusive reliance on revealed preference in micro-economic theory4 is valid only if individuals act in a fully rational way. But in reality people often make inconsistent choices: they fail to learn from experience or do so incorrectly, refuse to engage in beneficial trades, compare themselves to others, have insufficient self-control, mispredict future utilities of consumption and depart in many other ways from the model of the rational economic agent (for example, Rabin, 1998). To the extent that these effects occur, individual choices do not reflect true or normative preferences (Beshears et al., 2008), and expanding people’s opportunities will not necessarily increase their utility (for an application to TV viewing, see Benesch et al., 2006). This may lead to fundamental changes in evaluations, an example being Kahneman and Thaler’s (2006,

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p. 231) statement that ‘It is certainly possible that American workers would be happier with more vacation and less pay.’

14.3

MAXIMIZING AGGREGATE HAPPINESS

To focus on aggregate happiness rather than Gross National Product (GNP) (or another measure of economic activity) as an indicator of social welfare has several important advantages. As the limits of the traditional indicators are well documented (see, for example, Frey and Stutzer, 2002a, ch. 2), it suffices to briefly list them and put them in comparison with measures of happiness. 1.

Measures of happiness include non-material aspects of human wellbeing such as the influence of social relations, autonomy and selfdetermination. These are excluded, or most insufficiently included, in the traditional national accounts and therewith in GNP. One of the major challenges of happiness research is indeed to explain the ‘Easterlin Paradox’ (Easterlin, 1974, 1995, 2001) showing that in many countries real per capita income has dramatically increased but happiness has more or less stayed constant (see recently, for example, Di Tella and MacCulloch, 2008). They go well beyond existing extensions of GNP such as the ‘Measure of Economic Welfare’ (Nordhaus and Tobin, 1972), ‘Economic Aspects of Welfare’ (Zolatas, 1981), ‘Index of Sustainable Economic Welfare’ (Daly and Cobb, 1989) or ‘Human Development Index’ (United Nations Development Programme, 2005). These indicators exhibit a strongly different development over time than happiness indicators (see, for example, Blanchflower and Oswald, 2005).5 2. Measures of happiness consider outcome aspects of components already included in GNP via input measures. This holds in particular with respect to the vast area of government activity (measured in GNP by the costs of material and of labor). It is also directly relevant for (public) health and educational expenditures. ‘Social indicators’ (for example, the ‘Index of Social Progress’ by Estes (1988)) mostly measure the input side such as the number of hospital beds and of doctors, or of classrooms and teachers. 3. Measures of happiness look at subjectively evaluated outcomes in line with the basic methodological approach of economics. In contrast, the capabilities approach and the ‘Human Development Index’ by the United Nations look at objectively observable functionings (Nussbaum, 1999, 2000; Sen, 1985, 1992, 1999).

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The question arises whether for these reasons the maximization of (measured) happiness as a proxy for social welfare is a worthwhile approach to pursue. To maximize social welfare as the ultimate goal of economic policy is an old dream in economics dating back to Bentham (1789) and later Edgeworth (1881), and introduced into contemporary economics by Tinbergen (1956) and Theil (1964). This dream is closely associated with the effort of turning economics into a natural science comparable to physics. Consistent with this view, Edgeworth called his book Mathematical Psychics (1881). A major problem of this approach was that the social welfare function to be maximized could not be empirically measured. Di Tella et al. (2001) refer to this issue in the opening statement to their paper: Modern macroeconomics textbooks rest upon the assumption of a social welfare function defined on inflation, π, and unemployment, U. However, no formal evidence for the existence of such a function has been presented in the literature. Although an optimal policy rule cannot be chosen unless the parameters of the presumed W(π, U) function are known, that has not prevented its use in a large theoretical literature in macroeconomics. (p. 335)

The advent of happiness research has dramatically changed this situation: aggregates of existing measures of subjective well-being can be used as an approximations to a social welfare function. The proposal of National Well-Being Accounts by Kahneman et al. (2004b) seems indeed to reflect this spirit when they write: The goal of public policy is not to maximize measured GDP, so a better measure of well-being could help to inform policy. Here we propose measuring national well-being by weighting the time allocated to various activities by the subjective experiences associated with those activities. (p. 433)

The vision of aggregate happiness as a guideline for policy is also expressed by Layard in his well-received book on Happiness (2005): [. . .], there are many major choices where rules provide little guidance. There are public choices like how to treat criminals, or how to solve traffic problems. Simple appeals to principles of freedom or loving-kindness will help little here. [. . .] The answer can only be found from overarching objectives of maximising human happiness. (p. 124)

The development made possible by happiness measures has several attractive properties. First, it enables to derive optimal policies in a numerical way, increasing the usefulness of evaluation exercises for government policy. Second, in contrast to postulating a social welfare function at the

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aggregate level based on a wide range of different outcome variables, the well-being figures provided by happiness research offer an overall evaluation based on individuals’ judgments. Third, a measure of social welfare based on happiness data is democratic in the sense of attributing equal weight to every person. In contrast, the prices relevant for assessing the value of goods entering GNP are strongly determined by the preferences of people with high purchasing power. The preferences of individuals without income to spend are disregarded. Despite these developments working to the advantage of the idea of social welfare maximization, we argue in the following sections that this approach should be rejected for a number of important reasons. Thereby, we do not simply retreat to the traditional welfare-theoretic objections against aggregate welfare maximization that we present in the next section.

14.4

WELFARE ECONOMIC OBJECTIONS AGAINST SOCIAL WELFARE MAXIMIZATION

Classical welfare economics, initially due to, and strongly influenced by, Robbins (1932) and Hicks and Allen (1934), has for a long time raised fundamental arguments against using the concept of aggregate social welfare in contrast to individual welfare. The two most important, and partially interconnected (see Sen, 1970) objections to the concept of aggregate social welfare are, first, the impossibility of cardinal measurement and interpersonal comparisons, and, second, the impossibility theorem. Since Arrow (1951) it has been widely accepted that under a number of ‘reasonable’ conditions, no social welfare function exists that generally ranks individual orderings of outcomes consistently, except a dictatorship. This impossibility result spawned a huge amount of literature (called ‘social choice’), analysing its robustness to modifications of the assumptions. Theorem after theorem demonstrated that almost all changes in the axiomatic structure left the dictatorial result unchanged (see, for example, Sen, 1970, 1995; Slesnick, 1998). It has been concluded that ‘there is no way we can use empirical observations on their own to produce an ethically satisfactory cardinalization, let alone an ethically satisfactory social welfare ordering’ (Hammond, 1991, pp. 220–1). Does this verdict apply to happiness functions in their capacity as social welfare functions? The answer depends on whether one thinks that the premises of classical welfare economics still hold. The ordinalist revolution in economics on which classical microeconomics is firmly based takes it for granted that individual welfare can only be measured in an ordinal, but not in a cardinal way, and that it makes

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no sense to make interpersonal comparisons of utility. These are exactly the fundamental assumptions where the counter revolution of happiness research sets in. If the accumulated evidence (partly mentioned above) is judged sufficient in the sense that it allows to cardinally measure and interpersonally compare happiness, then a, or in fact many, social welfare functions exist. An appealing social welfare function probably is the unweighted sum of individual cardinal welfares or happiness. However, given that people have preferences over the distribution of happiness scores in a society, no consistent social welfare ordering can be derived. We do not take a position here. We think, however, that both cardinality and interpersonal comparability may be less of a problem on a practical level than on a theoretical level.6 Moreover, for many applications milder assumptions are sufficient. An important example is the valuation of public goods and public bads based on the life satisfaction approach (see, for example, Frey et al., 2009). Scores of life satisfaction are reported on an ordinal scale. Using adequate statistical techniques like ordered probit or ordered logit, the ordinal information is, however, sufficient to calculate a compensating surplus. Moreover, interpersonal comparability at the level of the single individual is not a necessary condition for valuing public goods in the life satisfaction approach. It is sufficient if individual specific response frames do not systematically vary between different groups exposed to different levels of the public good either across space or over time. It may be concluded that while the objections from classical welfare economics must be taken seriously, the existing state of research suggests that, for many purposes, happiness or reported subjective well-being is a satisfactory empirical approximation to individual welfare. However, the limits remain of setting up a consistent measure of aggregate social welfare.

14.5

OBJECTIONS FROM HAPPINESS RESEARCH AGAINST SOCIAL WELFARE MAXIMIZATION

In happiness research two phenomena are studied that put the maximization of aggregate happiness into question as an objective of public policy. The first phenomenon that gives rise to reservations has to do with one of the most central findings of happiness research: many changes of life circumstances have only a short-lived effect on reported subjective wellbeing because people adapt (Frederick and Loewenstein, 1999). Extreme and well-known examples are paraplegics who after a time of hardship in the long run report themselves to be only a little less happy than before, and lottery winners who after a short period of elation report themselves

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not to be much happier than before (Brickman et al., 1978). A more recent study based on longitudinal data finds that average life satisfaction drops when being subjected to a moderate disability but almost fully recovers to the pre-disability level after two years. In the case of a severe disability the recovery, however, is incomplete (Oswald and Powdthavee, 2008). More on the bright side, the period leading up to marriage significantly raises average happiness but over the course of marriage the happiness level turns back to only little above the pre-marriage level (Stutzer and Frey, 2006). The second, closely related phenomenon is the change of people’s aspirations due to changes in their life circumstances. In the context of economics, the most important finding is that people quite rapidly adjust to increases in their income: after about one year two-thirds or more of the benefits of an increase in income wear off as people increase their income aspirations (Stutzer, 2004; van Praag and Ferrer-i-Carbonell, 2004). This process has become known as the aspiration treadmill and has been used to explain the Easterlin Paradox mentioned above. Hedonic adaptation and the aspiration treadmill are not problematic as such for the measurement of individual welfare. However, they have great consequences for social welfare maximization depending on how they are treated. Imagine courts have to decide about compensation for losses suffered in a car accident. For the same physical harm, shall they award lower damages to people with a strong capacity to adapt and higher damages to others? Or in the area of government taxation, what costs of taxation shall be taken into account? Materialists with high income aspirations suffer a great deal from personal income taxes. Shall they be exempted from tax and government services financed by people who can easily arrange with whatever material living standard they experience? What matters in our context is that the way to deal with hedonic adaptation and the aspiration treadmill are not part of social welfare maximization but must be decided on a more fundamental level. Thus one needs a social decision-making mechanism to indicate how adaptation and aspiration effects have to be dealt with in public policy. Obviously such decisions have grave consequences for economic policy to which the social welfare maximization approach does not contribute anything.

14.6

OBJECTIONS FROM POLITICAL ECONOMICS TO THE MAXIMIZATION OF AGGREGATE HAPPINESS

The social welfare maximization approach disregards, and tries to substitute for, existing political institutions and processes. This is the ‘benevolent

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dictator’ view castigated in constitutional political economy and which need not be repeated here.7 The essential message is that in a democracy there are constitutionally designed rules and institutions allowing citizens to reveal their preferences, and to provide politicians (the government) with an incentive to put them into reality. The maximization of a social welfare function as such is an intellectual exercise. Even if the government were to take notice it has no incentive to follow it. These relationships can be formulated more precisely. The social welfare or happiness function H is H 5 H (X, Z), where X and Z are the determinants of happiness as determined in empirically estimated happiness functions. X are those factors which can be influenced by the government, and Z are exogenous determinants, among them demographic factors such as age, or genetic influences. A government does not maximize this aggregate social welfare or happiness function H. Rather, in a democracy politicians have to take into account the preferences of its citizens as revealed in vote outcomes.8 The vote function reflects the influence of the happiness of the voters, H, the factors the government can influence, X, and exogenous factors, Y, beyond the government’s influence: V 5 V (H, X, Y). The government politicians seek to maximize an objective function G by optimally choosing X. In so far as they are benevolent, it is composed of what they believe to make the population (or at least the voters) happy, H, the private benefits of politicians in power, P (gained by rent seeking), and the ideological goals, I, of the politicians’ party or coalition in power: G 5 G (H, P, I). This objective function is maximized subject to the normal resource constraints and subject to the re-election constraint V ≥ V9, where V9 is determined by the political system (it differs, for example, between a majoritarian and a proportional voting system). Two states can be distinguished:

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When the re-election constraint is non-binding, the government maximizes its own goal function, G. When the re-election constraint is binding, the government maximizes votes, V.

Against the (implicit) presumption of the social welfare maximization approach the government does not generally maximize the happiness, H, in the population (or at least of voters); it does so only under very restrictive conditions. Government maximizes votes only when its re-election chance is low, and when the determinants of votes, V, are the same as those of happiness, H. In general, the factors, X, under the control of government have a different impact on votes, V, than on happiness, H. In some instances the voters do not make the government responsible for some impacts of X (that is, dV/dX 5 0) though it influences happiness, H, and the reverse. When the government’s re-election chance looks good, the government maximizes G whereby ideological factors enter government behavior; they do not necessarily raise happiness, H, but often cater for special groups in the population in order to reap private benefits, P. The social welfare maximizing approach based on empirically estimated happiness functions thus disregards the institutions on which democracy is based. Citizens are reduced to ‘metric stations’. The interaction between citizens and politicians, the interest representation by organized groups and the concomitant information and learning processes are disregarded.

