The Rise of China and Structural Changes in Korea and Asia

The Rise of China and Structural Changes in Korea and Asia Edited by Takatoshi Ito Professor, Graduate School of Econo...

Author: Takatoshi Ito | Chin Hee Hahn

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The Rise of China and Structural Changes in Korea and Asia Edited by

Takatoshi Ito Professor, Graduate School of Economics, University of Tokyo, Japan

Chin Hee Hahn Senior Research Fellow, Korea Development Institute, Korea

Edward Elgar Cheltenham, UK • Northampton, MA, USA

© Korea Development Institute 2010 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: 2009940659

ISBN 978 1 84844 855 1

02

Printed and bound by MPG Books Group, UK

Contents List of contributors

vii

Introduction Takatoshi Ito and Chin Hee Hahn PART I

1 2 3

5

7

8

19 43

65

IMPACTS ON KOREA’S ECONOMY

Understanding the post-crisis growth of the Korean economy: growth accounting and cross-country regressions Chin Hee Hahn and Sukha Shin The economic growth of Korea since the 1990s: identifying contributing factors from demand and supply sides Seok-Kyun Hur

PART III 6

CHINA AS A GROWTH ENGINE OF ASIA AND THE WORLD

Post-1990s’ East Asian economic growth Danny Quah China’s economic rise and its impact Zhang Yunling China’s rise and East Asian economies: towards a Sino-centric regional grouping? John Wong

PART II 4

1

97

142

IMPACTS ON KOREAN FIRMS AND WORKERS

China’s rise and production and investment growth in Korean manufacturing industries: channels and the effects Chin Hee Hahn and Yong-Seok Choi The impact of outward FDI on export activities: evidence from the Korean case Siwook Lee The rise of the Chinese economy and Korea’s job growth Dae Il Kim v

175

203 232

vi

Contents

PART IV 9 10 11

IMPACTS ON OTHER COUNTRIES

The rise of China and the sustained recovery of Japan Shin-ichi Fukuda East Asian production networks and the rise of China Fukunari Kimura The rise of China and structural change in Thailand Kanit Sangsubhan

Index

261 287 310

341

Contributors Yong-Seok Choi, Associate Professor, School of Economics, Kyung Hee University, Korea. Shin-ichi Fukuda, Professor, Faculty of Economics, University of Tokyo, Japan. Chin Hee Hahn, Senior Research Fellow, Korea Development Institute. Seok-Kyun Hur, Reseach Fellow, Korea Development Institute. Takatoshi Ito, Professor, Graduate School of Economics, University of Tokyo, Japan. Dae Il Kim, Professor, Department of Economics, Seoul National University, Korea. Fukunari Kimura, Professor, Faculty of Economics, Keio University, Japan. Siwook Lee, Research Fellow, Korea Development Institute. Danny Quah, Head of Department and Professor of Economics, London School of Economics and Political Science, UK. Kanit Sangsubhan, Fiscal Policy Research Institute, Thailand. Sukha Shin, Research Fellow, Korea Development Institute. John Wong, Research Director, East Asian Institute, Singapore. Zhang Yunling, Professor, Director of the Academic Division of International Studies, Chinese Academy of Social Sciences.

vii

Introduction Takatoshi Ito and Chin Hee Hahn RISE OF CHINA This volume consists of chapters that were originally submitted as papers to the KDI conference, Growth and Structural Changes of the Korean Economy after the Crisìs: Coping with the Rise of China, 21–22 July 2008. After the conference the chapters were revised in light of comments by discussants and other participants in the conference, as well as the editors. A common theme is the rise of the Chinese economy and its impact on Asia, in particular Korea. After a sharp downturn in 1998, the Asian economies have recovered. The V-shaped recovery and continuing growth in East Asia are impressive. Among others, China’s performance, with its apparent acceleration of growth, stands out. The chapter by Quah, (Chapter 1) describes the growth process of Asia, in particular China, and how that was made possible. He emphasizes the roles of high human capital investment, in particular education. In order to sustain growth, however, a country needs to maintain productive dynamism and improve its resiliency to shocks in response to changes in the economic environment. In this regard, the rise of China and its integration into the world economy is probably one of the most important changes in the world economy for the past several decades. Since the economic reform in the late 1970s, the Chinese economy has made tremendous advances in economic growth, driven by the expansion of a modern, export-oriented industrial sector. The growth rate has been around 10 percent since 1991. At this rate of growth, the size of the economy doubles every seven years, just as Japan’s did in the 1960s and 1970s. The chapter by Wong (Chapter 3) compares the Chinese economic development to earlier episodes in Japan, Korea and other Asian economies. China’s rise has been accompanied by another important development in the world economy: fragmentation of production. For the past several decades, the fragmentation of production, driven by the technical progress which allows more finely divided production processes to find their best location worldwide, has allowed the formation of so-called regional 1

2

The rise of China and structural changes in Korea and Asia

production networks. This phenomenon is most pronounced in East Asian region, with China providing the preferred production location for many production stages of many manufacturing goods. The impact of the Chinese economic developments was felt all over the world. Foremost, the rapid growth of China, or the improvement of the standard of living of more than 1.3 billion people, reversed the trend in world income distribution which had been worsening for about 200 years since the industrial revolution. Meanwhile, a sharp rise in exports, especially after 2001, to the United States and Europe raised concerns in these countries, not only because of claimed displacement of jobs but also because of a sense of unfairness relating to the near fixed exchange rate to the US dollar. The global imbalances – large Chinese current account surpluses and large US current account deficits, among others – have provoked a debate in the G7 and the Internal Monetary Fund (IMF) since 2003. The rise of China also affected the Asian economies in a complex way. Its rapid growth meant that most Asian economies enjoyed a sharp increase of exports to China. For Korea and Japan, China became the number one destination of their exports. China became an engine of growth by absorbing more goods and accepting foreign direct investment (FDI). Chapter 2 by Zhang emphasizes this positive role of China. Nevertheless, the rise of China is also perceived as a threat, particularly to middle-income countries (for example, Lall and Albaladejo 2004; Gill and Kharas 2007). The huge increase in exports from China depressed prices of labor-intensive manufactured goods. This decline in manufacturing prices does not mean that labor-intensive growth strategies are impossible. It does, however, imply that they are more difficult to start and less effective in elevating incomes than they were in the past (World Bank 2008). Whether the rise of China benefits or hurts, on balance, other middle-income countries seems to be an empirical question. China’s rise has had a particularly large effect on the growth and structural transformation of the Korean economy through various channels. Above all, the rapid growth of the Chinese economy has provided a large export market for Korea. Between 1990 and 2007, China’s share of Korea’s exports rose from 0.9 percent to 22.7 percent. Major beneficiaries were capital- or skill-intensive industries, such as steel, machinery, electronics and transport equipment. Also, the large supply of unskilled labor in China, together with the formation of the regional production network, provided geographically close Korean firms with the opportunity of lowcost production and outsourcing. As of 2003, China is the number one destination of Korea’s outward foreign direct investment, with about twothirds of outward FDI in the manufacturing sector going to China. At the same time, however, the intensifying competition with China in both the

Introduction

3

domestic and the foreign market had the effect of speeding up the decline in labor-intensive manufacturing industries. Overall, for the past several decades, the rise of China has facilitated the structural transformation of the Korean economy from labor-intensive to skill- and capital-intensive industries; the value-added share of light industries in Korean manufacturing has rapidly declined from 56.3 percent in 1980 to 32.6 percent in 2002. Also, China’s rise, together with its skill-biased technical progress, is likely to have contributed to the unprecedentedly rapid decline in employment share of manufacturing in Korea since the early 1990s. Thus, the rise of China has presented Korea not only with opportunities but also with several challenges for sustained catch-up growth. For example, the rapid pace of structural transformation requires a huge amount of labor and capital to be reallocated both across and within industries in a relatively short period of time. This process should have involved non-trivial adjustment costs. Also, Korea needs to maintain factor endowment conditions that are distinct from those of China in order to benefit from China’s rise. This requires, for example, upgrading the quality of human capital and enhancing innovation capabilities. How did Korea respond to these challenges? Several chapters in this volume try to provide at least a partial answer to this question by assessing the impact of China on Korea, and evaluating Korea’s growth performance in an era of China’s rise.

THE ASIAN CRISIS TO THE SUBPRIME CRISIS The Asian crisis of 1997–98 was an epoch in the region that made countries aware of the importance of economic integration and cooperation. The Association of South East Asian Nations (ASEAN) Plus Three framework has been firmly established and many regional meetings have taken place regularly to discuss wide-ranging issues: the Chiang Mai Initiative – the bilateral swap network; the Asian Bond Market Initiative – a cooperative arrangement to build bond market infrastructures to issue and trade Asian currency denominated bonds; and the Asian Bond Fund, I and II – central banks’ efforts to invest in Asian bonds and to create listed markets for Asian bonds. About ten years after the Asian crisis, the subprime crisis erupted in the United States. Many investment banks in the US and Europe suffered huge losses in having created, traded and dealt with securitized mortgage loans and asset-backed securities in general. Asian financial institutions, including sovereign wealth funds, are now agreeing to capital increases of these institutions. After the Asian financial crisis, the Western institutions

4

The rise of China and structural changes in Korea and Asia

were buying up near-bankrupt financial institutions all over East Asia. The tables turn occasionally in the financial world. We have just witnessed another example. In 2007, the crisis started in the housing sector in the US and by mid2008 the impacts of the credit crunch and difficulties among financial institutions were evident all over the world. In the initial stage of the global financial crisis, the economies in Asia, including Japan, remained largely unaffected, since the Asian financial institutions had not invested in the US housing-related securities. However, as US investors and financial institutions sold off assets in Asia as well as in other emerging markets in order to repatriate gains back home, the Asian markets became affected, especially after Lehman Brothers failed in mid-September 2008. In the fourth quarter of 2008 (at the time of writing), the US economy is slowing down substantially, and it will bring down the rest of the world too. It remains to be seen whether the Asian economies remain strong, keeping their growth rates high, with China and India being the new twin engines of growth in the region. The ultimate test of the so-called decoupling theory will come in the next few years. Some observers believed that the Asian crisis of 1997–98 had been predicted by Alwyn Young (1995, 2003) and Paul Krugman (1994), as they asserted that Asian growth was only possible due to high inputs of capital and labor, and sooner or later would hit the wall of supply constraint. There was a debate whether estimates by Alwyn Young were robust. Challenges came from Hsieh (2002) and Jorgenson and Vu (2005) asserting that growth was due to productivity increases. Some of their evidence, especially for Singapore, seem to contradict the Young hypothesis. The controversy over the source of growth is summarized by Quah (Chapter 1 in this volume). The sources of growth of the Korean economy are carefully explored by Hahn and Shin (Chapter 4 in this volume). According to them, total factor productivity (TFP) growth of Korea in the post-crisis period was estimated to be higher than in the pre-crisis period in the 1990s – lending support to the view that pre-crisis growth was mostly labor and capital input growth for Korea. An interesting question is whether Chinese economic growth produces evidence one way or the other.

KEY QUESTIONS So far, China’s economy seems to be invincible, and it looks almost certain by extrapolation that, at least in terms of the size of gross domestic product (GDP), China will overtake Japan in ten to 15 years, and the US

Introduction

5

economy in 20 to 30 years. So far, China has recorded current account deficits against East Asian countries, while it has recorded much larger current account surpluses against the US and Europe. From the mercantilist viewpoint, the rise of China is a blessing for Asian countries, while it may be a threat to the US and Europe. However, there are some doubts as to whether the trading pattern and growth trend will continue in the next few decades just like it did in the past few decades. Quah’s chapter in this volume (Chapter 1) puts China and East Asian countries into a historical pattern of growth in the world economy. Wong (Chapter 3 in this volume) reviews the long history of political economy in China. These chapters give a good basis for understanding the past and predicting the future. The following questions, regarding the impacts of Chinese growth upon Asian neighbors, have been frequently asked among policy-makers and researchers, and are repeated in several chapters in this volume. The first set of questions concern the pace of economic growth and its sustainability. Will China continue to grow at its current pace? There are several dark clouds on the horizon. First, the resource constraint: China may soon face ever-increasing resource costs, along with other countries, and may have to slow down to instal energy-saving technology. Second, a failure of macro policy management: Chinese Consumer Price Index (CPI) inflation and the property price bubble may throw the macro-economy into chaos. If China continues to allow only a gradual appreciation of its currency (the renminbi, RMB) and maintains a low interest rate, then this risk will increase. Third, the social unrest due to inequality: there are many signs that the fruits of economic development in China are not shared widely – at least, more unequally than in the previous Japanese and Korean experiences. Inequality certainly exists between the coastal region and the inland regions. Inequality is also felt between the rich and poor in the coastal area and major cities – on average high-income areas. Uneven development may hit a critical point at which social and political conflict may emerge to disrupt economic development. The second set of questions concerns China’s relationship to neighboring economies. Do the neighboring countries continue to benefit from China’s fast development? The neighboring countries both benefit and suffer from China’s rapid economic growth: benefits come from an increase in exports to China; and suffering may come from reduced exports to competing destinations, like Japan, the US, and Europe. Wong (Chapter 3 in this volume) emphasizes different impacts from China on Japan, newly industrialized economics (NIEs) and ASEAN countries. Middle-income Asian countries may be particularly vulnerable because they compete over a wide spectrum of goods against China. An interesting

6

The rise of China and structural changes in Korea and Asia

aspect of China’s rise in industrialization is that their exports are simultaneously rising from low-tech industries to high-tech industries. Rodrik (2006) shows that the Chinese export structure is much more sophisticated than can be predicted by the level of development. It has been frequently mentioned that Asia has followed a ‘flying geese pattern’, which is mentioned by Wong (Chapter 3, this volume). The leader, Japan, has upgraded its industrial structure from low-tech (toys, apparel, sandals) to mid-tech (radio, TV, and other not-so-sophisticated electronics goods, and steel), to high-tech (auto, shipbuilding, sophisticated machine tools). Japan released low-tech industry to other follower countries when it moved to mid-tech, and again released mid-tech when it moved to high-tech. Now, Korea is producing very sophisticated electronic goods, autos and other high-tech goods, second only to Japan. Thailand, Indonesia and Malaysia seem to be developing their mid-tech industries, sometimes with FDI companies from Japan and Korea. In a sense, China suddenly started to increase exports of low-tech to mid-tech goods simultaneously. Wong (Chapter 3, this volume) thinks that China’s exports will sooner or later compete with even Japan’s exports. China does not seem to be following the ‘flying geese’ pattern but is fast overtaking several birds in the formation. If this depiction is correct, the Asian countries will sooner or later lose their production platform to China. As China becomes a center of the regional economy, as Wong’s chapter predicts, will China use economic power for its political advantage? This may be beyond the scope of this volume, but is certainly an interesting international political economic question. Hahn and Choi (Chapter 6, this volume) examine the trade relationship between Korea and China: import competition, third-market competition, and exports from Korea to China. Regression results show that capital goods industry in Korea enjoyed a sharp increase in exports to China, especially after the Asian financial crisis, while import competition from China had negative effects on Korean manufacturing industries, especially before the crisis. Kim (Chapter 8, this volume) has examined the impact of trade with China on the Korean labor market. Sangsubhan (Chapter 11, this volume) argues that an impact of expanding Thai–Chinese trade has been the transformation of Thai manufacturing industries. Exports from Thailand to China became more capital-intensive than labor-intensive; and Thailand benefited from the ‘early harvest’ of agricultural products in the Thailand-China Free Trade Agreement. Kimura (Chapter 10, this volume) describes how various production networks in Asia have been developed, and how China is being integrated in such a production network. Fukuda (Chapter 9, this volume) has analyzed impacts on the Japanese economy. He shows that the capital-

Introduction

7

intensive, high-tech companies in Japan enjoyed an increase of exports to China. For Japanese production activities, dependence on exports to China has become more important than exports to the US. One possible piece that would solve the puzzle is the vast disparity of the level of development among the provinces and the limited mobility of production factors (capital, labor and technology) across provincial boarders. The coastal provinces are very much connected to the rest of the world, but inland provinces are left behind. Wage rates in the coastal regions have started to increase, while wage rates of the inland region remain flat. The limited mobility of workers due to various difficulties is well known. Foreign companies are reluctant to invest in projects in inland provinces, maybe due to unfamiliarity with local provincial governments, and high transportation costs. Thus, China will be able to continue exporting both low-tech and mid-tech industries, because in a sense it has many ‘countries’ within the national border. Lee (Chapter 7, this volume) found that Korean outward FDI generally had positive effects on subsequent exports, lending support to the beachhead hypothesis. China is an easy target in the blame game of international problems, because of the growing size of its economy and its growing influence. Just a few years ago, China was blamed for causing global imbalances and exporting deflation, as it produced more goods – in scope, variety and volume – and exported them to the rest of the world. The competing tradable-goods industries in the West felt the strong competitive pressure and prices tended to go down as China produced more. Thus, wages in these industries did not rise either. Kim (Chapter 8, this volume) showed that unskilled workers in Korea suffered from competition from China. Now, China is blamed for causing energy and commodity price inflation. As China imports more and more oil, precious metals and food, the rest of the world experiences price increases due to tightening global markets. A demand shock due to Chinese economic growth is regarded as exporting inflation, or a supply shock, to the rest of the world. In particular, how inefficiently China is burning oil and coal for electricity is a concern to the world, from both the energy price point of view and the environmental point of view. This is due to the sheer size of the Chinese economy. It is a small player, and its behavior affects the global price. Hence, there may be a limit to decoupling. In sum, the challenge is how we are going to reap the benefits of China’s rise while managing the risk that is associated with fast growth. Opportunities and risk reside in both China and its neighboring economies. Below are the summaries of each chapter. In Part I the three chapters, by Quah, Zhang and Wong, give a good overview of China’s remarkable

8

The rise of China and structural changes in Korea and Asia China as an engine of growth

Asia’s growth

(2) Zhang (1) Quah

Impact on others (3) Wong Impact FDI and Exports

Korea’s firms

Korean’s Economy

Japan

Thailand

(6) Hahn and Choi (7) Lee

(4) Hahn and Shin (5) Hur

(9) Fukuda (10) Kimura

(11) Sangsubhan

Workers (8) Kim

Figure 0.1

Flow chart of chapters

economic growth and its impact on its Asian neighbors. The Chinese economy is getting larger, and this growth is forecast to continue in the future. In Part II the two chapters, by Hahn and Shin, and by Hur, describe the impacts on the Korean economy. In Part III the chapters, by Hahn and Choi, Lee and Kim examine the impact of China’s growth on Korean firms and workers. In Part IV the two chapters, by Fukuda and by Kimura, describe impacts on the Japanese economy. The last chapter of the volume, by Sangsubhan, examines the impact on Thailand. Figure 0.1 provides a flow chart of the chapters.

PART I

CHINA AS A GROWTH ENGINE OF ASIA AND THE WORLD

Chapter 1: ‘Post-1990s’ East Asian Economic Growth’ by Danny Quah Immediately after 1997 the Asian economies were viewed as catastrophes of financial excess, corporate and political misgovernance, and diminishing returns to overinvestment. But they are now freshly restored as the world’s economic powerhouses, just as before the 1997 financial crisis when they were the growth miracles and the successes of a then-emerging consensus on managed economic development. From a broad perspective of global growth and income distribution, the economic successes of

Introduction

9

East and Southeast Asia are striking: poverty alleviation in China alone has recently accounted for 100 percent of that for all of humanity. Even if still relatively small in size, the current contribution to world economic growth from East and Southeast Asia already matches that of economies many times larger. When the rest of the world economy has temporarily slowed, East and Southeast Asia have provided a stabilizing force in world business cycles. How have underlying fundamentals for economic growth changed since 1997? Is the current growth path sustainable; and if so, what has brought that about? What role has China played in driving economic growth throughout East and Southeast Asia? Have patterns of trade changed towards greater global balance? This chapter finds that in the main, productivity growth has improved since 1997. Increasing inequality is no obstacle to poverty reduction provided that economic growth is sufficiently rapid. Finally, international trade patterns have shifted towards greater exchange within the region itself. Chapter 2: ‘China’s Economic Rise and Its Impact’ by Zhang Yunling China has achieved great success in developing its economy since it conducted economy-wide reforms and opened itself to the outside world. Since the late 1970s, China has become a leading world economy, the second-largest in terms of FDI inflows, the third-largest in foreign trade, the fourth-largest in GDP, One of the key factors for China’s success has been its integration into the world economic system, enabling it to use global market resources (markets, capital and technology). Accession to the World Trade Organization (WTO) has made the Chinese economy more open, transparent and integrated into the world economic system. China’s economic rise has been a positive factor in keeping the world economy dynamic since it has become an important engine for global and regional economic growth. The Asia and Pacific region is the source of most of China’s FDI inflows, as well as the principal destination of its exports. East Asia accounts for half of China’s foreign trade and more than 70 percent of FDI inflows. With its increasing exports and imports, China has become the major trade partner in the Asia-Pacific region, especially in East Asia. China’s economic rise has also brought about significant change in the global and regional economic structure and relations. China is one of the most important parts of the production network in the region and plays a crucial role in the balance of the regional and global trade structure. With such high growth of the economy, Chinese people have become richer. Aside from the steady increase of GDP per capita, a sizeable middle class is emerging. This will work as an internal force supporting

10

The rise of China and structural changes in Korea and Asia

Chinese economic growth. In new sectors, such as the telecommunications sector, the numbers of mobile phone, Internet and computer users are all increasing, bringing China into the world’s top rank. Along with the high economic growth, China’s production capacity has been significantly increased, and in many areas it has become the world’s largest producer, or is among the major producers, such as for color TV sets, refrigerators, DVD players, computers and so on. If the current trend continues, China may become the world’s second-largest country in foreign trade by 2010 and in GDP by 2025, after the United States. However, China is facing the new challenges in its economic development, including rising labor costs, rising prices of raw materials, environmental deterioration, and global market uncertainty. Chapter 3: ‘China’s Rise and East Asian Economies: Towards a Sino-Centric Regional Grouping?’ by John Wong China’s economy has chalked up spectacular performance since the start of its reform in 1978, growing at 9.8 percent a year for almost three decades. With a total GDP of US$3.4 trillion at market exchange rate, China’s economy today is about to replace Germany’s as the world’s third-largest after the USA and Japan. Speed combined with size creates its own dynamics. Accordingly, China’s economic rise has produced profound regional and global impacts. Regionally, China’s economy has become an important engine of growth for its neighboring economies, which are making use of China’s huge domestic markets (for both manufactured products and primary commodities) as a source of their own growth. China’s rise has also radically altered the region’s trade patterns and financial flows, catalyzing the process of regional economic integration. This is because China is the home of many regional supply chains (or regional production networks). Beijing has reinforced these trends by initiating several regional economic cooperation schemes such as the China–ASEAN Free Trade Agreement (FTA). It is well known that East Asia constitutes the world’s most dynamic economic region. Its growth process is marked by three waves: the rise of Japan; the rise of the four East Asian NIEs (newly industrialized economies); and, more recently, the rise of China. The first two waves were dominated by Japan. But the third wave, heavily gravitating towards China, promises to be politically and economically more significant than the previous two. As China continues to sustain its high economic growth, East Asia’s geopolitics and geo-economics will also shift. China is set to develop

Introduction

11

an even closer economic symbiosis with other East Asian economies. Economic activities in the region will then increasingly be drawn towards China, giving rise to a kind of economic grouping that is largely oriented towards China. Over the longer run, it would not be unrealistic to argue that the emerging Chinese-dominated grouping could well dwarf the past Japanese-dominated grouping, given China’s vast size and Japan’s unfavourable demographics. Such could be the scenario for a Sino-centric East Asian Economic Community in future.

PART II

IMPACTS ON KOREA’S ECONOMY

Chapter 4: ‘Understanding the Post-Crisis Growth of the Korean Economy: Growth Accounting and Cross-Country Regressions’ by Chin Hee Hahn and Sukha Shin Korea maintained miraculously high and sustained economic growth at least up until the 1997 financial crisis, but after the crisis, its growth has slowed down significantly. Exploring some empirical facts that are helpful for understanding the post-crisis growth performance of Korea, this chapter examines sources of growth of Korea’s economy for the period from 1981 to 2005, based on both primal and dual growth accounting methodology employed by Young (1995) and Hsieh (2002). Also, this chapter evaluates the post-crisis growth performance of Korea, using cross-country comparison of growth accounting results and cross-country regressions. Above all, it was found that the growth slowdown after the crisis has been mainly driven by the slowdown of per worker capital accumulation. By contrast, the estimated total factor productivity growth (TFPG) of Korea for the period from 2001 to 2005 seems higher than, or at least roughly comparable to, the estimated TFPG in the pre-crisis period of 1991–95. In these respects, there were no substantial differences between the results obtained from primal and dual growth accounting methodology. Next, the cross-country regressions reveal that the postcrisis growth slowdown of Korea’s economy can be largely attributed to world growth slowdown (decade effect) and East Asia-specific effects. In particular, it was found that the noticeable deceleration in per worker capital accumulation can be mostly attributed to some unknown factors which commonly affected East Asian countries. Viewed from an international perspective, the lowered post-crisis per worker GDP growth rate, as well as per worker capital growth, which triggered concerns and debates in varying contexts, still seems respectable. So, the slowdown in capital accumulation is likely to be mainly a story of the spectacularly high rate

12

The rise of China and structural changes in Korea and Asia

of capital accumulation in the pre-crisis period, not a story of ‘weak’ investment after the crisis. Chapter 5: ‘The Economic Growth of Korea since the 1990s: Identifying Contributing Factors from Demand and Supply Sides’ by Seok-Kyun Hur This chapter’s purpose is to identify major factors that explain the path of the Korean economy in the past decades and evaluate their relative contributions. To that end, the author devises two economic models, which contrast the recent changes in the determination of foreign exchange rate as well as the monetary policy rule that the Korean economy underwent right after the East Asian Currency Crisis in 1998. Converted into the corresponding structural vector auto regression (SVAR) systems with longrun restrictions, the estimation results confirm that Korea’s decreased rate of economic growth since 2000 seems attributable to the decrease in Korea’s potential growth rate.

PART III

IMPACTS ON KOREAN FIRMS AND WORKERS

Chapter 6: ‘China’s Rise and Production and Investment Growth in Korean Manufacturing Industries: Channels and the Effects’ by Chin Hee Hahn and Yong-Seok Choi In this chapter, the authors examine what effects the rise of China has had on the growth of production and investment of Korean manufacturing industries. In doing so, they consider three main aspects of trade relations between Korea and China: import competition, third-market competition and export to China. In addition, they further divide exports to China into capital goods exports and (non-machinery and non-capital equipment) intermediate goods exports. From various regression results, the authors obtain both positive and negative effects of China’s rise on the production and investment growth of Korean manufacturing industries. On the one hand, capital goods exports to China, rather than intermediate goods exports, are estimated to have positive effects on the production growth of Korean manufacturing industries, especially during the period after the crisis. Results based on further division of capital goods into two subcategories reveal that in particular exports of parts and accessories of machinery and capital equipment to China promoted the growth of industries. Although some evidence was obtained that outward FDI to China promoted intermediate goods exports to China, particularly before the crisis,

Introduction

13

the authors were not able to find evidence that it promoted exports of parts and accessories (of machinery and capital equipment). On the other hand, import competition from China was estimated to have negative effects on both production and investment growth of Korean manufacturing industries, especially before the crisis. Overall, the regression results suggest that the positive effects from China’s rise on the growth of Korean manufacturing industries have been strengthened after the crisis. Chapter 7: ‘The Impact of Outward FDI on Export Activities: Evidence from the Korean Case’ by Siwook Lee This chapter empirically investigates the relationship between outward FDI and exports in the case of Korea for the period after the 1990s. In particular, this chapter examines the issues by using three-tiered Korean data, comprising of aggregate, industry and individual firm levels. According to the estimation results, there is little evidence that the expanded FDI of Korean companies has replaced exports or other domestic production activities. Generally, the author finds that FDI complements exporting activities, and that such a relationship is most apparent in the high-technology industries and in the period after the financial crisis. The industry-level analysis, which is useful in identifying the net effect of FDI on overall manufacturing, further suggests that Korean outward FDI has a so-called ‘beachhead effect’ and thus plays an important role in promoting subsequent exports. In addition, as for Korean multinationals, the estimation results indicate that the FDI–exports nexus mainly works through intra-firm exports from parent companies to foreign affiliates. Finally, while China is a major destination of the Korean FDI and its importance is expected to be ever increasing in the future, the author observes that the linkage between FDI activities and the Korean trade with China seems to be weakened in the 2000s. To maintain the strong FDI– export nexus found in this chapter, it is therefore important for Korea to make great efforts to enhance the industrial structure and secure its competitive edge in advanced high-tech products and core components. Chapter 8: ‘The Rise of the Chinese Economy and Korea’s Job Growth’ by Dae Il Kim This chapter evaluates how the labor demands, or job growth potentials, of Korea have been affected by the increased economic trade with China. The analysis focuses on three channels: the increase in goods trade; the increase in competition in the world market arising from the export growth of China; and the increase in direct investment of Korean firms in China. The

14

The rise of China and structural changes in Korea and Asia

results indicate that the large surplus in goods trade with China has led to an increase in labor demand, except for unskilled men in Korea, but at the same time Chinese exports have increasingly taken away Korea’s share in the world market of the key products such as electronics, suppressing Korea’s domestic labor demands. Overall, the effects on aggregate labor demand do not appear to have been large, but the labor demands for unskilled workers in Korea have been relatively suppressed and their relative wages have fallen. Given that trade with China is expected to expand, the trend is likely to continue.

PART IV

IMPACTS ON OTHER COUNTRIES

Chapter 9: ‘The Rise of China and the Sustained Recovery of Japan’ by Shin-ichi Fukuda After prolonged recessions, the Japanese economy has recovered from the crisis in the first half of the 2000s and has recorded sustained growth in the last several years. Tremendous structural changes during and after the financial crisis were one of the main driving forces for the recovery. However, dramatic increases in exports were another. In particular, increases of Japanese exports to China were substantial in the 2000s and supported the recovery of the Japanese economy from its demand side. The purpose of this chapter is to examine the role of the exports to China for the recovery in the 2000s. The dependence of the Japanese export sectors on the Chinese economy has risen especially since the 2000s. China now almost surpasses the United States as destination of Japanese exports. The author’s vector autoregressions (VARs) show that Japanese production, which had been driven by exports to the United States until the mid-1990s, started to be driven by exports to China after the late 1990s. However, the effects on production were very different across sectors. The increased exports to China were beneficial for the recovery of manufacturing industries with advanced technology. They also had beneficial impacts on small firms with advanced technology. The impacts were, in contrast, insignificant for the recovery of labor-intensive small firms and of non-manufacturing firms. Consequently, the sustained growth during the last several years was accompanied by widening inequalities across sectors. The results suggest that the rise of China is an opportunity for several large firms with advanced technology but a threat to other Japanese firms, particularly labor-intensive small firms. Heterogeneous effects across firms in different industries and with

Introduction

15

different firm sizes might be problematic in terms of income distribution. Even in terms of resource allocation, the heterogeneous effects may cause efficiency losses if sectoral adjustment costs exist. It is the sectoral adjustment costs that magnify the threat of the rise of China. Some policies that mitigate the adjustment costs may increase complementarities between the Chinese economy and Japanese economy. Chapter 10: ‘East Asian Production Networks and the Rise of China’ by Fukunari Kimura This chapter argues that China has become an important player in East Asia’s production and distribution networks and that recent changes in location advantages in China may call for reshuffling of the networks extended by Japanese and Korean firms. The chapter starts by examining international trade statistics to confirm the enhancing role of China in production and distribution networks, then reviews the essence of the fragmentation theory, and discusses the impact of a rapidly changing China on the operations of Japanese and Korean firms. Chapter 11: ‘The Rise of China and Structural Change in Thailand’ by Kanit Sangsubhan The rise of China has profound implications for the economies of the members of ASEAN. Increasingly, ASEAN is depending on China markets and reducing its export share to Korea and Japan. In the case of Thailand, there exists a strong regional bias in trade as 45 percent of exports are channelled to ASEAN13 markets, with China’s share sharply expanding. The trade relationship between Thailand and China has become more complex and in line with the regional network. As a result, the pattern of production in Thailand has continuously changed.