14.7

INDUCED INCENTIVE DISTORTIONS

So far it has been assumed that the decision to maximize social welfare in terms of aggregate (measured) happiness does not have any influence on the measurement of subjective well-being. This assumption is most doubtful. Indeed, the political use of aggregate happiness will certainly induce strategic interactions between the government and the individuals. Two kinds of distortions are to be taken into account. Once aggregate happiness has become politically relevant the government, public bureaucracy and interest groups have an incentive to manipulate it. This has proved to be true for GNP and other economic indicators declared to be goals of government activity. As the rate of unemployment has become a politically important indicator, governments have started to influence it in order to suggest a better picture of the state of the labor market than is true in reality. Thus, for instance, persons long unemployed are defined to no longer belong to the workforce and therewith no longer raise

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the official rate of unemployment. It is also well known that the measure of budget deficit has been strongly manipulated by some European countries when the rules for entering the European Monetary Union required budget deficits not to exceed 3 percent of GDP and the public debt not to exceed 60 percent of GDP. Many European Union member countries (most notably Greece and Italy) resorted to accounting tricks or ‘creative accounting’9 in order to meet these requirements though in reality they clearly violated them (see, for example, Forte, 2001; von Hagen and Wolff, 2004). Such distortions of indicators were so widespread that observers stated that ‘the determining factor for achieving membership of the planned European Monetary Union (EMU) seems to rely on widespread use of public-sector creative accounting measures’ (Dafflon and Rossi, 1999, pp. 59–60). In the (rare) case in which a government is unable to manipulate a particular indicator to its benefit, it has an incentive to create new indicators. This is easily possible in the case of happiness. As has been pointed out in Section 14.2, a variety of indicators may capture individual well-being. Governments and pressure groups will choose those most beneficial to their respective interests or will even create new ones suiting them well. The second systematic distortion stems from the incentive of respondents to misrepresent their well-being. When individuals become aware that the happiness level they report influences the behavior of political actors, they have an incentive to misrepresent it. They try to ‘play the system’. The two systematic distortions discussed represent a basic phenomenon even applying in the natural sciences. The Heisenberg Uncertainty Principle states that the observation of a system fundamentally disturbs it. In the social sciences both the observation and the public reporting can change the behavior observed of the persons involved. This reaction is known in macro-economics as Goodhart’s Law and the Lucas Critique (see Chrystal and Mizen, 2003). Goodhart’s Law (1975) states that any observed statistical relationship – such as the happiness function – will tend to collapse once pressure is placed upon it for control purposes. The Lucas Critique (1976) refers more specifically to econometric modeling: different policy-making behavior influences the expectations of private agents and this changes behavior in a rational-expectations model.

14.8

AN ALTERNATIVE VISION OF HOW TO USE HAPPINESS RESEARCH FOR POLICY

Our discussion has endeavored to show that the maximization of aggregate happiness as a social welfare function is a doubtful approach for several reasons:

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● ●

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Governments are not composed of purely benevolent politicians wanting to make the population as happy as possible. Rather, the personal interests of politicians also matter. The essential elements of democratic governance are disregarded: democracy does not simply consist in recording the reported wellbeing of the citizens. The government has an incentive to manipulate the happiness indicators and to create new ones suiting their goals. The individuals have an incentive to misrepresent their happiness levels strategically in order to influence government policy in their favor.

Some might also argue that problems of cardinality and interpersonal comparability can never be fully overcome. These arguments do, of course, not mean that the maximization of GNP would be preferable to maximizing aggregate happiness (however conceived). Rather, we argue that happiness research shall not aim at constructing a social welfare function at all but that the insights provided by happiness research should be used in a different way. Our vision rests on the fundamental presumption that the quality of the political process is key to people’s happiness and that the legitimacy of political action finally rests on the voluntary agreements of the citizens involved. Individuals’ sovereignty should not be reduced to self-reports of one’s well-being. It should also include the choice how to best pursue one’s happiness privately and collectively. The claim is not for ‘naive’ consumer or citizen sovereignty in the sense that behavior is always optimal. People are taken with their bounded rationality and bounded willpower sometimes aware of their own limitations and sometimes only of those of their fellow citizens. Accordingly, the political process should be institutionally structured so that people’s common interests become the principal controlling force. Economic policy must help to establish those fundamental institutions which make politicians and pubic bureaucrats most responsive to people’s common interests and which finally lead to the best possible fulfillment of individual preferences. Thereby happiness (in its various forms) might not be people’s ultimate goal. Other goals may, for instance, be loyalty, responsibility, self-esteem, freedom or personal development. Research in constitutional economics helps us to identify which institutions serve the goal of preference fulfillment. Thereby happiness research provides insights about how and to what extent institutions have systematic effects on indicators of individual well-being. The focus is thus on institutions rather than specific policy interventions. To give an example,

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the focus ought rather be on the relationship between the fiscal constitution of a jurisdiction and people’s subjective well-being than on the optimal tax scheme in terms of happiness. The range of institutions under study includes self-binding mechanisms, social norms, private and public law (that is, the rules of the game) as well as constitutional conditions on how to choose rules. The results gained from happiness research should be taken as inputs into the political process. These inputs have to prove themselves in political competition and in the discourse among citizens, and between citizens and politicians. This vision differs basically from an approach performing the maximization of a social welfare function. The arguments raised should not be understood as a pleading against better measures of happiness. Measuring citizens’ happiness should, however, not focus on generating an ever better single aggregate indicator but rather on improving proxies that allow insights about individual well-being broadly understood. Happiness research has already produced many insights which can be brought into the political discussion process. They include policy issues like, for example, the role of direct democratic decision-making in citizens’ well-being (Frey and Stutzer, 2000), the effect of mandatory retirement and mandatory schooling on happiness (Charles, 2002; Oreopoulos, 2007), the consequences of social work norms and birth control rights on women’s well-being (Lalive and Stutzer, 2010; Pezzini, 2005), the impact of tobacco taxes on smokers’ well-being (Gruber and Mullainathan, 2005) or the relation between working time regulation and people’s subjective well-being (Alesina et al., 2005). A competent overview of selected findings with policy relevance is provided in Diener and Seligman (2004).

14.9

CONCLUDING REMARKS

The objective of our chapter was to outline two possible views about the role of happiness research in public policy. A discussion is warranted as the view matters for the choice of research questions and thus the kind of knowledge happiness research aims to provide, as well as for the people seen as addressees. The big progress in the measurement of individual welfare makes it tempting to pursue the old dream of maximizing aggregate happiness as a social welfare function. Improvements in individual well-being are claimed to be measured directly and politics is seen as taking up advice and implementing it with suitable interventions in the political process. However, we postulate that the appropriate approach is not to maximize

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aggregate happiness directly in seeking to improve outcomes by direct interventions. We rather see the role of happiness research in seeking to improve the nature of the processes. People should become better able to advance their idea of the good life, individually and collectively. They should be made aware that different issues require different measures and indicators of well-being. Happiness research should remain open to constructing a number of different indicators, reflecting well-being according to different aspects of life. Plurality is a necessary consequence of the procedural view outlined. This is in stark contrast to the maximization approach requiring one single objective. All this does not mean that it would be useless to construct a National Happiness Indicator. It has an important role to fulfill as an important macro-economic input in the political discourse. It helps us in overcoming the currently dominant orientation towards the GNP centered on material concerns. Politicians get incentives to justify their actions in terms of a broader and better indicator of individual welfare. It is also useful in strengthening the yardstick competition between political units and political parties. ‘National’ Happiness Indicators should therefore be disaggregated to regional, county and communal levels. The useful role of having one happiness indicator (or, better still, several happiness indicators) is independent of maximizing the National Happiness Indicator.

NOTES 1. Both authors are also affiliated with CREMA – Center for Research in Economics, Management and the Arts. We are grateful to Bernd Hayo and the participants of the European Public Choice Conference and the Conference on New Directions in the Study of Happiness at the University of Notre Dame for helpful comments. 2. See, for example, the publications by the CATO Institute (Wilkinson, 2007), the Institute of Economic Affairs (Johns and Ormerod, 2007) or the New Economics Foundation (Shah and Marks, 2004). 3. Recent surveys on social indicators are provided in Michalos (2005), Hass et al. (2003) and Berger-Schmitt and Jankowitsch (1999). For the capabilities approach based on the work by Sen (1992, 1999) and Nussbaum (1999, 2000), see Comim (2005) and Gasper (2005). 4. But not in (applied) benefit cost analysis where the method of stated preference, especially via contingent valuation, is central. 5. But their result is criticized by Leigh and Wolfers (2006). 6. Interestingly enough psychologists (who otherwise are very demanding with respect to measurement) seem to be more comfortable with respect to comparing indicators of feelings or utility across individuals (Kahneman et al., 2004b, p. 432). 7. Originally Buchanan and Tullock (1962), see also Frey (1983), Brennan and Buchanan (1986), Mueller (1996, 2003) and Vanberg (2005). 8. In authoritarian and dictatorial systems the rulers also have to some extent to take into account the population’s wishes in order not to risk rebellions and revolutions, and thus to be thrown out of power.

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9. Creative accounting is no violation of the law but it is clearly against the spirit of the law and the accounting standards. It uses the rules, the flexibility provided by them and the omissions within them to make financial statements which look different from what is intended by the rule (Jameson, 1988).

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15.

Change your actions, not your circumstances: an experimental test of the Sustainable Happiness Model Kennon M. Sheldon and Sonja Lyubomirsky

Is it possible to become a happier person? This is an enormously important issue for subjective well-being (SWB) researchers, as well as for the burgeoning field of positive psychology (Seligman and Csikszentmihalyi, 2000; Sheldon, 2004). Indeed, if happiness cannot be lastingly increased, then one of the basic premises of positive psychology is suspect – namely, that positive psychology is about more than curing disorders or ‘bringing people back to 0’, but is instead about helping to move people ‘beyond 0’, to new heights of fulfillment and satisfaction (Seligman, 2002). The question of whether SWB can be sustainably improved naturally arises from the growing consensus that SWB is strongly influenced by genetics, with a heritability of around 0.50 according to twin studies (Diener et al., 1999). The behavioral genetics research implies that there may be a genetically determined ‘set-point’ for SWB, to which people are bound to return over time (Lykken and Tellegen, 1996; Tellegen et al., 1988). In other words, SWB may be the result of a homeostatic process that resists deviations away from a pre-determined baseline (Cummins, 2003). If this is true, then trying to become happier may be as fruitless as ‘trying to become taller’ (Lykken and Tellegen, 1996, p. 189). A further implication is that developing the strengths (Peterson and Seligman, 2004) and engaging in the practices (Emmons, 2007) emphasized by positive psychology researchers can have no lasting effect on peoples’ state of mind. Of course, such strengths and practices may provide other benefits besides permanently enhanced SWB, but elevating personal happiness is surely a predominant goal underlying many self-improvement efforts (Myers, 1991). The empirical literature on longitudinal SWB provides further reason for pessimism regarding the feasibility of the goal of enhancing wellbeing. In a four-year panel study, Headey and Wearing (1989) showed 324

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that, although participants varied around their own baseline over time as a function of various positive and negative life events, they tended to return to that baseline – a process Headey and Wearing referred to as ‘dynamic equilibrium’ (see also Suh et al., 1996). Lucas et al. (2003) analysed large-N longitudinal data and found that, although positive events such as marriage afford a temporary boost in SWB, this boost is transient, typically fading within a couple years. Even more worrisome, Lucas and his colleagues have shown that major negative events such as injury, divorce and unemployment can have negative effects that do persist over time (Lucas, 2005, 2007; Lucas et al., 2004). For example, a sample of spinal cord patients evidenced sharp declines in happiness with only a minimal rebound over time, stabilizing at a level far below their pre-injury baseline (Lucas, 2007). Together, these findings once again generate pessimism regarding one of positive psychology’s central aims and promises. Perhaps, rather than trying to improve their happiness (an unfeasible goal), people should instead focus on avoiding catastrophic events that could permanently detract from their well-being. Yet another reason for pessimism arises from literature suggesting that people have a powerful capacity to adapt to change – not just to sensory and perceptual changes, but also to changes that have positive or negative emotional implications. For example, Brickman et al.’s (1978) findings suggest that lottery winners may adapt to their newfound financial status, returning to their prior emotional baseline over time, and BiswasDiener and Diener (2001) showed that even street-dwelling prostitutes in Calcutta evidence surprising equanimity and even cheerfulness with their lot. The general tendency to adapt to emotion-relevant change has been termed hedonic adaptation or the ‘the hedonic treadmill’ (Brickman and Campbell, 1971; Frederick and Loewenstein, 1999). From this perspective, trying to make happiness-relevant changes is like trying to walk up a descending escalator: your circumstances may get better for a while, but you will get used to those circumstances, cease to notice them and be brought back to your own ‘ground floor’ of experience. In other words, as their circumstances improve (for example, they move to a more upscale neighborhood) and as the targets of their social comparisons increase in turn (for example, they notice that their neighbors throw even fancier parties), people raise their aspirations for the future (Easterlin, 2001; Kahneman, 1999; Stutzer, 2004), taking the previous advances for granted and now demanding even further improvement. Is there hope? Yes, according to the Sustainable Happiness Model (SHM; Lyubomirsky et al., 2005b; Sheldon and Lyubomirsky, 2004; 2007), which directly addresses the question of whether it is possible to boost and maintain one’s level of SWB. The SHM divides the possible