REFERENCES Gill, Indermit S. and Homi Kharas (2007), An East Asian Renaissance: Ideas for Economic Growth, Washington, DC: World Bank Publishing. Hsieh, C. (2002), ‘What explains the industrial revolution in East Asia?’, American Economic Review, 92, 502–26. Jorgenson, D. and K. Vu (2005), ‘Information technology and the world economy’, Scandinavian Journal of Economics, 107(4), 631–50. Krugman, P. (1994), ‘The myth of Asia’s miracle’, Foreign Affairs, 73(6), 62–78. Lall, S. and M. Albaladejo (2004), ‘China’s competitive performance: a threat to East Asian manufactured exports?’, World Development, 32(9), 1441–66.

16

The rise of China and structural changes in Korea and Asia

Rodrik, D. (2006), ‘What’s so special about China’s exports’, NBER Working Paper 11947. World Bank (2008), The Growth Report: Strategies for Sustained Growth and Inclusive Development, Washington, DC: World Bank. Young, A. (1995), ‘The tyranny of numbers: confronting the statistical realities of the East Asian growth experience’, Quarterly Journal of Economics, 110(3), 641–80. Young, A. (2003), ‘Gold into base metals: productivity growth in the People’s Republic of China during the Reform Period’, Journal of Political Economy, 111(6), 1220–61.

PART I

China as a Growth Engine of Asia and the World

1.

Post-1990s’ East Asian economic growth* Danny Quah

1.1

INTRODUCTION

Since 1960, East and Southeast Asia (or, succinctly, ESE Asia) more than doubled its share of world gross domestic product (GDP) and increased per capita income at an average growth rate almost two and a half times that in the rest of the world.1 By 2006, ESE Asia was producing 24 per cent of the world’s $38 trillion GDP, with per capita income 79 per cent of world average. At the same time, ESE Asia has recently been both a stabilizing influence on and a steady contributor to world economic growth. In 1991, at the end of a sustained period of productivity slowdown in the US, GDP in ESE Asia increased by nearly 20 times the size of the decline in US GDP. In 2001, the end of the dotcom boom, ESE Asia’s GDP grew by double the growth in US GDP. Outside of these extreme events as well, ESE Asia’s contribution to world economic growth has been strengthening. Over 1992–2000, growth in ESE Asia’s GDP was 63 per cent that of the US; by 2002–06, that ratio had risen to 112 per cent. In 2006, China’s GDP growth alone was 64 per cent that of the US, even with China’s GDP still less than one-fifth the US’s. In no more than plain arithmetic, ESE Asia has recently contributed more steadily and in greater quantity to world economic growth than has the US. A still very poor China – having per capita income only 4 per cent that of the US – single-handedly added to world economic growth nearly two-thirds as much as did the US. These statements of GDP at market exchange rates describe contribution to the world’s exchange of goods and services better than, say, statements made at purchasing power parity (PPP) exchange rates. But, to be clear, since the latter almost uniformly adjust upwards the assessed incomes in poorer places – the Balassa–Samuelson effect that is manifest empirically as the so-called Penn effect – at PPP the economic performance of ESE Asia would be even more remarkable.2 However, because PPP calculations seek to evaluate better the welfare 19

20

The rise of China and structural changes in Korea and Asia

that accrues to a population, they are more appropriate when reporting, say, the condition of the world’s poor. Between 1981 and 2005 the number of people in the world living on less than PPP$1.25 a day fell from 1904 million to 1400 million, a reduction in world poverty of 504 million people (Chen and Ravallion 2008, Table 8b). Over this time, the East Asia and Pacific region saw its population in that low-income bracket decline from 1088 million to 337 million: this is a reduction of 751 million, and thus 50 per cent larger than the world’s decline overall. In fact, in China alone, the number of people living on less than PPP$1.25 a day fell from 835 million to 208 million, a fall of 627 million, already itself greater than the entire world’s poverty reduction. Both in its contribution to world growth and in reducing global poverty, the economic development of ESE Asia has emerged over the last halfcentury as perhaps the single largest significant force in the world. Three large events have played significant roles in this macroeconomic history, and in different directions. First, Japan – in 2006 still ESE Asia’s largest economy, at market exchange rates more than double the size of China – has seen growth slow dramatically to an annual rate of just 1.3 per cent since 1990, from an annual average of 10 per cent in the 1960s, and 4 per cent in the 1970s and 1980s. Second, China has, as a matter of simple arithmetic, powered a lot of the growth in ESE Asia: from a GDP level only 5 per cent of ESE Asia’s total on average through the 1960s, China grew to make up 23 per cent of total ESE Asia GDP by 2006, just as Japan’s share in ESE Asia shrank from an average of over 80 per cent in the 1960s to 55 per cent by 2006. At the same time as China experienced spectacular economic growth and dramatically reduced the number of its people living in extreme poverty, inequality within China also sharply increased (for example, Quah 2003). Third, the 1997 Asian Currency Crisis saw a sharp simultaneous fall in the value of many ESE Asian currencies: from June 1997 to mid-January 1998 exchange rates against the US dollar of the currencies of Indonesia, South Korea, Malaysia, the Philippines and Thailand fell by over 50 per cent, and that of Singapore, 20 per cent (Ito 2007, Figure 1.3). In Japan and in every single one of these Asian Currency Crisis economies, GDP growth turned negative in 1998, with the combined fall in these economies’ 1998 GDP amounting to 2.4 per cent of GDP in ESE Asia the preceding year. This chapter assesses the factors surrounding ESE Asia’s remarkable recent economic performance, paying attention to these three large events. It concludes that in the main productivity growth has improved since 1997; and that trading patterns have shifted more towards trade across different parts of ESE Asia itself. Provided economic growth is sufficiently rapid, increased inequality does not hinder reduction in poverty. The balance in

Post-1990s’ East Asian economic growth

21

ESE Asia has been that economic growth has been sufficiently high, and poverty reduction has taken place. In ESE Asia, it is growth rather than the reduction of inequality that has most successfully brought the poor out of extreme poverty. The remainder of this chapter is organized as follows. Section 1.2 presents, again, facts on the patterns of economic growth in ESE Asia, this time in greater detail. It highlights the importance of both China and the 1997 Asian Currency Crisis for shaping recent growth in the region. Section 1.3 considers sources of growth in ESE Asia: it studies the evolution of productivity in different parts of ESE Asia, and points to where the situation has changed and where it has not since the 1997 Asian Currency Crisis. The data here vary across sources but, in this chapter’s reading, show productivity growth in ESE Asia as neither significantly worse nor better than that elsewhere in the world. Some of the data indicate improvement in ESE Asian productivity growth since 1997. Section 1.4 analyses patterns of trade across ESE Asia. It shows the importance of integration within the region itself. China’s trade with the rest of ESE Asia has consistently been double that with either the EU or the US. Similarly, Japan and South Korea’s trade with ESE Asia (including China) had by the mid-2000s similarly grown to be double that with either the EU or the US. Although Japan and South Korea used to have one-third of their trade with the US, since the mid-2000s or earlier, it has been with China that each of them has had much the larger and rising trade share. Section 1.5 concludes. (The appendix provides details on the data used in this chapter.)

1.2

THE BASIC FACTS AGAIN, IN GREATER DETAIL

This section provides more detail and context for the description of ESE Asian growth given in the introduction. To begin, this section draws together and quantifies the significance of three key observations: the large economy that is Japan; the fast growth in China; and the relative economic slowdown in ESE Asia following the 1997 Asian Currency Crisis. All three of these are examined in the following. 1.2.1

ESE Asian Economic Growth after 1997

If Japan is excluded from ESE Asia, the income growth path for the entire region is practically unchanged before and after 1997 (Figure 1.1).3

US$ (millions), constant year 2000

22

The rise of China and structural changes in Korea and Asia 5 4

ESE Asia/Japan GDP Fitted, through 1996 Extrapolated

3 2 1 0 1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

Note: The exponential trend fitted for 1960–96 shows growth at 7.6% per year. The figure shows 5.1% accumulated underperformance in GDP relative to the extrapolated trend over 1997–2006.

Figure 1.1

ESE Asia GDP growth

To assess the quantitative significance of this observation, Figures 1.2 and 1.3 provide the same calculations for world GDP and ESE Asia (now including Japan) in turn. In both these cases the underperformance relative to trend is marked: for world GDP the accumulated underperformance relative to the 1997–2006 extrapolated trend amounts to 11 per cent; for ESE Asia, 27 per cent. By contrast the underperformance for ESE Asia (excluding Japan) is only 5 per cent. The post-1997 trend performance of ESE Asia excluding Japan, compared to that for the world economy, is noteworthy for how it contradicts a widely held view on the permanent and significant effects of the 1997 Asian Currency Crisis. Indeed, by historical standards the region appears to have performed better than the world economy overall. Figure 1.4 illustrates how much of this is due to a single economy, China alone. Over 1997–2006 ESE Asia – excluding China and Japan – underperformed 21 per cent relative to the historical trend. Admittedly, the standard used is exacting: even for 1997–2006 the annual growth rate for this bloc of economies still exceeded 6 per cent while the extrapolated trend growth rate of 7.4 per cent is twice the pre-1997 growth rate for the world economy overall. This trend growth rate is approximately the same as when China is included (Figure 1.1). This relative slowdown in growth relative to historical trend has not reduced the increasing weight of ESE Asia’s GDP in the world economy.

US$ (millions), constant year 2000

Post-1990s’ East Asian economic growth

23

50 40

World GDP Fitted, through 1996 Extrapolated

30 20 10 0 1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

Note: World GDP growth after 1997 indicates a slowdown relative to earlier the trend. The exponential trend fitted for 1960–96 shows growth at 3.7% per year. The figure has 10.6% accumulated underperformance in GDP relative to the extrapolated trend over 1997–2006.

US$ (millions), constant year 2000

Figure 1.2

World GDP growth

15 ESE Asia GDP Fitted, through 1996 Extrapolated 10

5

0 1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

Note: ESE Asia GDP growth after 1997 indicates a slowdown relative to earlier the trend. The exponential trend fitted for 1960–96 shows growth at 5.7% per year. The figure has 26.6% accumulated underperformance in GDP relative to the extrapolated trend over 1997–2006.

Figure 1.3

ESE Asia GDP growth

US$ (millions), constant year 2000

24

The rise of China and structural changes in Korea and Asia 4

3

ESE Asia/Japan + China GDP Fitted, through 1996 Extrapolated

2

1

0 1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

Note: ESE Asia, without China and Japan, shows a marked slowdown in GDP growth after 1997.

Figure 1.4

ESE Asia, without China and Japan, GDP growth

Figure 1.5 shows that except for Japan, Thailand and Indonesia, every single economy in ESE Asia has increased its share of world growth after 1997, compared to before. Across all of ESE Asia, excluding Japan, the share of world growth doubled to 20 per cent after 1997 from only 10 per cent before. Figure 1.5 holds three key messages. First, Japan and China necessarily dominate any discussion of the performance of ESE Asia, with South Korea a relatively distant third. Second, is that already stated: the great majority of economies in ESE Asia contributed more to world growth after 1997 than before. Third, the figure gives a dramatic illustration of group (conditional) convergence in the sense described by Barro and Sala-i-Martin (1992), Baumol (1986) and Quah (1997). Those economies that were originally richer grow more slowly; those that were originally poorer, faster. With Japan and China by 2006 over one-half and nearly one-quarter of all ESE Asia respectively, the dynamics in Figure 1.5 show growth patterns that imply a force for equality in the region. As earlier stated, one of the virtues of measurement at current market exchange rates is that the results directly assess contribution to a global exchange of goods and services. To that end, Table 1.1 shows how growth in ESE Asia in general and China in particular has begun to match in magnitude that of the US economy. By 2002–2006 ESE Asia grew by 12 per cent more than the US did, the ratio having steadily risen over the preceding decade. In that period China alone, although having per capita

Post-1990s’ East Asian economic growth

25

Japan Taiwan Korea, Rep. Hong Kong, China China Vietnam Thailand Singapore Philippines Malaysia Indonesia Cambodia

1960–1996 1997–2006 0

Note:

5

10 % share

15

20

The underlying data are in constant (year 2000) US$ at market exchange rates.

Figure 1.5

Table 1.1

Share of world growth before and after 1997 for individual economies in ESE Asia Ratio of GDP growth to the US across episodes

Ratio of GDP growth

1961–90

1991 (denominator value of US decline)

1992–2000

2001

2002–06

ESE Asia/US China/US

1.03 0.08

18.19 2.99

0.63 0.26

1.78 1.34

1.12 0.54

Note: In 1991 US GDP, measured in constant (year 2000) US$, declined, while growth in both ESE Asia and China remained positive. The column for that year uses the absolute value of the US decline in its denominator. Source:

Calculated by the author from data in World Bank (2008).

GDP only 4 per cent of that in the US, contributed 54 per cent as much as did the latter to world economic growth. The world economy was also stabilized by ESE Asia and China through periods of US slowdown. In 2001 when US growth dipped, ESE Asia and China grew by 78 per cent and 34 per cent more than the US. In 1991 when US growth turned negative, ESE Asia and China grew by 18 and three times, respectively, more than the US growth slowdown.

26

The rise of China and structural changes in Korea and Asia 1981

People (millions) income
1000 China

800

600 India

400

200

SSA

EAP\China

LAC

MENA SA\India

0 –2

0 –200

Note:

4

6

8

10

12

See Appendix for the abbreviations used and for further details.

Figure 1.6

1.2.2

2

Income and poverty 1981

Poverty

The contribution of ESE Asia and China in the world economy occurred, however, not just through adding to world GDP growth but also through reducing the absolute numbers of poor in the world. In 1981 the world’s population living on less than PPP$1.25 a day numbered 1904.3 million; by 2005, that number had fallen to 1399.6 million, a reduction of 504.7 million people (Chen and Ravallion 2008).4 In this time the population of China in that same income bracket fell from 835.1 to 207.7 million, a decline of 627.4 million. Thus, China single-handedly lifted more people out of extreme ($1.25/day) poverty than did the entire world. Figures 1.6–1.9 show four snapshots of the evolution of world poverty and economic growth, and provide a striking depiction of the significance of China (and the ESE Asian region) in this history. An animation that dynamically describes this historical evolution is available at http://econ. lse.ac.uk/staff/dquah/p/2008.09-wpdyn-2005.gif. Each bubble in the figures represents the state of a continental grouping or large economy – China and India, in particular, are explicitly given, as are East Asia and the Pacific (EAP) excluding China, and South Asia (SA) excluding India. Sub-Saharan Africa (SSA), Latin America and the

Post-1990s’ East Asian economic growth

People (millions) income
1000

1990

800 China 600 India

400 SSA

EAP\China

200

LAC

EECA

MENA SA\India

0 –2

0

2

4

6

10

12

10

12

See Appendix for the abbreviations used and for further details.

Figure 1.7

Income and poverty 1990

People (millions) income < US$ 1.25/day (PPP constant year 2005)

1000

1999

800 India

600

400

China SSA EAP\China

200

MENA

–2

0 –200

EECA

LAC

SA\India

0

Note:

8

–200 Note:

27

2

4

6

8

< US$ (000s) per capita (PPP constant year 2005)

See Appendix for the abbreviations used and for further details.

Figure 1.8

Income and poverty 1999

28

The rise of China and structural changes in Korea and Asia 1000

2005

People (millions) income
800

600 India 400 SSA China 200

LAC MENA SA\India

0 –2

0 –200

Note:

EECA

EAP\China 2

4

6

8

10

12

See Appendix for the abbreviations used and for further details.

Figure 1.9

Income and poverty 2005

Caribbean (LAC) and the Middle East and North Africa (MENA) also appear explicitly, with Eastern Europe and Central Asia (ECA) unavailable until 1990. (The Appendix provides more detail on the data and the construction of these figures.) The horizontal axis measures per capita GDP, in thousands of PPP constant year 2005 US dollars; the vertical axis measures in millions the number of people living on less than $1.25 a day, in PPP constant year 2005 US dollars. The location of each bubble is the state of the economy; the relative size of each bubble, the population. As population increases, the bubble grows in size. For 1981 China appears in the extreme upper left in Figure 1.6: it is poor on average and holds many extremely poor people. Over time, the China bubble sinks and moves to the right. Economic growth occurs and lifts hundreds of millions of Chinese out of extreme poverty. By 2005 China both holds fewer extremely poor people and is per capita richer than India and sub-Saharan Africa. Figures 1.6–1.9 also show that the rest of East Asia and the Pacific region have, in parallel with China, grown and successfully reduced poverty, although nowhere to the same magnitude as China alone. By contrast, the rest of the world has changed little in that same positive direction. The only other significant event is, instead, a negative one. Figures

Post-1990s’ East Asian economic growth

29

People (millions) income < US$ 1.25/day (PPP constant year 2005)

1000 China India

800

1990

600 1987 400 200 0 500

1000

1500

2000

2500

3000

3500

4000

4500

Per capita GDP (PPP constant year 2005 US$) Note: China and India are the only billion-people economies extant. Together they make up one-third of the world’s population.

Figure 1.10

Growth and poverty in one-third of the world

1.6–1.9 show sub-Saharan Africa’s GDP declined and poverty nearly doubled between 1981 and 2005. By 2005 the population of all of subSaharan Africa was only 58 per cent that of China but in absolute numbers sub-Saharan Africa had 85 per cent more people living in extreme poverty than had China. The impact of China on world poverty is not due only to its having such a large population. Figure 1.10 better brings out the comparison with India – the only other billion-people economy in the world – implicit in these preceding figures. Three features are particularly striking. First, compared to China over this sample period, India has both grown a lot slower and seen much less poverty reduction – indeed, the number of people in India living on less than US$1.25 a day has remained approximately constant despite economic growth. This rise in poverty is because of India’s increased population and its relatively stable income distribution (for example, Quah 2003). Second, while successful overall, China’s poverty reduction has not been uniform throughout this time. Between 1987 and 1990 when economic growth slowed, poverty in China increased markedly as well. Third, from the 1987–90 episode in China, on the one hand, and comparison of China’s and India’s historical experiences reported here, on the other, it is clear that neither the sheer size of China nor the fact of economic growth alone makes large-scale poverty reduction automatic.

30

The rise of China and structural changes in Korea and Asia

Growth has to be sufficiently rapid to overturn the negative effects arising from increases in population and in inequality.

1.3

SOURCES OF GROWTH

Thus, even as ESE Asia has risen to contribute significantly to world economic growth, it has significantly reduced world poverty and stabilized the world economy against downturns. Japan continues to be the largest economy in ESE Asia but its growth slowdown is more than matched by the increased growth of China. How has this state of affairs come about? And what are prospects for its continuing? This second question is particularly compelling in light of observations by Krugman (1994) and Young (1995) on the factor inputdriven nature of Asia’s economic growth, suggesting that Asia’s growth has occurred not through increases in productivity especially, but instead through unsustainable ‘mere sweat’ – nothing more than hard work and savings. This section draws on comprehensive cross-country productivity estimates recently constructed in Jorgensen and Vu (2005) (subsequently updated and kindly provided this author by Khuong Vu). These estimates extend past 1997 and therefore allow evaluation of the impact of policies put in place or changes arising from the Asian Currency Crisis. From differences in data sources and detail the estimates in Jorgensen and Vu (2005) do not match exactly, say, Young’s (1995, 2003) estimates for the pre-1995 sample Table 1.2. Some estimates are surprisingly close (those for Hong Kong, South Korea and Taiwan); others are notably different, especially those for Singapore and China. The estimates in Hsieh (2002) for Hong Kong, South Korea and Taiwan are close to those in Young (1995) and therefore also to those from Jorgensen and Vu (2005) used here, and are thus not repeated in the table. Young (1995) estimates total factor productivity (TFP) contribution in Singapore to be negative. Hsieh’s estimate for Singapore moves TFP contribution to be at least positive but the gap between the resulting 23 per cent and that from Jorgensen and Vu’s estimate remains large. Young (2003, Table 24, p. 1258) reports a baseline estimate of TFP growth of 1.4 per cent for China over 1978–98 but says also that the range −0.4 per cent to 5.6 per cent is plausible, depending on the assumptions a researcher wishes to impose. The maximum in this range would give a TFP contribution of 88 per cent, double that estimated by Jorgensen and Vu (2005). I am unable to reconcile completely the different productivity estimates for Singapore and China. For consistent treatment across a broad range of

Post-1990s’ East Asian economic growth

Table 1.2

Comparing estimated TFP contribution to economic growth

Economy

Jorgensen and Vu (2005) and updates, 1989–95 %

Alternate estimates %

Hong Kong

34

38

South Korea

24

24

Taiwan

37

42

Singapore

41

-7 23

China

31

44

19

Source

Young (1995) Table 1.5, p. 657, 1986–91 Young (1995) Table 1.7, p. 660, outside agriculture 1985–90 Young (1995) Table 1.8, p. 661, outside agriculture 1989–95 Young (1995) Table 1.6, p. 658 Hsieh (2002) Table 1.1, p. 509, E-P ratio1973–90 Young (2003)

Note: Each entry in the table is the ratio of TFP growth to output growth in per cent. The figures given under ‘Alternate estimates’ have varying sources, as described in the corresponding rows. When a source reports only TFP growth but not output over the appropriate sample period, I calculated the latter from World Bank (2008) using constant (year 2000) US$ GDP evaluated at market exchange rates.

countries and across time, I hereafter use the estimates given in Jorgensen and Vu (2005) and updates kindly provided by Khuong Vu. 1.3.1

Growth Decomposions

Figure 1.11 shows growth decompositions, before and after 1997, of three different large blocs: the G7, India and China. The focus is China; the G7 and India provide comparison examples. Before 1997 growth in China was driven heavily (over 23 per cent) by labour hours, certainly at a pace much greater than the G7 but also than India. After 2000, however, the principal factor-input driver for growth in China shifted to physical capital, from 27 per cent earlier up to 44 per cent. Throughout this time TFP growth was maintained. Compared to China’s shift, changes in the G7 and India have been less readily observable. Figure 1.12 shows similar decompositions, again before and after 1997, but now comparing the three largest economies in ESE Asia, that is, China, South Korea and Japan. China’s shift from labour hours to physical capital, already noted, is notable even in comparison with these other

32

The rise of China and structural changes in Korea and Asia 1989–1995

70

G7 India China

60 50

%

40 30 20 10 0 Total physical capital

Labour hours

Labour quality

Labour total

TFP

2000–2005

70

G7 India China

60 50

%

40 30 20 10 0 Total physical capital

Labour hours

Labour quality

Labour total

TFP

Note: The figures show the percentage contribution of each factor input and of productivity to output growth. The single largest change is China’s shift from growth through labour hours to growth through physical capital. Labour total indicates the sum of the contribution from labour hours and labour quality; the latter takes into account formal education. Source: The underlying data are from Jorgensen and Vu (2005) with subsequent updates kindly provided by Khuong Vu.

Figure 1.11

Growth accounting across the G7, India and China, before and after 1997

large Asian economies. The difference from Japan is most stark: in the latter physical capital’s contribution more than halved from 94 per cent to 40 per cent, with the slack taken up entirely in TFP. South Korea’s position, in contrast to both China and Japan, is remarkably invariant: before

Post-1990s’ East Asian economic growth

33

1989–1995

100

China South Korea Japan

80

%

60 40 20 0 –20

Total physical capital

Labour hours

Labour quality

Labour total

TFP

2000–2005

100

China South Korea Japan

80

%

60 40 20 0 –20

Note:

Total physical capital

Labour hours

Labour quality

Labour total

TFP

See note to Figure 1.11.

Figure 1.12

Growth accounting across China, South Korea and Japan, before and after 1997

1997 physical capital contributed 50 per cent of growth, labour 26 per cent, and TFP 24 per cent; after 1997, physical capital contributed 47 per cent, labour 30 per cent, and TFP 23 per cent. If growth in South Korea had been overly intensive in physical capital before 1997, little seems to have changed. Finally, Figure 1.13 shows growth decompositions, before and after 1997, for Hong Kong, Singapore and Taiwan, whose growth performance in connection with productivity has been studied intensively (Hsieh 2002;

34

The rise of China and structural changes in Korea and Asia 1989–1995

70

Hong Kong Singapore Taiwan

60 50 %

40 30 20 10 0 Total physical capital

Labour hours

Labour quality

Labour total

TFP

2000–2005

70

Hong Kong Singapore Taiwan

60 50 %

40 30 20 10 0 Total physical capital Note:

Labour hours

Labour quality

Labour total

TFP

See note to Figure 1.11.

Figure 1.13

Growth accounting across Hong Kong, Singapore and Taiwan, before and after 1997

Young 1995). Here, the interest is in how that performance has varied before and after the Asian Currency Crisis. The most striking feature in Figure 1.13 is the stability of TFP’s contribution to growth in both Hong Kong and Singapore but its dramatic fall-away in Taiwan, where physical capital investment has surged after 1997. Singapore has reduced its reliance on labour hours and increased the growth contribution from physical capital: the two changes together kept TFP contribution to overall growth invariant.

Post-1990s’ East Asian economic growth

35

70 60

China

50

S Korea

%

40 30 Japan 20 10 0 1980Q1

1985Q1

1990Q1

1995Q1

2000Q1

2005Q1

Note: The figure shows bilateral trade (exports and imports) between each of China, Japan and South Korea, in turn, and the rest of ESE Asia, reported as a percentage of total trade between each named economy and the rest of the world. Source: Author’s calculations based on International Monetary Fund (IMF), Direction of Trade Statistics (DOTS) October 2008, ESDS International, (Mimas) University of Manchester.

Figure 1.14

1.4

Changing trade patterns in ESE Asia

TRADE

The analyses in previous sections of this chapter have considered the growth performance of ESE Asian economies either individually or together as a bloc. However, to consider changing trade dynamics or to examine the role of China’s growth on other economies in the region, we need to study bilateral or multilateral patterns of national engagement, where these interacting economies are explicitly identified.5 Figure 1.14 shows the evolving patterns of trade between the rest of ESE Asia and, in turn, China, Japan and South Korea – the three largest economies in ESE Asia. Figures 1.14–1.17 break down these trade patterns further: the figures display the changing trade relations for, respectively, China, Japan, and South Korea with each other and with the European Union and the US. The vertical axis in Figure 1.14 measures total trade (that is, the sum of exports and imports) that each of the named economies

36

The rise of China and structural changes in Korea and Asia 70 60 ESE Asia 50

%

40 30

Japan

20

EU

10 US 0 1980Q1

1985Q1

S Korea 1990Q1

1995Q1

2000Q1

2005Q1

Note: The figure shows total trade (exports and imports) China undertakes with a particular trading partner – here the rest of ESE Asia, Japan, South Korea, the US and the EU in turn – as a percentage of total trade undertaken with the world. Trade with Japan has declined sharply; that with South Korea has risen markedly, although still remaining relatively small. Trade with both the US and EU has fluctuated but not trended significantly up or down. Source: Author’s calculations based on International Monetary Fund (IMF), Direction of Trade Statistics (DOTS) October 2008, ESDS International, (Mimas) University of Manchester.

Figure 1.15

China’s changing trade patterns

undertakes with the rest of ESE Asia, as a percentage of that named economy’s world trade. The vertical axis in Figures 1.15–1.17 measures total trade that the named economy undertakes with a specific trading partner, as a percentage of that named economy’s world trade. Taken together, Figures 1.14–1.17 demonstrate that trade within ESE Asia has been large, and that for a range of measures that within-bloc integration has continued to rise relative to that with the rest of the world. Figure 1.14 shows that trade for Japan and South Korea with ESE Asia have risen sharply, while that for China has remained consistently large. China’s trade with the rest of ESE Asia grew to as high a share as 60 per cent of China’s overall international trade: however, that ratio has fluctuated, rising from 40 per cent in the early 1980s to 60 per cent ten years after, and then falling gradually back down again to 35 per cent in 2008. By contrast, Japan and South Korea’s trade with the rest of ESE Asia only

Post-1990s’ East Asian economic growth

37

45 40 ESE Asia

35 30 25 %

US

20 EU 15 China

10 5 0 1980Q1

S Korea 1985Q1

1990Q1

1995Q1

2000Q1

2005Q1

Note: The figure shows total trade (exports and imports) Japan undertakes with a particular trading partner – here China, South Korea, the US and the EU in turn – as a percentage of the total undertaken with the world. Source: Author’s calculations based on International Monetary Fund (IMF), Direction of Trade Statistics (DOTS) October 2008, ESDS International, (Mimas) University of Manchester.

Figure 1.16

Japan’s changing trade patterns

increased steadily. The share of ESE Asia in Japan’s international trade doubled from 20 per cent in the early 1980s to 40 per cent in the mid-2000s. In South Korea’s international trade the share of ESE Asia rose from 35 per cent in the early 1990s to almost 50 per cent in 2006. Even after the decline in ESE Asia’s share in China’s international trade, however, Figure 1.15 shows that it remains double that of both the EU and US shares. China trades far more with ESE Asia than it does with either the EU or the US: this has consistently been so since 1980. Evident in the figure is also how South Korea has seen a marked rise as a trading partner for China, its share rising from only 0.5 per cent in 1990 to over 7 per cent in 2007. At the same time Japan’s share has declined sharply, from a high of 31 per cent of China’s world trade in 1985 to only 11 per cent in 2007. In Figure 1.16 and Figure 1.17 the looming importance of China becomes apparent. Japan’s trade with China rose from under 3 per cent of Japan’s world trade in 1980 to nearly 20 per cent in 2006. By 2007 Japan was trading more with China than it was with the US, even though the

38

The rise of China and structural changes in Korea and Asia

60 50 ESE Asia 40 %

30 US Japan

20

China

EU

10 0 1980Q1

1985Q1

1990Q1

1995Q1

2000Q1

2005Q1

Note: The figure shows total trade (exports and imports) South Korea undertakes with a particular trading partner – here China, Japan, the US and the EU in turn – as a percentage of the total undertaken with the world. Source: Author’s calculations based on International Monetary Fund (IMF), Direction of Trade Statistics (DOTS) October 2008, ESDS International, (Mimas) University of Manchester.

Figure 1.17

South Korea’s changing trade patterns

latter had accounted for over one-third of Japan’s world trade in the mid1980s. In the early 1990s China accounted for 3 per cent of South Korea’s trade; by 2006 that ratio had risen to exceed 20 per cent. In 2003Q3 South Korea’s trade with China exceeded that with the US for the first time. This difference has grown larger ever since, even though the US share of South Korea’s trade had been as high as one-third in the mid-1980s.

1.5

CONCLUSION

This chapter has provided a large-scale, global perspective on growth in East and Southeast Asia since the 1990s. It has traced, in particular, the importance of the rise of China and changes in the region since 1997, when the Asian Currency Crisis appeared to diminish economic prospects following decades of rapid economic growth.

Post-1990s’ East Asian economic growth

39

Many of the important conclusions have already figured in the introduction. But they are numerically memorable and so might be useful to repeat here. Even with 1997 having dramatically perturbed growth in ESE Asia, the region has more than doubled its share of world GDP at market exchange rates. Much of that has been due to China alone. Over periods of short sharp slowdowns in the rest of the world, ESE Asia has continued to grow in sufficient absolute volume of goods and services, and thus has stabilized the world against yet sharper downturns. China by itself has brought over 600 million people out of extreme poverty in the last quarter-century, accounting for pretty much the entire reduction in extreme poverty in the world. Productivity growth in the region overall varies, but in the main is neither consistently better nor worse than that elsewhere; according to one view productivity growth has improved since 1997. The data here, however, vary considerably across different sources. In trade, ESE Asia has become ever more tightly integrated. Both Japan and South Korea used to have one-third of their international trade with the US alone. However, since the mid 2000s, their trade with China has consistently exceeded that with both the US and the EU. In all three of these – ESE Asia’s largest economies – trade with the rest of ESE Asia has become by far the largest meaningful share of their trade with the rest of the world.

APPENDIX This appendix details sources and construction for the data used in this chapter. As explained in note 1, ‘East Asia’ in this chapter means China, Hong Kong China, South Korea, Taiwan, and Japan, while Southeast Asia denotes Cambodia, Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam. The term ‘G7’ refers to the collection comprised of Canada, France, Germany, Italy, Japan, the UK and the US. Wherever possible, for consistency, data are taken from World Development Indicators (WDI) (World Bank 2008). Thus, GDP and population data are from World Bank (2008), augmented by data on Cambodia, Taiwan and Vietnam from Jorgensen and Vu (2005) and Asian Development Bank (2008). The World Bank does not report data on Taiwan separately; nor are Taiwan’s numbers added to those for China, although they are put back in to make up world GDP.6 WDI contains no GDP data for Cambodia and Vietnam prior to 1993. Trade statistics are from IMF (2008). Like the World Bank the International Monetary Fund

40

The rise of China and structural changes in Korea and Asia

(IMF) does not report data on Taiwan and so the latter’s trade statistics have not been available to use in this chapter. In 1960 East and Southeast Asia (or ESE Asia), with 33 per cent of the world’s population, generated at market exchange rates 12 per cent of world GDP. That year the region’s per capita income was 35 per cent of the world average. By 2006 per capita income in ESE Asia had risen to 79 per cent of the world average. Holding then 31 per cent of the world’s population, ESE Asia produced at market exchange rates over 24 per cent of world GDP. In 2006 world GDP, measured in constant year 2000 US dollars, was $37.9 trillion, while the world’s population comprised 6.54 billion people. Over this period, 1960–2006, per capita income in ESE Asia grew at 3.7 per cent per year, exceeding the annual growth rate in overall world per capita income by 1.8 percentage points. Indeed, taking out ESE Asia, the rest of the world had per capita income growing at only 1.5 per cent per year over 1960–2006. In Figures 1.6–1.9 EAP stands for East Asia and the Pacific region; in Figure 1.6 ECA stands for Eastern Europe and Central Asia, LAC for Latin America and the Caribbean, MENA for the Middle East and North Africa, SA for South Asia, and SSA for sub-Saharan Africa. The poverty data are taken from Chen and Ravallion (2008), with some minor calculations added by this author. The PPP income data are from WDI (World Bank, 2008). Both variables use PPP constant year 2005 US dollars. PPP income data for Eastern Europe and Central Asia are unavailable before 1989, and so the ECA bubble does not appear until 1990. The GIF animation http://econ.lse.ac.uk/staff/dquah/p/2008.09wpdyn-2005.gif has first each underlying image generated in Microsoft Excel and printed as a collection of Postscript files. Then the entire sequence is strung together in LaTeX, emitted as PDF, and finally converted to animated GIF by ImageMagick (of course, alternatives to achieve the same outcome are available at each step: the piped Unix commands shown simply provide a particularly compact summary of the procedure).

NOTES *

I thank Chin Hee Hahn, Shin-ichi Fukuda, Takatoshi Ito, John Wong, Zhang Yunling, and other participants at the KDI Conference July 2008 for comments and suggestions. Delger Enkhbayar and Luke Miner provided research assistance. Khuong Vu was extremely generous with his time and data updates. 1. These are incomes at market exchange rates and measured in constant year 2000 US dollars. All numerical calculations in this section are the author’s, except where explicitly

Post-1990s’ East Asian economic growth

2.

3.

4. 5. 6.

41

described otherwise. By East Asia I mean China, Hong Kong China, South Korea, Taiwan and Japan. By Southeast Asia I mean Cambodia, Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam. These correspond to Asian Development Bank (ADB) (2008) terminology, except: (1) Japan is added to East Asia, because the interest in this chapter lies primarily in a geographical dimension, rather than a division across developing and developed economies; and (2) Brunei, Laos, Mongolia and Myanmar are excluded altogether because of insufficient data. Section 1.2 provides details on these and other statements about the underlying data. See Balassa (1964) and Samuelson (1964), and Penn World Tables (Heston et al. 2006). ADB (2008) discusses how it matters greatly which PPP – that for GDP, household final consumption expenditure, government final consumption expenditure, gross fixed capital formation, or a poverty-specific PPP – is used and to what end. By construction the accumulated underperformance over the fitted sample period is approximately zero. It is the out-of-sample outcome that is informative. Jones (1995) had previously used this technique to argue that the US economy had been on the same stable growth path from even before the Great Depression. These numbers use PPP indexes from the 2005 International Comparison Project (Asian Development Bank 2008). In this time the world’s population rose from 4.51 to 6.46 billion (World Bank, 2008). Explicit identification of trading partners featured prominently in convergence clusters discussed in Quah (1997). http://go.worldbank.org/44YJTN9WY0 (accessed September 2008).

REFERENCES Asian Development Bank (ADB) (2008), Key Indicators for Asia and the Pacific 2008, Manila: Asian Development Bank. Balassa, B. (1964), ‘The purchasing power parity doctrine: a reappraisal’, Journal of Political Economy, 72(6), 584–96. Barro, R.J. and X. Sala-i-Martin (1992), ‘Convergence’, Journal of Political Economy, 100(2), 223–51. Baumol, W.J. (1986), ‘Productivity growth, convergence, and welfare’, American Economic Review, 76(5), 1072–85. Chen, S. and M. Ravallion (2008), ‘The developing world is poorer than we thought, but no less successful in the fight against poverty’, Policy Research Working Paper No. WPS 4703, World Bank. Heston, A., R. Summers and B. Aten (2006), Penn World Table Version 6.2, September, Centre for International Comparisions of Production, Income and Prices, University of Pennsylvania. Hsieh, C.T. (2002), ‘What explains the industrial revolution in East Asia? Evidence from factor markets’, American Economic Review, 92(3), 502–26. IMF (2008), Direction of Trade Statistics, October. Ito, T. (2007), ‘Asian Currency Crisis and the International Monetary Fund, 10 years later: overview’, Asian Economic Policy Review, 2, 16–49. Jones, C.I. (1995), ‘R&D-based models of economic growth’, Journal of Political Economy, 103(3), 759–84. Jorgensen, D. and K. Vu (2005), ‘Information technology and the world economy’, Scandinavian Journal of Economics, 107(4), 631–50. Krugman, P. (1994), ‘The myth of Asia’s miracle’, Foreign Affairs, 73(6), 62–78.

42

The rise of China and structural changes in Korea and Asia

Quah, D. (1997), ‘Empirics for growth and distribution: polarization, stratification, and convergence clubs’, Journal of Economic Growth, 2(1), 27–59. Quah, D. (2003), ‘One third of the world’s growth and inequality’, in Theo Eicher and Stephen J. Turnovsky (eds), Growth and Inequality: Issues and Policy Implications, Cambridge, MA: MIT Press, pp. 27–58. Samuelson, P. (1964), ‘Theoretical notes on trade problems’, Review of Economics and Statistics, 46(2), 145–54. World Bank (2008), World Development Indicators (WDI), April. Young, A. (1995), ‘The tyranny of numbers: confronting the statistical realities of the East Asian growth experience’, Quarterly Journal of Economics, 110(3), 641–80. Young, A. (2003), ‘Gold into base metals: productivity growth in the People’s Republic of China during the Reform Period’, Journal of Political Economy, 111(6), 1220–61.

2.

China’s economic rise and its impact Zhang Yunling

2.1

INTRODUCTION

China has achieved great success in developing its economy since implementing a reform and opening policy. In just three decades, China has become a leading global economy, the second-largest in terms of foreign direct investment (FDI) inflows, the third-largest in foreign trade, and the fourth-largest in gross domestic product (GDP). One of the key factors for China’s success has been its integration into the world economic system, enabling it to access the global market and utilize global resources (capital and technology). Accession to the World Trade Organization (WTO) has made the Chinese economy more open, transparent and firmly integrated into the world economic system. Rapid economic growth has transformed China into a major player in the global and regional economies. China’s economic growth has been a positive factor in keeping the world economy dynamic, becoming an important engine for global and regional economic growth. Alongside high economic growth, China’s production capacity has significantly increased and, in many areas, it has become the world’s largest producer, or among the largest producers, for example of color TV sets, refrigerators, DVD players, computers and other appliances. If the current trend continues, China may become the world’s second-largest country in foreign trade and in GDP by 2010, after the United States. China’s economic rise has also brought about significant changes in the global and regional economic structure and relations. China is central to the East Asian production network and plays a crucial role in the regional trade balance. However, China is facing new challenges in its economic development: rising labor costs, the rising price of raw materials, environmental deterioration and global market uncertainty, to name a few. The issue of the sustainability of China’s economic dynamism has become a great concern for policy makers. 43

The rise of China and structural changes in Korea and Asia 16 14 12 10 8 6 4 2 0

19

90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07

%

44

Source: China Statistical Yearbook (1991–2007 versions), http://www.stats.gov.cn; UNCTAD, World Investment Report, 2007.

Figure 2.1

2.2

China GDP growth 1990–2007

CHINA’S ECONOMIC GROWTH

China has achieved great economic success due to its economic reforms and opening of the economy to the outside world that began in 1978. The average GDP growth rate was 9.7 percent during the period of 1979–2007 (Figure 2.1). China has had one of the fastest GDP growth rates in the world and became the fourth-largest economy in 2007. The rise in China’s GDP per capita (shown in Figure 2.2) has been equally rapid. In 1990, per capita GDP was only $342 based on market exchange rate weights. This doubled to a little more than $700 in 1997, and more than tripled again by 2007, when the per capita GDP reached $2482. How has the Chinese economy sustained high growth for so long? The foremost important factor is that China has conducted consistent reforms and opening policies. In particular, there are four major sources that have contributed to the country’s steady and high economic growth. 2.2.1

Rural Reform

China began its reforms in the rural region. In 1978, the Chinese economy was basically rurally based as the rural population accounted for 85 percent, and the rural sector contributed close to 30 percent of GDP.1 The rural economy was in a disastrous state at the time because of the collective commune system that had been in place. A major rural reform was therefore to abandon the collective commune system. By adopting

China’s economic rise and its impact

45

3000 2500

$

2000 1500 1000 500

Source:

07

06

20

05

20

04

20

03

20

02

20

01

20

00

20

99

20

98

19

97

19

96

19

95

19

94

19

93

China Statistical Yearbook (1991–2007 versions), http://www.stats.gov.cn/.

Figure 2.2 Table 2.1

China GDP per capita at current market prices 1990–2007 China’s grain output and labor force

Grain output* Rural labor** Note:

19

92

19

91

19

19

19

90

0

1990

1995

2000

2006

446 333.4

467 323.3

462 328.9

497 299.8

* Million tons; ** millions, including agriculture, forestry, husbandry.

the individual contract system and a more supportive agricultural policy, China succeeded in raising grain production and reducing poverty. For example, the population in poverty was down from 250 million in 1978 to 23.6 million in 2005, while only 2.5 percent of the rural population fell below the poverty line in the rural areas.2 Through these reforms, China secured an adequate food supply for its large population and simultaneously mobilized an abundant and cheap labor force for industrial development. China’s grain output increased while the labor force declined, as shown in Table 2.1. The stable and gradual transition of the agriculture and rural areas in general is crucial for China in its grand transformation from a planning system to a market system, and from a rural society to an industrialized society. 2.2.2

SOE Reform

The major goal of China’s reform is to change its old planning system and to establish a new market system. Among all of its reform agendas, the key is to reform its dominant, inefficient state-owned enterprises (SOEs). However, considering the significant importance of the role of SOEs

46

The rise of China and structural changes in Korea and Asia

Table 2.2

Share of SOEs in the economy

SOEs

1990

1995

2000

2006

Investment* Employment**

65.6 75.0

54.4 66.3

50.1 56.8

30.0 33.6

Note: * Share of SOE investment in total fixed assents; ** share of SOE employment in total industrial investment. Source:

China Statistical Yearbook, 1993, 2007.

Table 2.3

SOE Collective* Private

Sources of gross industrial value in China (billion yuan, current value) 1990

2006

1306.4 852.3 129.0

3072.8 917.4 6723.9

Note: * The collective enterprises are so-called township industries. Many of them are actually private enterprises but registered as collectively owned. Large numbers of SOEs have been converted to actual private ownership. This is the primary reason why the output of collective enterprises increased very slowly while those of the private sector increased quickly. Source: China Statistical Yearbook, 1993, 2007.

in the economy and the difficulty in changing the system, the Chinese government adopted a gradual approach for SOE reform. Two major reform measures have been taken: one is to change the majority of small and medium-sized enterprises (SMEs) into non-state-owned enterprises (NSOEs), while keeping the large ones state-owned; another is to open SOEs for competition and introduce shared ownership.3 As a result, SOEs have experienced fundamental restructuring as shown in Tables 2.2 and 2.3. By now (2009), even some large SOEs are no longer solely state-owned since they have either become shareholding enterprises or are jointly owned with FDI or local private companies. The gradual reform of SOEs has helped greatly in maintaining social stability during the reform process and preventing SOEs from sudden collapse, which would have created massive unemployment and social chaos. The declining role of SOEs in generating industrial output and employment has quickly been countered by the emerging NSOEs.4

China’s economic rise and its impact

2.2.3

47

SME Dynamics

The most effective reform that has contributed to China’s high economic growth is the development of NSOEs, which is referred to as ‘playing outside the system’ (outside of the planning and SOE system). In 2003, the Standing Committee of the People’s Congress issued the Small and Medium Enterprises Promotion Law to provide legal support to SME development and, in 2005, the State Council issued the document to encourage the development of private enterprises. Encouraged by these policies, SMEs,5 mostly owned by private investors, have developed very quickly in both the urban and rural areas (so-called ‘township industry’). In 2006, there were about 42 million SMEs in operation. These companies contributed 60 percent of industrial output, 62 percent of exports, 80 percent of urban and township employment, and 50 percent of tax revenue. About 52 percent of SMEs are in the manufacturing business while 35 percent are in retail and wholesale. SMEs are also major producers of labor-intensive goods for export.6 2.2.4

Market Opening

As an important reform policy, opening the market has played a significant role in sustaining Chinese economic dynamism. By opening the market, the Chinese government has adopted dual measures: reducing market protection – lowering tariffs and non-tariff measures (NTMs) and joining the WTO – and introducing FDI. This policy has helped to address development gaps (capital, technology and management) on the one hand, and integrate China’s economy with the world market on the other hand. By opening the market, FDI, SMEs and SOEs have to compete with each other in the Chinese market, which fosters economic efficiency.7 In the outside market, Chinese exporters have to compete with their international partners. The market-opening policy drives Chinese economic growth in an open environment. 2.2.5

Other Factors

The expansion of exports has played an important role in keeping the economy dynamic. With the exception of a few years in past decades, export growth rates have doubled or tripled GDP growth rates. China emerged as the third-largest global exporter from a minor player when it began implementing reforms and opening policy measures in the late 1970s. As a developing economy, high investment plays a crucial role in

48

The rise of China and structural changes in Korea and Asia

supporting long-term high growth in China. China has maintained a high savings rate and a high investment rate. About 60 percent of its growth has resulted from growth in capital stock, which leads to a high and increasing investment–GDP ratio. For example, the investment–GDP ratio during 1978–93 was about 30 percent but increased to above 40 percent after 2000.8 Investment motivation has stemmed from new industrial projects, new infrastructure and construction and real estate development (a booming home market). In actuality, the comprehensive structure of the Chinese economy has created some internal built-in stabilizers. China is a vast country with many regions. The differences among the regions – coastal, middle and western – offer economic flexibility and dynamic economic activity. The Chinese economy also encompasses all three levels of technological structures: high-tech (information, telecommunication, space, and shipbuilding), medium-tech (capital-intensive, machinery, transportation), and low-tech (labor-intensive). Basic industries established after 1950s were strong as they underwent reforms in ownership and management. These two characteristics have solidified China’s economic foundation while enhancing its potential more than other emerging economies, as well as rendering the economy more stable when countering economic instabilities and shocks. Moreover, China’s steady economic growth has been made possible by an effective and improved macroeconomic policy. For example, the Chinese economy was faced with overheating and very high inflation in 1993. But the Chinese government succeeded in realizing an economic soft landing by 1996 before the Asian financial crisis in 1997. Although the crisis still had a negative impact on the Chinese economy, the economy was able to revert quickly to a high growth curve by withstanding the direct contagion effects of the financial crisis. The general forecast for Chinese economic growth comes from four sources: (1) continuing urbanization; (2) developing the middle and western regions; (3) new waves of infrastructure construction (high-speed railway, subways, new airports and new ports); and (4) restructuring of the industries based on new technology. Given the country’s size and potential, China is expected to stay on its high economic growth track from now on. At present, the Chinese economy is faced with a combination of challenges that require a more effective policy response by the government, as well as a united effort by the business community. A serious challenge to economic growth is inflation that emerged from the second half of 2007 – first in the form of sharply rising food prices, and then sky-high energy and material prices. For the first time after a decade of low inflation, the

400

0

200

–10

0

–20

Source:

Import

Export Growth

06 20

20

20

20

19

19

19

19

19

Export

04

10

02

20

600

00

800

98

30

96

1000

94

40

92

50

1200

%

49

1400

90

US$ billions

China’s economic rise and its impact

Import Growth

Yearbook of China’s Customs Statistics, 1990–2007.

Figure 2.3

Growth of China’s foreign trade

Chinese economy is facing high inflationary pressure due to internal and external factors.9

2.3

ROLE OF FOREIGN TRADE AND FDI

By adopting the market opening policy, China intended to realize two goals: to capitalize on foreign resources (capital, technology and materials), and to explore foreign markets for exports. FDI inflow and demand from external markets have played very important roles in generating China’s economic dynamism. 2.3.1

Export-Led Strategy

Like other emerging economies in East Asia, China also adopted an export-led growth policy. The government has provided preferential policies for FDI and the export business (foreign exchange, tax refunds, and so on). The export sector generally serves four roles: (1) attracting FDI to use China’s cheap labor and cheap land for reprocessing products; (2) as a leading growth sector and a growth engine; (3) accumulating foreign exchange for importing equipment, technology and materials; and (4) creating jobs to absorb the unemployed SOE workers and rural labor force. Foreign trade has grown rapidly (shown in Figure 2.3). Total trade increased from $115.4 billion in 1990 to $2.2 trillion in 2007, growing on

50

The rise of China and structural changes in Korea and Asia

Table 2.4

Ex./GDP

Importance of export in Chinese economy (%) 1990

1995

2000

2006

2007

16.0

21.2

23.1

36.8

37.1

Source: China Statistical Yearbook, 1993–2007; China Foreign Trade Statistics, 2007.

average 18.9 percent every year. Exports increased from $62.06 billion to $1218 billion, growing on average 19.1 percent; and imports increased from $53.4 billion to $955.8 billion, or at an annual average rate of 18.5 percent. As a result, exports have played an increasing role in supporting Chinese economic growth, that is, China’s high economic growth has been greatly supported by its very dynamic development of foreign trade as shown in Table 2.4. 2.3.2

Role of FDI

FDI in particular has played a crucial role in the rapid growth of China’s exports. In general, FDI in China has two major strategies: one is to use China’s abundant and cheap labor for reprocessing products and reexports, and the other is to explore China’s potential internal market, that is, producing and selling locally. The special advantage plus China’s FDI friendly policy have made China a very attractive place for FDI inflows. The rise in FDI inflows is shown in Figure 2.4. FDI flow into China has grown significantly, with annual FDI inflow increasing to $45 billion in 1998 and to $74.8 billion in 2007, with the share of FDI stock in GDP as high as 23.4 percent in 2007 (Figure 2.5). Due to the increasing size of China’s GDP and rising domestic savings and investment, the share of FDI inflows into China as a percentage of gross fixed capital formation (GFCF), in addition to the share of FDI stock in China’s GDP have been declining. However, the role of FDI in China is still playing an important role in economic growth by virtue of the nation’s vast size, and its policy is still friendly to FDI. In the future, FDI will be met with a very different business environment from earlier years because of various factors such as rising labor costs, rising land prices, an integrated tax system and external market protection. Diversification of FDI is needed, for example a shift from labor-intensive to capital- and technology-intensive sectors. The source countries of FDI to China are shown in Figure 2.6. The unprecedented growth of FDI has been accompanied by China’s

51

800 700 600 500 400 300 200 100 0

19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07

US$ billions

China’s economic rise and its impact

Source: Foreign Investment Department of the Ministry of Commerce of the People’s Republic of China.

FDI inflows in China 1979–2007

50 45 40 35 30 25 20 15 10 5 0

07

06

20

05

20

04

20

03

20

02

20

01

20

00

20

99

20

98

19

97

19

96

19

95

19

94

19

93

19

92

19

19

19

19 Source:

91

FDI inflows/GFCF FDI stock/GDP

90

%

Figure 2.4

China Statistical Yearbook (1991–2007 versions) and http://www.stats.gov.cn/.

Figure 2.5

FDI role in Chinese economy

impressive progress in foreign trade and economic development. In general, FDI has been accompanied by capital, technology and management know-how; stimulated reforms among SOEs; upgraded workforce skills; generated employment and, ultimately, the growth of output and incomes. In addition to its important role in China’s economic growth, FDI has also helped to accelerate the Chinese economy’s transition to a market system and its integration with the world economy. FDI companies are a major source of China’s foreign trade. For example, in 2007, among China’s total exports, FDI companies contributed 57.1 percent, compared to SOEs at 18.4 percent and other domestic companies at 24.4 percent. When categorizing FDI by products, for

52

The rise of China and structural changes in Korea and Asia

KOREA (6.2%) OTHER AREAS (20.5%) PO, KOREA HTM JAPAN ASEAN EU15 USA OTHER AREAS

HTM (42.0%)

USA (7.8%)

EU15 (8.60%)

ASEAN (6.4%) JAPAN (8.6%) Note:

Realized FDI stock by source areas in PRC, 1990–2006.

Figure 2.6 Table 2.5

FDI share

Source of FDI flow in China Share of FDI in China’s reprocessing trade 1991–95

1996–2000

2001–05

2006

47.7

55.8

55.1

52.7

Source: China Statistical Yearbook, 2007.

example computers, electronics and other high-tech exports, the share of FDI’s contribution is even higher.10 Relying heavily on reprocessing production in China’s foreign trade, as shown in Table 2.5, the FDI-led trade structure has helped to develop China’s production network in the region.11 Contribution of FDI to China’s growth is shown in Table 2.6.

2.4

IMPACT OF CHINA’S ECONOMIC RISE

China’s economic rise has been felt strongly by others because it is a country with a large population and sizable economic scale, and has quickly integrated with the regional and global economy. In East Asia, we have witnessed the rise of Japan, four dragon economies (the Republic of Korea – ROK, Singapore, Hong Kong and Taiwan) and also Thailand and Malaysia. What are the differences between China and these other

China’s economic rise and its impact

Table 2.6

53

Contribution of FDI Inflows to China’s economic growth

Year

Realized FDI ($ bil.)

Shares of FDI in fixed-assets investments (%)

Contribution of FDI to industrial output (%)

Share of FDI in exports (%)

1993 1995 2000 2003 2006

27.52 35.72 40.72 53.5 63.0

12.1 15.7 10.5 8.03 4.6

9.2 14.3 22.5 40.77 15.9

27.5 31.5 47.9 55.48 58.2

Source:

http://www.fdi.gov.cn; http://www.mofcom.gov.cn.

countries? From the perspective of the export-led economic growth model, similarities abound in the form of export promotion policy and exports as a leading growth sector. However, some differences are obvious. For example, unlike Japan and ROK, China adopted an FDI-friendly policy, and FDI’s role in the export sector has been significant. Although Thailand and Malaysia have also adopted FDI-friendly policies, China has a more complex regional production network compared to these countries. Additionally, the ratio of FDI flowing into mainland China from Hong Kong and Taiwan is very high, comprising a ‘Grand China’ business network.12 The size and speed of Chinese economic development, especially the rapid rise of foreign trade in the regional and global market, makes China’s rise in the global economy a striking phenomenon in our time. As a rising economic power, the impact of China is very comprehensive. China plays the role of both a contributor and a competitor in regional and global economic development. 2.4.1

As a Growth Engine

China’s economic growth has made a large contribution to world economic growth. Although China’s economic weight in itself is not extraordinary, only 5.3 percent in 2006, China has enjoyed continuous high economic growth, which is instrumental in supporting the regional and global economy. For example, in 2006, the world created US$2605.2 trillion in new GDP. China alone produced US$293.5 trillion, amounting to more than 11 percent of the total global output, while the US contributed about 14 percent, and Japan only 3.7 percent.13 For the global manufacturing industry, China contributed 13.2 percent of industrial output in 2007, while the US contributed 20 percent. Based on these trends, in

Percentage of country’s total

54

The rise of China and structural changes in Korea and Asia

10 8 6 4 2 0 China

Japan

France

World

Source: World Development Report, 2008, Table 2.4

Figure 2.7

Average annual GDP growth rate during 2000–2006

2009, China’s contribution share will rise to 17 percent, while the U.S. will decline to 16 percent.14 Figure 2.7 shows the average annual growth rates in 2000–2006 of major economies, clearly indicating China in the lead. China’s share in global exports was 3 percent in 1995, 3.9 percent in 2000 and up to 8 percent in 2006.15 Now China is the leading producer and exporter of an increasing number of products, including TV sets, DVD players, cell phones, microwaves, computers and telecommunication equipment, as well as labor-intensive, capital-intensive and high-tech products. 2.4.2

As a Big Market

China’s economic growth is based on an open economic structure. High economic growth has created extended economic linkages, both imports and exports. The importance of China’s role as a big import market can be well demonstrated when compared to the trend of exports of the world’s two largest economies, the United States and Japan in recent years. Association of South East Asian Nations (ASEAN) exports as a whole to China have quadrupled from the mid 1990s, and its export share to China rose to 12 percent. The share of newly industrialized economy (NIE) (Singapore, ROK, Hong Kong and Taiwan, China) exports to China as a total has now surpassed that to the United States. All East Asian economies have increased their export share to China. The strength of China’s imports stems from two sources: the increase in domestic demand, in particular domestic consumption, as well as the surge

China’s economic rise and its impact

55

1990 2007

20 15 10

n pa Ja

e

iw an Ta

or ap ng Si

or

s pi lip

K

ne

nd ai

la Ph i

M

al

ay

ne do In Source:

Th

sia

0

ea

5

sia

Percentage of country’s total

25

Direction of Trade Statistics, IMF.

Figure 2.8

Export share to China’s market (in total)

of exports in reprocessed products. In the future, the increase in internal demand is expected to become more significant as the level of Chinese income rises. FDI flows can also create more trade between host and home economies. The FDI experience of Japan and Korea show sizable exports to China created as a result of FDI. For example, Korea has gained a large trade surplus with China because FDI-related exports increased very quickly. Currently, China is the largest or second-largest export destination for many economies in East Asia. Figure 2.8 shows that the export share to China for East Asia countries increased significantly between 1990 and 2007. From the mid 1990s, the annual growth rate of China’s imports approached 20 percent, and the share of its imports in GDP rose above 33 percent, far surpassing the US (12 percent) and Japan (9 percent). Chinese imports are a key factor in high intra-regional trade in East Asia.16 For many economies, exports to China represent the lion’s share in their trade increase. For example, the value of Japan–China trade has exceeded Japan–US trade since 2003. The export surge to China has become an important factor in stimulating Japanese economic recovery.17 More importantly, with its growing integration into the East Asian region, China plays a unique role in recycling capital through its trade balance in the East Asian region. According to Roland-Holst et al.

56

The rise of China and structural changes in Korea and Asia

Table 2.7

China’s bilateral trade balance scenario in 2020 (billion US, 1997 exchange rates)

Partner

Japan

NIEs

ASEAN

US

EU

ROW

Balance

−5

−135

−41

166

66

71

Source:

Roland-Holst et al. (2003), p. 19.

(2003), from the beginning of the 21st century China will continue to gain a huge trade surplus with the US and EU, and at the same time, a large trade deficit with East Asia.18 Table 2.7 shows China’s bilateral trade balances. China is expected to become another important engine for world economic growth (for regional economies in particular) based on the sizable increase of its domestic consumption tantamount to the United States. Currently, the surge of China’s imports is still highly dependent on its export expansion since about half of China’s imports are export-related, with an even higher proportion of the imports in the area of manufactured parts. A domestic consumption-led import structure will only continue to grow. Of course, on the other hand, China’s imports have sharply inflated domestic prices for many goods, especially certain raw materials and energy during the period of spiked energy prices. China’s imports can be seen as a double-edged sword, hurting itself as well as others by raising the cost of economic activities.19 2.4.3

Hub of Production Network

Because of its large accumulated investment and production capacity, China is a production hub with network linkages formed not just between host and home countries, but also with many other economies. This kind of network is also known as ‘parallel development’, which is different from the traditional vertical or hierarchical transfer of technology.20 With its continuous high economic growth, China is increasingly a central player in this production network, which significantly benefits regional economic growth.21 This network is representative of the ‘bamboo capitalism’ phenomenon in East Asia as a culminating feature of an FDI-driven supply chain that has created diverse and vibrant local industries around the East Asian region. The further the supply chains (the root system) are decomposed and extended geographically, the faster and more profuse the proliferation of new enterprises.22

China’s economic rise and its impact

Table 2.8

57

China’s FDI outflow 2003–05 ($ million)

Economy/area Total outflow ASEAN-10 ROK Japan Hong Kong, China

2003

2004

2005

2854.65 122.53 8.92 7.37 1148.98

5497.99 195.56 40.23 15.30 2628.39

12 261.17 157.71 588.82 17.17 3419.70

Source: 2005 Statistical Bulletin of the People’s Republic of China’s Outward Foreign Direct Investment (Non-finance Part), released by the Ministry of Commerce and the National Bureau of Statistics.

In the production network, China’s role is also changing, from a pure importer of foreign technologies and parts for reprocessing, to a technology and parts supplier. For example, during 2002–07, the highest growth of imported commodities from China was mainly parts and components of electronics, from 15 percent of total imports in 2002 to 30 percent in 2007.23 This trend is expected to increase further in the future. In recent years, China’s investment abroad has increased as well. While China’s FDI outflows are still small relative to global flows, the rate of growth is high, with the amount of investments rising from $0.3 billion in 1991 to $18.7 billion in 2007. FDI destination by country is shown in Table 2.8. By the end of 2007, the cumulative stock of China’s FDI outflows exceeded $93.7 billion. Chinese companies have become active in purchasing foreign companies from resource-oriented firms to manufacturing-oriented firms. Following China’s ‘investing abroad strategy’ and the rising cost of labor-intensive products (plus renminbi appreciation), more Chinese companies, including SMEs, have started to reallocate their production overseas.24 2.4.4

As a Competitor

China is a strong competitor in the regional and global market in many areas, not just for labor-intensive products, but also for capital- as well as technological-intensive products. Cheap labor, an FDI-friendly policy and the resulting large FDI inflows make China’s products very competitive. According to a study, the competition between China and East Asian economies on the US market increased significantly during the 1990s.25 However, general ‘product similarity’ is misleading since the products may be significantly different in each product category, level, and quality. If compared to China’s export expansion and the exports of the other

58

The rise of China and structural changes in Korea and Asia

East Asian developing economies, the trade-off effects are unclear but still may indicate the presence of a trade-off effect to specific products. 26 Furthermore, any negative effects that exports may have on other markets are well compensated for by the export surge to China.27 China is also facing competition from other developing economies in the low-labor-cost product market. China’s exporters are also challenged by rising labor costs and ‘discriminatory’ trade protection policies such as quotas or antidumping measures from not only the United States, but also developing countries like Mexico, Brazil and India.

2.5

NEW CHALLENGES

After three decades of high growth, the Chinese economy is facing great challenges that cast a shadow over its growth prospects. Chinese economic growth has followed the traditional industrial model – starting from lowtechnology, labor-intensive, massive manufacturing with high raw material and energy consumption. Such long-term high economic growth has created some serious imbalance. 28 The manufacturing sector has the largest weight in the Chinese economy, while the service sector is still too small. That is to say, Chinese economic growth has been largely driven by the expansion of the manufacturing sector (see Table 2.9). Because of its low level of technology, the growth of the manufacturing sector relied heavily on inputs of capital and materials, causing demand for raw materials and energy to grow very quickly. This trend translated into increased imports. For example, the annual energy consumption of China increased 1.39 times in 1995–2000, and 1.55 times in 2000–2006. The import of oil increased from 0.75 million tons in 1990 to 195 million tons in 2006.29 The Chinese economy is facing enormous pressure to absorb the soaring prices of energy and materials. Continuous growth has also led to serious environmental damage. The pollution of air, water, rivers and land has reached serious levels, even threatening human livelihoods in some areas. A serious environmental challenge is access to water. The country’s annual per capita water supply is only 25 percent of the global average. About 60 million people in China find it difficult to get enough water for their daily needs. More than threequarters of the water flowing through China’s urban areas is considered unsuitable for drinking. China’s overwhelming reliance on coal, that is, almost three-quarters of its energy needs, has polluted its air, and 16 of the 20 most polluted cities in the world are in China. China must reduce its coal dependence, but the lack of an affordable and clean alternative stands in the way. Much of

China’s economic rise and its impact

Table 2.9

Share of sectors in China’s GDP (%)

Manufacture Service Primary Source:

59

1990

2006

41.1 31.6 27.1

48.9 39.4 11.7

China Statistical Yearbook, 2000, 2007.