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influences on SWB into three broad categories: genetics, circumstances and activities. Genetics represents the ‘set-point’, the temperamental and psychobiological characteristics with which one is born, which will have a strong and lasting influence. Again, the most common estimate for the heritability of SWB is approximately 0.50, so genetics presumably account for half of the variance in SWB. Circumstances represent a person’s demographic profile (gender, ethnicity, income, health status), as well as the influence of non-psychological variables, such as a person’s possessions, geographic location and immediate surroundings. The central characteristic of circumstances is that they tend to be relatively unchanging over time. Because of their static nature, people tend to adapt to their circumstances, even life changes such as ‘moving to California’ (Schkade and Kahneman, 1998). These adaptation processes likely explain the relatively small influence of circumstances on SWB (approximately 10 percent of the variance, or slightly more; Andrews and Withey, 1976; Diener et al., 1999). The remaining 40 percent of the variance, according to the SHM, is accounted for by what people do, that is, the intentional activities that they undertake within their daily lives, for good or ill, and with varying degrees of pleasure and success. Of course, ‘activities’ is a very broad category, and one that can overlap with ‘circumstances’, because many circumstances require activity to bring about, and because circumstances provide for differing kinds and amounts of activity. Still, the SHM focuses on the activities category as the route that offers the best potential for sustainably increasing one’s SWB. Peoples’ genetics are immutable, and their circumstances are generally alterable but subject to quick adaptation. In contrast, peoples’ activities are also alterable, but are less subject to quick adaptation. According to the SHM, intentional activities have the capacity to resist adaptation because they are changeable – that is, they can be optimally varied, developed, timed and modified. One need not always do an activity at the same time of day, in the same place, in the same way, and with the same goals and purposes. For example, consider a person who initiates the activity of running as part of their daily health and self-maintenance efforts. This can be done with a sense of resignation and drudgery, but it can also be practiced as a way to obtain positive experiences. For example, running can be varied: one can run in different places (the state park versus one’s neighborhood versus on a track), at different times (before work versus after) and with different purposes (to defuse a stressful day versus to lose weight versus to experience a new footpath through the woods). Also, one can run in ways that provide a wide variety of positive experiences, for example, one can run with a friend to catch up on each other’s lives or with a camera to catch the morning light. Also, one can set goals that further enhance the interest

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and appeal of the activity – for example, to complete a half-marathon six weeks hence or to run every single trail in the nearby forest. The key, according to the SHM, is to engage in activity in such a way as to provide a continual stream of fresh, positive experiences. Of course, this is not easy, but it has the advantage of being an enjoyable adventure; after all, people are naturally inclined to find and follow intrinsic motivations, and to seek states of absorption and flow (Csikszentmihalyi, 1997; Deci and Ryan, 2000). However, as soon as the activity becomes rote or routinized, then its potential to influence SWB diminishes. Another way to illustrate the propositions of the SHM is via a withinsubject regression equation in which SWB at time t is influenced by three major classes of factors: genetic/temperamental, circumstantial/ demographic and activity/motivational. The genetic set-point defines the intercept or expected value, all other factors being equal. This factor is theorized to be fixed and stable over time. Circumstances (positive or negative) have the potential to contribute positively or negatively to SWB at time t, but these effects are relatively small and tend to fade over time (that is, one might include a circumstances X time elapsed interaction term in the equation). Activities (positive or negative) have a larger potential to contribute to SWB at time t, because they can provide dynamically varying experiences. The SHM also emphasizes that the activity effects likely depend on a variety of moderators, such as how diligently or successfully one performs the activity, how well the chosen activity fits one’s personality and interests, and how much one varies the manner and timing of activity (Lyubomirsky et al., 2005b). These moderators could also be modeled as part of the equation. As this regression metaphor illustrates, the set-point should probably not be construed as a point, but rather as a range, which is in part defined by the set-point at the middle, but which is also defined by current life characteristics, both static and dynamic. The goal, then, is to construct one’s life in such a way that one stays in the upper half of one’s set range, finding ways to remain at a level of happiness that is higher than one’s genetics alone would dictate. Again, the SHM asserts that intentional activities provide the only feasible way to do this, and only under the right conditions. Some published data supports these ideas. Sheldon and Houser-Marko (2001) showed that successful goal striving during the freshman year of college could produce enhanced SWB at the end of the first semester and again at the end of the second semester, which the authors referred to as an ‘upward spiral’ of well-being. Furthermore, successful goal striving was more likely if students chose ‘self-concordant’ goals for the first semester, that is, goals that better fit their interests and values (see also the results of Lyubomirsky et al., 2007). Sheldon (2008) followed up this sample in the

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senior year, showing that freshman goal progress still predicted enhanced SWB three years later. Thus, by engaging successfully in the activity of pursuing self-appropriate goals during their first year, students were able to enhance their emotional state for their entire college career. More recently, Sheldon and Lyubomirsky (2006) directly tested the key postulates of the SHM via two 12-week longitudinal studies. In both studies participants’ SWB was measured at an initial time point, using measures including positive affect, negative affect, life satisfaction, subjective happiness and Ryff and Keyes’s (1995) psychological well-being scales. At a second time point six weeks later participants again rated their SWB, then rated to what extent they had experienced a positive circumstance change or a positive activity change since the beginning of the study. ‘Circumstances’ were defined as ‘facts about your life, such as living arrangement, monetary situation or course load. For example, you may have moved to a better dorm or better roommate, received an increase in financial support so you can have more fun, or dropped a course that you were really going to have trouble with.’ An ‘activity’ was defined as ‘something you chose to do or get involved in, which takes effort on your part. For example, you may have joined a rewarding new group, club or sports team, decided on a major or career direction which makes it clear what to focus on, or taken on some other important new project or goal in your life.’ Finally, SWB was measured again, 12 weeks after the study’s beginning. For every measure and in every study, the same pattern applied: both participants who reported a positive circumstantial change and those who reported a positive activity change evidenced enhanced SWB at Time 2, compared to their own baselines and compared to the group that reported no positive changes. However, by Time 3, the gains of the circumstantial change group had entirely faded, whereas the gains of the activity change group tended to persist. In other words, only the activities group experienced ‘sustainable change’ (at least over this 12-week period). A third study by Sheldon and Lyubomirsky (2006) compared the two types of changes in a different way, by asking participants to self-select into the study because they had either recently experienced a positive activity change or a positive circumstance change (defined in the same way as above). Upon reporting to the laboratory, participants were asked to describe the change they had experienced. Examples of listed circumstantial changes included ‘I learned that I won’t have to be in a lottery in order to get in my Broadcast 1 class’, ‘My roommate at the beginning of the semester was a cocaine addict; she is no longer my roommate’ and ‘This week I found out that I received a scholarship that I wasn’t expecting at all.’ Examples of listed activity changes included ‘When I first got here my classes seemed hard and I didn’t study as much as I should have. I set

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myself a goal to study for at least five hours a day and now my classes are going a lot better for me’, ‘I enrolled in a class that is helping me to figure out a correct career choice for me’ and ‘I used to not ever go to church but now I am going to Campus Crusade for Christ meetings, and God is more a part of my life than He ever has been.’ The chief findings of this third study were that, relative to the circumstantial change group, the activity change group (a) rated themselves as having put more intentional effort into making their change happen, (b) reported that their change provided a greater variety of experiences, and (c) reported that they had habituated less to their change, that is, had not ‘gotten used to it’ as much. The latter two characteristics helped to account for activity changes’ relatively stronger association with positive affect. In other words, as we predicted, activity changes were less prone to affective adaptation or ‘the hedonic treadmill’ than circumstantial changes. Notably, these three findings are further supported by recent studies from our laboratory that have shown that ‘happiness interventions’ are more successful at increasing and sustaining personal happiness levels when participants invest effort in the intervention (Lyubomirsky et al., 2007), when they vary their activities (Boehm et al., 2007) and when they try to appreciate what they have (Lyubomirsky et al., 2005b, 2007). However, an important limitation of the Sheldon and Lyubomirsky (2006) research was that participants either self-selected into the ‘positive activity change’ and ‘positive circumstance change’ categories or rated these two changes by self-report. As a consequence, their membership or scores within these categories might reflect personality or situational variables that have little to do with any actual activity or circumstance changes within their lives. Conversely, those who selected themselves into a ‘no positive change’ category or rated little positive change of either type may be revealing more about their dispositions than about what changes they have or have not recently made. The SHM would be better supported if the same pattern of effects could be shown using an experimental methodology with random assignment. If this occurred, then we could more confidently recommend that it is better to start a new activity (that is, join a group, practice an exercise or pursue a goal) than to change one’s circumstances (that is, buy a new car, move to a new state or obtain a face lift). The purpose of this chapter is to present some initial data bearing on this issue.

15.1

STUDY OVERVIEW AND PROCEDURE

We measured participants’ SWB at Time 1 (T1), and then randomly assigned them to make a circumstance change or an activity change in their

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lives. We then measured their SWB twice more, to examine the temporal shape of the curve for all three groups. Could we replicate the findings of Sheldon and Lyubomirsky (2006) to show that only the activity change group would demonstrate maintained change at Time 3 (T3)? Notably, although we requested of our participants to make certain changes in their lives, we could not force them to do so. Thus, an additional feature of the study was to assess, at Time 2 (T2), whether participants actually made the requested change. Our hypotheses apply primarily to those participants who followed through with the change they listed. Thus, our study design was a 2 (group: circumstance change versus activity change) × 2 (change: made versus not made) × 3 (time of assessment: T1, T2, or T3) factorial design, with repeated measures on the third factor. A total of 113 participants were introduced to the study in small group sessions. Upon arriving at the laboratory, participants first completed an initial well-being questionnaire. Then the research assistant said to all of them: In this research, we are studying positive mood, and the factors that sustain it. We will assess your mood and happiness several times during this semester, to see how they fluctuate. We will also ask you to do something during this time that might affect your mood. This ‘something’ has already been shown to have significant positive effects on peoples’ lives, and we want to further examine its potential.

As can be seen, we chose to inform all participants of the purpose and possible benefits of the study, reasoning that this might enhance their motivation. Participants assigned to the ‘activities’ condition (n 5 60) were then told: You have been randomly assigned to change something about your activities and goals in life. ‘Goal/activity’ means something you choose to do or get involved in, which takes continual effort on your part. For example, you might join a rewarding new group, club, or sports team, decide on a major or career direction which makes it clear how to focus your life, or take on some other important new project in your life. In all of these cases you are taking on a new activity or commitment, which you think will have a positive effect in your life.

Participants were then asked to: think of the single best new life activity or goal that you could start doing in the next couple of weeks. This should be some change that you can make relatively easily – something that you’ve been ready to take on and start doing, that you can go ahead and begin. But making this simple change should have a strong positive effect on your mood and life satisfaction.

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Participants wrote down the change they wished to make. The circumstances group (n 5 53) was instead told: You have been randomly assigned to change something about the external circumstances of your life. ‘Circumstances’ means ‘facts’ about your life, such as living arrangement, monetary situation or course load, which require a onetime effort on your part to change. For example, you might buy yourself something you need or want; arrange to get an on-campus parking permit or drop a course that you were really going to have trouble with. In all of these cases you are making a one-time change regarding your living arrangements or life circumstances that you think will have a positive effect in your life.

Participants were then asked to: think of the single best change in your life circumstances you could make in the next couple of weeks. This should be some change that you can make relatively easily – something that’s been needing to be done, that you can go ahead and take care of. But making this simple change should have a strong positive effect on your mood and life satisfaction.

Participants wrote down the change they wished to make. Two weeks later participants were emailed a link to an online questionnaire in which their well-being was first assessed; then they were asked whether they had made the designated change (yes or no). If they had, they were asked further questions about the change. Finally, four weeks later participants were emailed a link to a final questionnaire in which their wellbeing was assessed and then further questions were asked about the change.

15.2

STUDY MEASURES

15.2.1

Well-being

At all three time points, participants completed the positive affect scale and the negative affect scale from the 20-item Positive and Negative Affect Schedule (Watson et al., 1988). We computed an ‘affect balance’ score at each time point by subtracting negative affect from positive affect (Diener et al., 1999). This allowed us to consider the relative predominance of positive mood compared to negative mood within the participant’s life, particularly as this balance shifts over time. Such affect measures are both theoretically linked (Diener, 1984) and intercorrelated (Busseri et al., in press; Diener, 1994) with other measures of well-being, such as happiness and satisfaction with life.