China’s pollution stems from paper and pulp mills, printing and dyeing factories, chemical plants and other small, unregulated township and village enterprises. 30 The environmental problem is engendering a range of social, political and economic challenges within China. Acid rain, resulting from sulfur dioxide emissions from coal burning, affects over one-quarter of China’s land, including one-third of China’s agricultural land, damaging crops and fisheries throughout the affected provinces. Environmentally unfriendly practices are exerting a profoundly negative impact on the country’s economy. The Chinese government has adopted a new ‘scientific development strategy’ by making environmental protection a priority. But China’s structural complexity and massive scale of environmental deterioration have made it very difficult to realize a clean and environment-friendly economy in a timely manner. In facing a more restrictive environment policy and increasing costs for environmental protection, many Chinese enterprises will be forced to undergo difficult restructuring in their operations, and many will have to close down. The key to future Chinese economic sustainability is to develop an energy-saving paradigm by adopting new technology and a new economic model.31 2.5.1

Export-Led Growth Model

China’s exports have met serious challenges. In the past, China’s export competitiveness was largely based on cheap labor, low land prices and a low renminbi exchange rate. Today, labor costs and land prices are much higher, with serious labor shortages seen in certain coastal areas. Scarcity of land supply leads to sharply increasing land prices. In many areas, it is difficult to secure new land for industrial expansion, in particular for starting new projects. Additionally, before 2008, the renminbi appreciated steadily (in relation to the US dollar), reducing profit margins for exports.

60

The rise of China and structural changes in Korea and Asia

A large number of enterprises in those areas have to either close down or move out. Also, Chinese exports have relied heavily on reprocessing products, with few innovative improvements made by the local enterprises. This makes Chinese companies very vulnerable to outside changes. For example, in Guangdong Province, which accounts for more than onethird of China’s machinery, electric and electronic exports, 78 percent of these export products are reprocessing products, and half of them have foreign brands. Few producers have invested in research and development (R&D).32 In 2004–2007, export growth rates slowed.33 A serious challenge now is the sharp decline of outside demand (especially from the three major markets – the US, EU and Japan) due to the effects of the worst global financial crisis since the Second World War. Chinese exports have declined sharply since November 2008: −2.2 percent, −2.8 percent, −17.5 percent, −25.7 percent and −17.1 percent respectively monthly from November of 2008 to March of 2009.34 It is expected that the recovery of the outside demand will be very slow, and the long-term trend may not support China’s continuous export expansion. There is no other big economy like China with such a high export–GDP ratio. Chinese economic growth requires that the country strengthen its internal dynamics and systems so as to be able to support future growth – more so in the domestic consumption-led sectors than in export-led sectors. However, considering the gradual growth in domestic consumption and increasing FDI production capacity in China, Chinese economic growth will continue to rely on the export expansion, though the structural changes must be made in facing the changing situation in the global market. 2.5.2

Growing Gaps

The dynamics of Chinese economic growth has come mostly from the coastal areas. Alongside high economic growth, the regional gap between the coastal and inland regions is increasing. Take household consumption as an example. The average level of consumption in Zhejiang Province (east coast) is 2.6 times that in Qinghai Province (Western inland).35 Aside from the geographical constraints, the gaps are also the result of government policy. Almost all special economic zones in which the government has provided preferential FDI and export policies have been concentrated in the coastal areas, since the coastal provinces and cities can provide a much better environment for investors compared to the inland regions. The coastal regions are a major source of China’s exports and imports. For example, the sum of exports from Shanghai, Guangdong and Jiangsu provinces reached almost 60 percent of China’s total exports in 2006 (up

China’s economic rise and its impact

61

from 55 percent in 1995), and Guangdong Province alone accounted for one-third of China’s exports in the same year (up from 40 percent in 1995).36 The transfer of industries from the coastal to the inland regions is supposed to occur in the natural progression of economic development. However, this process seems very slow in China, due to many factors including the physical cost of the management inefficiencies transferred from the inland regions. Many companies would rather move to other countries with cheaper labor and more incentives provided by the host government than tackle the rising cost of doing business in China. Although the Chinese government has adopted a Western Development Initiative since the late 1990s, by which more preferential incentives and support are given to the inland provinces, the gaps between the coastal and western areas may not be reduced quickly. Actually, the gaps between the urban and rural areas are even more striking. For example, taking the country as a whole, the level of household consumption in cities was 3.6 times rural consumption in 2006. Within a province, this gap is also very significant.37 Before 2006, the economic and social policies of the Chinese government favored urban development. Due to the fast growth of urban economies, both workers’ income and government tax revenues increased quickly, while the increase in rural income and infrastructural improvements were slower. This big gap encouraged more and more rural youth to move to urban areas for jobs. Although the remittances to their hometowns helped increase the income of their rural families, the lack of young laborers in rural areas negatively impacted agricultural production. Since 2007, the Chinese government has adopted more effective policies to support agriculture and to establish a basic rural social protection system (a mutual health care system and basic educational support). The situation in the rural areas has since been improving (also partly attributable to higher grain prices). The Chinese economy is currently facing several new challenges, including structural imbalance, downward trend of growth and related high unemployment, slow recovery of the US economy and the uncertainty of financial markets stemming from the growing subprime credit crisis. The Chinese government has adopted strong measures to deal with the crisis and challenges, including a big stimulus package aiming at supporting economic growth, structural reform of industries by promoting innovation and establishment of the social safety net, helping to increase internal demand for the longer term. These measures seem to help the economy to keep a reasonable growth rate (7–8 percent growth rate). However, after continuous high growth for three decades based on a high investment and

62

The rise of China and structural changes in Korea and Asia

export expansion-led structure, Chinese economy is facing ever higher pressure to restructure. Although the above challenges are serious enough to command a great effort to be made, a majority of economists in China are still optimistic about future Chinese economic development and continuous economic growth, since as a large developing economy, its growth potential is still great.

NOTES 1. 2. 3.

National Bureau of Statistics of China (2000). Tang (2008), p.4. By 2006, more than 64 percent of SOEs were transformed into shareholding companies (China Institute of Reform and Development (2008), p. 151). 4. Although the number and share of SOEs have declined, their total assets, production and profits have increased significantly. For example, during 2003–06, the number of SOEs declined 20.7 percent, but assets increased 45.7 percent, sales value 50.9 percent, profit 147 percent, and tax contributions 72 percent. SOEs still dominate some major sectors like banking, insurance, oil and coal. Economic Daily, 12 July 2007, p. 1. 5. By definition, small enterprises have less than 300 employees and 30 million RMB in terms of annual sales value; and medium-sized enterprises have 300–2000 employees and 30–300 million RMB in sales value. 6. News Report, ‘State Economic Reform and Development’, People’s Daily (overseas edition), 7 June 2007; Lim (2007), p. 37. 7 .In fact, the Chinese economy has benefited both from operating in conjunction with FDI as well as in competition with FDI, given how FDI has encouraged more skilled labor, improved management and enhanced entrepreneurship. According to the study, the main factor contributing to China’s industrial growth is the increase in labor productivity resulting from open competition (World Bank, 2006. p. 7). 8. National Bureau of Statistics of China (1998, 2007). 9. But a reversed situation appeared in late 2008 due to the international financial and economic crisis that started from the subprime credit crisis in the US. The Chinese economy suffered from a sharp decline of outside demand. Exports witnessed two digit rate reduction and economic growth slowed down to 6.8 percent in the fourth quarter of 2008. The inflationary pressure quickly turned to deflationary pressure since both the Consumer Price Index and the Production Price Index turned to negative rates. 10. For example, about 70 percent of China’s machinery, electric and electronics exports originated from FDI companies in 2005. China Mofcom statistical data, 2008, www. mofcom.gov.cn. 11. For example, close to 40 percent of China’s imports were based on reprocessing trade in 2007, (www.mofcom.gov.cn). 12. The majority of FDI from Hong Kong is actually money owned by Chinese companies, with overseas businesses as a way for them to enjoy the policy preferences exclusive to FDI. 13. National Bureau of Statistics of China (2007), www.stats.gov.cn. 14. Estimated by Global Insight, reported by the Financial Times, 11 August, 2008. 15. National Bureau of Statistics of China (2007), www.stats.gov.cn. 16. Gill and Kharas (2007), p. 6. 17. Economic Daily, 3 December, 2003; Lianhe Zaobao, 17 February 2004. 18. Roland-Holst et al. (2003), p. 19.

China’s economic rise and its impact 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37.

63

We saw a significant increase in the prices of steel, oil and some other raw materials on the world market in 2003 because of the surge in China’s imports. Referred to as ‘a new paradigm for East Asian economic development’, (Chen 2002), p. 10. Krumm and Kharas (2003), p. 23. Roland-Holst et al. (2003), p. 16. Kanit Sangsubhan, Chapter 11 in this volume. For example, due to rising labor and land prices, appreciation of the renminbi and reduction of tax incentives, large numbers of SMEs in textiles, clothing and shoes manufacturing in Guangdong have begun to move to Vietnam and Cambodia. Kwan (2002), p. 8. Krumm and Kharas (2003), p. 23. According to the study, among the 16 sectors that were negatively effected, 11 consisted of the fastest-growing exports to China (Gill and Kharas (2007), p. 101). Xiao (2008). China Statistical Yearbook of 1991–2007. For example, industrial sulfur dioxide emissions in 2006 were 1.5 times those in 2001, and only 60 percent of the companies that created serious pollution have been stopped (only 36 percent in 2001) (National Bureau of Statistics of China, 2002, 2007). Stiglitz (2008), p. 155. The author’s study on China’s exports shows that the expansion of China’s exports relies heavily on an increase in existing goods, rather than new products. See also Xu (2008), p. 50. 21st Century Business Herald, 31 July 2008. www.customs.gov.cn, statistics. National Bureau of Statistics of China (2007). Nine provinces account for 90 percent of China’s exports. National Bureau of Statistics of China (2007). National Bureau of Statistics of China (2007).

BIBLIOGRAPHY Chen Yu-shi (2002), ‘A new paradigm shift in East Asian economic studies’, Ritsumeikan Journal of Asia Pacific Studies, 10, December. Chiba Institute of Reform and Development (2008), The Patch to a Stronger China, Beijing: China Economic Publishing. Gill, Indermit and Homi Kharas (2007), An East Asian Renaissance: Ideas for Economic Growth, Washington, DC: World Bank. Ho, O.C. (2004), ‘Determinants of foreign direct investment in China: a sectoral analysis’, paper presented at 16th Annual Conference of the Association for Chinese Economics Studies, Australia (ACESA), Brisbane, QLD, 19–20 July. Krumm, Kathic and Homi Kharas (2003), East Asia Integrates: A Trade Policy for Shared Growth, Washington, DC: World Bank. Lim, Hank (ed.) (2007), ‘Asian SMEs and globalization’, ERIA Research Project No. 5, Tokyo, available at: http://www.eria.org/research/no5.html. Ministry of Commerce and China National State Statistical Bureau (2006, 2007), Statistical Bulletin of China’s Outward Foreign Direct Investment, available at http://aaa.ccpit.org/Category7/mAttachment/2006/Dec/19/asset000070002035118file1.pdf. Ministry of Commerce, Department of Foreign Capital Utilization (2005), China’s Foreign Investment Report 2005, People’s Republic of China.

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National Bureau of Statistics of China (various years), China’s Statistical Yearbook, Beijing: China Statistics Press. Roland-Holst, David, Iwan Aziz and Li Gang Lin (2003), ‘Regionalism and globalism: East and Southeast Asia trade relations in the wake of China’s WTO accession’, ADB Institute Research Paper Series No. XX, January. Stiglitz, J. (2008), ‘Restructuring Chinese economy’, Speech on China Development Forum, 22–24 March, Beijing, China, in China Social Sciences (domestic edition), 3. Tang Min (2008), ‘Sharing economic growth and China’s poverty reduction in the new stage’, Report of the China Development Research Foundation, No. 40. World Bank, World Development Report, 2008. World Bank (2007), ‘China: country partnership strategy’, 23 May, Washington, DC: World Bank. World Trade Organization (2005), World Trade Developments in 2005, 2007, available at http://www.wto.org/english/res_e/statis_e/its2006_e /its06_General_ overview_e.pdf. Shanghai Academy of Social Sciences (2003), ‘International space for China’s growth’, International Relations Study Report, No. 8. Xiao Bin (2008), ‘Chinese economic expansion can be sustainable’, available at: http:www.chinanews.com.cn/407111.html. Xu Bin (2008), ‘Technological upgrading and China’s export competitiveness’, International Economic Review, 5–6.

3.

China’s rise and East Asian economies: towards a Sino-centric regional grouping?* John Wong

3.1

RELENTLESS GROWTH

The Chinese economy since 1978 has experienced spectacular performance on account of its successful economic reform and open-door policy. Average annual economic growth for the period of 1978–2007 was 9.8 per cent, with many ups and downs in the process. Real growth for 2007 was 11.9 per cent, up from the high rate of 11.2 per cent of 2006. In fact, China has chalked up double-digit rates of growth for five years in a row, averaging at 10.8 per cent a year (2002–2007), since its accession to the World Trade Organization (WTO) in 2001. This is truly phenomenal, especially because such ‘hyper-growth’ took place amidst a low annual inflation rate, below 3 per cent for the whole period – inflation only appearing in the last quarter of 2007. As shown in Figure 3.1, China’s economic growth process in the 1980s (its first decade of reform) fluctuated quite a lot, due to the so-called ‘reform cycles’. Since 1990, the growth process has displayed two spurts of high growth. One was sparked off by Deng Xiaoping’s Nanxun (tour of South China) in early 1992 and the other by China’s accession to the WTO in 2001. The Nanxun effect, as it may be called, signals China’s long march into a market economy by deepening and broadening economic reform, as Deng started a bold move to convert China into the so-called ‘socialist market economy’. The extensive marketization that followed tremendously enhanced the economic efficiency and productivity of China’s economy. The WTO effect marks the rapid integration of China into the global economy. It was the climax of Deng’s open-door policy that started in the early 1980s. This has made it possible for China to capture the mechanism of international capitalism – mainly through trade, foreign direct 65

66

The rise of China and structural changes in Korea and Asia

GDP (%) 16

13.5% 15.2%

14

11.6%

10.9%

12

11.7% 9.1%

10 8

8.8%

9.3% 7.8% 17.1% 14.7%

6

9.3%

2

0.7%

2.0%

6.0% 2.4% 1.9%

2.8% 1.5%

25

GDP

10.9% 24.1% 10.0%

11.3% 18.8% 18.0% 9.2%

7.6%7.8% 5.2%

4

CPI (%) 30

14.0% 13.1% 14.2%

8.4% 7.6%

10.2% 10.1% 10.0% 9.1% 8.3%

11.9% 11.1% 10.6%

8.0% 3.8% 7.3% 6.5% 4.1%

8.3% 6.4% 3.1%

3.4%

CPI

4.8%

20 15 10 5

3.9%

2.8% 1.2% 0.4% 0.7% –0.8% –0.8% –1.4%

1.8%1.5%

0

0

1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Q1

–5

Source:

National Bureau of Statistics (various years).

Figure 3.1

China’s economic growth and inflation, 1978–2008 Q1

investment (FDI) and technology transfers – to raise its own economic growth to an even higher level. In retrospect, the second spurt of growth after 2001 was far more significant, not just because it chalked up a double-digit rate of growth, but also because growth occurred on a much larger base at the tail end of the long growth period. Thus, China’s total gross domestic product (GDP) in 2007 almost doubled its 2002 level. When Deng introduced economic reform and the open-door policy at the historic Third Party Plenum in December 1978, China’s total GDP was only 365 billion yuan. By 2007, total GDP had increased to 24 000 billion yuan or about 67 times more. In 1978, China’s nominal GDP per capita was only 380 yuan. In 2007, it increased 45-folds to 17 000 yuan or about US$ 2500 at current market exchange rate. Many dynamic East Asian (EA) economies like Japan, Korea, Taiwan and Singapore had sustained similar high growth for two to three decades before, basically in the 1960s, 1970s and most of the 1980s. But they had never registered double-digit rates of growth continuously for five years in a row. China’s recent dynamic growth is therefore historically unprecedented, even in the context of past high-performance East Asian economies. In fact, whereas the 1997 Asian financial crisis brought down many EA economies, China’s economy was hardly affected by the crisis as it continued to grow at 9.3 per cent in 1997 and 7.8 per cent in 1998. After this crisis, while economic growth in most of Asia had fallen to low or negative rates, China’s economy alone was steaming ahead with strong growth.

China’s rise and East Asian economies

67

20 Thailand China

15

Malaysia

5

2007

2005

2003

2001

1999

1997

1995

1993

1991

1989

1987

1985

–5

1983

0 1981

% Growth

10

Philippines

–10

Indonesia –15 China

Source:

Malaysia

Thailand

Indonesia

Philippines

National Bureau of Statistics (various years).

Figure 3.2

Economic growth of china and ASEAN-4, 1981–2007

20 Singapore China

15

HK Taiwan

% Growth

10

5

Japan

–5

China

S Korea

Japan

HK

Taiwan

Singapore

2007

2005

2003

2001

1999

1997

1995

1993

1991

1989

1987

1985

1983

1981

0

S Korea

–10

Source:

National Bureau of Statistics (various years).

Figure 3.3

Economic growth of China and other East Asian economies, 1981–2007

In 2003, despite disruptions caused by severe acute respiratory syndrome (SARS) and global economic recession, it still chalked up a hefty 10 per cent growth. Furthermore, high growth momentum has been sustained until the outbreak of the 2008 financial crisis with double digit-rates of growth (Figures 3.2 and 3.3). As a matter of fact, China’s hyper-growth in recent years has been

68

The rise of China and structural changes in Korea and Asia

unexpected even by China’s own economic policy-makers, who originally conceived China’s warranted rates of growth to be around 8 per cent. The planners of the 11th Five-Year Programme (2006–10) envisioned the potential growth rates at only 7–8 per cent. Not surprisingly, the Chinese government was initially quite worried about the possibility of economic ‘overheating’. Premier Wen Jiabao in 2003 did try to cool the high growth administratively with macroeconomic control measures, but without success. For several years, many foreign commentators also predicted an imminent ‘hard landing’ for the Chinese economy, which nonetheless refused to cool down, and instead kept on growing and growing, and at higher rates.

3.2

THE ECONOMIC RISE OF CHINA

By 2007, China has become a huge economy of US$3.3 trillion at market exchange rate and was about to displace Germany as the world’s thirdlargest economy. In PPP (purchasing power parity) terms, China has long been the world’s second-largest economy after the USA, even though the PPP measure often tends to exaggerate the reality, particularly for the non-tradable service activities. It may be noted that the World Bank has since revised downward China’s PPP-based GDP substantially; but China is still ranked as the world’s second-largest economy in PPP terms. China’s foreign trade has also grown rapidly during the period 1980– 2007, averaging 17 per cent, after the adoption of the export-oriented development strategy. In 1978 when Deng Xiaoping announced the introduction of the ‘open door policy’, China’s total exports amounted to only US$9.8 billion or 0.6 per cent of the world’s share. By 2007, China’s exports increased 124 times to US$1.2 trillion, accounting for 8 per cent of the world’s total exports. In fact, with its total trade of US$2.17 trillion in 2007, China has overtaken Germany as the world’s second-largest trading nation.1 In particular, China’s exports (95 per cent being manufactured exports) have been growing at a phenomenal rate of 30 per cent a year since its accession to WTO in 2001. As shown in Figure 3.4, because exports have been for many years growing faster than imports, China has chalked up a huge trade surplus, which in 2007 amounted to US$260 billion or about 8 per cent of GDP. For FDI, China has since the early 1990s become the world’s most favoured destination in comparison with all other developing countries. Between 1990 and 2007, China attracted a total of US$610 billion in FDI. For years, China has consistently captured more than half of all FDI in Asia. Not surprisingly, more over 80 per cent of the world’s 500 largest

40

27.8%

22.9%

15.8%

30

27.2%

25.7%

28.4%

20

22.4%

18.1%

18.2%

10

6.8%

6.1%

Growth (%)

34.6%

21.0%

8.0%

Import

2007

2006

2005

2004

2003

2002

2001

2000

0 1999

0.5%

1998

1997

1996

1995

1994

1993

1992

1.5%

Export Source:

69 35.4%

Export Growth

31.9%

1991

1400 1200 1000 800 600 400 200 0

1990

Import & Export (US$ billion)

China’s rise and East Asian economies

Export Growth

National Bureau of Statistics (various years)

Figure 3.4

China’s trade growth, 1990–2007

companies and its top 100 information technology firms have already set up businesses in China.2 Above all, on account of its strong external balance as result of its persistent ‘twin surplus’ (that is, surplus in both current and capital accounts), by 2007 China’s total foreign exchange reserves soared to US$1.5 trillion to become the world’s largest, surpassing Japan. This, in turn, had led to mounting international pressures on China to revalue its renminbi (RMB). Indeed, the much-anticipated revaluation of the RMB took place on 21 July 2005, when the RMB officially went off the US dollar peg for a process of gradual appreciation. By mid-2008, the RMB had appreciated nearly 20 per cent against the US dollar while at the same time it had also depreciated about 10 per cent against the euro, though less against the Japanese yen – this is because the RMB’s float is being managed on a basket of currencies. In any case, all the world’s major financial markets have since been watching closely the movements of the RMB. Another indicator of China’s rising global financial clout is associated with the sudden rise of its capital markets. In September 2007 the Shanghai Stock Exchange, with its index reaching the all-time high of around 6000, became the world’s fourth-largest, after New York, Tokyo and London, in terms of total capitalization, even though the Shanghai bourse was only partially opened to foreign investors. At its peak in October 2007, five of the world’s ten largest corporations were from China, headed by China Petroleum. (Just as in the early 1990s a number of Japanese corporations also counted among the top ten in the world.) Suffice it to say that, starting in the early 2002, the meteoric rise of China’s economy has become a ‘hot’ topic in the international and

70

The rise of China and structural changes in Korea and Asia

Table 3.1

Production of major industrial products, 1978–2007

Coal (million tons) Crude steel (million tons) Cement (million tons) Electricity (billion kwh) Automobiles (million units) Colour TV sets (million units) Refrigerators (million units) Air conditioners (million units) Personal computers (million units) Note:

1978

2007

2007 over 1978 %

618 22 65 257 0.15 * * * 0.08 (1990)

2536.0 489.6 1360.0 3277.0 8.7 84.3 43.9 80.1 120.7

310 2125 1992 1175 57 – – – –

* Output just a few hundred.

regional media.3 Many Asian economies were concerned about the potential displacement effect of China becoming the factory of the world. A few years ago, some pointed the finger at China for exporting deflation to the world, because of China’s massive exports of low-priced manufactured products; and lately, China was accused of ‘exporting inflation’. Even the Japanese were initially quite worried by China’s recent dynamic industrial expansion. The noted Japanese economist Kenichi Ohmae even used a sensational title, ‘Asia’s next crisis: “Made in China”’, to talk alarmingly about the rise of China.4 And not surprisingly, other smaller countries in Southeast Asia have been watching the rise of China with apprehension. In the early 2000s China was mostly referred to as a rising regional economic power, with its growth producing mainly regional impact. In recent years especially after 2005, China’s economy reached a new plateau whereby its domestic production, consumption and foreign trade started to carry significant global ramifications. Indeed, as a huge and diverse economy, every item of production and consumption in China inevitably becomes a ‘jumbo number’. Thus, as shown in Table 3.1, China is the world’s top producer of coal (2.5 billion tons), steel (490 million tons) and cement (1.4 billion tons), and the world’s second-largest producer of electricity (3277 billion kwh). Viewed from a different angle, China is also (and necessarily so) the world’s top consumer of a wide variety of mineral resources and primary commodities from iron ores to oil and gas, and from palm oil to timber. China’s rising demand for these products has driven up their world prices. For instance, the oil price hike in 2007 was attributed to China’s increased demand for oil as it has now become the world’s second-largest consumer of oil (about

China’s rise and East Asian economies

71

9 per cent). Worse still, as the world’s leading producer of those basic industrial products, China has also become the world’s leading polluter, being the world’s second-largest emitter of the GHG (greenhouse gases), after the USA. In an economic perspective, the fact that China in 2007 produced 8.7 million of automobiles and 121 million personal computers (PCs), signifies not just China’s mammoth manufacturing and technological capacities but also points to its enormous productivity potential. Any producer turning out such a large volume of output will naturally enjoy the advantage of economies of scale, with low average cost and near-zero marginal cost. Such is China’s inherent comparative advantage for a wide range of manufactured products, particularly vis-à-vis its much smaller neighbouring economies in the EA region. Size always matters when it comes to the economics of production. In China’s case, its economic rise can also be attributed to the outcome of the dynamic combination of speed and scale. Human history has never before experienced such a massive scale of industrialization proceeding at such a breakneck speed as it is taking place in China today. Hence, for boom or for bust, the operation of China’s economy inevitably carries significant regional and global ramifications.

3.3

GROWTH AND INTEGRATION IN EAST ASIA

East Asia (EA) as an economic region is conventionally defined to comprise Japan, China, the four East Asian NIEs (newly industrialized economies) of South Korea, Taiwan, Hong Kong and Singapore, and other Southeast Asian economies that constitute ASEAN (Association of South East Asian Nations). Politically, this corresponds to the current regional concept of ‘ASEAN13’. Situated on the western rim of the Pacific, many EA economies registered dynamic growth for a sustained period until 1997 when they were hit, in varying degrees, by the regional financial crisis. The World Bank in its well-known study referred to EA’s high-growth phenomenon as the ‘East Asian Miracle’.5 Rapid economic growth of the EA economies has also brought about greater economic integration among them, mainly through trade and foreign investment, that is, through market-driven, open integration. Historically speaking, the EA growth process is marked by three waves. Japan was the first non-Western country to become industrialized. Its high growth dated back to the early 1950s amidst its rapid post-war recovery, and carried the growth momentum over to the 1960s and much of the

72

The rise of China and structural changes in Korea and Asia

1970s. Japan’s economic growth engine was initially based on the export of labour-intensive manufactured products. But it was soon forced by rising wages and increasing costs to shed its comparative advantage for labour-intensive manufacturing in favour of the four NIEs, which started their industrial take-off in the 1960s. These four NIEs, once dubbed ‘Asia’s Four Little Dragons’, were arguably the most dynamic economies in Asia, as they had sustained near double-digit rates of growth for over three decades, from the early 1960s to the 1980s. The rise of the NIEs constituted the second wave of the region’s growth and integration. By the early 1980s, high costs and high wages had also caught up with these four NIEs, which had to restructure their economies towards more capital-intensive and higher-value-added activities after passing their comparative advantage in labour-intensive products to the latecomers of China and the four ASEAN economies of Indonesia, Malaysia, Thailand and the Philippines (dubbed ‘Asia’s Tiger Economies’) and thereby spreading economic growth to the latter. In this way, China and some ASEAN economies were able to chalk up high growth through the 1980s and the 1990s. This constitutes the third wave of high growth. Many Japanese scholars like to depict this pattern of development in Asia as the ‘flying geese’ model6 (see Table 3.2 and Figure 3.5). Furthermore, the EA region has already developed a high level of intraregional trade. As shown in Table 3.3, the EA region in 2006 absorbed 46 per cent of Japan’s total exports (22 per cent in 1980), 37 per cent of China’s total exports; (39 per cent in 1980); 44 per cent of Korea’s (24 per cent in 1980); 62 per cent of Taiwan’s (63 per cent in 2000); 62 per cent of Hong Kong’s (48 per cent in 1980); 60 per cent of Singapore’s (40 per cent in 1980); and 45 per cent of the average of the ASEAN-4 (Indonesia, Malaysia, the Philippines and Thailand) (51 per cent in 1980). The sharp rise in the intra-regional trade over the past two decades for Japan, Korea, Hong Kong and Singapore (and possibly for Taiwan) is undoubtedly due to the rise of China. The decline in the regional share for China and the ASEAN-4 is because of their high trade orientation towards the USA and the EU, and also their global trade diversification. Japan’s shift in its export orientation towards a greater regional focus is even more remarkable. Apart from intra-regional trade, intra-regional FDI flows have also operated as a powerful integrating force for the EA region, especially since a great deal of regional FDI is trade-related in nature. As essentially open and outward-looking economies, the EA economies are, in varying degrees, dependent on foreign trade and foreign investment for their economic growth. In particular, both China and ASEAN have devised various incentive schemes to attract FDI, which is generally treated not

73

48 23 7 4.6

1321 128

2007

19 750 16 605 29 650 35 162

2460 34 312

2007

24 782 30 126 41 995 49 713

5292 33 576

2007

Popu- GDP per PPP lation capita estimates (mn) (US$) of GDP per capita (US$)

957 383 206 161

3250 4383

Total GDP (US$ bn), 2007

8.6 9.2 10 8.8

5.2 10.9

1960– 70

East Asian economies: performance indicators

NIEs South Korea Taiwan Hong Kong Singapore

China Japan

Table 3.2

10.1 9.7 9.3 8.3

5.5 4.3

1970– 80

8.9 7.9 6.9 6.7

10.3 4.1

1980– 90

5.7 5.7 3.8 7.4

9.7 1.3

1990– 2001

Growth of GDP (%)

4.6 3.4 3.9 3.4

9.3 1.5

2000– 2005

5.2 4.3 6.4 6.9

11.1 6.4

2006

4.9 5.7 6.2 7.7

11.9 2.1

2007

74

Sources:

2659

3724 13 315 3377 7900 2586

2007

1098

433 186 144 245 570

Total GDP (US$ bn), 2007

3.4

3.9 6.5 5.1 8.4 2

1960– 70

Based on data from China Statistical Yearbook and IMF sources.

977

For comparison India 1123

2007

1924 6947 1624 3736 818

2007

Popu- GDP per PPP lation capita estimates (mn) (US$) of GDP per capita (US$)

(continued)

225 27 88 66 86

ASEAN-5 Indonesia Malaysia Philippines Thailand Vietnam

Table 3.2

3.6

7.2 7.9 6 7.1 2

1970– 80

5.8

6.1 5.3 1 7.6 2

1980– 90

5.5

3.8 6.5 3.3 3.8 7.3

1990– 2001

Growth of GDP (%)

6.3

4.8 4.4 4.4 5.0 7.4

2000– 2005

8.8

5.2 5.5 5 4.5 8.8

2006

8.7

6.3 6.3 7.3 4.7 8.5

2007

China’s rise and East Asian economies

75

12.0 S Korea

China

% Growth

10.0 Singapore

8.0 6.0

Japan Taiwan

4.0 HK

2.0

China

Japan

S Korea

Taiwan

HK

Singapore

7 00

5

–2 01 20

20

01

–2

19

00

90

s

s 80

s 70

19

19

19

60

s

0.0

Sources: IMF World Economic Outlook; National Bureau of Statistics of China; Hong Kong Statistics; Korea Statistical Yearbook; www.statgov.trw; www.singstat.gov.sg; Japan Statistical Yearbook.

Figure 3.5

East Asia economic growth: The ‘flying geese’ pattern

just as an additional source of capital supply but, more importantly, as a means of technology transfer and export market development. What is more important is that an increasing share of EA’s FDI flows originates from the region itself. Overall, this also points to the ongoing process of EA’s growing economic interdependence.