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Self-concordant Motivation

An important feature of the SHM is that the ‘fit’ between the person’s personality and the person’s change should make a difference (Lyubomirsky et al., 2005b). In other words, one must not make just any change, but, instead, must select a change that is important to who one is, and that one can stand behind. To assess this factor, we relied on Sheldon and colleagues’ self-concordance measure (Sheldon and Elliot, 1999; Sheldon and Houser-Marko, 2001), which is based on self-determination theory (Deci and Ryan, 1985, 2000). Specifically, at Time 1, we asked participants to rate ‘why you might make this change, in terms of each of the following reasons’. The four reasons provided were: ‘because somebody else wants me to, or because my situation will force me to’, ‘because I would feel ashamed, guilty or anxious if I don’t do it; I will force myself’, ‘because I value and identify with doing it; I will do it freely even when it is not enjoyable’ and ‘because I will really enjoy doing it; I will find it to be interesting and challenging’. These four reasons (external, introjected, identified and intrinsic, respectively) are located on a continuum, ranging from not at all internalized (that is, external motivation) to completely internalized (that is, intrinsic motivation; Deci and Ryan, 2000). An aggregate self-concordance measure was computed by subtracting external and introjected ratings from identified and intrinsic ones. Sheldon and Elliot (1999) and Sheldon and Houser-Marko (2001) have argued that in the case of self-generated personal goals and initiatives, this measure represents the fit between the goal and the person’s inherent interests and values. We treated it as such in this research (see also Sheldon and Lyubomirsky, 2006). 15.2.3

Additional Measures

We administered further measures at Time 1. In one measure we asked participants to rate ‘how much effort will you have to put into making the change?’ This was to test the SHM’s postulate that activity changes require relatively more effort to carry out, because they involve instigating a program of volitional activity, not just making a one-time alteration in one’s circumstances. In addition, we asked participants to make affective forecasts regarding the anticipated effects of the change on their mood, by rating ‘To what extent do you expect this change to affect your levels of positive mood’ and ‘To what extent do you expect this change to affect your levels of negative mood.’ The aim was to examine whether people are aware of the hypothesized difference between activity changes and circumstance effects, in terms of their potential impact on mood. We made no hypotheses concerning the forecast variables, although previous affective

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forecasting research suggests that people often make erroneous judgments about their future emotional states (see Wilson and Gilbert, 2003, 2005, for reviews). At Times 2 and 3 we administered additional measures to only the group of participants who reported at Time 2 that they had made the change (as it did not make sense to ask about a change that did not occur). These measures were designed to test other predictions derived from the SHM. To this end, participants rated at Time 2 ‘To what extent is the change something that varies over time, that is, something that adds variety to your life?’ This was to test the SHM’s postulate that activity changes are more effective when people vary how they do the activity, as in the aforementioned example of the runner. At Time 3 participants rated ‘To what extent are you still aware of the change, that is, do you still think about the change?’ This was to test the SHM’s postulate that the change will cease to affect SWB if one begins to take it for granted; in order for the change to continue to have effects and to resist adaptation, one must remain cognizant of it.

15.3

STUDY RESULTS

15.3.1

Preliminary Results

We first tested for pre-manipulation differences in Time 1 affect balance between the two conditions. As would be expected given random assignment, the activity and circumstance groups were equivalent at the beginning of the study (Ms 5 1.48 versus 1.42, respectively, p . 0.50). Also, there were no differences on Time 1 positive affect and negative affect examined separately. We then tested for differences on the Time 1 variables rated after the manipulation. First, there were no differences between the activity and circumstances group on either the positive affective or negative affective forecast variables (both ps . 0.50). For the positive affective forecast, both groups were slightly over 4 on a 5-point scale (Ms 5 4.01 and 4.02), equally expecting the change to have a strong positive effect on their moods. Also, for the negative affective forecast, the two groups equally expected the change to help reduce their negative moods in life (Ms 5 3.52 and 3.49, respectively). This suggests that participants did not share our theory-based expectation that activity changes would be relatively more beneficial. However, activity-change participants did report more self-concordant motivation to make the change than did the circumstance-change participants (Ms 5 3.77 versus 3.32), t(111) 5 3.00, p , 0.01. This effect was due

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Table 15.1

Affect balance means split by condition and whether the change was made Activity Change

Circumstance Change

T1

T2

T3

T1

T2

T3

Not Made

1.58

1.26

1.42

1.42

1.68

1.42

1.26 (n = 17) 1.48 (n = 36)

1.21

Made

0.76 (n = 21) 1.62 (n = 39)

1.26

largely to a difference in rated intrinsic motivation to make the change, that is, activity participants expected to enjoy their change more than did circumstance participants. Furthermore, activity-change participants reported that making their change would require more effort (Ms 5 3.97 versus 3.57, t(111) 5 2.30, p , 0.05). Both of these findings are consistent with the SHM’s claim that activity changes are more engaging but also require more effort and commitment to enact. 15.3.2

Hypothesis Tests

Our primary hypothesis was that actually making the listed change (whether related to activities or circumstances) would produce enhanced affect balance at Time 2, but that only the activity change group would show maintained change at Time 3. Table 15.1 presents the 12 means relevant to this hypothesis. As can be observed, those who committed to adopting a new activity, but who did not follow through, dropped substantially in their affect balance at Time 2, and had partially recovered at Time 3. Those who committed to changing a circumstance, but who did not follow through, dropped a little, then slightly more. In contrast, those who followed through in changing a circumstance in their lives evidenced slightly increased affect balance at Time 2, but then a large drop at Time 3; not only did their slight boost not last, but they ended up worse than they started off. Finally, and most important, those who followed through on changing an activity experienced a modest boost in affect balance at Time 2, and a further slight boost at Time 3. Thus, no adaptation was evident for this group. It is instructive to consider the pattern of effects in an analysis of the full 2 × 2 × 3 design. A mixed-model MANOVA revealed no significant main effects. That is, the activity and circumstance groups did not differ across the three time points, those who made the change did not differ across the three time points, and there was no main effect of time point (1, 2 or 3)

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upon the means. However, this is not surprising, especially given that the groups were all equivalent on affect at Time 1. What is more instructive is to examine the interactions between the two conditions and the repeated measures factor, as these interactions bear directly on the SHM’s predictions. Indeed, there was a significant change made/not made by time of assessment interaction, F(2,108) 5 4.48, p , 0.02. Although the change/no change groups were equal on affect balance at Time 1 (Ms 5 1.44 versus 1.51), participants who made the change were higher in affect balance at Time 2 than participants who did not make the change (Ms 5 1.55 versus 0.98), a pattern that tended to persist at Time 3 (Ms 5 1.49 versus 1.24). Thus, it appears to be important to follow through on intended changes, if one wishes to obtain an affective benefit. No other two-way interactions reached significance. But what about the activity versus circumstance contrast? If the difference between these two groups moderates the above pattern, then a three-way interaction would be expected. The 2 (group: activity versus circumstance) × 2 (change: made versus not made) × 3 (time of assessment: T1, T2 or T3) interaction approached but did not reach statistical significance, F(2,108) 5 2.01, p 5 0.139. Thus, this most specific prediction of the SHM was not supported, although it is worth noting that three-way interactions are difficult to obtain and the means were in the expected direction. However, the SHM’s more general prediction that SWB can be changed by taking action in one’s life was indeed supported, if we acknowledge that it takes action to change a circumstance, just as it does to initiate a new goal or activity. 15.3.3

Focusing on the ‘Change Made’ Group

Next we focused on the 75 participants who reported actually making their change. Recall that we asked such participants questions about the change they made, attempting to find further support for the postulates of the SHM. Specifically, we asked participants whether the change added variety to their life, and whether they remained aware of the change over time; these variables were theorized to help counteract the mitigating effects of hedonic adaptation. To test the effects of these factors, we regressed Time 3 affect balance on Time 1 affect balance, so that we could evaluate what predicts longer term change from the beginning to the end of the study. At step 2 of this regression we entered the two predictors. Finally, at step 3, we entered a product term representing the interaction of these two (centered) predictor variables, for exploratory purposes. In step 1 of the regression Time 1 affect balance was a significant

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Change in Affect Balance

1.6 1.4 1.2 Low awareness High awareness

1.0 0.8 0.6 0.4 0.2 0 Low variety

Figure 15.1

High variety

Change in effect balance by awareness level

predictor of Time 3 affect balance (that is, the test-retest coefficient was significant; b 5 0.52, p , 0.001; we interpret this as the effect of the individual’s set-point). More important, at step 2 both the ‘variety’ and the ‘awareness’ variables were significant predictors of enhanced affect balance (bs 5 0.22 and 0.19, respectively, both ps , 0.05). Thus, regardless of the type of change, reporting that the change adds variety to one’s life, and also that one remains aware of the change, are associated with greater shifts in SWB. Finally, at step 3 the interaction product term was also significant (b 5 0 .24, p , 0.02). As the positive coefficient illustrates, Time 3 affect balance was especially high (controlling for Time 1 affect balance) given the combination of both variety and awareness. What about the activity versus circumstances change factor? In a second regression we included this dummy variable in the equation, and also examined the interaction of change-type with the above results. Change (activities versus circumstances) did not interact with either predictor taken singly. However, there was a significant three-way interaction, moderating the significant two-way interaction reported above (b 5 −0.89, p , 0.03). When we split the data by change-type, we discovered that the variety X awareness interaction was significant in the activity-change condition (b 5 0.44, p , 0.01) and non-significant in the circumstancechange condition (b 5 0.06, p . 0.50). The two-way interaction is plotted in Figure 15.1 for those who made the change within the activity-change condition (n 5 39).

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15.4

337

DISCUSSION

In this section we summarize the results of the study and then consider some implications. Participants assigned to adopt a new life activity did not differ on Time 1 affect balance from participants assigned to change a circumstance in their lives; nor did they differ in their affective forecasts regarding the likely effects of this change upon their mood. However, they reported more self-concordant (especially intrinsic) motivation to make the change, and believed that making the change would take more effort on their part. Furthermore, participants who followed through and actually made their change experienced a boost in affect balance compared to participants who did not, an effect that tended to be stronger in the activity condition than in the circumstance condition. Finally, among only the participants who made the change, the effects on affect balance were even stronger when they reported that they remained aware of the change, and when the change added variety to their lives. The strongest effect of all was observed in the activity change made condition, for participants who reported that the change added variety to their lives and who reported remaining aware of the change. In contrast, this two-way interaction was non-significant in the circumstance change made condition. What do these data mean? Taken together, they suggest that it is possible to increase one’s happiness level, at least for a span of weeks. Participants in both the circumstance-change and activity-change conditions who actually made their change reported higher SWB at T2 and T3 compared to those who did not make the change, even though change makers and non-makers did not differ in initial SWB. This latter finding is noteworthy, as it can be argued that people who are inclined to follow through on commitments to make life changes may initially differ on important variables (such as happiness, conscientiousness or agreeableness) from those that do not tend to follow through, and that such a confound could have accounted for the differences that we found between change makers and non-makers. In other words, although the current study rectified one limitation of our earlier studies by randomly assigning participants to make an activity change or a circumstance change, we could not randomly assign participants to actually make the change or not, and, thus, in this factor, self-selection effects may persist. However, the fact that change makers and non-makers began our study with identical levels of SWB reassures us that change makers are not simply dispositionally happier. Intriguingly, our data showed that the change makers did not experience a large boost from their initial baselines; instead, they displayed a relatively small boost, while the non-makers experienced a somewhat larger decline. Does this suggest that committing to make a change makes

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one vulnerable – paying off only modestly if successful, and threatening to usurp one’s equanimity if one is not? If so, then the pattern would be consistent with the argument that ‘bad’ may often be stronger than ‘good’ (Baumeister et al., 2001), and might also indicate that people should focus on avoiding negative life events, rather than seeking positive life events. However, considering participants’ changes from their own baselines, rather than their changes relative to participants in other conditions, may be misleading. Studies of this nature from our laboratories have typically found a sample-wide decrease in SWB over the (fall) semester, as winter sets in and the work and stress pile up. And, indeed, there was a significant sample-wide decline in affect balance across the entire sample, if the ‘activity change made’ group is excluded (pre/post Ms 5 1.48 versus 1.27, t(73) 5 2.20, p , 0.05). In contrast, the ‘activity change made’ group experienced a trend to increase in affect balance (pre/post Ms 5 1.42 versus 1.68, t(38) 5 1.30, p 5 0.10, one-tailed). If the entire sample were given a boost of, say 0.30 points at Time 3 to compensate for a general temporal decline effect, then the activity change makers would appear to increase much more and then rise a little higher, whereas the non-makers would decline a bit and then return to their initial baselines (the exact pattern predicted by the SHM). Unfortunately, we did not track this sample long enough to take into account and remove any such yearly or semester-long cycle effects that may have influenced the raw means. Therefore, we believe what is most instructive to examine is the performance of the two groups relative to one another. In this comparison the advantage of making positive life changes is clear. Nevertheless, it is important to emphasize that the longer term sustainability of these positive changes cannot be demonstrated within a 12-week study. For example, it is unlikely that the effects of the change factor (made versus not made) would persist a year later. However, this underscores an important assertion of the SHM, namely, that happiness cannot be taken for granted, but rather, must continually be pursued anew. In other words, only by ongoing effortful and successful practice of varied new activities can people hope to remain in the upper half of their ‘set range’. Failing this, they will almost inevitably revert back to their genetically determined baselines. Our results showed the largest boosts in SWB for individuals who reported that their particular life change was characterized by variety and that they continued to think about it. Not surprisingly, both of these factors have been implicated in the literature as helping to impede hedonic adaptation. Variety is important because it is innately stimulating and rewarding (Berlyne, 1970) and because adaptation, by definition, occurs in response to constant, not dynamic, stimuli. Attention is important because the moment that a thing, circumstance or activity fails to captivate attention

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– the moment that it fades into the psychological background – one can be said to have adapted to it (cf. Kahneman and Thaler, in press). It appears that one needs to be quite diligent to prevent this from happening. Finally, it is worth considering these results from an economic policy perspective. Our data suggest that supporting peoples’ economic lives is unlikely to bear lasting fruit, as income represents a relatively static ‘circumstance’ to which individuals quickly adapt (Easterlin, 2005; Layard, 2005). This may be especially true when people use their rising income to purchase mere luxury goods and status possessions, which may be especially subject to adaptation (Kasser, 2002). However, rising income may potentially lead to lead to gains in SWB when people use this income to expand their range of activities and experiences (Scitovsky, 1976; Van Boven, 2005). For example, spending one’s money on adventure travel, or on taking time off from one’s day job to pursue a dream (like writing screenplays), or on the purchase of items that afford new hobbies (such as a high-end mountain bike or a ski condo that allows one to pursue skiing) may help one to become sustainably happier – but again, only if one uses the new bike or condo, in ways that create varied, dynamic positive experiences and that allow one to continue to attend to the life change. In this light, it may be more important to support workers’ ‘time affluence’ than their ‘monetary affluence’ (Kasser and Sheldon, 2009), so that they have the free time necessary to enjoy the fruits of their labors. Obviously, this is the employee perspective, but it is also important to consider the managerial perspective. Should employers and economists care that the key to happiness enhancement is optimizing experience, not optimizing economic commodities such as income and consumption? We suggest that they should care, because happy people tend to be more productive, creative, flexible, persistent and group-centered than their less happy peers (Lyubomirsky et al., 2005a). Because creating more satisfied workers may help businesses to enhance the bottom line, this goal may be a win-win proposition for employees and managers alike. Our research suggests that meeting the goal may be as simple as providing workers with opportunities to find, engage in, and succeed at satisfying and varied new activities and tasks.