3.4 3.4.1

THE REGIONAL IMPACT OF CHINA’S RISE Challenges for Japan

In the post-war Asia, Japan played a leading role in the region’s economic growth and integration. Japan’s sustained high growth spilled over first to the four NIEs and later to some ASEAN economies and China. Japan was the natural economic leader of the group because of its ability to provide the needed capital and technology for the other EA economies, first the NIEs and then China and ASEAN. For years, Japan’s economic presence was most prominent in the EA region. As a result, it rendered the EA region economically oriented towards Japan. However, Japan’s strong economic presence in the EA region has now slowly and steadily been eroded by the rise of China. Initially, China’s dynamic economic growth complemented well and even reinforced Japan’s

76

Year

1980 1988 2000 2004 2006

1980 1988 2000 2004 2006

1980 1988 2000 2004 2006

1980 1988 2000 2004 2006

Japan

China

Korea

Taiwan

– 60 667 148 321 182 370 243 801

17 505 60 696 172 268 253 845 325 465

18 099 47 540 249 203 593 439 969 380

130 441 264 856 479 249 565 675 649 931

Total exports (US$ Millions)

– – 11.2 7.6 7.3

17.4 19.8 11.9 8.5 7.4

22.3 16.9 16.7 12.4 9.5

Japan

– 3.7 16.9 19.9 23.2

– – 10.7 19.6 19.4

3.9 3.6 6.3 13.1 14.3

China

– – 2.6 3.1 3.2

– – 4.5 4.7 4.6

4.1 5.8 6.4 7.8 7.7

Korea

– 1.6 4.7 3.9 3.6

– – 2 2.3 2.1

– 5.4 7.5 7.4 6.8

Taiwan

– – 21.1 18 16.6

– 5.9 6.2 7.1 5.3

24.1 38.4 17.9 17 16.0

3.7 4.4 5.7 6.3 5.6

Hong Kong

– – 3.7 3.7 4.2

1.5 2.2 3.3 2.2 2.7

2.3 3.1 2.3 2.1 2.4

3 3.1 4.3 3.2 3.0

– – 7.4 7.4 7.3

4.6 2.8 7.2 5.8 5.1

4.3 2.8 3.7 4.1 4.0

7 4.9 9.5 9.1 8.1

– – 62.9 59.7 61.8

23.5 32.3 44 47.1 43.5

53 61.2 47.1 42.6 38.6

21.7 27.2 39.7 46.9 45.5

Singapore ASEAN-4* EA SUM

Share of regional exports designated for: (%)

Origins and destinations of East Asian intra-trade

Origin of regional exports

Table 3.3

77

1980 1988 2000 2004 2006

ASEAN-4

47 100 80 080 269 099 333 108 442 265

19 375 39 306 137 804 179 615 271 799

19 730 63 163 201 860 259 314 316 816

34.5 19.5 16.0 15.0 13.7

8.1 8.6 7.5 6.4 5.5

6.1 5.2 5.5 5.3 4.9

1.1 2.2 3.4 6.8 8.3

1.6 3.0 3.9 8.6 9.8

34.9 34.4 34.6 44.0 47.0

1.7 2.8 3.7 2.9 3.9

1.5 2.0 3.6 4.1 3.2

1.5 1.0 1.9 2.2 2.1

Source: Direction of Trade Statistics Yearbook, 2007, IMF. Taiwan’s data are obtained from Bureau of Foreign Trade website.

* ASEAN-4 denotes Indonesia, Malaysia, the Philippines and Thailand.

1980 1988 2000 2004 2006

Singapore

Note:

1980 1988 2000 2004 2006

Hong Kong

– 2.0 4.2 3.5 3.3

– 2.8 6.0 4.6 3.5

2.5 2.5 2.5 2.4 2.6

1.9 2.9 4.2 5.1 4.7

7.7 6.2 7.9 9.8 10.1 11.8 9.0 12.6 10.4 11.3

2.6 2.3 2.3 2.2 2.0 20.8 20.3 24.9 21.7 28.3

0.5 0.3 0.5 3.3 3.2

51.0 38.4 44.1 43.7 45.2

39.7 42.9 53.8 55.2 60.4

48.1 45.7 47.3 59.4 61.8

78

The rise of China and structural changes in Korea and Asia

leading role in the region. Subsequently, as China’s rapid economic growth was sustained and continued, China started to pose a challenge to Japan’s leading economic role in the region, particularly as Japan’s economy was trapped in a prolonged recession. Since the structure and pattern of China’s recent economic growth is different from that of Japan’s in the past, the regional impact of China’s rise is also substantially different from that of Japan. To begin with, China’s economic growth process is more ‘inclusive’ than that of Japan, and it has therefore produced a more extensive regional impact in a very short span of time. In fact, China’s rise today also embraces Japan, helping Japan to pull itself out of its economic doldrums. Furthermore, China’s economic rise is occurring in a world that is today much more globalized. As the world’s foremost manufacturing powerhouse, China is also home to numerous regional and global production networks, which operate to integrate a lot of manufacturing activities in its neighbouring economies, including Japan, to their mutual benefit. In this sense, China’s economic growth has generated far-reaching spillover effects, both regionally and globally. China is not just a new engine of economic growth, but increasingly it is also taking on the role of integrating EA’s economic activities for global outreach. This point will be further discussed later. If China’s economy were to continue at its present pace of dynamic growth for a decade or more (not an unrealistic assumption), China would eventually dwarf Japan’s leading economic role in the EA region as the major force for growth and integration, simple because of China’s size and diversity on the one hand, and Japan’s growing ageing population on the other. There is, of course, a great deal of uncertainty pertaining to the exact pattern of economic relationship of China and Japan vis-à-vis the EA region in the years to come. Economic relations between powerful states are much more complicated, often operating in a win–win situation rather than in zero-sum terms. Japan has already developed a new economic symbiosis with China to each other’s benefit, and both economies have thrived on this economic relationship, for example each being a leading trade partner of the other. China’s rise may gradually change the geopolitics and geo-economics of the EA region, but Japan is likely to maintain its high level of economic presence in the region and stay on as one of its key development partners for a long time to come. In the meanwhile, the region is actually blessed with two engines of economic growth – a two-engined flying geese formation is inherently a more powerful one.

China’s rise and East Asian economies

3.4.2

79

China as the ‘Dragon-Head’ for the EA Economies

China’s economic growth actually fits in quite well with the overall EA growth pattern. Since the EA region absorbs around 50 per cent of China’s exports and supplies about 60 per cent of China’s FDI, it is not hard to explain why China’s rapidly growing economy since 1978 has impacted significantly on many EA economies. However, the actual impact of the fast-growing Chinese economy on the EA economies has been quite uneven. China’s dynamic economic growth has produced both positive and negative effects for the individual EA economies in the region. From the outset, Japan and the four NIEs have been able to benefit a lot from China’s open-door policy first by trading with China and then investing in China, that is, capital and technology to China. Deng’s open-door policy presented Hong Kong, Taiwan and South Korea with a god-sent opportunity to upgrade their own manufacturing industries by conveniently shifting their labour-intensive production bases to China. In the process, they also forged very close economic linkages with China. Hence China has become their leading trade partner. In contrast, China and the ASEAN economies initially tended to be more competitive than complementary with each other. In many ways, China’s dynamic economic growth has exerted strong competitive pressures on the ASEAN economies, which are vying for FDI with China as well as competing head-on with China’s manufactured exports in the developed-country markets. Figure 3.6 does show up some prima facie evidence for this view, even though the actual situation is not so straightforward.7 Initially, China’s success in economic reform and development produced very little impact on the ASEAN countries to its south, because Sino-ASEAN trade was then very small – in fact, only a small fraction of each other’s total trade and with a large part of it being centred in Singapore (Figure 3.7). For FDI, it had soon become apparent that China and ASEAN were not really directly competing with each other. Even by the late 1990s, when massive FDI began to flow into China, there was no clear-cut evidence that China had ‘sucked’ in a lot of capital from the ethnic Chinese in Southeast Asia.8 A study by the United Nations Conference on Trade and Development (UNCTAD) has also confirmed that China’s growth has not adversely affected FDI inflow to other East Asian economies. Furthermore, China ‘appears to be crowding in rather than crowding out FDI in the region’.9 Still, many ASEAN economies were apprehensive about the economic rise of China, particularly in the aftermath of the 1997 Asian financial crisis. While many ASEAN countries were plagued by persistent economic crises and domestic political instability, China was intent on its

80

The rise of China and structural changes in Korea and Asia 80 70

US$ billions

60

China

50 40 30 ASEAN-5

20 10

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

0

Note: ASEAN-5 includes Indonesia, Singapore, Malaysia, Philippines and Thailand. Sources:

National Bureau of Statistics (various years).

Figure 3.6

Asean-5 and China competing for FDI

US$ billions

45 40

Malaysia

Indonesia

Thailand

35

Philippines

Singapore

Vietnam

Singapore Malaysia Thailand

30

Philippines

25 20

Indonesia

15 10 5

Vietnam

Source:

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

1989

1988

1987

1986

1985

1984

1983

0

UN Comtrade; Direction of Trade Statistics.

Figure 3.7

China’s trade with ASEAN, 1980–2006

single-minded pursuit of economic modernization, adding to ASEAN members’ fears that they might eventually be left behind by China’s continuing relentless economic growth. More significantly, China’s recent spurt of dynamic economic growth since its WTO membership has transformed the old pattern of China’s economic relations with the EA region. In the short span of just a few years, China’s economic growth and exports have started to alter the region’s trade patterns and FDI flows.

China’s rise and East Asian economies

81

India 2007

Australia Thailand Indonesia Philippines Malaysia

2006

Taiwan Korea Japan Singapore HK USA EU –100

Source:

–50

0

50

100

150

200

China Monthly Customs Statistics; Ministry of Commerce, www.mofcom.gov.cn.

Figure 3.8

China’s trade balance with selected countries (US$ billions)

Take China’s trade relations with EA. In recent years, China has become the top trade partner (No. 1 or No. 2) of most of its neighbouring economies. China’s unique pattern of trade balance with its major trading partners has been the major driving force behind the region’s economic growth after the 1997 Asian financial crisis. As shown in Figure 3.8, China in 2006 and 2007 continued to run substantial trade deficits with its neighbouring economies, from Japan, Korea, Taiwan and ASEAN-5 to Australia and India. China turned around by incurring a large trade surplus with the USA and the EU. In this way, China could still end up with an overall trade surplus. China’s trade deficits with its neighbours also mean that it has opened up its vast domestic market for their exports (both manufactured products and primary commodities), thereby operating as an engine for their economic growth. The underlying economic implications of China’s overall trade pattern for both trading partners and trade balance are even more profound. Since most of China’s exports are processed products (53 per cent of total exports in 2006) or final products generally with low domestic valueadded and low domestic content (domestic content is generally around 40 per cent, but can be 20 per cent or lower for some products), China must import in order to export. Since over half of China’s foreign trade is handled by its foreign-invested enterprises (on average 59 per cent in 2006, with much higher proportions for IT products), particularly those from Japan, Korea, Taiwan and Hong Kong, China’s foreign trade has become a critical link in the East Asian supply chains. It can further be argued that, as shown in Figure 3.9, China’s foreign trade is also an important force for regional economic integration. As the

82

The rise of China and structural changes in Korea and Asia

Capital, technology, equipment, high-tech parts & components

Primary commodities & natural resources & energy

Financial, commercial & legal services

Japan, Korea, Taiwan

ASEAN, Australia, Middle East

Hong Kong, Singapore

Surplus

Surplus

China:

Manufacturing, processing, assembling, turning ‘Made in Asia’ into ‘Made in China’ Surplus

Europe

Figure 3.9

Surplus USA

Surplus

And, shipping to

Surplus

Rest of world

China at the centre of global and regional production networks

world’s foremost manufacturing processing base, China occupies a central place in various EA supply chains. It imports raw materials, intermediate products, machinery and equipment, and services from different EA economies, converting ‘Made-in-Asia’ into ‘Made-in-China’ products for export to different markets in the region and beyond. In this way, China operates as an important ‘integrator’ of regional and global manufacturing activities. In this way, ASEAN’s old fears that the rising China could create competitive pressures on its manufactured exports and divert FDI from ASEAN, have largely dissipated. Now, as China and other EA open and outward-looking economies have become increasingly integrated into many common international supply chains, the resultant new global trade–FDI–technology linkages will further bring economic growth to the EA region as a whole. 3.4.3

China’s Regional Initiatives with ASEAN

It needs to be emphasized that the increasing regional impact of China’s economic growth has been largely market-driven. But this market-based pattern of economic integration has been further reinforced by Beijing’s far-sighted diplomatic policies, thereby lending strong institutional support to forge China’s further economic integration with the EA region. Mindful of ASEAN’s worries over the possible disruptive effects of its

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rapid economic rise, China has been under mounting pressure to dispel the ‘China threat’ fears by improving its overall relations with its ASEAN neighbours. The process started in 1992 when China formally became a ‘Dialogue Partner’ of ASEAN. Prior to this, China took steps to defuse the issue related to the hotly disputed Spratly Islands in the South China Sea by agreeing to joint consultation and joint development with the relevant ASEAN states. During the 1997 Asian financial crisis, Beijing’s steadfast refusal to devalue its renminbi was much appreciated by ASEAN as such a move could have further aggravated the region’s financial woes. But the single most important step ever undertaken by China in recent years to upgrade its long-term political and economic relations with the ASEAN region is China’s bold Free Trade Area (FTA) initiative. At the ASEAN–China Summit in November 2001, former Chinese Premier Zhu Rongji proposed the creation of a free trade area between China and ASEAN within ten years. On 4 November 2002, China and the ASEAN countries signed a framework agreement in Cambodia to establish a FTA by 2010.10 To show its serious intentions and to expedite the process, China on 1 January 2004 further initiated the Early Harvest Programme with some ASEAN countries by cutting tariffs on 500 items of agricultural products. On 29 November 2004, China and ASEAN formally concluded in Vientiane, Laos, the Agreement on Trade in Goods of the Framework Agreement on Comprehensive Economic Cooperation between the two sides for tariff liberalization under the China–ASEAN Free Trade Area. Tariff liberalization would be under a ‘normal track’ and a ‘sensitive track’. Duties on many commodity items under the normal track would be eliminated by 2010.11 On 20 July 2005, China and ASEAN started to cut tariffs on more than 7000 commodity items.12 China’s average tariff on ASEAN products was reduced from 9.9 per cent to 8.1 per cent in 2005, and would be further reduced to 6.6 per cent in 2007. By 2010, 93 per cent of ASEAN products are expected to be tariff-free when the China–ASEAN FTA is fully implemented.13 The formation of the China–ASEAN FTA, on paper, signifies the creation of an economic region of nearly 2 billion consumers with a combined GDP of more than US$5 trillion. It could offer an effective means for smaller ASEAN states to overcome their disadvantage of smallness by pooling their resources and combining markets. This would in time lead to greater economic integration between China and ASEAN, clearly a win–win situation.14 The much-touted Chinese ‘economic threat’ would then turn into an opportunity for ASEAN. In the short run, however, ASEAN has to deal with the initial risks of a potential trade diversion effect and related structural adjustment, as to be

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expected in any such regional integration process.15 In general, the FTA scheme could give rise to an uneven distribution of costs and benefits for different industries, different sectors, and even different ASEAN countries. After the initial process of adjustment, individual ASEAN economies would then develop their own niches in their economic relations with China. With China continuing its dynamic economic growth, opportunities will certainly arise for the ASEAN countries to exploit China’s vast growing market. Apart from its primary commodities, ASEAN’s resource-based products will be in great demand in China. The recent years have witnessed an upsurge of ASEAN’s exports of natural resource products, from timber to palm oil, to China to satisfy the voracious demands of its manufacturing sector. China is such a vast and differentiated market that East China, South China and Southwest China can individually offer different opportunities to different ASEAN producers. Not surprisingly, Sino-ASEAN two-way trade had surpassed US130 billion in 2005, with ASEAN becoming one of China’s largest trading partners.16 In 2007, the two-way trade reached US$190 billion, with ASEAN and China each being the fourth-largest trade partner with the other. Total trade between China and ASEAN is expected to reach US$200 billion by 2008, one year ahead of schedule.17 Beyond merchandise trade, FTA also promotes trade in services, including tourism. China may generally have a strong comparative advantage in manufacturing because it enjoys the economies of scale, which however may not apply to many service activities. In fact, a lot of China’s service activities, on account of their past socialist legacies, are known to be more backward than those in ASEAN.18 In the years to come as the China–ASEAN FTA scheme is gradually phased in, multinationals in the region will gradually restructure their supply chains and rationalize their production networks by taking China and ASEAN together as a single market. This will eventually lead to a reshuffle of regional production networks and hence also a redistribution of the regional FDI flows. The new regional production patterns will then be based on a bigger and more diverse market. In short, both trade and FDI in the region should continue to grow under the impact of the China– ASEAN FTA. And this would certainly be a win–win outcome. China’s FTA initiative with ASEAN, as the first of its kind (the first ASEAN11 trade arrangement), also created new impetus for the region to revitalize its integration process. In fact, the China–ASEAN FTA exerted tremendous pressure on Japan and Korea to follow suit, prompting similar responses from them. Accordingly, in the wake of the China–ASEAN FTA, Japan had to take action by signing a Framework for Comprehensive Economic Partnership with ASEAN, which is not a

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true FTA but can comprise Japan’s bilateral FTA arrangements with individual ASEAN member countries. Korea also made a similar move. The EA economies in the region were virtually scrambling to set up bilateral FTAs or EPAs (economic partnership arrangements) with each other or with countries outside the region.19 China, too, did not stop at the China–ASEAN FTA. In June 2003, China signed the Closer Economic Partnership Arrangement (CEPA) with Hong Kong (and subsequently with Macau). CEPA is obviously aimed at the eventual integration of these Greater China economies after the inclusion of Taiwan in future.20 Prior to this, China had agreed to initiate a joint study with Japan and Korea on possible Northeast Asian economic cooperation. In October 2003, Premier Wen Jiabao attended the 9th ASEAN Summit in Bali, where he signed with the heads of government from Japan and Korea the Joint Declaration on the Promotion of Tripartite Cooperation among these three Northeast Asian countries. This tripartite cooperation is not just for the promotion of economic cooperation and peace dialogue in Northeast Asia, but is also aimed at strengthening the process of ASEAN economic integration with other EA economies, that is, a more concrete way of accelerating the realization of the greater East Asian economic integration through the ASEAN13 process. Of equal importance, Premier Wen at the Summit also signed the Treaty of Amity and Cooperation (TAC) with ASEAN in order to express China’s goals of establishing a strategic partnership with ASEAN for ‘peace and prosperity’.21 China is the first country to accede to ASEAN’s TAC, which is a distinctive regional code of conduct governing state-to-state relations within ASEAN. The most important principle in the TAC is the provision that requires all parties involved to renounce the use of force in the settlement of any dispute. In concluding this historic treaty, China has signalled to the ASEAN countries its acceptance of ASEAN’s norms and values, and its willingness to play by the rules. In other words, ‘China wants to be seen as a responsible member of the international community’.22 Since India also followed China by concluding a similar TAC with ASEAN, Japan was once again under tremendous pressure to follow suit. Besides the China–ASEAN FTA initiative, China has also undertaken several subregional cooperation schemes to facilitate economic integration with relevant ASEAN countries. A few years back, Guangdong Province started the ‘912’ (nine provinces in South China plus Hong Kong and Macau) scheme for greater interprovincial economic integration among these provinces and Hong Kong and Macau, and as a vehicle for Chinese enterprises to ‘go out’ (zou chu qu), particularly to Southeast Asia. Later on, in 2006, Guangxi Province took the initiative to develop the ‘Pan Beibuwan’ cooperation, which would promote a wide area of

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cooperation between China’s three provinces of Guangxi, Guangdong and Hainan, and eight ASEAN states including Vietnam, Cambodia and Thailand. More recently (March 2008), Premier Wen Jiabao attended the Third Greater Mekong Sub-region (GMS) Summit in Vientiane, endorsing China’s active participation in the GMS development, which will benefit China’s several land-locked provinces like Yunnan and Sichuan.23 While China’s economy is increasingly globalized, it has also intensified its subregional cooperation efforts vis-à-vis individual EA economies, mainly on a decentralized basis. This makes much sense for China, as a large and diverse continent-sized country, to encourage individual provinces to forge closer economic links with adjacent EA economies so that they can better maximize each other’s comparative advantages. It may be remembered that many of China’s provinces are huge entities on their own: for example Guangdong has a population of more than 80 million. In effect, China is ‘one country with many economies’. In summary, China’s drive for globalization and regionalization go hand in hand. Regionally, it places greater priority on cooperation initiatives with ASEAN, partly because of history and geography and partly in order to meet China’s specific geopolitical needs. China’s rapid economic rise has been perceived by as a disruptive force by some of its neighbours, giving rise to the ‘China threat’ perception. In response, Beijing put forth its ‘peaceful rise’ argument. China is making use of Southeast Asia as the best diplomatic space for it to demonstrate that its rise is indeed peaceful and benign.

3.5

TOWARDS A SINO-CENTRIC EAST ASIAN ECONOMIC GROUPING?

China’s economic rise has far radically transformed the region’s growth patterns and its landscape for trade and investment. What is the future shape of China’s changing economic relations with the EA region? When people are talking about ‘China’s rise’, they are actually referring to China’s dynamic economic growth and its consequences for both China and other countries. For a more realistic projection of the future scenario, two immediate questions need to be posed: Is China’s dynamic growth sustainable? How will its neighbouring economies respond and adapt to China’s future growth? 3.5.1

Sustainability of China’s Dynamic Growth

To begin with, China’s future growth cannot consistently remain at double-digit rates. Now bigger and more mature, the Chinese economy

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just cannot keep on growing at such a speed without getting overheated or running into physical and structural constraints. More sustainable levels of long-term growth should be at the warranted rate of around 8 per cent, which is still high growth by all accounts. China’s high growth over two decades essentially stemmed from its exceedingly high levels of domestic investment, at more than 40 per cent of GDP, and equally high levels of domestic savings, also at more than 40 per cent, much like other East Asian economies in their early periods of growth. For domestic investment, China will continue to have an enormous need for infrastructural investment in transportation, communications, ports, airports and power plants. Take railways as an example. China’s railway network in 2006 amounted to 77 000 km, and China is target is to extend its total railway track length to 100 000 km. Big cities like Beijing, Shanghai, Guangzhou are also building high-speed railways for intercity links. Furthermore, large cities like Beijing, Shanghai, Guangzhou, Tianjin, Chongqing, Shenyang Wuhan, Xian, Wuxi and Suzhou are all busy expanding their subway systems, all at huge capital costs. In the years to come, China will also need to invest a lot for environmental protection like cleaning up the rivers and water supply sources. With rapid urbanization, there will be rising demand for social infrastructure like housing, schools, hospitals and recreation facilities. This explains why fixed asset investment will continue to be a highly significant source of growth for China at least up to 2020. For a capital-surplus, high-saving economy like China, it is the abundance in investment opportunity, not the availability of investment capital, that is more critical. China’s future economic growth can also be boosted by rising consumption. Rapid income growth, particularly for the urban population, has created a fast-growing xiaokang (moderately affluent) society, with a rising middle class of over 200 million. Their appetite for durable consumption goods like automobiles is enormous. When the urban elites have satisfied their basic material consumption needs, they will go for consumption in services like travel and entertainment. The same thing has happened to Japan and the four NIEs before. Above all, by considering the historical patterns of EA economic growth, one can be easily optimistic about China’s future growth potential. Historically, as shown in Table 3.2, Japan enjoyed over 25 years of high economic growth while the four NIEs of Korea, Taiwan, Hong Kong and Singapore had over 30 years. Why not China? China’s present run of high growth has barely reached 30 years, and it could easily continue for another one or two decades. China’s is a much larger and more diverse economy, and it should therefore have much greater internal dynamics to sustain higher growth for a longer period. In other words,

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China’s economic presence is going to persist and get larger in the years to come. This powerful historical argument provides yet another simple but convincing support to China’s high-growth thesis. 3.5.2

The Challenges for China

Even trying to realize its future warranted growth potential at the more sustainable rate of around 8 per cent, China still needs to strengthen its growth-inducing forces by stepping up its remaining market reform and structural adjustment efforts so as to capture greater efficiency gains for growth. In the long run, all economic growth has to come from productivity growth, that is, not just by dumping in more capital and more labour, but also by boosting efficiency. China’s industrial development has indeed reached a critical point whereby its manufacturing sector is badly in need of upgrading and restructuring, from labour-intensive industries into more capital-intensive and higher value-added activities. Recently, there are frequent reports of the shutting down of labour-intensive factories and plants in the Pearl River Delta region and their removal to interior China, because of rising wages, rising costs and RMB appreciation. As costs rise, some foreign enterprises have pulled out of China and moved to its neighbouring economies with lower labour costs such as Vietnam and Indonesia.24 In economic theory, this means that the supply curve for the older industrialized areas of the Pearl River Delta region is no longer perfectly inelastic, but it has reached what the Nobel economist Arthur Lewis called the ‘turning point’, signalling the need for industrial upgrading. Beyond growth in terms of GDP increases, China also needs to ‘fix’ many of its ‘growth problems’ in socio-economic areas such as employment, income equality and environmental degradation. Success in fixing those problems will actually increase the future growth capacity. A more fundamental issue is how far the Chinese economy needs to be structurally rebalanced. This is about changing China’s basic growth strategies, for instance, with its growth engine being based more on domestic demand particularly domestic consumption, and less on exports. Ultimately this will involve changing the nature of economic growth with greater emphasis on the ‘quality of GDP’ and not just the sheer quantity. In fact, many Chinese economists have been hotly debating the need for such a fundamental shift in China’s development strategies. But changes have been slow and gradual. It became more likely that the government would step up such policy shifts after the Beijing Olympics. It may be noted that the Olympic event was the economic turning point for both Japan and South Korea.

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Responses from other EA Economies

So much for China. But the challenges for other EA economies are no less important. Needless to say, other EA economies have to embrace China’s continued rise, politically and economically. But it is also imperative for them to adapt and respond to China’s rise. Economically, this means that other EA economies too have to step up their own structural adjustment, not just for their own economic growth, but also to capture greater benefits or spillovers of China’s dynamic growth. A recent International Monetary Fund (IMF) study has warned that as China continues to grow, its trade patterns will change and the China-based international and regional supply chains will also have to be changed. Clearly, as China continues to upgrade its manufacturing activities, it will move away from simple assembly operations towards production with greater scope for using more domestic inputs, either through industrial upgrading or by extending more backward linkages into interior China. As a matter of fact, the government has already taken measures to discourage or reduce simple processing trade activities because of their lower margins (that is, low value-added to China) due to the tight labour market and rising energy costs. Eventually, China could be less dependent on imported parts and components for its industrial production.25 Rising energy costs and the concomitant rising shipping costs will also affect the structure and pattern of production networks in future. Factories will be forced to outsource to nearby suppliers as far as possible and try to integrate the production linkages more domestically rather than internationally, in order to cut down transport costs.26 In the years ahead, though, China will continue to import natural resources and primary commodities from Southeast Asia. But some ASEAN economies need to develop their own niches, for example moving into more resource-based activities, and upgrade their industries so as to stay competitive. As for the more developed EA economies, including Japan, they too need constantly to upgrade the technological sophistication of their industries in order to stay relevant, that is, to remain being part of the China-based production networks. Structural adjustment includes intersectoral restructuring. The more developed EA economies need to step up their economic restructuring by giving up low-tech manufacturing activities for the latecomers and moving into more service-oriented activities, particularly tradable services like finance and banking, and economic and technological consultancies. Even tourism, community services, education and health services could be future sources of economic growth and regional cooperation.

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The rise of China and structural changes in Korea and Asia 13

GDP growth (%)

11 9

China

China 2010*

China 2015**

7

Hong Kong

Singapore

5 Taiwan

3

Japan Korea

1 –1 0

5 000

10000

15000

20000

25000

30 000

35 000

40 000

45 000

GDP per capita (US$)

Notes: Economic size is measured by nominal GDP China’s nominal GDP is US$3.4 trillion in year 2007. * is forecast based on GDP growth of 9%. ** is forecast based on GDP growth of 8%.

Figure 3.10

East Asia growth performance, 2007 (growth rate, economic size and per capita GDP level)

It may be stressed that the ‘flying geese’ pattern itself is a dynamic model of economic growth on the one hand and structural adjustment on the other. Its dynamic growth is based on the underlying economic rationale of continuous structural adjustment among its constituent members in order to cope with the dynamics of shifting comparative advantage. Suffice to say that it is imperative for both China and other EA economies to step up their structural adjustment for mutual benefits. Figure 3.10 provides a reasonably realistic trajectory of China’s future growth. It can be seen that China’s economy will be bigger than Japan’s in the next few years, even though China’s per-capita GNP will still be only a fraction of Japan’s. In total terms, China’s will be a big economic dynamo. The Chinese people do not wait until they get rich before their country has become economically powerful. 3.5.4

An East Asia Economic Condominium?

As China continues to sustain its high economic growth momentum, it is set to develop an even closer economic symbiosis with other EA economies so that the region as a whole will continue to benefit from China’s economic rise. Economic activities in the region will then be increasingly

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gravitating towards China, giving rise to a Sino-centric economic grouping in the region, or the kind of Chinese-led ‘flying geese’ formation that is potentially much greater than the Japanese-led one in the past. Historically, dynastic China has long been a dominant player in the region. In the words of the eminent Harvard historian John K Fairbank, China through successive dynasties used to perceive itself as the ‘centre of the world’. Imperial China never treated its neighbours as equals.27 When China was weak, its neighbours invaded China or encroached on Chinese territories. When Imperial China became strong, it treated its neighbours as tributary states, who were obliged to acknowledge China’s predominance in the region by regularly sending tributes to Beijing. Will such a ‘Middle Kingdom’ syndrome return? To begin with, for any regional grouping today, it is well-nigh impossible for any member to exert political and economic dominance over others. Such domination is no longer acceptable in this globalized world. The emerging EA grouping may be ‘Sino-centric’ in an economic sense, but it is not to be politically and economically dominated by China, for many obvious reasons. Even in Imperial China, the tributary relations between China and its smaller neighbours were actually the Chinese way of conducting formal diplomacy with other states, which did not entail any physical Chinese political and economic domination in real terms. In fact, the tribute-bearing missions in the past were, as noted by Fairbank, often a convenient ‘cloak for trade’.28 Furthermore, future economic integration in the region will continue to be open and market-driven. This means that the economic relations will be win–win. It may further be argued that Japan will continue to be both an economically powerful and a technologically advanced entity able significantly to offset China’s growing predominance. Korea, particularly taking both South and North together, will also be an emerging countervailing power. It must also be emphasized that China is only economically powerful in the mass. Even when China’s total GDP has surpassed that of the USA to become the world’s largest, Chinese per capita income will remain low by the average standard of the developed world. China has to keep growing and developing in order to cope with a whole range of domestic economic problems, including employment and regional disparity, not to mention the recurrent problems of natural disasters (floods and droughts) every year. A big country is also beset by big problems. Politically, the Chinese leadership will be mostly preoccupied with maintaining social stability and national unity. As in the old days of Imperial China, the government will continue to donate a lot of its political resources to trying to keep various parts of China together. All big states have to devote a huge amount of resources to national economic

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and political integration. The challenge for China would have been much less if it were organized as a federation. But it is run as a unitary state. Accordingly, a great deal of energy of the Chinese central government is necessarily absorbed in coping with problems from the local governments. This means that politically, China as a country will remain inward-looking. At most, China will become more assertive on certain regional and global affairs along with the rising scale of its economic influence. All in all, the future architecture of the Sino-centric EA regional grouping is more likely to be a kind of economic condominium with China occupying a huge unit at the centre, whose activities at home affect all the other neighbours. But at the same time, other units would remain free to interact with the outside, that is, other EA economies will continue to cultivate other sources of growth outside the region. China’s economy may be the most important engine for the region’s economic growth, but it is not the only engine of growth for every EA economy. Such a pattern of regional growth may be closer to the New Age economic integration, something that is more viable and acceptable to all. Indeed, such a peaceful and prosperous regional condominium is actually the extension of Hu’s ‘harmonious society’ to the ‘harmonious world’ around China.

NOTES * 1. 2. 3.

4. 5. 6. 7. 8. 9.