REFERENCES Andrews, F.M. and S.B. Withey (1976), Social Indicators of Well-being: America’s Perception of Life Quality, New York: Plenum Press. Baumeister, R.F., E. Bratslavsky, C. Finkenauer and K.D. Vohs (2001), ‘Bad is stronger than good’, Review of General Psychology, 5, 323–70.

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Berlyne, D. (1970), ‘Novelty, complexity, and hedonic value’, Perception and Psychophysics, 8, 279–86. Biswas-Diener, R. and E. Diener (2001), ‘Making the best of a bad situation: satisfaction in the slums of Calcutta’, Social Indicators Research, 55, 329–52. Boehm, J.K., K.M. Sheldon and S. Lyubomirsky (2007), ‘Spicing up kindness: the role of variety in the effects of practicing kindness on improvements in mood, happiness, and self-evaluations’, University of California-Riverside, Unpublished data. Brickman, P. and D.T. Campbell (1971), ‘Hedonic relativism and planning the good society’, in M.H. Appley (ed.), Adaptation-level Theory, New York: Academic Press, pp. 287–302. Brickman, P., D. Coates and R. Janoff-Bulman (1978), ‘Lottery winners and accident victims: is happiness relative?’, Journal of Personality and Social Psychology, 36, 917–27. Busseri, M.A., S.W. Sadava and N. Decourville (in press), ‘A hybrid model for research on subjective well-being: examining common- and component-specific sources of variance in life satisfaction, positive affect, and negative affect’, Social Indicators Research, 6. Csikszentmihalyi, M. (1997), Finding Flow: The Psychology of Engagement with Everyday Life, New York: Basic Books. Cummins, R.A. (2003), ‘Normative life satisfaction: measurement issues and a homeostatic model’, Social Indicators Research, 64, 225–56. Deci, E.L. and R.M. Ryan (1985), Intrinsic Motivation and Self-determination in Human Behavior, New York: Plenum. Deci, E.L. and R.M. Ryan (2000), ‘Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being’, American Psychologist, 55, 68–78. Diener, E. (1984), ‘Subjective well-being’, Psychological Bulletin, 95, 542–75. Diener, E., E.M. Suh, R.E. Lucas and H.L. Smith (1999), ‘Subjective well-being: three decades of progress’, Psychological Bulletin, 125, 276–302. Easterlin, R.A. (2001), ‘A puzzle for adaptive theory’, Journal of Economic Behavior and Organization, 56, 513–21. Easterlin, R.A. (2005), ‘Life cycle welfare: evidence and conjecture’, Journal of Socio-Economics, 30, 31–61. Emmons, R. (2007), Thanks!: How the New Science of Gratitude Can Make You Happier, New York: Houghton Mifflin. Frederick, S. and G. Loewenstein (1999), ‘Hedonic adaptation’, in D. Kahneman, E. Diener and N. Schwarz (eds), Well-being: The Foundations of Hedonic Psychology, New York: Russell Sage Foundation, pp. 302–29. Headey, B. and A. Wearing (1989), ‘Personality, life events, and subjective wellbeing: toward a dynamic equilibrium model?’, Journal of Personality and Social Psychology, 57, 731–9. Kahneman, D. (1999), ‘Objective happiness’, in D. Kahneman, E. Diener and N. Schwarz (eds), Well-being: The foundations of hedonic psychology, New York: Russell Sage Foundation, pp. 3–25. Kahneman, D. and R.H. Thaler (in press), ‘Anomalies: attention and experienced utility’, Journal of Economic Perspectives. Kasser, T. (2002), The High Price of Materialism, Cambridge, MA: MIT Press. Kasser, T. and K.M. Sheldon (2009), ‘Material and time affluence as predictors of subjective well-being’, Journal of Business Ethics, 84, 243–55.

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Layard, R. (2005), Happiness: Lessons from a New Science, New York: Penguin. Lucas, R.E. (2005), ‘Time does not heal all wounds: a longitudinal study of reaction and adaptation to divorce’, Psychological Science, 16, 945–50. Lucas, R.E. (2007), ‘Long-term disability has lasting effects on subjective wellbeing: evidence from two nationally representative longitudinal studies’, Journal of Personality and Social Psychology, 92, 717–30. Lucas, R.E., A.E. Clark, Y. Georgellis and E. Diener (2003), ‘Reexamining adaptation and the set point model of happiness: reactions to changes in marital status’, Journal of Personality and Social Psychology, 84, 527–39. Lucas, R.E., A.E. Clark, Y. Georgellis, and E. Diener (2004), ‘Unemployment alters the set point for life satisfaction’, Psychological Science, 15, 8–13. Lykken, D. and A. Tellegen (1996), ‘Happiness is a stochastic phenomenon’, Psychological Science, 7, 186–9. Lyubomirsky, S., L.A. King and E. Diener (2005a), ‘The benefits of frequent positive affect: Does happiness lead to success?’, Psychological Bulletin, 131, 803–55. Lyubomirsky, S., K.M. Sheldon and D. Schkade (2005b), ‘Pursuing happiness: the architecture of sustainable change’, Review of General Psychology, 9, 111–31. Lyubomirsky, S., R. Dickerhoof, J.K. Boehm and K.M. Sheldon (2007), How and Why do Positive Activities Work to Boost Well-Being?: An Experimental Longitudinal Investigation of Regularly Practicing Optimism and Gratitude, Manuscript submitted for publication. Myers, D.G. (1991), The Pursuit of Happiness, New York: Avon Books. Peterson, C. and M.E.P. Seligman (2004), Character Strengths and Virtues: A Handbook and Classification, New York: Oxford University Press. Ryff, C.D. and C.L.M. Keyes (1995), ‘The structure of psychological well-being revisited’, Journal of Personality and Social Psychology, 69, 719–27. Schkade, D.A. and D. Kahneman (1998), ‘Does living in California make people happy? a focusing illusion in judgments of life satisfaction’, Psychological Science, 9, 340–46. Scitovsky, T. (1976), The Joyless Economy: The Psychology of Human Satisfaction, New York: Oxford University Press. Seligman, M.E.P. (2002), Authentic Happiness, New York: The Free Press. Seligman, M.E.P. and M. Csikszentmihalyi (2000), ‘Positive psychology: an introduction’, American Psychologist, 55, 5–14. Sheldon, K. M. (2004), Optimal Human Being: An Integrated Multi-level Perspective, New Jersey: Erlbaum. Sheldon, K.M. (2008), ‘Assessing the sustainability of goal-based changes in wellbeing over a four-year period’, Journal of Research in Personality, 42, 223–9. Sheldon, K.M. and A.J. Elliot (1999), ‘Goal striving, need-satisfaction, and longitudinal well-being: the Self-Concordance Model’, Journal of Personality and Social Psychology, 76, 482–97. Sheldon, K.M. and L. Houser-Marko (2001), ‘Self-concordance, goal-attainment, and the pursuit of happiness: can there be an upward spiral?’, Journal of Personality and Social Psychology, 80, 152–65. Sheldon, K.M. and S. Lyubomirsky (2004), ‘Achieving sustainable new happiness: prospects, practices, and prescriptions’, in A. Linley and S. Joseph (eds), Positive Psychology in Practice, Hoboken, NJ: John Wiley & Sons, pp. 127–45. Sheldon, K.M. and S. Lyubomirsky (2006), ‘Achieving sustainable gains in

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happiness: change your actions, not your circumstances’, Journal of Happiness Studies, 7, 55–86. Sheldon, K.M. and S. Lyubomirsky (2007), ‘Is it possible to become happier? (And if so, how?)’, Social and Personality Psychology Compass, 1, 129–45. Sheldon, K.M., A.J. Elliot, Y. Kim and T. Kasser (2001), ‘What is satisfying about satisfying events? Testing 10 candidate psychological needs’, Journal of Personality and Social Psychology, 80, 325–39. Stutzer, A. (2004), ‘The role of income aspirations in individual happiness’, Journal of Economic Behavior & Organization, 54, 89–109. Suh, E., E. Diener and F. Fujita (1996), ‘Events and subjective well-being: only recent events matter’, Journal of Personality and Social Psychology, 70, 1091–102. Tellegen, A., D.T. Lykken, T.J. Bouchard, K.J. Wilcox, N.L. Segal and S. Rich (1988), ‘Personality similarity in twins reared apart and together’, Journal of Personality and Social Psychology, 54, 1031–9. Van Boven, L. (2005), ‘Experientialism, materialism, and the pursuit of happiness’, Review of General Psychology, 9, 132–42. Watson, D., L.A. Clark and A. Tellegen (1988), ‘Development and validation of brief measures of positive and negative affect: the PANAS scales’, Journal of Personality and Social Psychology, 54, 1063–70. Wilson, T.D. and D.T. Gilbert (2003), ‘Affective forecasting’, Advances in Experimental Social Psychology, 35, 345–411. Wilson, T.D. and D.T. Gilbert (2005), ‘Affective forecasting: knowing what to want’, Current Directions in Psychological Science, 14, 131–4.

16.

What is to be done? Toward a ‘happier’ world Amitava Krishna Dutt and Benjamin Radcliff

16.1

INTRODUCTION

In this brief concluding chapter we discuss what happiness studies (especially the contributions to this volume) says about what should be done, individually and collectively, to increase happiness and well-being. We will take it for granted that happiness and well-being are broadly defined, not to mean merely immediate gratification and the accumulation of stuff (which we have seen may not actually increase even subjective well-being), and to be multidimensional, that is, incorporating not only subjective well-being but also such things as flourishing and self-actualization (as argued, for instance, by Ong, this volume). We also take it for granted that the goal is not to maximize national happiness in some formal and narrow sense, but to simply increase happiness, broadly defined. A brief chapter clearly cannot be expected to provide a comprehensive discussion of all the things that can be done to increase happiness in its various forms. The aim of this chapter is much more modest. It is to provide some examples of what is to be done to illustrate two main points. First, action needs to be taken at several different levels: at the level of the individual, groups, nations and even the world, and that operating at only one level may not be enough. Second, that things need to be done in different spheres of life to address problems arising from sources emphasized by different disciplines, so that a multidisciplinary perspective is necessary not only for understanding happiness and its determinants – as stressed earlier in this book – but also for increasing happiness. The rest of this chapter examines examples of things that can be done at different levels to argue why action at only one level may be inadequate and why a multidisciplinary approach is necessary. It discusses, in turn, individual, group, nations and global levels of action.

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THE INDIVIDUAL LEVEL

It is easiest to initiate action individually since it can be done by one person without requiring other people’s agreement or reciprocation. There are, indeed, many things that can be done individually, as the contribution to this volume by Sheldon and Lyubomirsky makes clear. Rather than review that analysis here, let us instead mention some of the less obvious individual-level strategies that might be implied by this volume, taken as a whole. For instance, in the economic sphere one can try to work fewer hours, choose jobs which one likes and not just which pay the most, and to develop other interests and compete with oneself rather than with others. Perhaps the most general advice, which emerges as a latent theme in many of the chapters in the present volume, is the central argument of Robert Lane’s (2001) work on The Loss of Happiness in Market Democracies. Lane argues that the market encourages us to find happiness there, but is at the same time incapable of providing the most important sources of happiness, which relate to our connections to other human beings. Simply put, Lane observes that it is friendship and other intimate connections that are the most important contributors to a rewarding life. The market is not only unable to provide such things, but by may actually increase unhappiness by encouraging individuals to seek the emotionally empty goals that markets reinforce. That same theme is pressed in a different way by the theorists of social capital, most notably Putnam (2000), who argues explicitly that health, including mental health, taking its most sublime expression in the form of happiness itself, is fostered by the inclusion of individuals within social networks of all kinds, ranging from the family and friends to compatriots in political or charitable causes. In any event, this line of reasoning leads to the suggestion that individuals devote more time and energy to family, friends and community organizations. More generally, perhaps, individuals may benefit by shifting their internal calculus away from material or career goals, substituting in their place social, political or religious goals that take them outside the world of personal gain, and, thus, outside of the economic sphere as conventionally construed. Also in the economic sphere, one can try to consume in a way that promotes health and long-term well-being, and to obtain gains which last and which do not lead to boredom or which yield benefits which are lost when other people also consume them (such as things consumed for status). Solutions such as these may involve issues that are typically examined in different disciplines. For instance, volunteering to work on a political campaign might be thought of as a political act, thus subject to the domain of the political scientist, but at the same time is an act of community involvement, which concerns the sociologist and even the economist (for

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whom any volunteering would seem to involve both an immediate disutility as well as a collective action problem). Moreover, the solution to such problems which arise from the economic and social sphere may well be found outside the normal boundaries of these social sciences, for example, through greater interest in spirituality, religion or other causes greater than oneself which can help to reduce the importance given by people to status competition, which again underscores the importance of an interdisciplinary approach to the study of happiness. Although it may be easy to initiate individual action, it may not always be easy to sustain such action in an effective manner only at the individual level. In the economic sphere, for instance, one can try to work fewer hours and consume more carefully, but the social pressures to work more and engage in more status consumption may be too strong to overcome individually. Others, of course, must of necessity work longer hours for purely financial reasons in more unsatisfying jobs than they might like, a point to which we return when considering other levels of analysis, suggesting as it does the need for collective solutions to such problems as low wages. In the political sphere people may try to support particular policies, but whether these changes come to pass depends on what others do. Socially, one cannot join community organizations which do not exist, to make friends when other people do not want to make friends and spend more time with family members when others in the family have no time to do so.