Paper presented at KDI International Conference on ‘growth and Structural Changes of the Korean Economy after the Crisis: Coping with the Rise of China’, Seoul, 21–22 July 2008. National Bureau of Statistics (relevant years). Wu (2005). At the World Economic Forum in Davos, ‘everything is China, China, and China’, according to one observer (‘The Talk of the Town at Davos: China’, International Herald Tribune, 26 January 2004. China’s emergence as the world’s manufacturing powerhouse after two decades of dynamic growth has invited prominent worldwide attention. The international media have recently portrayed China’s economic resurgence as an economic threat. David Roche, a famous Wall Street economist, commented on China being a source of current global recession with its mass production of a wide range of low-priced manufactured products for the world market. In early 2003, Japan’s Nikkei Weekly reported on China setting the pace in markets for commodities around the world. The Chinese media and academia have since come out to defend China’s position. Ohamae (2001). World Bank (1994). The ‘flying geese’ concept of development was coined by a Japanese economist, Kaname Akamatzu (1962). For further discussion of this topic, see Loungani (2000). See Wong (1998). UNCTAD (2005)

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10.

The framework agreement signed by the 11 nation states sets out a road map for trade liberalization in goods and services for most countries by 2010 and for the lessdeveloped ASEAN nations (namely Cambodia, Laos, Myanmar and Vietnam) by 2015. 11. ‘ASEAN tariff-cut steps towards free trade’, China Daily, 30 November 2004. 12. ‘China–ASEAN FTA necessary and beneficial’, China Daily, 27 October 2006. 13. ‘China, ASEAN speed up tariff reduction process’, China Daily, 11 October 2006). 14. For further discussion of this topic, see Wong and Chan (2003a). 15. Trade diversion occurs when members of a free trade grouping trade more among themselves than with other non-member countries, due to a lowering of tariffs or non-tariff barriers within the FTA. Structural adjustments occur because when intra-regional barriers are dismantled, industries will expand in some countries and contract in others as industries relocate in response to differences in factor endowments. The costs of adjustment resulting from such relocation of economic activity can be asymmetrical since some economies will incur higher costs in the short run than others. 16. China Monthly Statistics, December 2005. 17. ‘Sino-ASEAN partnership’, China Daily, 1 November 2006; and ‘China View’, www. chinaview.cn, 20 October 2007. 18. See Wong and Liang (2003). 19. See the JETRO homepage, http:www.jetro.go.jp/indexj.html, for a list of FTAs in the region. 20. See Wong and Chan (2003b). 21. ‘ASEAN (2003). 22. See de Castro (2002). 23. For a further discussion of this topic, see Lim (2008). 24. See, for example, the report, ‘As costs soar, a ‘China plus one’ strategy’, International Herald Tribune, 18 June 2008. 25. Cui (2007). 26. This is actually happening now. See ‘Rising shipping costs alter calculus of trade’, International Herald Tribune, 4 August 2008. 27. Fairbank (1968). 28. Fairbank (1953), p. 32.

REFERENCES Akamatzu, Kaname (1962), ‘A historical pattern of economic growth in developing countries’, Developing Economies, 1 (March–August), 3–25. ASEAN (2003), ‘China forge strategic partnership’, available at www.chinaview. cn. China Monthly Statistics, December 2005. Cui, Li (2007), ‘China’s growing external dependence’, Finance and Development, 44(3), September. de Castro, Isagani (2002), ‘China snuggles up to Southeast Asia’, available at http://www.atimes.com. Fairbank, John K. (1953), Trade and Diplomacy on the China Coast, Cambridge, MA: Harvard University Press; p. 32; reprinted in John Wong (1984), The Political Economy of China’s Changing Relations with Southeast Asia, London: Macmillan Press. Fairbank, John K. (ed.) (1968), The Chinese World Order, Cambridge, MA: Harvard University Press.

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Lim, Tin Seng (2008), ‘China’s active role in the greater sub-region: a win–win outcome?’, EAI Background Brief No. 397, 6 August, Singapore. Loungani, Prakash (2000), ‘Comrades or competitors? Trade links between China and other East Asian economies’, Finance and Development, 37(2), June. National Bureau of Statistics of China (various years), China Statistical Yearbook, Beijing: China Statistics Press. Ohmae, Kenichi (2001), ‘Asia’s next crisis: made in China’, Straits Times (Singapore), 2 August. UNCTAD (2005), ‘China is not crowding out FDI from the rest of East Asia, experts say’, Information Note (Press Information), UNCTAD/PRESS/ IN/2001/007, 7 March. Wong, John (1984), The Political Economy of China’s Changing Relations with Southeast Asia, London: Macmillan Press. Wong, John (1998), ‘Southeast Asian ethnic Chinese investing in China’, EAI Working Paper 15, 23 October. Wong, John and Sarah Chan (2003a), ‘China–ASEAN Free Trade Agreement: shaping future economic relations’, Asian Survey, 43(3), 507–23. Wong, John and Sarah Chan (2003b), ‘China’s Closer Economic Partnership Arrangement (CEPA) with Hong Kong: a gift from Beijing?’, EAI Background Brief, 177, December. Wong, John and Ruobing Liang (2003), ‘China’s service industry (II): gearing up for WTO challenges’, EAI Background Brief, 163, July. World Bank (1994), The East Asian Miracle, New York: Oxford University Press. Wu Wenhe (2005), ‘Investors keep eyes peeled on dragon’, Beijing Review, 48(22), 2 June.

PART II

Impacts on Korea’s Economy

4.

Understanding the post-crisis growth of the Korean economy: growth accounting and cross-country regressions* Chin Hee Hahn and Sukha Shin

4.1

INTRODUCTION

Korea maintained miraculously high and sustained economic growth at least up until the 1997 financial crisis, becoming one of the newly industrialized economies (NIEs) in the 1980s. After the crisis, however, the GDP growth rate slowed down significantly. Annual average gross domestic product (GDP) growth rate declined from 7.5 percent during the period from 1991 to 1995 to 4.5 percent on average from 2001 to 2006. The growth slowdown was accompanied by a significant decline in investment growth and worsened employment conditions (see Figures 4.1–4.3). In this chapter, we try to provide some empirical facts that are helpful for understanding the post-crisis growth performance of Korea. The main questions asked in this chapter are as follows. What are the respective roles of inputs accumulation and total factor productivity growth (TFPG) in explaining the growth slowdown? How does the post-crisis growth performance of Korea compare with other countries, in terms of per worker GDP growth, per worker capital growth, and TFPG? This chapter uses both growth accounting and cross-country regression methodologies to answer these questions, and tries to evaluate post-crisis growth of the Korean economy. As is well known, the studies by Young (1995) and Kim and Lau (1994) suggested that the growth rates of total factor productivity (TFP) of Korea and other East Asian countries were only moderate relative to those recorded by many developed countries in the past. These empirical findings were considered surprising by many who presumed that the miraculous growth performance of East Asian countries would be accompanied by ‘high’ TFP growth, which triggered the so-called TFPG controversy.1 Although whether the TFPG of East Asia was high or low before 97

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%

6

1

–4

–9

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004

Figure 4.1

GDP growth

40

%

35

30

25

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004

Figure 4.2

Investment ratio

65

%

60

55

50 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004

Figure 4.3

Employment rate

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99

the 1990s is an issue that probably has not yet been completely resolved, the TFPG controversy renewed our awareness of the importance of total factor productivity in the long-term growth of countries.2 Indeed, there are many empirical studies which show that a country’s long-term growth is mainly driven by TFPG performance (for example, Klenow and Rodriguez-Clare 1997; Hall and Jones 1999).3 Other studies show that even medium-term changes in growth are driven by variations in TFPG rather than variations in inputs accumulation (Easterly et al. 1993; Rodrik 1999; Hayashi and Prescott 2002). Theoretically, both neoclassical growth theories and endogenous growth theories point to the importance of technological progress or human capital accumulation in determining the long-run standard of living of a country. Insofar as the measured TFPG reflects improvement of human knowledge or technology, examining the role of TFPG in the growth of countries is a meaningful exercise to understand a country’s growth performance. After the outbreak of the crisis in 1997, the Korean government undertook various far-reaching microeconomic structural reforms in four main areas – financial sector, corporate sector, labor market and public sector – in addition to the initial stabilization program adopted under the auspices of the International Monetary Fund (IMF).4 By and large, those structural reforms could be understood as an attempt to move away from the chaebol- and bank-centered economic system towards ‘a more decentralized, atomistic corporate sector, a more competitive, market-based financial sector, a more flexible labor market, and a less interventionist public sector’.5 These reforms were pushed through based on the recognition that the chaebol- and bank-centered economic system, which had supported the so-called ‘input-driven’ growth of Korea in the past, was at the root of the problems in the corporate and banking sector that existed even before the crisis. However, these reforms were not without controversies. In particular, they were criticized for focusing on issues that were not directly related to the causes of the crisis, and for ‘overlooking the fundamental strengths of the Korean model while attempting to remake the economy along Anglo-Saxon lines’.6 While the controversies about the structural reforms still remain unsettled, the prolonged slowdown in growth after the crisis has triggered debates about the causes of the slowdown. Although the specific contexts have differed from the earlier controversies on the structural reforms, the nature of the debated issues was very similar to the earlier one. At the risk of oversimplification, there have been broadly two contrasting views. One view is that Korea’s growth before the crisis was too ‘high’ to be sustained. Those who hold this view often suggest that pre-crisis growth of Korea was sustained by the ‘overinvestment’ of chaebols, which are under the

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implicit guarantee provided by the government.7 By contrast, another view is that the growth potential of the Korean economy has been weakened since the crisis due to some of the reform measures that were implemented after the crisis. Those who are on this side of the argument insist, for example, that the strengthened regulations on governance and capital structure of chaebols in particular, as well as opening of the stock market allowing foreign mergers and acquisitions (M&As), have constrained the investment decisions of chaebol firms, weakening the growth potential of the whole economy. As exemplified by these debates, adequate understanding of the postcrisis growth of the Korean economy seems important in formulating an appropriate policy direction. In this regard, empirical assessment of the post-crisis growth performance of Korea seems to be important. In this study, we use both primal and dual approaches to growth accounting to decompose output growth of Korea into inputs accumulation and TFPG. Roughly speaking, the former uses primarily factor quantities, while the latter uses factor prices. If the factor price data are consistent with the factor quantity data, the primal estimates should be identical to the dual estimates. In this sense, by comparing the primal estimates with the dual estimates, we can examine the reliability of data used in our growth accounting exercises. Meanwhile, examining Korea’s growth performance alone cannot shed much light on evaluating the post-crisis growth of Korea. For a more informed assessment of Korea’s growth, this chapter evaluates Korea’s post-crisis growth performance in a cross-country comparative perspective. To do so, we use both growth accounting and cross-country regressions. In particular, using a cross-country regression approach allows us to control for the effects of various factors, such as initial conditions and region- or period-specific effects, in explaining the post-crisis growth of Korea. Although this chapter is not aimed at illuminating what those region- or period-specific effects are, if any, examining whether those effects exist at all would be the first step toward understanding Korea’s growth performance. Furthermore, explaining Korea’s economic growth for the long period spanning before, during and after the 1997 crisis from a broad international perspective allows us to understand better the debates outlined above: the TFPG controversy, the appropriateness of IMF-led reforms as crisis management, and the reasons for the slowdown after the crisis. This chapter is organized as follows. The next section discusses our primal and dual growth accounting results based on data from national sources. Section 4.3 will discuss Korea’s post-crisis growth performance, using cross-country comparison of growth accounting results as well as

Understanding the post-crisis growth of the Korean economy

101

cross-country regressions. The final section summarizes our chapter and concludes.

4.2 4.2.1

SOURCES OF KOREAN ECONOMIC GROWTH: 1981–2005 Methodology and Data

In this section, we perform growth accounting of Korea’s economy for the period from 1981 to 2005. Growth accounting does not provide information on fundamental determinants of economic growth, but information on the proximate determinants of growth such as inputs accumulation and technological change. Hence it can be viewed as a preliminary step for the analysis of fundamental determinants of economic growth. The goal of growth accounting exercises in this chapter is to figure out which proximate determinant has mainly driven the growth slowdown after the crisis. We employ the method of Young (1995) for the primal approach, and Hsieh (2002) for the dual approach, with minor modifications when necessary. Primal growth accounting approach We start with the Cobb–Douglas production function.8 Y (t) 5 AtK (t) aL (t) 1 2a

(4.1)

where Y , A, K, and L denote output, total factor productivity, capital input, and labor input respectively, and a denotes the elasticity of output with respect to capital which is equivalent to the capital income share under the assumption of perfect competition. Differentiating the logarithm of equation (4.1) with respect to time, we have: Y^ (t) 5 A^ (t) 1 aK^ (t) 1 (1 2 a) L^ (t)

(4.2)

where x^ denotes a growth rate of x. To consider more finely differentiated inputs, we assume that aggregate capital and labor input are translogarithmic indices of subinputs. Then in a way analogous to equation (4.2), we can obtain: K^ (t) 5 a qK (t) K^ i (t) , L^ (t) 5 a qL (t) L^ i (t) i

i

i

(4.3)

i

where qi 5 [ qi (t) 1 qi (t 2 1) ] /2 and where qi’s denote the elasticity of an aggregate input with respect to each of its component subinputs, which

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The rise of China and structural changes in Korea and Asia

can be regarded as the share of each subinput in total payments to the aggregate input under the assumption of perfect competition. As Young (1995) pointed out, it is worthwhile to note that these indices adjust for improvements in the quality of aggregate inputs, by weighting the growth of each subinput by its average marginal product. The appropriate measure of capital and labor input for the production function is not the stock of these inputs, but the service flow from these inputs. As it is difficult to measure the flow of capital services due to limited data on capital utilization, we assume that capital service flow is proportional to the capital stock, denoted by Ci (t) : that is, Ki (t) 5 lK Ci (t) . Then: i

K^ (t) 5 a qK (t) C^ i (t) i

(4.4)

i

In the case of labor, we assume that labor service flow is proportional to total hours of work: Li (t) 5 lL Hi (t) . Therefore: i

L^ (t) 5 a qL (t) H^ i (t) i

(4.5)

i

Dual growth accounting approach The dual approach suggested by Hsieh (2002) can be derived readily from the basic equality between national output and factor incomes: Y (t) 5 r (t) K (t) 1 w (t) L (t)

(4.6)

where r and w denote real rental price of capital and real wage per hour, respectively. Differentiating equation (4.6) with respect to time and dividing by Y, we obtain: Y^ (t) 5 QK (r^ (t) 1 K^ (t)) 1 QL (w^ (t) 1 L^ (t))

(4.7)

where Qi denotes the income share of input factor i. Rearrangement of the terms involving the growth rates of factor quantities on the left-hand side of the equation leads to: Y^ (t) 2 QKK^ (t) 2 QLL^ (t) 5 QKr^ (t) 1 QLw^ (t)

(4.8)

The left-hand side of equation (4.8) represents the primal estimate of TFP growth, and the dual estimate of the TFP growth is obtained as the shareweighted growth in factor prices, shown on the right-hand side of equation (4.8). Hence, the equality between the primal estimates and the dual

Understanding the post-crisis growth of the Korean economy

103

estimates is based on only the condition that output equals factor incomes. No other assumptions about factor prices or production function are needed for this result. In a similar way to the factor quantities, the aggregate factor prices can be measured as the share-weighted sum of the subinput prices. r^ (t) 5 a qK (t) ri (t) , w^ (t) 5 a qL (t) w^ i (t) i

i

i

(4.9)

i

Data and measurement issues We divide capital input into five subinputs: residential buildings, nonresidential buildings, other durable structures, transport equipment and machinery. For the economy as a whole, national accounts provide data on investment in these five subinputs, but data on investment in each subinput at industry level is not available. To estimate the capital stock, we use a standard perpetual inventory method. Young (1995) pointed out that using the national wealth survey results as the initial value of the capital stock can be problematic because some non-ignorable discrepancies are found between the results in the national wealth survey and the annual investment flows in the national accounts. Instead, he recommended the following method for estimating the initial value of the capital stock. Assuming that the average growth rate of investment in the first five years is representative of the growth of investment prior to the beginning of the series, the initial value of the capital stock can be expressed by: `

Cj (0) 5 a (1 2 d) iIj ( 2 i 2 1) i `

5 a (1 2 d) iIj (0) (1 1 gj) 2i21 5 Ij (0) / (gj 1 dj)

(4.10)

i

where Ij (0) is the investment for asset j in the first year, gj is the average growth rate of investment in the first five years, and dj is the depreciation rate. Since we construct capital stock series starting from 1953, sufficiently long prior to the first date of our analysis, the initial level of capital should not make a significant difference in our growth accounting results, given positive rates of depreciation and fairly high growth rates of investment. Our depreciation rates in the analysis are based on those from the Bureau of Economic Analysis (BEA) which provides the estimates of depreciation rates for very specific asset types. We use the unweighted average of the depreciation rates of the detailed asset types which are likely to be found in each of the five broad asset types.9 For labor inputs, we divide the working population into 30 subgroups,

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The rise of China and structural changes in Korea and Asia

cross-classified by three attributes, that is, sex (two categories), age (five categories), and education (three categories). Since the National Statistical Office Census does not publish the information specific enough for the cross-classification of these three attributes, we use the raw data of Occupational Wage Survey (henceforth, OWS) to estimate the working population of each subgroup.10 With regard to the overall size of the labor force, we accept Young’s argument that there can be a sizable gap between Census and OWS. We estimate the number of workers for each subgroup by multiplying the total number of workers from Census by the share of each subgroup calculated from OWS. In this way, our growth accounting analysis is confined to Census years only.11 The hours of work for each subgroup are calculated from the raw data of OWS. Turning to factor shares, we adopt the labor income share of 0.646 from Kim (1998) and take the capital income share to be simply one minus the labor income share under the assumption of perfect competition and constant return to scale. To obtain the share of each subgroup in the total labor income, we combine hourly wage and total hours of work for each subgroup. To allocate capital income by asset type, we estimate the rental price of a capital good ki following Young (1995): Pk (t) 5 PI (t 2 1) R (t) 1 dPI (t) 2 [ PI (t) 2 PI (t 2 1) ] i

i

i

i

i

(4.11)

where PI denotes the investment price of capital good i and R (t) is the nominal rate of return. The nominal rate of return, being assumed to be common for all asset types, is chosen to make the sum of rental payments to capital by equation (4.11) satisfy the aggregate income share of capital, 0.354. For dual approach, we estimate nominal wage of each subgroup of workers by combining the compensation of employees from national accounts and the hours of work and relative wage of each subgroup of workers from the OWS. The GDP deflator is used to convert the nominal wage into the real wage. While we can use the rental price of capital calculated by the equation (4.11) with the ex post nominal rate of return which ensures the aggregate capital income share of 0.354, it is more desirable to use some ex ante market nominal rate of return from financial market data, considering that the purpose of the dual approach is a consistency check of data. Hsieh (2002) examined curb market loan rate, deposit rate and discount rate as the market interest rate of Korea for the 1966–90 period. However, it is well known that the deposit rate and discount rate were regulated by the monetary authority in Korea until 1991. The data on the curb market loan rate lacks the homogeneity of the loan and has not been available since i

Understanding the post-crisis growth of the Korean economy

105

60 Corporate bonds

Curb loan

Call

50

%

40 30 20 10 0

1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004

Source:

Bank of Korea (1995); Collins and Park (1989).

Figure 4.4

Trends in nominal interest rates

20

15

%

10

5

0

–5

Note:

1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004

Real interest rate = corporate bond yield – inflation rate of capital goods.

Figure 4.5

Real interest rate

1990. Call rate is regarded as a policy interest rate under the inflation targeting regime after the economic crisis. Considering all the shortcomings of these interest rates, we used the yield of corporate bonds as the nominal rate of return, as corporate bond yield has not been directly regulated by the monetary authority since 1980 and was highly correlated with the curb market loan rate (see Figure 4.4). The real interest rate computed by subtracting the inflation rate from the corporate bond yield exhibits substantial fluctuations (see Figure 4.5),

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The rise of China and structural changes in Korea and Asia

Table 4.1

Primal growth accounting of the Korean economy: 1981–2005 (%)

Time period GDP

1981–85 1986–90 1991–95 1996–2000 2001–05

7.5 9.2 7.5 4.3 4.5

Raw Weighted Raw Weighted capital capital labor labor 9.8 11.3 11.4 6.9 5.0

9.5 12.3 11.6 6.6 4.7

0.7 2.3 2.5 0.1 0.0

2.7 4.0 4.2 1.6 1.3

TFP TFP (raw (weighted inputs) inputs) 3.7 3.8 1.9 1.8 2.8

2.5 2.3 0.8 1.0 2.0

which means the growth accounting results can be sensitive to different initial points and end points. Following Hsieh’s (2002) suggestion to mitigate this sensitivity issue, we used the time trend of the sum of the real interest rate and the depreciation rate in calculating the growth rate of the real rental price.12 4.2.2

Aggregate GDP Growth

Primal estimates Table 4.1 presents the primal growth accounting results for 1981–2005.13 It is easily noticeable that the slowdown of growth after the economic crisis has come from decelerated growth of inputs, both capital and labor. In particular, the capital growth rate declined substantially after the crisis. In terms of weighted inputs, capital growth fell sharply to 4.7 percent per annum in the 2001–05 period from 11.6 percent in the 1991–95 period. Labor input growth has also decelerated significantly from 4.2 percent in the 1991–95 period to 1.3 percent in the 2001–2005 period. In contrast to decelerated input growth, total factor productivity growth appears to have improved after the economic crisis, rising from 0.8 percent per annum in the 1991–95 period to 2.0 percent in the 2001–2005 period. Considering that TFP growth of the Korean economy had been around 1.5 percent for the 1961–90 period, the recent performance of TFP can be evaluated to be above its historical trend. Dual estimates Table 4.2 reports dual estimates of TFP growth based on factor prices. The real rental price of capital in Korea has exhibited a declining tendency reflecting fast capital deepening, except for some periods of stagnant investment during the early 1980s and the economic crisis. Real wage

Understanding the post-crisis growth of the Korean economy

Table 4.2

107

Dual growth accounting of the Korean economy (%)

Time period 1981–85 1986–90 1991–95 1996–2000 2001–05

GDP

Rental price of capital

Wages

Dual TFP

7.5 9.2 7.5 4.3 4.5

0.9 −4.3 −2.8 0.1 −2.9

3.2 4.6 2.6 0.3 3.5

2.4 1.5 0.8 0.2 1.3

4 Primal TFP Dual TFP

3

%

2 1 0 –1 –2

1981–85

Figure 4.6

1986–90

1991–95

1996–2000

2001–05

Primal and dual TFP growth

growth peaked in the 1986–90 period when the labor unions were very vigorous, while it was depressed around the economic crisis when the employment conditions were severely aggravated. As shown in Figure 4.6, the dual estimates of TFP growth seem to coincide with the primal estimates, at least concerning the slowdown of economic growth after the economic crisis. The dual estimate of TFP growth decelerated only slightly from 0.8 percent per annum in the 1991–95 period to 0.2 percent in the 1996–2000 period, implying that it could not be a main contributor to the slowdown of economic growth after the crisis. Furthermore, the TFP growth estimate rose to 1.3 percent per annum in the 2001–2005 period. 4.2.3

Per Capita GDP Growth

We can gain a better understanding about the main contributors to GDP growth slowdown by dividing the GDP growth into GDP per capita

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The rise of China and structural changes in Korea and Asia

growth and population growth, and in turn by decomposing the growth in GDP per capita into the changes in capital per worker, hours of work, composition of workers, TFP, ratio of workers to population of working age, and ratio of population of working age to total population: Y^ (t) 2 P^ (t) 5 (1 2 a) 1 (1 2 a) a qL h^ j (t) 1 (1 2 a) a qL n^ j (t) i

j51

i

j51

1 A (t) 1 (N^ (t) 2 W^ (t)) 1 (W^ (t) 2 P^ (t))

(4.12)

where P denotes total population, hj denotes the hours of work per worker of subgroup j, nj denotes composition of workers of subgroup j, N denotes the total number of workers, and W denotes population of working age. Table 4.3 shows that the slowdown of GDP growth after the economic crisis was mainly due to GDP per capita growth rather than population growth. Population growth had already decreased to 0.5 percent per annum in 1991–95 period before the economic crisis. While most components except TFP contribute to the deceleration of three percentage points in GDP per capita growth between the 1991–95 period and the 2001–05 period, capital per worker and ratio of workers to working age the population are most prominent factors for slowing GDP per capita growth, each contributing −1.8 percent points and −1.5 percent points respectively. Hours of work, composition of workers, and ratio of working age population to total population also provided negative contributions to GDP per capita growth; however, the contribution of each factor is relatively small, −0.5 percent points at most. In other words, it is neither an adverse change in demography, nor working hours but stagnant investment and worsened employment conditions that are the key phenomena related to the slowdown of growth after the economic crisis. 4.2.4

Sectoral Growth

Table 4.4 presents growth accounting results at industry level. Output growth slowdown after the economic crisis was common in services, manufacturing and other industry,14 but was more pronounced in services than manufacturing. Output growth in services fell from 7.4 percent per annum in the 1991–95 period to 3.8 percent in the 2001–05 period, while that in manufacturing declined moderately from 7.9 percent to 6.4 percent. Deceleration of capital growth has been more outstanding in services and other industry, with a dramatic fall of around seven percentage points in both sectors between the 1991–95 period and the 2001–05 period. In manufacturing, capital growth has shown a relatively mild slowdown, with a fall of 4.2 percentage points.

109

Annual growth of GDP per capita

6.0 7.8 7.0 3.6 4.0

1981–85 1986–90 1991–95 1996–2000 2001–05

2.5 2.3 0.8 1.0 2.0

TFP

2.9 3.1 3.1 2.1 1.3

1.2 0.9 1.0 0.8 0.7

Capital per Composition worker of workers −0.1 −0.4 0.1 −0.1 −0.4

Hours of work

Contribution of:

Decomposition of per capita GDP growth (%)

Time period

Table 4.3

−1.6 1.2 1.4 −0.6 −0.1

Worker / PWA 1.1 0.8 0.7 0.5 0.5

PWA / population

1.5 1.4 0.5 0.7 0.5

Annual growth of population

7.5 9.2 7.5 4.3 4.5

Annual growth of GDP

110

1981–85 1986–90 1991–95 1996–2000 2001–05

1981–85 1986–90 1991–95 1996–2000 2001–05

Services

Other Industry

1981–85 1986–90 1991–95 1996–2000 2001–05

Time Period

0.4 1.1 −1.6 −1.3 0.4 1.0 4.5 −0.1 −1.0 1.7

1.0 1.8 −1.2 −0.3 1.2 1.3 4.8 0.1 −0.5 2.7

4.3 5.7 7.1 3.9 2.4 4.9 5.5 5.1 −1.9 2.3

3.3 4.7 6.4 2.4 1.1 4.4 5.1 4.7 −2.6 0.8

NA NA NA NA NA

9.2 7.9 9.9 5.3 2.7

7.4 10.8 6.6 −0.3 4.2

5.1 1.5 3.7 5.8 4.6 6.4 2.7 4.8 6.6 5.4

3.5 7.7 1.3 −0.7 −0.2

NA NA NA NA NA

1.6 5.8 −0.5 −1.9 −1.4

TFP (Weighted Input)

TFP (Raw Input)

Weighted Labor

10.2 10.6 12.5 7.5 5.4

NA NA NA NA NA

9.0 15.6 9.9 6.6 5.7

10.6 11.9 7.9 7.6 6.4

Raw Labor

6.7 8.5 7.4 3.9 3.8

Weighted Capital

Raw Capital

GDP

Sectoral growth: manufacturing and services (%)

Manufacturing

Table 4.4

Understanding the post-crisis growth of the Korean economy

111

It is also in services that labor input growth slowed down most severely, declining from 7.1 percent per annum in the 1991–95 period to 2.4 percent in the 2001–2005 period. Other industry also experienced a substantial deceleration of labor input growth with a fall of 2.8 percentage points between the 1991–95 period and the 2001–05 period. Though labor input growth in manufacturing has recorded negative numbers since the mid1990s, reflecting deindustrialization, manufacturing exhibited a relatively moderate deceleration in labor input growth after the crisis. In contrast to diverging input growth across industries, improvement in TFP growth seems to be across the board. The TFP growth in manufacturing became stronger after the crisis, while services and other industry experienced a turnaround of productivity growth from some negative numbers in the 1990s to positive numbers in the 2001–05 period. However, productivity growth in services, though improved significantly from −1.6 percent per annum in the 1991–95 period, remained at the low 0.4 percent per annum in the 2001–05 period. The improvement of TFP growth across industries does not contradict the argument that all the structural reforms broadly implemented after the economic crisis might enhance overall productivity of the Korean economy. Though we do not pursue further what has contributed to the improvement of TFP growth, it is worthwhile to mention that firm dynamics is probably one of the key factors. Based on an analysis using firm-level data on manufacturing, Ahn (2006) suggested that the improvement of TFP growth is likely to be a result of heightened firm dynamics since the crisis, such as entry and exit of firms and interindustry movements, to which some structural reforms have facilitated. According to his results, the contribution of firm dynamics to the overall TFP growth, having remained below 15 percent in the early 1990s, jumped to around 70 percent during the crisis and has stabilized at about 20 percent since then. Ahn (2006) also provided the TFPG estimates of more-disaggregate industries in manufacturing. In his study, the improvement of TFPG in manufacturing has been mainly attributed to the high-tech industry whose productivity growth has accelerated after the crisis, whereas the mediumtech industry has been at a standstill and the productivity growth of the low-tech industry has declined. A recent study of Pyo et al. (2008), using the EU KLEMS (capital (K), labour, energy, material and service inputs) approach, also suggests that the rise in manufacturing industry’s contribution to the aggregate TFPG is largely due to the information technology (IT) product industry and other export-oriented industries like motor vehicles and chemicals, along with overall improvement across industries. In contrast, service industry’s contribution to aggregate TFPG after the crisis is confined to only a few industries such as wholesale, hotel and restaurants, and financial intermediation.