16.3

THE GROUP LEVEL

Some of the problems that arise at the individual level can be overcome at the group level. Regarding the relation between consumption and happiness, groups can overcome the problems faced by individuals in reducing and reorienting consumption in ways that can increase their happiness. For instance, people can form groups to help each other to overcome habits and addictions, an idea which is exploited by organizations such as Alcoholics Anonymous. Moreover, people can come together and agree (implicitly or explicitly) to not compete with each other through status consumption, creating consumption norms among themselves that reduce total consumption by them. Regarding relations between family members and friends, people can agree to spend more ‘quality’ time together in ways that result in gains that last, implying higher levels of happiness. Latent groups can also, through the efforts of ‘entrepreneurial’ individuals, come into being, transforming

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what might be solitary acts into communal ones – obvious examples including the idea of the book club or reading group, or, to borrow now the familiar metaphor from Putnam (2000), people can choose to form or join bowling leagues, rather than merely playing alone or with a single friend. Although group-level activities can overcome some of the problems associated with increasing happiness by individuals, it is, in many instances, difficult or even impossible for this to happen. Regarding consumption, it may be difficult for groups to change their consumption norms which are at variance with norms that are followed by larger groups. It may be difficult to break addictions without government funding or interventions through taxes. Government policies which may increase average levels of happiness need to be adopted at state or even national levels, and there is only so much that smaller groups of friends can do.

16.4

THE NATIONAL LEVEL

Although some policies can be adopted at lower levels of government, many which aim to increase happiness or well-being may need to be undertaken at the national level. Examples of such policies at the national level include those which impose limits on the length of the standard working day, worker safety regulations, pensions and benefits, and the public policies that support a middle-class level of consumption, such as the minimum wage and income maintenance programs (that is, the welfare state). All of these practices and policies, and many others besides, have historically depended upon organized labor. As we have seen, labor unions appear to increase happiness both directly and indirectly via their impact on policy. To the extent that unions and the policies they favor do indeed promote happiness, innovations to make it easier for workers to organize may have a major long-term impact on quality of life. The ‘card check’ provision currently being debated in the USA, which would move US labor law closer to international norms by allowing workers to organize merely by obtaining a majority in favor of doing so, would seem to hold great potential for realizing the promise of greater happiness. Tax policy is potentially equally important. Of particular interest is a proposal by Frank (1999) which replaces the US income tax by a consumption tax. Frank’s argument is that with a consumption tax people would be encouraged to save more and consume less than under the current income tax system, and there would also be a further negative effect on consumption to the extent that people consume more, for example, for status

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reasons, when others consume more. Frank argues that such a tax could be made more progressive than the current income tax schedule to take into account the fact that people at lower levels of income have a higher propensity to consume than those at higher levels, and that the tax would not need the government to make arbitrary distinctions between necessities and luxuries and tax only expenditures on the latter: people would themselves consume what they feel are more necessary. It should also come as no surprise that people report increasing levels of subjective well-being with a cleaner environment, and well-being as measured by health indicators also improves with environmental improvements. Economists have for quite some time advocated economic solutions, such as effluent fees and environmental standards, to reduce environmental problems. Their approach has been to view environmental damage as resulting from externality in the sense that it affects others (more than the person causing the damage), and that economic actors do not take this negative externality into account in making their consumption and production decisions. Effluent taxes make polluters pay for the pollution they cause, and induce them to pollute less. These examples can be used to illustrate how solutions need to take into account issues examined by different disciplines. For instance, the consumption tax proposal takes into account the concerns of both economists (how taxes affect individual behavior and internalize consumption externalities, because of which people do not take into account the effects of their consumption on the behavior of others, as in the pollution example) and sociologists (regarding status and social norms, for instance). Another example can be found by examining the effects of some tax and labor policies. A possible effect of the consumption tax is that it may reduce aggregate demand and increase unemployment and that it may reduce the willingness of people to work longer hours and thus increase their leisure time (although these two effects will work in opposite directions as far as the level of unemployment is concerned). The reduced incentive to work as well as direct policies to reduce the length of the working day can be expected to free up time people have for other activities. Such changes can create problems – obviously by raising the specter of unemployment – and also by increasing leisure time in which people have nothing enjoyable to do. The political support for government policies which maintain aggregate demand (which, of course, is a principal concern of organized labor, which has long pressed for full employment policies, as well as more conventional strategies, such as generous unemployment compensation and more expansive job training, all of which maintain pressure on demand, and thus employment) and which create conditions in which people can pursue enjoyable activities may well be necessary to overcome such problems.

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The examples can also be used to illustrate that changes at different levels may be needed to solve some of the problems. For instance, it is possible that the consumption tax may make people – especially those with lower incomes – continue spending on status goods while reducing their expenditure on food and housing, thereby adversely affecting their health and security, and therefore, their well-being. They may do this because they may be overwhelmed by social pressures to consume, and because saving on food has adverse effects on health which may not be immediate. For this and other possible problems, solutions such as the consumption tax may not have their desirable effect, and may need to be supplemented by greater individual efforts to overcome the status motive. Moreover, economists may have been too quick to dismiss individual solutions to the problem of pollution by assuming that people only care about their private benefits and costs and not about how their activities affect others. By so doing, they unnecessarily limit their attention to taxes and standards, rather than supplementing such policies with efforts to inform people about the environmental consequences of their actions which may well induce people to be more careful about damaging the environment.

16.5

THE GLOBAL LEVEL

Some problems can be fully addressed only at the global level. An obvious example is the problem of global warming, where efforts by one country to limit the damage it does to the environment may be nullified by the activities of people in other countries. The solution to such global problems, of which global warming is the most visible, requires global agreements. Another issue is that in a globalized world what happens in one country has effects far beyond its borders. For instance, efforts to reduce pollution through regulations in one country may simply induce production to shift to other countries in which environmental regulations are more lax, often because these countries are less developed economically and do not have the resources or the capability to have appropriate regulations which are properly implemented. Moreover, increases in consumption norms in one country can, through what have been called international demonstration effects, affect consumption levels in other countries, because of technological changes and the reduced costs of transport and communications. In the political realm global agreements may be needed to allow countries that choose to adopt policies that are designed to increase happiness and well-being to pursue their experiments without interference by rich

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countries which believe that such policies are against their economic interests directly or by influencing the policies of international organizations, such as the World Bank, the International Monetary Fund and the World Trade Organization. These institutions take us to a final concern: economic globalization itself. We have already reviewed in this volume the role of the welfare state, and similar political interventions in the market for the benefit of workers, that appear to support higher levels of well-being. Globalization generally, and often via the auspices of the Bretton Woods institutions specifically, makes the maintenance of such programs ever more difficult. The same international competition for low-cost labor places similar downward pressure on the ability of workers to organize. To be sure, globalization is a complicated phenomenon, likely to produce different sets of winners and losers, improving some conditions in some places, but having the opposite effects in others (see, for instance, Bhagwati, 2004; Chang, 2008; Stiglitz, 2002 for general discussions from different points of view). It may well be that future generations may see the process as positively transformative, the costs of which, like those that accompanied the end of feudalism, having proved necessary for a better future. That said, however, it seems likely that globalization will, at least for the foreseeable future, decrease the overall level of well-being of many people in the world, by weakening the two central institutions (the welfare state and the labor union) that insulate citizens against the insecurity created by market fluctuations. This may be doubly so, when we consider that the increases in consumption that globalization is argued to provide may well, for reasons now familiar, fail to provide more happiness in the way that other activities do not. Thus, even if the advocates of globalization prove to be correct in their judgment (itself passionately disputed by opponents) that the process will eventually result in a more equitable and even richer world in terms of material goods, well-being and happiness may still decline. If so, citizens of the world need to control not only the negative externalities of globalization, such as environmental destruction, but to face more directly the process of globalization itself, in so far as it entails a similar destruction of the institutions that protect individuals against market forces that are, of their very nature, indifferent to the fate of human beings.

REFERENCES Bhagwati, Jagdish (2004), In Defense of Globalization, Oxford and New York: Oxford University Press.

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Chang, Ha-Joon (2008), The Bad Samaritans, New York: Bloomsbury Press. Frank, Robert (1999), Luxury Fever. Why Money Fails to Satisfy in an Era of Excess, New York: The Free Press. Lane, Robert (2001), The Loss of Happiness in Market Democracies, New Haven, CT: Yale University Press. Putnam, Robert (2000), Bowling Alone, New York: Simon & Schuster. Stiglitz, Joseph (2002), Globalization and its Discontents, New York: W.W. Norton.

Index Abbot, P. 235, 236 action to increase happiness 343 global 348–9 group 345–6 individual 344–5 national 346–8 adaptation 141–2, 156, 310–11, 325 affect theory 45, 62 cognitive theory, interaction with 62–3, 64–5 as dominant explanation 63–7 empirical support 61 in evolutionary perspective 65–6 happiness definition 49 implications for happiness promotion 60 set-point theory, interaction with 61–2, 64, 65 tenets frequency of affect 58 mood as informant 58–9 motivation to act 60 needs gratification 59–60 theoretical plausibility 60–61 Affleck, G. 38 aggregate happiness maximization and social welfare 246–8, 307–9 happiness maximization as policy function 307–9, 314–15 happiness research and quality of government 248–9, 315–16, 317 happiness research objections 310–11 incentive distortions 313–14 political economic objections 311–13 welfare economic objections 309–10 Akerlof, G.A. 117, 206 Alesina, A. 11, 159, 162, 316 Allen, R.G.D. 309 Allport, G.W. 36 Allshouse, J.E. 108

Altonji, J.G. 202 Alvarez-Diaz, A. 271 Ameriks, J. 101 Anderson, C.S. 286 Andrews, F.M. 303, 326 Annas, J. 49 Argentina, democracy and happiness 263, 264 Argyle, M. 286 Aristotle 27, 241 Arnett, M. 281 Arrow, K.J. 205, 247, 309 aspiration treadmill 311, 325 attitudinal definitions of happiness 49–50 Bagwell, L. 135 Ball, K. 110 Barker, E. 241 Barro, R. 159 Bartolini, S. 137, 239 Baum, C.L. 111 Baumeister, R.F. 338 Becker, L.B. 106 Benabou, R. 159 Bender, K. 295 Benesch, C. 106, 306 Bentham, J. 45, 49, 241–2 Beresin, E.V. 116 Berlyne, D. 338 Bernheim, B.D. 107, 135 Beshears, J. 306 Bhagwati, J. 349 Binswanger, M. 143 Birdsall, N. 159 Biswas-Diener, R. 325 Bjornskov, C. 238, 239, 242 black workers’ perceptions of discrimination and psychological balance 202–3, 220 cognitive dissonance 204–6

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data 210–14 empirical results 215–20 perceived discrimination and racial wage gap 215–19 strategies to restore balance 219 wage hierarchy 219–20 methodology 214–15 psychological balance 202–3, 205–6 statistical discrimination 205, 206–10 worker strategies to restore balance notification 208–10, 219 shirking 208–10, 219 waiting 207–8, 210, 219 Blanchflower, D.G. 77, 162, 307 Blank, R. 202 Blundell, J.E. 110 Boehm, J.K. 329 Boker, S.M. 40 Bonatti, L. 137 Bourdieu, P. 238 brain imaging 305–6 Brehm, J. 238 Brenner, M.H. 288 Brickman, P. 311, 325 Brown, S. 144 Bruni, L. 105, 238 Buchanan, J. 247 Busseri, M.A. 331 Buys, L. 238, 239 Camerer, C. 306 Campbell, A. 71, 72, 86, 267 Campbell, D.T. 325 Cantril, H. 72 Carlyle, T. 28 Carver, C.S. 205 Chang, H.-J. 349 Charles, K.K. 316 Chekola, M.G. 50 China, subjective well-being 233, 257 choice see free choice; suboptimal choice and individual welfare Chrystal, K.A. 314 civic engagement 238–9 Clark, A. 162, 193, 295 Clark, A.E. 71, 72 Clore, G.L. 305 Coate, S. 205 Cobb, J.B. 307

cognitive dissonance theory 204 see also discrimination, perceptions of, and psychological balance cognitive theory 55, 59, 66, 67 affect theory, interaction with 62–3, 64–5 empirical support 57–8 happiness definition 49 implications for happiness promotion 56 set-point theory, interaction with 61–2, 64 tenets comparison 55 reflected appraisal 56 social construction 55 theoretical plausibility 56–7 Cohen, S. 287 Cole, H.L. 134, 138 Coleman, J. 238 Collins, L.M. 39 comparison theory 6, 7, 10, 45, 55 see also cognitive theory consumer choice and individual welfare 116–17 normative basis and evaluation metric happiness approach 99–100 revealed preference approach 99 obesity 108–10 previous evidence 110–11 and willpower 111–14, 115, 116 reverse causality 115 self-control behavior generalization 114–15 smoking 106–8 suboptimal choice due to limited willpower, identification of behavior prediction 101 ex post evaluation based on reported SWB 101–3 self-infliction of costs 101 TV viewing 103–4 heavy viewing and subjective well-being 105 willpower and choice set 105–6 consumer finance 144–5 consumption 10, 127–8, 345, 346–7, 348 see also relative consumption hypothesis