112

4.3

The rise of China and structural changes in Korea and Asia

EVALUATING POST-CRISIS GROWTH IN AN INTERNATIONAL PERSPECTIVE

In the previous section, we performed a detailed growth accounting exercise of the Korean economy, utilizing data from national sources. However, it is difficult to evaluate Korea’s growth experience based on growth accounting without appropriate benchmarks, which can be provided by comparison with other countries’ experiences. Thus, in this section, we try to evaluate the growth performance of the Korean economy since the 1990s in a broad international context. We use both growth accounting and cross-country regressions, which are two widely employed methodologies in this field. In particular, using crosscountry regressions allows us to control for the effects of, for example, initial conditions and period-specific factors that are common across countries. In this study, we first perform growth accounting exercise for 83 countries for the period from 1960 to 2004 to decompose growth of GDP per economically active population (worker, henceforth) into accumulation of inputs per worker and TFPG, relying on common methodology and data. Using common methodology and data allows us to make a meaningful comparison of growth accounting results across countries, since growth accounting results are usually sensitive to methodology and data. Then, we evaluate the pre- and post-crisis growth performance of the Korean economy in terms of per worker GDP growth, capital accumulation per worker, and TFPG, respectively. The growth accounting methodology of this study closely follows Bosworth and Collins (2003), which is outlined below. We assume a constant returns to scale production function of the form: Y 5 AKaL1 2a where Y denotes real output, K is capital stock, L is economically active population, and A is a parameter denoting total factor productivity. With some manipulation, the above equation can be rearranged to give: K a EAP # WAP # Y5A#a b # POP L WAP POP where EAP (5 L), WAP and POP are economically active population, working-age population and total population, respectively. If we take the log difference of the above equation, the resulting equation decomposes real output growth into five components: population growth, changes in working-age population ratio, Dlog (WAP/POP) changes in participation

Understanding the post-crisis growth of the Korean economy

113

ratio, D log (EAP/WAP) contribution from per worker capital stock, aD log (K/L) and total factor productivity growth TFPG. The real GDP data is the purchasing power parity (PPP)-adjusted real GDP from Penn World Table 6.2. The capital stock data is from Nehru and Dhareshwar (1993) and was extended up to 2004 using real investment growth rate data from World Development Indicators (WDI) from the World Bank. The data for population, working-age population and economically active population were extracted from WDI. As in Bosworth and Collins (2003) we assume a capital income share of 0.35 which is common across countries. 4.3.1

Sources of Growth: Korea and Major Regions

Table 4.5 (also Appendix Table 4A.2 and Figure 4.7) shows a growth accounting summary of Korea together with main regions and countries for the period from 1961 to 2004. The regional averages were calculated using PPP-adjusted GDP, averaged over the corresponding period, as weights. The table shows some of the salient features of world growth experiences since the 1960s – the end of the Golden Age and the productivity slowdown of industrial countries after the first oil shock, rapid catchup growth of East Asian countries, the lost decade of Latin American countries, and the growth tragedies of sub-Saharan African countries, the rise of China since the late 1970s, and so on – which have been documented and examined numerously elsewhere. In addition, the figures in the table are also consistent with Easterly et al. (1993), which shows that capital accumulation of countries is more persistent over time than TFPG. The table also replicates several key characteristics of Korea’s economic growth since the 1960s. Firstly, Korea’s per worker GDP growth is not only spectacular but is also sustained over a long period of time relative to other developing regions, such as Latin America or sub-Saharan Africa. Secondly, rapid income growth of Korea has been driven mainly by capital accumulation. Finally, in view of the ‘miraculous’ output growth, the TFPG of Korea is rather modest from an international perspective.15 Above all, in spite of the substantial ‘slowdown’, the post-crisis growth performance of the Korean economy is still respectable by international standards. Per worker GDP growth rate of Korea for the period from 2001 to 2004, which is 2.9 percent per annum, is still substantially higher than most developing regions including East Asia and industrial countries.16 In fact, the Korean economy slowed down after year 2000 along with the global slowdown. Table 4.5 shows that the weighted per worker GDP growth rate of 83 sample countries declined from 3.6 percent in 1990s to 2.6 percent in the first half of the 2000s. The notable exceptions are China

114

The rise of China and structural changes in Korea and Asia 1961–2004

10

TFP (K/L)

9 8 7

%

6 5 4

3.4

1.8

3 1

2

1.1 2.1

1

1.1

1.8

0.4 0.6

East

Latin

0 Industrial China

1.8

0.9

2.9

Korea

10

1.1

0.3 0.6

1.2

SouthA Africa MiddleA

1961–70

TFP (K/L)

9 8 7

%

6 5 4

1.6

3

2.7

2.3 1.1

2 1

1.7

1.6

2.1

1

3 1.6

1.1

1.5

1.1

Latin

SouthA

Africa

0.1

0

Industrial China

1.8

Korea

East

1971–80

10

1.8

MiddleA TFP (K/L)

9 8 7

%

6 5 0.8

4

2.0 2.2

3

0.1

1.5

2

3.8 0.7

1

1.0

1.3

2.6

1.9

1.6

0.9

0.0

2.7

1.6

0 Industrial China

Figure 4.7

Korea

East

Latin

SouthA Africa MiddleA

Sources of growth by region, 1961–2004 (weighted, %)

Understanding the post-crisis growth of the Korean economy 10 9 8 7 6 5 4 3 2 1 0 –1 –2

1981–1990

4.7

%

TFP (K/L)

3.4 0.4

1.1 0.7

2.3

2.8

2.4 1.8

–0.1

Korea

East

Latin

–0.1

SouthA

0.3

0.1

0.9

–1.7

Industrial China 10 9 8 7 6 5 4 3 2 1 0 –1

115

0.5

Africa MiddleA

1991–2000

TFP (K/L)

5.1

1.5

0.9 0.8

3.3

Industrial China

0.6 2.7

Korea

1.7

East

1.8 0.1

1.1

0.1

0.2

–0.1

Latin

SouthA Africa MiddleA

2001–04

10

1.1

–0.2

TFP (K/L)

9 8 7

%

6 3.2

5 4 3 2 1

0

3.6

0.9

2.1

1.5 1.3

0

0.9 0.5

0.2 –0.8

1.2

0.7 0.5

–0.1 –0.1

–1 Industrial China

Korea

East

Latin

SouthA Africa MiddleA

116

Table 4.5

The rise of China and structural changes in Korea and Asia

Sources of growth in major regions: 1961–2004, weighted (%)

Region/period

World (83) 1961–70 1971–80 1981–90 1991–2000 2001–04 1961–04 Industrial (22) 1961–70 1971–80 1981–90 1991–2000 2001–04 1961–04 China 1961–70 1971–80 1981–90 1991–2000 2001–04 1961–04 Korea 1961–70 1971–80 1981–90 1991–2000 (1991–97) 2001–04 1961–04 East Asia (5) less China and Korea 1961–70 1971–80 1981–90 1991–2000 2001–04 1961–04 Latin America (83) 1961–70 1971–80

GDP growth

Per worker GDP growth

5.3 4.0 3.7 3.6 2.6 4.0

Contribution from (K/L)

TFP

3.5 2.2 2.0 2.2 1.5 2.4

1.5 1.3 0.8 1.0 1.0 1.2

2.1 0.9 1.1 1.2 0.4 1.3

5.3 3.2 2.9 2.6 1.8 3.3

3.9 1.7 1.8 1.7 1.1 2.1

1.7 1.0 0.7 0.8 0.9 1.1

2.3 0.7 1.1 0.9 0.2 1.1

3.5 5.9 9.5 9.7 7.8 7.2

1.6 4.1 6.9 8.4 6.9 5.4

0.1 1.9 2.3 3.3 3.6 2.1

1.6 2.2 4.7 5.1 3.2 3.4

7.7 7.3 8.6 5.8

4.7 4.6 6.1 4.1

3.0 3.8 2.8 2.7

1.6 0.8 3.4 1.5

4.5 7.1

2.9 4.7

1.3 2.9

1.5 1.8

5.7 7.5 5.6 4.9 3.4 5.7

2.7 4.5 2.3 2.3 1.3 2.8

1.6 2.6 1.8 1.7 0.5 1.8

1.1 2.0 0.4 0.6 0.9 1.0

5.8 5.8

3.2 3.1

1.1 1.6

2.1 1.5

Understanding the post-crisis growth of the Korean economy

Table 4.5

117

(continued)

Region/period

GDP growth

1981–90 1.4 1991–2000 3.1 2001–04 1.5 1961–04 3.7 South Asia (4) 1961–70 5.3 1971–80 3.9 1981–90 5.3 1991–2000 4.7 2001–04 5.6 1961–04 4.9 Sub-Saharan Africa(19) 1961–70 4.5 1971–80 3.7 1981–90 3.0 1991–2000 2.7 2001–04 2.9 1961–04 3.4 Middle East and North Africa (9) 1961–70 6.3 1971–80 4.2 1981–90 3.8 1991–2000 4.0 (1991–97) 2001–04 3.0 1961–04 4.4

Per worker GDP growth

Contribution from (K/L)

TFP

−1.8 0.2 −1.0 1.0

−0.1 0.1 0.2 0.6

−1.7 −0.2 −0.8 0.4

3.3 2.2 3.3 2.9 3.3 3.0

1.5 0.9 0.9 1.1 1.2 1.1

1.8 1.3 2.4 1.8 2.1 1.8

2.1 1.6 0.0 0.1 1.4 1.0

1.1 1.6 −0.1 −0.1 0.5 0.6

1.8 1.3 2.4 1.8 2.1 1.8

2.1 1.6 0.0 0.1

1.1 1.6 −0.1 −0.1

1.0 0.0 0.1 0.1

1.4 1.0

0.5 0.6

0.7 0.3

and India (included in South Asia), which seem to dwarf the still respectable growth performance of Korea after the crisis.17 In short, at least part of the growth slowdown of the Korean economy might be attributable to the slowdown of the global economy. As is well known, the pace of capital accumulation in Korea before the crisis was not only spectacular by international standards, but also was sustained for a long period of time. Compared with the pre-crisis level, the post-crisis per worker capital accumulation slowed down to less than half. This has raised concerns about ‘depressed’ investment by the public and policy-makers and triggered several studies examining its causes.18 However, the post-crisis per worker capital growth rate in Korea, which is 1.3 percentage points per annum in terms of its contribution to per worker

118

The rise of China and structural changes in Korea and Asia

output growth, is still higher than any other regional averages, although not as spectacular as in the pre-crisis period. Again, the most notable exception is China, which recorded per worker capital growth contribution of 3.6 percentage points per annum for the period 2001–04. In sum, a fair assessment would be that the period that distinguishes Korea most from other regions or countries in terms of capital accumulation is before, rather than after the crisis. In other words, per worker capital accumulation in Korea after the crisis still seems respectable, although not miraculous. One interesting aspect of Table 4.5 is that the significant slowdown of capital accumulation after the year 2000 is a phenomenon which is not confined to Korea but is commonly observed in East Asian countries. Specifically, the growth rate of capital per worker in East Asian countries (excluding Korea) declined from 1.7 percent in the 1990s to 0.5 percent in the first half of the 2000s. The slowdown in growth of capital per worker in Korea is not much different in its pace from other East Asian countries. No other regions seem to have experienced a significant slowdown of per worker capital accumulation after the year 2000. This observation suggests that at least part of the slowdown might be related to factors that are common across East Asian countries. It also suggests that Korea-specific factors might be insignificant in explaining the slowdown of capital accumulation.19 The total factor productivity growth rate for 2001–04, which is 1.5 percent per annum, seems not much different either from that of the 1990s, nor from the average for the whole period from 1961 to 2004, which is 1.8 percent. Thus, as we discussed above, the post-crisis slowdown of per worker GDP growth is not likely to have been driven by slowdown of TFPG. How then does the post-crisis performance of TFPG in Korea compare with other countries or regions? In contrast with the TFPG of the Korean economy for decades of period before the crisis, TFPG after the crisis seems to be higher than most other regions. Again, the TFP growth rates of China (3.2 percent) and the South Asia region (2.1 percent) were higher than that of Korea for the period from 2001 to 2004. However, the post-crisis TFPG of Korea was significantly higher than that of industrial countries (0.2 percent) or most other developing regions. In fact, the (weighted) TFPG of the world since the year 2000, which is 0.4 percent per annum, is much lower than in the 1990s (1.2 percent).20 These observations suggest that the post-crisis TFPG performance of Korea is fairly strong, and even became stronger in a comparative perspective, although its absolute level did not change much over the crisis. It is also suggested that in terms of relative rankings of TFPG, Korea’s standing might have improved after the crisis. This conjecture is actually confirmed (Table 4.6). With and without labor quality adjustment, Korea’s

119

Note:

4 (3.4) 20 (1.5) 14 (1.5) 11 (1.8)

39 (1.6) 47 (0.8)

Korea

Finland (2.3) Italy (1.8) Ireland (1.1) Cyprus (1.4) Tunisia (1.1) Portugal (1.4)

25 Egypt (1.5) Cameroon (1.1) Australia (0.3) Senegal (0.8) Turkey (0.0) Dominican (0.8)

50

Percentile

Education uncontrolled

Relative TFPG performance of Korea

New Zealand (0.6) Ethiopia (0.1) Colombia (−1.2) Switzerland (−0.5) Cote d’Ivoire (−1.3) New Zealand (0.1)

75 41 (1.0) 55 (−0.1) 5 (2.3) 21 (1.0) 13 (1.2) 16 (1.1)

Korea

France (2.2) Panama (1.5) Japan (0.8) Korea (1.0) Malaysia (0.9) Finland (1.0)

25

Dominican (1.0) Austria (0.6) Canada (-0.2) Bolivia (0.4) Peru (−0.2) Cameroon (0.4)

50

Percentile

Education controlled

Numbers denote rankings in TFPG among 83 sample countries. Numbers in parenthesis denote TFPG (%).

1961–04

2001–04

1991–2000

1981–90

1971–80

1961–70

Table 4.6

Uganda (0.1) Sierra Leone (−0.1) Uruguay (−1.8) Zimbabwe (−1.3) Iran (−2.2) Peru (−0.5)

75

120

The rise of China and structural changes in Korea and Asia

ranking in TFPG performance in the period from 2001 to 2004 is 14th and 13th, respectively, among 83 countries, which have improved from the ranking (20th and 21st) in the 1990s. This conclusion still holds even if we control for improvement of quality of labor, as shown in Appendix Table 4A.4. 4.3.2

Assessment of Post-Crisis Growth of Korea: Cross-Country Regressions

In the previous subsection, we discussed the post-crisis growth performance of Korea in comparison with those of other countries in the same period. In this subsection, we evaluate the pre- and post-crisis growth performance of Korea using the framework of cross-country growth regressions. As mentioned earlier, using cross-country regressions allows us to control for some of the well-known determinants of growth, such as initial conditions, in evaluating Korea’s growth performance.21 In addition, we pay particular attention to the respective roles of period-specific factors which are common across countries, and region-specific factors in East Asian countries in explaining changes over the crisis in growth rates of GDP per worker, capital per worker, and TFPG. First of all, Table 4.7 shows pooled ordering least squares (OLS) regressions of decadal growth rate of per worker GDP. The first regression includes a dummy variable for Korea interacted with decadal dummies. So, the estimated coefficients on the interaction terms are the differences between per worker GDP growth rates of Korea for the corresponding period and the average of the 83 countries over 1961–2004 (1.5 percent, annual average). Generally, the positive coefficients on interaction terms in the first column reflect the relatively high per worker GDP growth rate of Korea in a comparative perspective, consistent with our discussion in the previous subsection. Per worker GDP growth rate of Korea in the 2000s is lower by 1.2 percentage points than in the 1990s, as can be seen by comparing the 1990s with the 2000s. Yet it is still higher than the sample average by 1.4 percentage points. As discussed earlier, the growth slowdown of Korea proceeded along with the slowdown of the global economy. To control for these effects that are common across countries, we included decade dummy variables in the second regression. Then, it turns out that the per worker GDP slowdown in Korea is much less visible, controlling for decade effects. It is found that the per worker GDP growth rate of Korea in the 2000s is lower only by 0.7 percentage points. So, it is suggested that period-specific factors, such as global economic slowdown, account for a significant part (0.5 percentage points) of the decline in the per worker GDP growth of Korea.

121

0.015*** (12.46) 0.032 (1.32) 0.031 (1.29) 0.047** (1.94) 0.026 (1.10) 0.014 (0.57)

constant

Per capita GDP (relative to US) Life expectancy at birth Trade share

2000s × Korea

1990s × Korea

1980s × Korea

1970s × Korea

1960s × Korea

Model 1 0.030*** (11.94) 0.017 (0.75) 0.023 (1.06) 0.058*** (2.62) 0.029 (1.31) 0.022 (0.98)

Model 2 −0.192*** (−4.46) 0.012 (0.55) 0.018 (0.83) 0.055*** (2.54) 0.028 (1.33) 0.021 (0.99) −0.008*** (−4.04) 0.053*** (5.19)

Model 3 −0.226*** (−5.26) 0.001 (0.05) 0.008 (0.39) 0.048*** (2.42) 0.029 (1.48) 0.025 (1.28) −0.016*** (−7.51) 0.053*** (5.25) 0.009** (2.31)

Model 4

Regression of per worker GDP growth with Korea dummy variable

Variable

Table 4.7

−0.211*** (−4.90) 0.003 (0.12) −0.012 (−0.57) 0.031 (1.42) 0.016 (0.74) 0.017 (0.79) −0.016*** (−7.16) 0.050*** (4.92) 0.008* (1.89)

Model 5

−0.254*** (−3.97) 0.003 (0.19) 0.013 (0.82) 0.039** (2.45) 0.022 (1.36) 0.018 (1.12) −0.013*** (−5.97) 0.068*** (4.49)

Model 3 (sub sample)

122

X 0.021 404

O 0.186 404

Model 2

O 0.238 402

Model 3

O 0.368 365

0.004*** (5.48) −0.055*** (−4.04)

Model 4 0.004*** (5.54) −0.057*** (−4.21) 0.013 (1.32) 0.008 (0.79) O 0.385 365

Model 5

O 0.364 205

Model 3 (sub sample)

Notes: Pooled OLS regressions. Dependent variable is decadal average per worker GDP growth rate. Numbers in parentheses are t-statistics. Coefficients with asterisks are significant at 1% (***), 5% (**), and 10% (*) level. Coefficients of interaction terms of decadal dummy variables with East Asia dummy variable are shown only for 1990s and 2000s. Last column of the table shows regression result for a subsample, which excludes South America and sub-Saharan African countries.

Decade dummy R2 obs.

2000s × East Asia

Natural resource endowment 1990s × East Asia

Model 1

(continued)

Institutional quality

Variable

Table 4.7

Understanding the post-crisis growth of the Korean economy

123

In regression (4.3), we included initial conditions: per worker GDP relative to the US at the beginning year of each period, and life expectancy at birth. Nevertheless, the coefficients on the Korea dummy interacted with dummy variables of the 1990s and 2000s hardly changed. This suggests that the convergence effect has little role in explaining the post-crisis growth slowdown in Korea. Also, inclusion of some of the well-known growth determinants – such as trade (exports plus imports) share of GDP, institutional quality, natural resource endowment – did not change the picture.22 In regression (4.5) we additionally included an East Asia region dummy variable interacted with decade dummy variables. In this case, the coefficient on the Korea dummy in the 2000s became almost similar in size to that of the 1990s. This suggests that almost all of the growth slowdown of Korea after the crisis can be attributed to the combined effects from East Asia region-specific factors and period-specific factors, such as the global economic slowdown. Also, it is still a valid conclusion that per worker GDP growth of Korea after the crisis is not ‘low’ in a comparative perspective.23 Next, we turn to the regressions of per worker capital growth. In the previous subsection, we argued that the post-crisis slowdown of per worker capital growth mainly reflects the spectacular rate of capital accumulation before the crisis, rather than weak performance after the crisis. This argument is supported by the first column of Table 4.8, which shows large and significantly positive coefficients on the Korea dummy variable up to the 1990s. Although post-crisis per worker capital growth in Korea seems dwarfed by the spectacularly high rate of accumulation before the crisis, it is still respectable by international standards. In contrast with per worker GDP growth, period-specific factors do not explain the post-crisis slowdown of per worker capital growth in Korea, as shown in regression (4.2). The inclusion of initial conditions or other policy variables hardly affect the coefficients on interaction terms. However, regression (4.5) strongly suggests that the post-crisis decline of per worker capital growth in Korea is likely to be due, to a large extent, to some East Asia region-specific factors. Specifically, the coefficient on the Korea dummy variable interacted with the dummy variable for the 2000s became almost similar in size to that of 1990s, with the inclusion of interaction terms between East Asia dummy variables and period dummy variables. Taken together, the regression results indicate that the abrupt slowdown of capital accumulation in Korea is synonymous with the end of the miraculously fast and sustained capital accumulation before the crisis, which was a common characteristic among high-performing East Asian

124

0.024*** (16.07) 0.063** (2.17) 0.085*** (2.91) 0.056** (1.93) 0.052** (1.80) 0.014 (0.49)

constant

Per capita GDP (relative to US) Life expectancy at birth Trade share

2000s × Korea

1990s × Korea

1980s × Korea

1970s × Korea

1960s × Korea

Model 1 0.039*** (13.69) 0.047* (1.83) 0.068*** (2.63) 0.069*** (2.64) 0.063*** (2.41) 0.026 (0.98)

Model 2 −0.110** (−2.1) 0.045* (1.77) 0.065*** (2.52) 0.066*** (2.58) 0.061*** (2.37) 0.023 (0.9) −0.003 (−1.21) 0.036*** (2.95)

Model 3 −0.112** (−2.18) 0.032 (1.41) 0.050** (2.15) 0.055*** (2.41) 0.056*** (2.46) 0.020 (0.88) −0.010*** (−3.84) 0.032*** (2.63) 0.015*** (3.2)

Model 4

Regressions of per worker capital growth with Korea dummy variable

Variable

Table 4.8

−0.082 (−1.64) 0.014 (0.57) 0.021 (0.85) 0.016 (0.66) 0.021 (0.85) 0.023 (0.93) −0.008*** (−3.31) 0.025** (2.14) 0.013*** (2.80)

Model 5

−0.121 (−1.26) 0.030 (1.25) 0.056** (2.35) 0.051** (2.12) 0.054** (2.25) 0.020 (0.85) −0.009*** (−2.78) 0.040* (1.75)

Model 3 (subsample)

125

X 0.049 400

O 0.255 400

O 0.288 390

O 0.421 353

0.002*** (2.86) −0.105*** (−6.5)

O 0.458 353

0.002*** (2.96) −0.110*** (−7.12) 0.037*** (3.21) −0.004 (−0.36) O 0.333 202

Notes: Pooled OLS regressions. Dependent variable is decadal average per worker GDP growth rate. Numbers in parentheses are t-statistics. Coefficients with asterisks are significant at 1% (***), 5% (**), and 10% (*) level. Coefficients of interaction terms of decadal dummy variables with East Asia dummy variable are shown only for 1990s and 2000s. Last column of the table shows regression result for a subsample, which excludes South America and sub-Saharan African countries.

Decade dummy R2 obs.

2000s × East Asia

Natural resource endowment 1990s × East Asia

Institutional quality

126

The rise of China and structural changes in Korea and Asia

countries. In this respect, the causes of the slowdown in capital accumulation are likely to be related to factors that affected East Asian countries at the same time.24 Finally, we turn to regressions of TFPG (Table 4.9). Overall, Table 4.9 shows that the TFP growth rate of Korea is not significantly different from the international norm, although it is somewhat higher. If we control for the period effects (regression 4.2), the coefficient on the Korea dummy in the 2000s becomes somewhat higher than in the 1990s. This suggests that Korea maintained rather well its pace of efficiency improvement during the 2000s, in spite of the global slowdown in TFPG. The regressions also suggest that other East Asian countries, as well as Korea, also exhibited relatively strong TFPG performance during the 2000s. That is, when we included interactions between East Asia dummy variables and period dummy variables, the coefficient on Korea in the 2000s became similar to that in the 1990s. To summarize our main regression results, first of all, the post-crisis growth slowdown of the Korean economy is mostly explained by East Asian region-specific factors as well as period-specific factors, such as global slowdown. East Asia region-specific factors are found to have affected the per worker GDP growth slowdown through the capital accumulation channel, while period-specific factors worked through the TFPG channel. Other than these two factors, there is almost nothing left to be explained about the growth slowdown of Korea.

4.4

CONCLUDING REMARKS

In this chapter, we have tried to examine sources of growth of the Korean economy and evaluate the post-crisis growth performance from an international perspective using both growth accounting and cross-country regressions. Above all, it was found that the post-crisis growth slowdown in Korea was mainly driven by the slowdown of per worker capital accumulation. By contrast, TFPG of Korea in post-crisis period was estimated to be somewhat higher, if at all, than the pre-crisis period in the 1990s. Next, the cross-country regressions reveal that the post-crisis growth slowdown can be mostly attributed to East Asia-specific effects and period effects, such as global slowdown. In particular, the noticeable deceleration in per worker capital accumulation was found to be mostly attributable to some unknown factors which commonly affected East Asian countries. Overall, the evidence indicates that the lowered pace of growth and capital accumulation of the Korean economy after the crisis, which triggered concerns and debates in diverse contexts, still seems respectable from

127

0.007*** (7.24) 0.009 (0.50) 0.001 (0.06) 0.027 (1.43) 0.008 (0.42) 0.008 (0.45)

constant

Per capita GDP (relative to US) Life expectancy at birth Trade share

2000s × Korea

1990s × Korea

1980s × Korea

1970s × Korea

1960s × Korea

Model 1 0.016*** (7.91) 0.000 (0.00) 0.000 (−0.02) 0.034* (1.89) 0.007 (0.41) 0.012 (0.68)

Model 2 −0.160*** (−4.49) −0.004 (−0.22) −0.005 (−0.27) 0.031* (1.79) 0.007 (0.41) 0.012 (0.71) −0.007*** (−4.15) 0.042*** (4.96)

Model 3

Regressions of TFPG with Korea dummy variable

Variable

Table 4.9

−0.195*** (−5.38) −0.010 (−0.61) −0.009 (−0.58) 0.028* (1.76) 0.010 (0.59) 0.017 (1.07) −0.012*** (−6.69) 0.044*** (5.22) 0.004 (1.07)

Model 4 −0.189*** (−5.19) −0.002 (−0.11) −0.019 (−1.08) 0.025 (1.40) 0.008 (0.47) 0.009 (0.48) −0.012*** (−6.51) 0.043*** (5.05) 0.003 (0.80)

Model 5

−0.213*** (−4.49) −0.007 (−0.63) −0.007 (−0.55) 0.022* (1.81) 0.003 (0.27) 0.010 (0.87) −0.010*** (−6.11) 0.054*** (4.83)

Model 3 (sub sample)

128

(continued)

X 0.007 391

Model 1

O 0.097 391

Model 2

O 0.152 390

Model 3

O 0.250 353

0.003*** (4.59) −0.017 (−1.49)

Model 4 0.003*** (4.61) −0.017 (−1.50) 0.001 (0.12) 0.009 (1.07) O 0.259 353

Model 5

O 0.278 202

Model 3 (sub sample)

Notes: Pooled OLS regressions. Dependent variable is decadal average per worker GDP growth rate. Numbers in parentheses are t-statistics. Coefficients with asterisks are significant at 1% (***), 5% (**) and 10% (*) level. Coefficients of interaction terms of decadal dummy variables with East Asia dummy variable are shown only for 1990s and 2000s. Last column of the table shows regression result for a subsample, which excludes South America and Sub-Saharan African countries.

Decade Dummy R2 obs.

2000s × East Asia

Natural resource endowment 1990s × East Asia

Institutional quality

Variable

Table 4.9

Understanding the post-crisis growth of the Korean economy

129

an international perspective. Also, the abrupt slowdown of capital accumulation in Korea is synonymous with the end of the miraculously fast and sustained capital accumulation before the crisis, which was a common characteristic among high-performing East Asian countries. In this respect, the terminology ‘depressed’ investment might be a misnomer. What, then are the exact natures of these East Asia region-specific factors? At this stage, we have no clear answer for this question. However, we think answering this question seems to be important for better understanding of the growth process of the Korean economy, as well as the economies of other East Asian countries, before and after the crisis. Further studies are needed to address this issue.

NOTES *

1. 2.

3. 4. 5.

6.

This chapter was originally prepared for the KDI conference on ‘Growth and Structural Changes of the Korean Economy after the Crisis: Coping with the Rise of China’. We are grateful for helpful comments and suggestions from the seminar participants. All errors are the author’s own. Discussion of the large literature related to this issue is outside the scope of this chapter. Hsieh (2002), among others, argued that estimated TFPG in Singapore was not ‘low’ as suggested by Young (1995), based on dual growth accounting methodology. See Hsieh (2002) for a discussion of the issues on the ‘TFPG controversy’. See also Barro (1999) for a discussion of more general methodological issues on growth accounting and the TFPG controversy. Mankiw et al. (1992) show, however, that accumulation of inputs accounts for most of the cross-country variations of growth rates, once the improvement of schooling quality is adequately accounted for. See Chung and Eichengreen (2004) for a summary of these structural reforms. For a more detailed description of the contents of the structural reforms, see Koh et al. (2007). The quoted phrase is from Chung and Eichengreen (2004). The financial reform in Korea is succinctly summarized by the following paragraph from Chung and Eichengreen (2004): ‘It proved easier to push through changes in the structure of the financial sector, in part because the banks had long been under implicit or explicit government control. Central bank independence was buttressed. Statutes and regulations governing foreign bank ownership were liberalized. Prudential rules governing loan classification, provisioning, connected lending, short term foreign borrowing and foreign currency exposures were tightened, and responsibility for supervision and regulation was consolidated in a single independent agency. Insolvent banks and nonblank financial institutions were nationalized, merged, or closed.’ Alternatively, Koh et al. (2007) summarize that two main goals of the financial reform were normalization of the financial system and improvement of the financial safety net. Meahwhile, corporate reforms were aimed at the restructuring of distressed firms, as well as strengthening market discipline and improving efficiency in the corporate sector (Koh et al. 2007). The quoted phrase is also from Chung and Eichengreen (2004). As is well known, there were two contrasting views on the cause of the Korean exchange crisis: the fundamental view and the panic view. Koh et al. (2007) argue that there are some elements of truth in both views as an explanation of the Korean crisis.

130 7.

8.

9.

10.

11.

12.

13.

14. 15.

The rise of China and structural changes in Korea and Asia Hahn (2000) provides empirical evidence, based on sales accelerator model of investment, suggesting that Korean top chaebol firms exhibited higher investment rates than independent firms before the crisis. Hong (2006b) reports that, compared with the precrisis period, profitability and the default risk became a more significant determinant of investment in Korean firms after the crisis. For growth accounting, we do not need this specific form of production function. Young (1995) employed a more general form of production function, the translogarithmic value-added production function which was developed by Christensen et al. (1971). Diewert (1976) discussed several advantages of the translogarithmic function approach. We adopt the Cobb–Douglas function since we assume the factor income share between aggregate capital and aggregate labor to be fixed over time. We also tried other depreciation rates such as those in Hulten and Wykoff (1981) and Pyo (2003). The results with Hulten and Wykoff’s (1981) depreciation rates are not significantly different from those with the BEA’s depreciation rates. There are some noticeable differences when Pyo’s (2003) depreciation rates used, since Pyo (2003) includes some negative depreciation rates. Young (1995) estimated each cell of working population by the iterative proportion fitting technique with the published information of Census. His method has some advantage over using OWS, because OWS does not include the self-employed and unpaid family workers while Census does. However, the published Census for some years did not provide specific information enough to apply the iterative proportion fitting technique at industry level. Since the changes in the quantity of labor inputs have dominated the quality changes, which method is employed for quality adjustment of labor input does not seem to affect the growth accounting results significantly. How the sample period is split, either by Census years or by before and after the crisis, does not seem to change the qualitative implication of the growth accounting. As seen in Appendix Table 4A.2 which presents another growth accounting results using annual data, there is no significant difference between the accounting results for 1991–2000 and that for 1991–97. Dividing equation (4.11) by the GDP deflator and differencing it with respect to time, the growth rate of the real rental price of capital is obtained as the sum of the growth rate of the relative price of capital and the growth rate of the sum of the real interest rate and the depreciation rate. We replace the growth rate of the sum of the real interest rate and the depreciation rate by the point estimate of its time trend divided by its average value. For comparison purposes with previous studies, we analyzed the entire economy as well as the non-agricultural economy to which Young applied his analysis. The results for the non-agricultural economy are not reported here but are available upon request. Due to transfers of labor from agriculture to the other sectors, the non-agricultural economy exhibits higher labor input growth and, as a result, lower TFP growth. In spite of some modifications in methodology and data sources, our estimate results of labor seem to be comparable to Young (1995). For example, the annual growth of weighted labor inputs for the 1981–85 period and the 1986–90 period are 4.8 percent and 6.8 percent respectively, compares to 4.7 percent and 7.2 percent respectively in Young (1995). However, our estimates of TFP are not close to those of Young (1995), because the GDP and investments in our analysis are measured in 2000 prices and in the 1993 System of National Accounts (SNA) while those in Young (1995) were measured in 1985 prices and in the 1968 SNA. ‘Other industry’ combines mining, electricity, gas and water, and construction. Young (1995) argues that the estimated TFPG of Korea and other East Asian Tigers are only comparable to those observed in industrial countries. The total factor productivity growth rate of Korea in Table 4.5 might appear somewhat ‘high’ relative to the industrial region. However, if we control for labor quality with education measures, the TFPG of Korea for the whole period becomes similar to those of industrial countries (Appendix Table 4A.4). Meanwhile, the labor quality index was calculated by assuming

Understanding the post-crisis growth of the Korean economy

16.

17.

18. 19.

20.

21.

22.

23. 24.