Index consumption norms 6, 134–5, 136, 345, 346 consumption tax 248, 346–7, 348 contentment 51–2 Contreras, D. 160 Corneo, G. 103 Costa, P.T. 302 Couch, K. 202 credit 144 Cress, D. 240 Crosnoe, R. 111 Csikszentmihalyi, M. 100, 103, 304, 324, 327 culture 53, 234–5, 259, 272–3, 290–91 Cummins, B. 53 Cummins, R.A. 72, 245, 324 Cutler, D.M. 108 Dafflon, B. 314 Daly, H.E. 307 Daly, M.C. 202 Damasio, A. 66 Davidson, R.J. 306 Davis, J.A. 73, 303 Davis-Blake, A. 240, 286, 295 Day Reconstruction Method 304–5 DDB Life Style Survey 289 de la Croix, D. 71, 142 debt 144–5 Deci, E.L. 73, 327, 332 decommodification 244, 274–5 Deheija, R. 146 Deiner, E. 127, 146 DellaVigna, S. 101 democracy 13, 232–7 democracy and happiness relationship 256–9, 269 Argentina 263, 264 East European countries 236 happiness levels predicting 266–7 predicting shifts in 268 Hungary 261, 262 Mexico 263, 264 Romania 261–2 Russia 233, 235–6, 237, 260–61 Slovenia 261, 262–3 South Africa 263–4, 265 South Korea 263–4, 265

353

Sweden 265 USA 265 Democracy in America (de Tocqueville) 29–30 democratic welfare regimes and happiness, causal link 271, 281–3 data 273–4 findings 277–81 measures construction happiness 275–6 politics 274–5 social capital 276–7 theoretical connections 271–3 democratization 259–64 Derenne, J.L. 116 Di Tella, R. 71, 163, 175, 240, 301, 307, 308 Diaz-Serrano, L. 72 Diener, E. 34, 35, 36, 50, 54, 57, 58, 77, 231, 232, 245, 272, 285, 288, 302, 303, 306, 316, 324, 325, 326, 331 direct democracy 234–5 discrimination, perceptions of, and psychological balance 202–3, 220 cognitive dissonance 204–6 data 210–14 empirical results 215–20 perceived discrimination and racial wage gap 215–19 strategies to restore balance 219 wage hierarchy 219–20 methodology 214–15 psychological balance 202–3, 205–6 statistical discrimination 205, 206–10 worker strategies to restore balance notification 208–10, 219 shirking 208–10, 219 waiting 207–8, 210, 219 divine predestination 52 domain satisfaction 70 conceptual framework 70–72 conclusions 85–7 data and methods 73–7 prior work 72–3 results actual happiness 77–82 domain satisfaction 81, 83–5 predicted happiness 79–80, 82–3 Dorn, D. 234, 235 Douglas, M. 136

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Happiness, economics and politics

Duesenberry, J. 128, 134, 135 Dutt, A.K. 143, 144, 146 dynamic systems analysis 39–40 East European countries, democracy and happiness 236 Easterlin, R. 6, 9, 10, 127, 139, 161, 307, 325, 339 Easterlin Paradox 9, 151, 152–3, 157, 307 economic growth and measured happiness 155–6 happiness and welfare 154–5, 157 income and measured happiness 151–3 income-happiness positive relationship, recent study 153–4 economic globalization 349 economic growth 154–6, 257, 259 economics and happiness 97–117, 127–47, 151–7, 158–96, 202 Edgeworth, F.Y. 304 Edwards, R. 287 Eggers, A. 163 Ehrhardt, J.J. 5, 54, 302 Elazar, D. 272, 290 electronic diaries 38, 304 Elliot, A.J. 332 Ellison, C.G. 146 Emmons, R. 324 environmental issues 347, 348 Erikson, K. 287 Esping-Andersen, G. 243, 244, 274 Estes, R. 307 eudaimonic well-being 35–6 Europe, inequality and happiness 160, 162, 164, 195 experience sampling method 304 Farmer, A. 207 Fehr, E. 306 Feldman, J. 274, 275, 281 Felton, A. 111 Fenwick, R. 287 Fernández-Dols, J.-M. 302 Ferrer-i-Carbonell, A. 72, 301, 311 Festinger, L. 202, 204 Finifter, A. 237 Finkelstein, E.A. 108, 109, 111 Fiske, S.T. 205

Flegal, K.M. 108 Ford, W.F. 111 Fordyce, M.W. 49 Formisano, R.P. 272 Forte, F. 314 Frakes, M. 115 Frank, R. 1, 10, 134, 135, 139, 141, 142, 248, 346 Frederick, S. 310, 325 Fredrickson, B.L. 60 free choice 259, 268–9 see also suboptimal choice and individual welfare Freedman, J.L. 54 Freeman, R.B. 295 Freud, S. 28–9 Frey, B.S. 9, 71, 103, 105, 117, 127, 234, 247–8, 249, 257, 285, 290, 295 Fukuyama, F. 238 Galay, K. 306 Galbraith, J.K. 143 Gardner, J. 57 General Social Survey (GSS) 73, 275, 303 genetic influence on subjective well-being 52, 324, 326 Gentzkow, M. 104 Germany, inequality and life satisfaction 164 Gilbert, D.T. 333 Gillett, A. 110 global action to increase happiness 348–9 global warming 348 globalization 349 Godbey, G. 72 Goodhart’s Law 314 government composition 245 decommodification 244 quality of 246, 248 size 241, 242 spending policies 242–3 taxation 248, 250 welfare state 243–5 see also social welfare and happiness maximization Graham, C. 71, 111, 233, 236 Greenberg, E. 287

Index Greeno, C.G. 116 Griffith, T. 250 Grob, A. 112 group action to increase happiness 345–6 growth 154–6, 257, 259 growth curve modeling 39 Gruber, J.H. 107, 108, 115, 316 Grunberg, L. 287 GSS see General Social Survey (GSS) Gundelach, P. 238, 243 habit formation 141–2 Hagerty, M. 54, 162 Hallock, K.F. 203 Hamagami, F. 39 Hammond, P.J. 309 happiness determinants of 8, 17 and economics 8–12 history of 3–5, 25–32 as life satisfaction 48–50 and politics 12–15, 271–3 as quality of life 46–7 theories of 5–8 see also affect theory; cognitive theory; set-point theory happiness maximization and social welfare 246–8, 307–9 happiness maximization as policy function 307–9, 314–15 happiness research and quality of government 248–9, 315–16, 317 happiness research objections 310–11 incentive distortions 313–14 political economic objections 311–13 welfare economic objections 309–10 happiness measures 302–7 asking people 303–4 brain imaging 305–6 Day Reconstruction Method 304–5 experience sampling method 304 U-Index 305 Harpfer, M. 164 Hayo, B. 72, 236 Headey, B. 37, 53, 57, 232, 324, 325 hedonic adaptation 141, 156, 310–11, 325 hedonic affect 51, 62–3

355

hedonic well-being 34–5 Heisenberg Uncertainty Principle 314 Helliwell, J.F. 238, 246, 248, 272, 282, 302 Hennigan, K.M. 104 Hero, R. 290 Hersch, J. 107 Hewitt, L.N. 272 Hicks, A. 289 Hicks, J.R. 309 Hirsch, B.T. 290 Hirsch, E. 240 Hirsch, F. 134 homeostatic theory 53, 54 Hopkins, E. 136 Horn, J.L. 39 Horthcott, H.C. 288 Houser-Marko, L. 327, 332 Hsieh, C.M. 72 Huang, H. 246, 248 Huber, E. 245, 275, 289 Hudson, J. 239 human well-being 33–4, 40–42 eudaimonic well-being 35–6 hedonic well-being 34–5 psychological well-being (PWB) 5, 34, 36, 41–2 research, methodological innovations 36–7 dynamic systems analysis 39–40 growth curve modeling 39 intensive bursts designs 38–9 longitudinal panel designs 37–8 subjective well-being (SWB) 4, 34–5, 41–2, 302 Hungary, democracy and happiness 261, 262 Hunter, J. 100, 304 income and happiness 151–3, 156, 158, 172 individual action to increase happiness 344–5 inequality 11–12, 158–61, 249 inequality and individual welfare in Latin America 11–12, 160–61, 195–6 data 165–7, 168–9 inequality, effects of 167, 170–78

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Happiness, economics and politics

Honduras and Chile example 178–9 illustration of 178–82 inequality and well-being, perceptions of 182–92 Chile and Costa Rica example 188 redistribution 164–5, 196 unemployment, costs of 191, 192–4 inequality and well-being studies 161–5 Inglehart, R. 53, 232–3, 234, 235, 237, 245, 272, 276, 290 Inkeles, A. 234, 245 intensive bursts designs 38–9 Isherwood, B. 136 Jackson, P. 287 Jahoda, M. 41 Johnson, D.M. 49 Kahneman, D. 34, 49, 72, 99, 100, 301, 302, 304, 305, 306, 308, 325, 326, 339 Kasser, T. 57, 63, 105, 248–9, 339 Kelman, M. 100 Kenny, D.A. 39 Keyes, C.L.M. 36, 37, 328 Kingdon, G. 164 Klingemann, H.-D. 232–3, 268 Knight, J. 164 Kohn, M. 287 Koivumaa Honkanen, H. 302 Komlos, J. 110 Korkeila, M. 111 Kornhauser, M. 250 Kornienko, T. 136 Korpi, W. 240 Koszegi, B. 108 Kranton, R.E. 117 Kreiner, S. 238, 243 Kroll, C. 239 Krueger, A.B. 302, 305 Kubey, R. 103 Kuhn, P.J. 203 labor organization and life satisfaction in US States 293–5 analysis 289–90 aggregate level 293 individual level 290–92 conclusion 293–4

unionization direct effects 286–8 societal effects 289 labor unions 14–15, 240–41, 295, 346 Lakdawalla, D. 108 Lalive, R. 193, 316 Lane, R.E. 2, 13, 240, 243, 272, 286, 288, 291 Latin America, democracy and happiness 236 Latin America, inequality and individual welfare 11–12, 160–61, 195–6 data 165–7, 168–9 inequality, effects of 167, 170–78 Honduras and Chile example 178–9 illustration of 178–82 inequality and well-being, perceptions of 182–92 Chile and Costa Rica example 188 redistribution 164–5, 196 unemployment, costs of 191, 192–4 Layard, R. 9, 71, 105, 247, 249, 301, 339 Lepper, H.S. 302 Levi, M. 240 Lieberman, D.R. 49 life satisfaction 47, 48–50, 303 life-time comparison theory 55, 58 Lindblom, C. 272 Linder, S.B. 142 Loewenstein, G. 117, 310, 325 Londono, J.L. 159 longitudinal panel designs 37–8 Loscocco, K. 287, 288 The Loss of Happiness in Market Democracies (Lane) 344 Loury, G.C. 205 Lowe, G.S. 288 Lucas, R.E. 36, 77, 325 Lucas Critique 314 Lundberg, S.J. 205 Luttmer, E. 162–3, 175 luxury fever 248 Lykken, D.T. 52, 324 MacCulloch, R. 71, 163, 175, 240, 301, 307 Macpherson, D.A. 290

Index Making Democracy Work (Putnam) 237 March, J.G. 71 Marx, K. 31 Maslow, A. 6 Mason, P.L. 202 Mason, R. 135, 136 materialism 248–9 McArdle, J.J. 39 McCarthy, J.D. 240 McDowell, I. 49 McElroy, S.L. 111 McLennan, M. 203 McMahon, D.M. 3 McMurrer, D. 162 measures of happiness 302–7 asking people 303–4 brain imaging 305–6 Day Reconstruction Method 304–5 experience sampling method 304 U-Index 305 Medoff, J.L. 295 Mexico, democracy and happiness 263, 264 Michalos, A.C. 55, 57, 71 Mickiewicz, E. 237 Miller, E. 238, 239 Mizen, P.D. 314 Moene, K. 164 Moller, V. 233, 236 Moral Consequences of Economic Growth (Friedman) 155 Mullainathan, S. 107, 316 multiple discrepancies theory 55, 71 Muraven, M. 115 Murray, C. 246 Myers, D.G. 288, 324 national action to increase happiness 346–8 National Happiness Indicator 317 national happiness maximization and social welfare 246–8, 307–9 happiness maximization as policy function 307–9, 314–15 happiness research and quality of government 248–9, 315–16, 317 happiness research objections 310–11 incentive distortions 313–14

357

political economic objections 311–13 welfare economic objections 309–10 Needham, B.L. 111 needs 59–60, 140–41 Nesselroade, J.R. 37, 40 Nettles, D. 4 network externalities 134, 135–6 Neumark, D. 203 Newell, C. 49 Nordhaus, W. 307 Nussbaum, M.C. 307 Oatley, K. 63 obesity, willpower and subjective well-being 102 hypothesis and data 111–12 obesity explanations for 108–10, 117 and subjective well-being, previous evidence 110–11 results 112–14 reverse causality 115 self-control behavior generalization 114–15 see also suboptimal choice and individual welfare objective happiness 49 O’Donoghue, T. 117 Offer, A. 110 Oishi, S. 127, 302 Olson, J. 287 Oreopoulos, P. 316 organized labor 14–15, 240–41, 295, 346 organized labor and life satisfaction in US States 293–5 analysis 289–90 aggregate level 293 individual level 290–92 conclusion 293–4 unionization direct effects 286–8 societal effects 289 Oswald, A.J. 57, 77, 111, 127, 162, 164, 193, 307, 311 Ouweneel, P. 244 overall happiness 50–52, 59, 62, 64 Pacek, A. 271 Parmagent, K.I. 146

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Paserman, M.D. 101 Pateman, C. 295 Pearlin, L.I. 112 personality trait 52–3 Peru, inequality and well-being 164 Peterson, C. 324 Pettinato, S. 164, 166, 233, 236 Pezzini, S. 316 Pfeffer, J. 240, 286, 295 Philipson, T. 108 Polanyi, K. 272 political participation 233–4 political parties 239–40 politics and happiness 231–2, 271–3 democracy 232–7 government composition 245 decommodification 244 quality of 246, 248 size 241, 242 spending policies 242–3 taxation 248, 250 welfare state 243–5 organized labor 240–41 political parties 239–41 social capital 237–9 see also social democratic welfare regimes and happiness, causal link; social welfare and happiness maximization pollution 347, 348 positional properties 134, 136 Positive and Negative Affect Schedule 36 positive psychology 7, 39, 41, 324, 325 post-authoritarian regimes 233, 235–6, 257, 258, 260–63 Postlewaite, A. 138 Powdthavee, N. 111, 311 psychological balance and perceptions of discrimination 202–3, 220 cognitive dissonance 204–6 data 210–14 empirical results 215–20 perceived discrimination and racial wage gap 215–19 strategies to restore balance 219 wage hierarchy 219–20 methodology 214–15 psychological balance 202–3, 205–6

statistical discrimination 205, 206–10 worker strategies to restore balance notification 208–10, 219 shirking 208–10, 219 waiting 207–8, 210, 219 psychological well-being (PWB) 5, 34, 36, 41–2 Psychological Well-Being Scales 36 Pugno, M. 306 Putnam, J.J. 108 Putnam, R. 2, 146, 237, 238–9, 240, 272, 281, 289, 290, 344, 346 PWB see psychological well-being (PWB) quality of life 46–7, 303 Rabin, M. 117, 306 racial wage gap see discrimination, perceptions of, and psychological balance Radcliff, B. 14, 231, 240–41, 244–5, 248, 271, 272, 273, 274, 275, 276, 282, 295 Rahn, W. 238 Rangel, A. 107 Rashad, I. 108 Raudenbush, S.W. 38, 39 redistribution 164, 171, 196, 282 relative consumption hypothesis 128–33, 146–7 alternative explanations of 133–6 consumption norms 134–5, 136 information issues 134, 135–6 instrumental motive 133–4 network externalities 134, 135–6 positional properties 134, 136 status consumption 135, 136 alternative formulations 136–40 alternatives to, and relationship with 140–45 adaption and habit formation 141–2 consumer finance and debt 144–5 consumption and time 142–3 needs 140–41 sales promotion activities 143–4 ethical and religious perspectives 145–6 religion and happiness 29–30, 146

Index Reno, R. 238 Ricks, D.F. 49 Robbins, L.C. 309 Roberts, R.E. 111 Robinson, J.P. 72, 303 Robinson, M.D. 305 Robson, A. 136 Rojas, M. 72 Romania, democracy and happiness 261–2 Rossi, S. 314 Ruiz-Belda, M.-A. 302 Ruscher, J.B. 205 Russia democracy and happiness 233, 235–6, 237, 260–61 happiness, fall in 54 inequality and well-being 163 Ryan, R.M. 57, 73, 327, 332 Ryff, C.D. 34, 36, 63, 73, 328 Saiz, M. 240 sales promotion and consumption 143–4 Sandvik, E. 302 Sanz-de-Galdeano, A. 108 Sapsford, R. 235, 236 Saris, W.E. 73 satisfaction 47–8 ‘Satisfaction With Life Scale’ (Diener et al) 36, 303 Sawhill, I. 162 Sayer, A.G. 39 Scheier, M.F. 205 Schimmack, U. 302 Schkade, D.A. 326 Schmitz, O.A. 49 Schoenbach, K. 106 Schor, J. 1, 10, 135 Schwarz, N. 58, 303 Schwarze, J. 164 Schyns, P. 294 Scitovsky, T. 141, 142, 339 Scollon, C.N. 100, 304 Seeman, M. 286 Segal, J.M. 140 Seifert, W. 72 self-control, lack of, and individual welfare 116–17 normative basis and evaluation metric

359

happiness approach 99–100 revealed preference approach 99 obesity 108–10 previous evidence 110–11 and willpower 111–14, 115, 116 reverse causality 115 self-control behavior generalization 114–15 smoking 106–8 suboptimal choice due to limited willpower, identification of behavior prediction 101 ex post evaluation based on reported SWB 101–3 self-infliction of costs 101 TV viewing 103–4 heavy viewing and subjective well-being 105 willpower and choice set 105–6 Seligman, M.E.P. 316, 324 Sen, A. 5, 47, 135, 307, 309 Senik, C. 163 set-point theory 6, 7, 45, 66 affect theory, interaction with 61–2, 64, 65 cognitive theory, interaction with 61–2, 64 empirical support 54 implications for greater happiness 53 theoretical plausibility 53–4 variants cultural view 53 divine predestination 52 genetic disposition 52 homeostatic maintenance 53, 54 personality trait 52–3 Shalev, M. 240 Shapiro, C. 206 Shin, D. 49 SHM see Sustainable Happiness Model (SHM) Simon, H.A. 71 Singer, B. 36 Slesnick, D.T. 309 Sloane, P. 295 Slovenia, democracy and happiness 261, 262–3 Smith, A. 135 Smith, T.B. 146 Smith, T.G. 110

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Happiness, economics and politics

Smith, T.W. 73 smoking, suboptimal choice and subjective well-being 106–8 see also suboptimal choice and individual welfare Snow, D. 240 social capital 237–9, 272–3, 276–7, 281, 288 social class 294–5 social comparison theory 55, 58 social construction, happiness as 55 social democratic regimes 245 social democratic welfare regimes and happiness, causal link 271, 281–3 data 273–4 findings 277–81 measures construction happiness 275–6 politics 274–5 social capital 276–7 theoretical connections 271–3 social movements 239–40 social networks 288, 344 social welfare and happiness maximization 246–8, 307–9 happiness maximization as policy function 307–9, 314–15 happiness research and quality of government 248–9, 315–16, 317 happiness research objections 310–11 incentive distortions 313–14 political economic objections 311–13 welfare economic objections 309–10 Solberg, E.C. 72 Sousa-Poza, A. 286 South Africa democracy and happiness 236, 263–4, 265 inequality and well-being 164 South Korea, democracy and happiness 263–4, 265 Spitze, G. 287, 288 Stanca, L. 105, 238 Startz, R. 205 status consumption 135, 136, 345 Steele, B. 272, 275, 276 Stephens, J. 245 Stephens, J.D. 289 Stevenson, B. 11, 153, 154 Stiglitz, J.E. 206, 349

Strack, F. 58, 303 Stutzer, A. 9, 71, 127, 193, 234, 247–8, 249, 257, 285, 290, 295, 325 subjective well-being (SWB) 4, 34–5, 36, 41–2, 50, 302 suboptimal choice and individual welfare 116–17 normative basis and evaluation metric happiness approach 99–100 revealed preference approach 99 obesity 108–10 previous evidence 110–11 and willpower 111–14, 115, 116 reverse causality 115 self-control behavior generalization 114–15 smoking 106–8 suboptimal choice due to limited willpower, identification of behavior prediction 101 ex post evaluation based on reported SWB 101–3 self-infliction of costs 101 TV viewing 103–4 heavy viewing and subjective wellbeing 105 willpower and choice set 105–6 Sun, E.M. 232, 272, 285, 325 Sukhtankar, S. 164 Sullivan, T.A. 145 Sumner, L.W. 50 Sustainable Happiness Model (SHM) 337–9 background 7, 325–7 studies, previous 327–9 study measures additional measures 332–3 self-concordant motivation 332 well-being 331 study overview and procedure 329–31 study results ‘change made’ group 335–6 hypothesis tests 334–5 preliminary results 333–4 subjective well-being, influences on circumstances 326, 327, 328–9 genetics 324, 327 intentional activities 326–9

Index Sutton, J. 240, 286 SWB (subjective well-being) 4, 34–5, 36, 41–2, 50, 302 Sweden, democracy and happiness 265 Tangney, J.P. 101 Tavits, M. 234 taxation 248, 250, 346–7, 348 Taylor, M. 238 Taylor, P. 110 television viewing 103–4 heavy viewing and subjective well-being 105 willpower and choice set 105–6 see also suboptimal choice and individual welfare Tellegen, A. 37, 324 temptation and individual welfare 116–17 normative basis and evaluation metric happiness approach 99–100 revealed preference approach 99 obesity 108–10 previous evidence 110–11 and willpower 111–14, 115, 116 reverse causality 115 self-control behavior generalization 114–15 smoking 106–8 suboptimal choice due to limited willpower, identification of behavior prediction 101 ex post evaluation based on reported SWB 101–3 self-infliction of costs 101 TV viewing 103–4 heavy viewing and subjective well-being 105 willpower and choice set 105–6 Tennen, H. 38 Terrell, D. 207 Thaler, R.H. 101, 301, 306, 339 Theil, H. 308 Thoits, P.A. 272 Tinbergen, J. 308 Tobin, J. 307 Tolbert, C.J. 290 Tomes, N. 162 trait theories 5–6 see also set-point theory

361

trust 238, 239, 272, 276–7 Tullock, G. 247 TV viewing 103–4 heavy viewing and subjective well-being 105 willpower and choice set 105–6 see also suboptimal choice and individual welfare Uehara, E. 287–8 U-Index 305 unemployment 192–4 Unger, H.E. 56 unions 14–15, 240–41, 295, 346 unions and life satisfaction in US States 293–5 analysis 289–90 aggregate level 293 individual level 290–92 conclusion 293–4 unionization direct effects 286–8 societal effects 289 United States democracy and happiness relationship 265 income and satisfaction 152 inequality and happiness 160, 162, 164, 195 labor organization and life satisfaction 293–5 analysis 289–93 conclusion 293–4 unionization, effects of 286–9 see also wage discrimination, perceptions of, and psychological balance Ura, K. 306 Van Boven, L. 339 van Praag, B.M.S. 72, 301, 311 Veblen, T. 1, 10, 135 Veenhoven, R. 5, 231, 235, 243, 244, 245, 247, 249, 285, 288 Vera-Toscano, E. 72 von Hagen, J. 314 wage discrimination, perceptions of, and psychological balance 202–3, 220

362

Happiness, economics and politics

cognitive dissonance 204–6 data 210–14 empirical results 215–20 perceived discrimination and racial wage gap 215–19 strategies to restore balance 219 wage hierarchy 219–20 methodology 214–15 psychological balance 202–3, 205–6 statistical discrimination 205, 206–10 worker strategies to restore balance notification 208–10, 219 shirking 208–10, 219 waiting 207–8, 210, 219 Wallerstein, M. 164 Warr, P. 72 Waterman, A.S. 34, 35 Watson, D. 36 Wearing, A. 53, 232, 324, 325 Weimann, G. 106 welfare and happiness 154–5, 157 welfare state 14, 243–5 well-being 33–4, 40–42 eudaimonic well-being 35–6 hedonic well-being 34–5 psychological well-being (PWB) 5, 34, 36, 41–2 research, methodological innovations 36–7 dynamic systems analysis 39–40 growth curve modeling 39 intensive bursts designs 38–9 longitudinal panel designs 37–8 subjective well-being (SWB) 4, 34–5, 41–2, 302 Welzel, C. 233, 237, 257, 259, 266, 268 Wessman, A.W. 49 Western, B. 240, 286 Williams, T.M. 104

willpower, lack of, and individual welfare 116–17 normative basis and evaluation metric happiness approach 99–100 revealed preference approach 99 obesity 108–10 previous evidence 110–11 and willpower 111–14, 115, 116 reverse causality 115 self-control behavior generalization 114–15 smoking 106–8 suboptimal choice due to limited willpower, identification of behavior prediction 101 ex post evaluation based on reported SWB 101–3 self-infliction of costs 101 TV viewing 103–4 heavy viewing and subjective well-being 105 willpower and choice set 105–6 Wills, T.A. 287 Wilson, E. 18–19 Wilson, T.D. 333 Wingenbach, E. 295 Withey, S.B. 326 Wolfers, J. 11, 153, 154 Wolff, G.B. 314 Woolcock, M. 238 World Value Surveys 303, 304 Young, P. 162 Zajonc, R.B. 66 Zak, P.J. 306 Zald, M.N. 240 Zautra, A. 39 Zevon, M.A. 37 Zolatas, X. 307