131

a 7 percent rate of return to additional schooling year, H 5 (1.07) s, as in Bosworth and Collins (2003). We used average years of schooling of population aged 25 or older from Barro and Lee (2001). The East Asia region (excluding China) in this chapter includes Korea, Singapore, Malaysia, Thailand, Indonesia and the Philippines, and excludes countries such as Taiwan and Hong Kong (SAR). As will be discussed again later, not only Korea but also other East Asian countries experienced a growth slowdown after the 1990s. Tamura (1996) shows both theoretically and empirically that, given the world knowledge spillover, countries that start the catch-up growth process later grow faster. Lucas (2002) also argues that this view is consistent with the long-run historical experiences of countries. From this perspective, it is not surprising to observe rapid growth in China and India which can be deemed to be ‘latecomers’ in the catch-up process. For example, see Hong (2006a, b) and Lim and Choi (2006). Hong (2006a) argues, based on a similar observation, that adjustments of capital structure of highly leveraged firms in Korea after the East Asian financial crisis in late 1990s is likely to be one of the reasons behind the post-crisis slowdown in the investment growth of Korea. It should be noted, however, that Singapore also experienced a significant slowdown in capital accumulation, but did not experience a financial crisis. One could conjecture that the slowdown of East Asian countries might be due to the ‘convergence’ effect. As we will discuss below, however, this effect is not quantitatively important in explaining the abrupt and large decline in per worker capital accumulation. The slowdown of the world weighted TFPG since the year 2000 mainly reflects the deteriorated TFPG performance of industrial countries. Deteriorated TFPG performance of the world is also observed in terms of unweighted averages, which is shown in Appendix Table 4A.5. One could think of taking into account the roles of various determinants of growth, such as policies or institutions, in explaining the growth slowdown of Korea. However, primarily due to the problem of data availability for such variables, our attempt in this direction is very limited. Instead we focus our efforts on providing some facts on Korea’s economic growth which are useful for understanding growth slowdown after the crisis. It should be noted, however, the institutional quality and natural resource endowment are fixed for each country. One should be careful to interpret this result as indicating that policy or institutions did not matter for the growth slowdown. The institutional quality variable is from Knack and Keefer (1995) and natural resource endowment is the share of primary product exports in GDP from Sachs and Warner (1995). The last column of Table 4.7 shows subsample regression, which excludes Latin American as well as sub-Saharan African countries. The regression result does not affect our conclusion. Again, the exclusion of sub-Saharan African countries and Latin American countries does not affect the conclusion.

REFERENCES Ahn, Sanghoon (2006), ‘A micro-data-based analysis of industrial productivity of the Korean economy after the 1990s’, in Inseok Shin and Chin Hee Hahn (eds), Structural Changes of the Korean Economy After the Crisis, Korea Development Institute Research Monograph 2006-07 (in Korean). Bank of Korea (1995), Statistics of BOK – Past and Present, Seoul: Bank of Korea. Barro, Robert (1999), ‘Notes on growth accounting’, Journal of Economic Growth, 4(2), 119–37.

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Bosworth, Barry P. and Susan M. Collins (2003), ‘The empirics of growth: an update’, Brookings Papers on Economic Activity, 2003(2), 113–79. Christensen, L.R., Dale W. Jorgenson and L.J. Lau (1971), ‘Conjugate duality and the transcendental logarithmic production function’, Econometrica, 39, 255–6. Chung, Duck-Koo and Barry Eichengreen (2004), The Korean Economy Beyond the Crisis, Cheltenham, UK and Northampton, MA, USA: Edward Elgar. Collins, Susan M. and Won-Am Park (1989), ‘External debt and macroeconomic performance in South Korea’, in Jeffrey D. Sachs and Susan M. Collins (eds), Developing Country Debt and Economic Performance, Vol. 3, Chicago, IL: University of Chicago Press, pp. 151–369. Diewert, W.E. (1976), ‘Exact and superlative index numbers’, Journal of Econometrics, 4, 115–45. Easterly, William, Michael Kremer, Lant Pritchett and Lawrence H. Summers (1993), ‘Good policy or good luck? Country growth performance and temporary shocks’, Journal of Monetary Economics, 32, 459–83. Hahn, Chin Hee (2000), ‘Implicit loss-protection and the investment behavior of Korean chaebols’, in Inseok Shin (ed.), Korean Crisis: Before and After, Seoul: Korea Development Institute, pp. 215–51. Hahn, Chin Hee (2006), ‘Import competition from China and developed countries and growth of plants’, in Inseok Shin and Chin Hee Hahn (eds), Structural Changes of the Korean Economy After the Crisis, Korea Development Institute Research Monograph 2006-07 (in Korean), pp. 431–75. Hall, Robert E. and Charles I. Jones (1999), ‘Why do some countries produce so much more output per worker than others?’, The Quarterly Journal of Economics, 144(1), 83–116. Hayashi, Fumio and Edward C. Prescott (2002), ‘The 1990s in Japan: a lost decade’, Review of Economic Dynamics, 5(1), 206–35. Hong, Ki-Seok (2006a), ‘Fixed investment in Korea and other crisis-hit Asian countries’, in Inseok Shin and Chin Hee Hahn (eds), Structural Changes of the Korean Economy After the Crisis, Korea Development Institute Research Monograph 2006-07 (in Korean), pp. 107–55. Hong, Ki-Seok (2006b), ‘Micro analysis of determinants of investment by Korean firms’, Economic Analysis, 12(1) (in Korean). Hsieh, C. (2002), ‘What explains the industrial revolution in East Asia? Evidence from the factor markets’, American Economic Review, 92, 502–26. Hulten, Charles R. and Frank C. Wykoff (1981), ‘The measurement of economic depreciation’, in Charles R. Hulten (ed.), Depreciation, Inflation, and the Taxation of Income from Capital, Washington, DC: Urban Institute Press, pp. 81–125. Kim, Jong-Il and Lawrence J. Lau (1994), ‘The sources of economic growth of the East Asian newly industrialized countries’, Journal of the Japanese and International Economies, 8(3), 235–71. Kim, Jong-Il and Lawrence J. Lau (1996), ‘The sources of Asian Pacific economic growth’, Canadian Journal of Economics/Revue canadienne d’Economique, 29(2), S448–S454. Kim, Joon-Kyung, Yangseon Kim and Chung H. Lee (2006), ‘Trade, investment and economic integration of South Korea and China’, Korea Development Institute Working Paper 2006-01. Kim, Kwangsuk (1998), ‘Sources of Korea’s economic growth and future growth potential’, IGE Research Report 98-01, Institute for Global Economics.

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Klenow, Peter J. and Andres Rodriguez-Clare (1997), ‘The neoclassical revival in growth economics: has it gone too far?’, NBER, Macroeconomics Annual, 12, 73–103. Knack, Stephen and Philip Keefer (1995), ‘Institutions and economic performance: cross-country tests using alternative institutional measures’, Economics and Politics, 7(3), 207. Koh, Young-Sun, Kyungsoo Choi, Inseok Shin, Won-Hyuck Lim, Jin Park, Chin Hee Hahn, Sukha Shin, Chang-gyun Park, Chang-yong Rhee and Dae-Keun Park (2007), Ten Years After the Crisis: Evaluation and Agenda, Seoul: Korea Development Institute (in Korean). Lall, Sanjaya and Manuel Albaladejo (2004), ‘China’s competitive performance: a threat to East Asian manufactured exports?’, World Development, 32(9), 1441–66. Lee, Hangyong (2005), ‘An empirical analysis of the uncertainties and investment’, Korea Development Institute Journal of Economic Policy, 27(2) (in Korean), 89–121. Lim, Kyung-Mook and Yong-Seok Choi (2006), ‘Patterns and determinants of cash holdings of firms’, Korea Development Institute Policy Research Series, 2006-11 (in Korean). Lucas, Robert E. (2002), Lectures on Economic Growth, Boston, MA: Harvard University Press. Mankiw, N. Gregory, David Romer and David N. Weil (1992), ‘A contribution to the empirics of economic growth’, Quarterly Journal of Economics, 107(2), 407–37. Nehru, Vikram and Ashok Dhareshwar (1993), ‘A new database on physical capital stock: sources, methodology and results’, Revista de Analisi Economico, 8(1), 37–59. Pyo, Hak K. (2003), ‘Estimates of capital stocks by industries and types of assets in Korea (1953–2000)’, Journal of Korean Economic Analysis, 8(3). Pyo, Hak K., Hyunbae Chun and Keun Hee Rhee (2008), ‘Total factor productivity by 72 industries in Korea and international comparison (1970–2005)’, Working Paper No. 324, Institute for Monetary and Economic Research, The Bank of Korea. Rodrik, Dani (1999), ‘Where did all the growth go? External shocks, social conflict, and growth collapses’, Journal of Economic Growth, 4(4), 385–412. Sachs, Jeffrey and Andrew Warner (1995), ‘Economic reform and the process of global integration’, Brookings Papers on Economic Activity, 1, 1–118. Tamura, R. (1996), ‘From decay to growth: a demographic transition to economic growth’, Journal of Economic Dynamics and Control, 20, 1237–62. Young, Alwyn (1995), ‘The tyranny of numbers: confronting the statistical realities of the East Asian growth experience’, Quarterly Journal of Economics, 110(3), 641–80.

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APPENDIX Table 4A.1

Country groups

Group

Countries

East Asia (7 countries)

China, Indonesia, Korea, Malaysia, Philippines, Singapore, Thailand

Latin America (22 countries)

Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Rep., Ecuador, El Salvador, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Trinidad and Tobago, Uruguay, Venezuela

Industrial countries (22 countries)

Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom, United States

South Asia (4 countries)

Bangladesh, India, Pakistan, Sri Lanka

Middle East and N. Africa (9 countries)

Algeria, Cyprus, Egypt, Iran, Israel, Jordan, Morocco, Tunisia, Turkey

Sub-Saharan Africa (19 countries)

Cameroon, Cote d’Ivoire, Ethiopia, Ghana, Kenya, Madagascar, Malawi, Mali, Mauritius, Mozambique, Nigeria, Rwanda, Senegal, Sierra Leone, South Africa, Tanzania, Zambia, Zimbabwe

135

1961–65 1966–70 1971–75 1976–80 1981–85 1986–90 1991–95 1996–00 2001–06

Table 4A.2

3.24 7.54 5.54 5.52 6.14 8.75 6.45 3.31 4.03

= a−h = c+f+g

= b+h = c+i

5.68 9.79 7.54 7.07 7.50 9.73 7.47 4.14 4.50

b

2.39 6.92 4.19 5.00 5.60 6.68 5.27 2.98 3.03

= a−i = d+e

c

GDP GDP growth growth per capita per worker

a

GDP growth

1.05 2.21 0.94 0.67 2.82 3.89 2.10 0.85 1.72

d

TFP

1.34 4.71 3.25 4.33 2.79 2.79 3.17 2.13 1.31

e

K/L

1.05 0.20 −0.06 −0.66 −0.58 1.05 0.72 0.04 0.89

f

EAP WAP

−0.39 0.43 1.42 1.18 1.11 1.01 0.46 0.29 0.09

G

WAP POP

Contribution by component(percentage point)

Alternative Estimate of the Sources of Growth in Korea (1961-2006)

2.59 2.25 2.00 1.55 1.36 0.99 1.01 0.83 0.47

h

POP

3.29 2.87 3.35 2.07 1.89 3.05 2.19 1.16 1.47

i

Growth of EAP

136

Notes:

5.39 5.53 7.44 4.88 (5.90) 4.03 (3.89) 5.61

= a−h = c+f+g

= b+h = c+i

7.74 7.30 8.62 5.80 (6.90) 4.50 (4.45) 7.05

b

4.66 4.59 6.14 4.13 (4.69) 3.03 (2.85) 4.68

= a−i = d+e

c

GDP GDP growth growth per capita per worker

a

GDP growth

(continued)

1.63 0.81 3.35 1.48 (1.67) 1.72 (1.52) 1.81

d

TFP

3.03 3.79 2.79 2.65 (3.01) 1.31 (1.32) 2.87

e

K/L

0.63 −0.36 0.24 0.38 (0.78) 0.89 (1.00) 0.29

f

EAP WAP

0.02 1.30 1.06 0.38 (0.43) 0.09 (0.03) 0.62

G

WAP POP

Contribution by component(percentage point)

EAP = economically active population, WAP = working age population, POP = total population.

1961–70 1971–80 1981–90 1991–00 (1991–97) 2001–06 (2001–04) 1961–06

Table 4A.2

2.42 1.78 1.17 0.92 (0.99) 0.47 (0.56) 1.45

h

POP

3.08 2.71 2.47 1.67 (2.21) 1.47 (1.60) 2.37

i

Growth of EAP

Understanding the post-crisis growth of the Korean economy

137 ⌬TFP ⌬(K/L)c ⌬(EAP)c ⌬(WAP)c ⌬TPOP

2.2 3.9 0.7

0.9 3.2

2.1

4.3

1.3

2.8 1.7

2.1

1.3

0.0 0.3 0.8

0.9 0.1 0.5

19

–0 01

96

–2

00

6

0

1.0

5

1.0

–9

–8 81

76

0.7 0.5

–9

–0.6

1.0

0

–0.7

5

1.4

–8

5

1.5

19

71

–7

0 19

19

66

–7

5 –6 61

1.1

0

–0.1

–0.4

19

1.1

1.2

86

2.2

2.0

0.9

3.2

19

1.4

19

2.6

0.2 0.4

20

2.8 1.1

91

1.1

2.8

19

4.7

Note: TFP = Total factor productivity. (K/L)c = contribution from per worker physical capital. (EAP)c = contribution from changes in participation rate. (WAP)c = contribution from changes in working age population ratio. TPOP = total population.

Figure 4A.1 Table 4A.3

Sources of growth in Korea (1961–2006) Decomposition of growth slowdown

GDP Per capita GDP Per worker GDP TFP K/L EAP/WAP WAP/POP POP

Average growth rate 2001–06

Average growth rate 1991–97

Difference

4.50 4.03 3.03 1.72 1.31 0.89 0.09 0.47

6.90 5.90 4.69 1.67 3.01 0.78 0.43 0.99

−2.40 −1.87 −1.66 0.05 −1.70 0.11 −0.34 −0.53

Notes: EAP = economically active population, WAP = working age population, POP = total population. Numbers below the fourth column denote contribution to GDP growth.

138

The rise of China and structural changes in Korea and Asia

Table 4A.4

Region/Period

Alternative estimate of TFPG in major regions: education controlled (%) GDP growth

World (83) 1961–70 5.3 1971–80 4.0 1981–90 3.7 1991–00 3.6 2001–04 2.6 1961–04 4.0 Industrial (22) 1961–70 5.3 1971–80 3.2 1981–90 2.9 1991–00 2.6 2001–04 1.8 1961–04 3.3 China 1961–70 3.5 1971–80 5.9 1981–90 9.5 1991–00 9.7 2001–04 7.8 1961–04 7.2 Korea 1961–70 7.7 1971–80 7.3 1981–90 8.6 1991–00 5.8 (1991–97) 2001–04 4.5 1961–04 7.1 East Asia (5) less China and Korea 1961–70 5.7 1971–80 7.5 1981–90 5.6 1991–00 4.9 2001–04 3.4 1961–04 5.7 1961–04 3.7

per worker GDP growth (%)

Contribution from (K/L)

(H/L)

TFPG

3.5 2.2 2.0 2.2 1.5 2.4

1.5 1.3 0.8 1.0 1.0 1.2

0.3 0.5 0.3 0.3 0.3 0.3

1.8 0.4 0.9 1.0 0.3 0.9

3.9 1.7 1.8 1.7 1.1 2.1

1.7 1.0 0.7 0.8 0.9 1.1

0.3 0.6 0.2 0.2 0.2 0.3

1.9 0.0 0.9 0.7 0.0 0.8

1.6 4.1 6.9 8.4 6.9 5.4

0.1 1.9 2.3 3.3 3.6 2.1

– 0.2 0.7 0.2 0.2 0.4

– 3.2 4.0 4.9 3.0 3.0

4.7 4.6 6.1 4.1

3.0 3.8 2.8 2.7

0.7 0.9 1.1 0.5

1.0 −0.1 2.3 1.0

2.9 4.7

1.3 2.9

0.3 0.7

1.2 1.1

2.7 4.5 2.3 2.3 1.3 2.8 1.0

1.6 2.6 1.7 1.8 0.5 1.8 0.6

0.4 0.4 0.4 0.6 0.4 0.4 0.3

0.7 1.6 0.1 0.0 0.5 0.6 0.0

Understanding the post-crisis growth of the Korean economy

Table 4A.4 Region/Period

139

(continued) GDP growth

per worker GDP growth (%)

South Asia (4) 1961–70 5.3 3.3 1971–80 3.9 2.2 1981–90 5.3 3.3 1991–00 4.7 2.9 2001–04 5.6 3.3 1961–04 4.9 3.0 Sub-Saharan Africa (19) 1961–70 4.5 2.1 1971–80 3.7 1.6 1981–90 3.0 0.0 1991–00 2.7 0.1 2001–04 2.9 1.4 1961–04 3.4 1.0 Middle East and North Africa (9) 1961–70 6.3 4.5 1971–80 4.2 2.7 1981–90 3.8 0.8 1991–00 4.0 1.3 (1991–97) 2001–04 3.0 −0.4 1961–04 4.4 2.0

Contribution from (K/L)

(H/L)

TFPG

1.5 0.9 0.9 1.1 1.2 1.1

0.2 0.3 0.4 0.4 0.4 0.3

1.5 1.0 2.0 1.4 1.7 1.5

1.1 1.6 −0.1 −0.1 0.5 0.6

0.1 0.2 0.2 0.8 0.0 0.3

1.5 0.4 −0.2 −1.0 0.9 0.3

1.8 2.7 0.5 0.2

0.1 0.4 0.6 0.5

2.5 −0.3 −0.3 0.6

−0.1 1.2

0.5 0.4

−0.9 0.4

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The rise of China and structural changes in Korea and Asia

Table 4A.5

Region/period

Sources of growth in major regions: 1961–2004, unweighted (%) GDP growth

World (83) 1961–70 5.2 1971–80 4.3 1981–90 2.9 1991–00 3.5 2001–04 2.7 1961–04 3.8 Industrial (22) 1961–70 5.1 1971–80 3.4 1981–90 2.5 1991–00 2.6 2001–04 2.1 1961–04 3.3 China 1961–70 3.5 1971–80 5.9 1981–90 9.5 1991–00 9.7 2001–04 7.8 1961–04 7.2 Korea 1961–70 7.7 1971–80 7.3 1981–90 8.6 1991–00 (1991–97) 5.8 2001–04 4.5 1961–04 7.1 East Asia (5) less China and Korea 1961–70 6.4 1971–80 7.7 1981–90 5.7 1991–00 5.5 2001–04 3.3 1961–04 6.1 Latin America (83) 1961–70 5.1 1971–80 4.7 1981–90 1.1

Per worker GDP growth

Contribution from (K/L)

TFP

3.0 2.3 0.4 1.3 0.7 1.7

1.4 1.4 0.4 0.5 0.4 0.9

1.6 0.8 0.0 0.8 0.3 0.8

4.0 1.8 1.4 1.7 1.1 2.1

1.9 1.2 0.7 0.7 0.7 1.1

2.2 0.7 0.7 1.1 0.3 1.1

1.6 4.1 6.9 8.4 6.9 5.4

0.1 1.9 2.3 3.3 3.6 2.1

1.6 2.2 4.7 5.1 3.2 3.4

4.7 4.6 6.1 4.1 2.9 4.7

3.0 3.8 2.8 2.7 1.3 2.9

1.6 0.8 3.4 1.5 1.5 1.8

3.2 4.4 2.3 2.9 1.3 3.1

2.4 2.6 1.7 1.7 0.5 2.0

0.8 1.8 0.6 1.2 0.8 1.1

2.6 2.2 −1.8

0.9 1.3 −0.1

1.6 0.9 −1.7

Understanding the post-crisis growth of the Korean economy

Table 4A.5 Region/period

141

(continued) GDP growth

1991–00 3.4 2001–04 2.1 1961–04 3.4 South Asia (4) 1961–70 5.9 1971–80 4.7 1981–90 5.1 1991–00 4.2 2001–04 4.8 1961–04 4.9 Sub-Saharan Africa (19) 1961–70 4.2 1971–80 3.5 1981–90 2.8 1991–00 3.0 2001–04 3.1 1961–04 3.3 Middle East and North Africa (9) 1961–70 6.2 1971–80 4.6 1981–90 4.1 1991–00 (1991-97) 4.2 2001–04 2.9 1961–04 4.6

Per worker GDP growth

Contribution from (K/L)

TFP

0.6 −0.6 0.8

0.3 0.0 0.6

0.2 −0.4 0.2

3.9 2.5 2.9 2.3 2.6 2.8

1.6 0.9 1.0 1.0 1.0 1.1

2.1 1.5 1.9 1.3 1.8 1.7

1.8 1.6 −0.2 0.5 0.9 0.9

1.0 1.1 −0.1 0.0 0.3 0.5

0.8 0.5 −0.1 0.5 0.3 0.4

3.9 3.2 1.1 1.0 −0.1 2.0

1.5 2.4 0.7 −0.1 −0.1 1.1

2.4 0.8 0.4 0.7 0.2 1.0

Note: pwGDP = per worker GDP; TFP = Total factor productivity; (K/L)c = the contribution of per worker physical capital.

5.

The economic growth of Korea since the 1990s: identifying contributing factors from demand and supply sides Seok-Kyun Hur

5.1

INTRODUCTION

This chapter stems from the question, ‘How should we understand the growth pattern of the Korean economy after the 1990s?’ Among various quantitative methods applicable, this study chooses the structural vector autoregression (SVAR) with long-run restrictions, identifies diverse impacts from either demand or supply sides that gave rise to the current status of the Korean economy, and differentiates the relative contributions of those impacts. Following Blanchard and Quah’s (1989) tradition, I distinguish permanent supply shocks from transient demand ones by levying various identification restrictions. In the first half of this chapter, I replicate Blanchard and Quah’s original two-variable model using Korean macro data. Then, I extend the models to a three-variable format consisting of demand, supply, demand, supply and price shocks. I demonstrate the estimation results of these two models here because these types of models are quite popular and could be used as benchmarks for other estimations. However, these models are not so sophisticated1 that they may reflect Korea’s specific features and historical experiences. As of the year 2007, looking back to the 1990s, the East Asian Currency Crisis in 1997 was a burning point for the Korean economy. In particular, for the foreign exchange market and in the money market, a flexible exchange rate system and the inflation-targeting rule in monetary policy were introduced, respectively. Needless to say, all the reform measures taken since the financial crisis exerted an enormous impact on the whole economy. Among these measures, however, the transition from a fixed exchange rate system to a floating one as well as the transition 142

The economic growth of Korea since the 1990s

143

from monetary aggregate targeting to an inflation-targeting regime was crucial. In this context, I introduce the next two linear stochastic differential systems of equations, both of which contrast such drastic institutional changes while adhering to the same set-up in other aspects. By solving the models, I represent key macro variables as linear functions of exogenous shocks coming possibly from various sources, and derive long-run identification restrictions following Blanchard and Quah (1989). Then, I levy the identifying restrictions to VAR systems consisting of the key variables and derive estimations using Korean data. I demonstrate estimation results in terms of Impulse Responses (IR) and forecasting error variance decomposition (FEVD) and interpret them in terms of economic growth. Eventually, my objective is to discern what portion of the economic growth of Korea is influenced by the impact of productivity growth through technological progress, or changes in aggregate demand induced by fluctuating consumption and investment, or exogenous shocks like those resulting from volatile oil prices. The contents of this chapter are construed as follows. The second section observes the recent trend in Korea’s economic growth and reviews several relevant pieces of domestic literature, which might help in clearly defining the scope and analytic methodology of this study. The third section provides a quantitative tool – structural VAR (SVAR) as mentioned above – to be used in this study. Accordingly, the variables used, estimation equations and the identification conditions of impacts are also explained. The fourth section reports estimation results derived in previously introduced models, and the fifth section concludes the chapter.

5.2

THE ECONOMIC GROWTH OF KOREA: A PHENOMENON AND DISCUSSIONS

In this section, I exhibit the economic growth of Korea in past decades and summarize the relevant domestic literature. Despite the abundant existing literature on the issue, I restrict my attention to those using SVAR methodology. 5.2.1

The Economic Growth of Korea

The fast-growing Korean economy, dating back to the 1960s, has been showing signs of a gradual slowdown. The lower economic growth following the financial crisis in 1997 is feared to be an indication of a slowdown in the growth of potential gross domestic product (GDP), which is at least partially attributed to the quickly aging demographic composition. As

144

Table 5.1

Period Average Volatility 15

The rise of China and structural changes in Korea and Asia

Averages and standard deviations of real GDP growth rate (1971.1Q–2007.2Q) (year-on-year % change) 1971–79

1980–89

1990–99

2000–2007 2Q

Whole period

8.1 3.4

7.4 3.8

6.0 4.8

5.0 2.1

6.7 3.9

(Year-on-year % change, Quarter-on-quarter % change)

10

5

0

–5

–10 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 ln (real GDP)

Figure 5.1

ln (real GDP(S.A))

Trends of real GDP growth rate (with or without treatment of seasonality)

seen in Table 5.1, the average real GDP growth has been falling from an impressive 8.1 percent during the 1970s to 5.0 percent during the 2000s. In the meantime, the volatility of GDP growth (measured by standard deviation) rose from 3.4 percent during the 1970s to 4.8 percent during the 1990s, falling again to 2.1 percent during the 2000s. When considering that the East Asian Currency Crisis broke out in the fourth quarter of 1997, it seems that the severity of business cycle fluctuations stayed more or less at the same level up to the late 1990s, becoming more subdued in the 2000s (see Figure 5.1). Such dampening business fluctuation seems to be related to the global prevalence of low interest rates and the emergence of China as a new world economic power. Bringing all these into consideration, it would be pivotal to identify post-crisis changes in various Korean market institutions and the surrounding global environment in order to understanding the growth path

The economic growth of Korea since the 1990s

145

of the Korean economy (at least) after the 1990s. Among the most remarkable post crisis reform measures2 taken in Korea, an inflation-targeting rule and the floating exchange rate system were introduced, while financial institutions were restructured. As is widely believed, financial restructuring led to changes of behaviors on both the demand and supply sides of the domestic capital market. Banks moved their focus from business finance to consumer loans in order to reduce risk exposure while enhancing profitability. Accordingly, households could enjoy the benefit of consumption smoothing from the alleviation of liquidity constraints (Hur and Sung 2003). In the meantime, most large firms, forced to lower their debt–equity ratios, began to accommodate the capital requirements through intial public offerings (IPOs) or internal reserves rather than debt financing. Banks could then enjoy excess capacity to lend, which in turn was directed towards consumer credit. In addition, the global phenomenon of low interest rates and mild inflation, which sustained stable growth from the late 1990s to the mid 2000s, contributed to settling the newly adopted inflation targeting rule (in 1997) and the flexible exchange rate system (in 1998) in post-crisis Korea. While those internal and external environmental changes could have lowered the business cycle amplitude, the slowed pace of economic growth in Korea still remains a puzzle. Hence, it is important to devise analytical frameworks beyond merely introducing major institutional changes so as to include various sources of shocks and their transmission channels, which may hinder economic growth. 5.2.2

Literature

In this section, I introduce three papers – all of which explore the economic growth and/or the business cycle of Korea since the 1990s using SVAR. The papers differ in the time span of data set used and the pool of variables chosen. Hence, direct comparison may be less conclusive than an assessment of their methodological differences. First, Shim (2001) deconstructs a post-crisis business cycle through factors based on Blanchard and Quah (1989) (B-Q hereafter). A linear system of sectoral equations, intended for deriving long-run restrictions, is arranged so that its structural moving average representation (SMAR) or a long-run impulse response matrix could be formed into a lower or upper triangular format.3 Shim (2001) does not consider post-crisis changes in the monetary policy rule and the exchange rate system,4 let alone foreign sectors. Second, Kim (2005) concentrates on analyzing the impact of foreign shocks on the domestic business cycle. Hence, Kim uses foreign variables,

146

The rise of China and structural changes in Korea and Asia

such as oil price and exchange rates, jointly with domestic variables including interest rate, Consumer Price Index (CPI), and the growth rate. Kim’s (2005) model, in common with Shim’s (2001), does not derive the relationship among shocks from an economic model. Instead he uses the Cholesky decomposition a priori. Third, Oh (2007) considers an open economy version of the Blanchard and Quah model. Matched with the three key variables of world import volume GDP and CPI he introduces three shocks of domestic supply, demand, and world supply. In terms of shock identification, Oh (2007) also assigns long-run restrictions to disturbances a priori.5 Keeping a distance from these predecessors, this chapter is based on economic models which allow the presence of shocks from various sources. This chapter introduces institutional changes in the monetary policy regime and the foreign exchange market. Then, I derive long-run restrictions by solving the models, and use them in estimating corresponding SVAR models.

5.3

MODELS

In the neoclassical framework, it is inevitable in the long run for an economy to experience a slowdown of growth. In reality, however, it is difficult to distinguish the long-run trend of a slowdown from the short-run business downturns. There are various statistical methods for decomposing the path of economic growth into the long-run trend and the short-run fluctuations. With the long series of macro variables available, these statistical methods are relatively easy to implement, but it is not uncommon to find the results hard to interpret under conventional economic reasoning. In contrast, there has been huge literature on identifying the transmission channels of shocks with the perception that a change in economic growth is the accumulated responses of various sectors to external shocks. Analysis of this category, based on an economic model, has a certain advantage of being consistent with economic institution. It is, however, unsatisfactory in that a slight change in the architecture of the model may lead to a different outcome. In this context, a more robust check would be required. This study encompasses the first approach from the standpoint of the second approach. The study derives long-run restrictions of an SVAR representation from a simple macroeconomic model. In the meantime, a number of shocks are introduced in the model. Some of these shocks affect a sector while others have influence on the economy beyond a sector. Roughly speaking, those shocks are categorized into two groups – demand

The economic growth of Korea since the 1990s

147

and supply shocks – which are, in turn, believed to reflect the business cycle and long-run growth trend, respectively. Behind this logic lies the general notion that demand shocks are transient whereas supply ones are permanent. As admitted by B-Q (1989), however, transient supply shocks or persistent demand shocks may exist in reality. Thus, it would be absurd to associate demand shocks with a volatile business cycle and supply shocks with the changing growth trend. In this context, my chapter resists the temptation to decompose economic growth into the long-run trend and the short-run fluctuations. 5.3.1

Sources of Shocks and Transmission Channels

In the following models, all the shocks are classified into demand-driven and supply-driven shocks, which are in turn grouped into domestic and foreign shocks. In addition, I consider the possibility that changes in the economic environment (internal or external) that the Korean economy has experienced since 1990 may have altered transmission channels while providing new sources of shocks. To begin with, noticeable internal changes in the economic environment have been made in restructuring the financial markets and adopting the inflation targeting rule and the floating exchange rate system, largely contributing to altering transmission channels. The global phenomenon of low interest rates, rising housing prices and the emergence of China as a world economic power are major external changes surrounding the Korean economy. Next, understanding demand and supply shocks within a framework of aggregate demand – aggregate supply (AD-AS), I define internal demand shocks to be idiosyncracies in consumption, investment, government budget, and the markets for domestic and foreign currencies, and represent external demand shocks to be rooted in the terms of trade and world economic growth. On the other hand, I comprehend that supply shocks are caused internally by changes in factor and total factor productivities, and externally by price fluctuations of raw materials (such as oil and iron ore) and technology spillover. A notable point here is that such a way of sorting shocks (and discerning changes in transmission channels from those in the magnitudes of shocks) is rather conceptual and does not provide a reliable yardstick to apply in reality. For example, alleviation of household credit constraints induced by the restructuring of the financial sector accompanies consumption growth. Also, it is not fully convincing to define total factor productivity (TFP) growth to be the sole domestic supply shock. TFP growth may result from international competition, or TFP growth may interact with

148

The rise of China and structural changes in Korea and Asia

increased demand for investment. In this regard, my way of introducing shocks has limitations. As a remedy, I present the four incomplete models and compare their results instead of searching indefinitely for just one complete model. 5.3.2

Equations of Estimation and Identifying Restrictions

In this study, I estimate the following four SVARs with long-run restrictions. The first two are based on Blanchard and Quah (1989), extending the original version of the two variables and two shocks to a variant of three variables and three shocks, which is to reflect the reality that the Korean economy is exposed to foreign risks more heavily than other economies. Thus, I add the inflation (pt) to real GDP growth (Dyt) and the unemployment rate (Ut) and match them with price shock6 (ept ), supply shock (est), and demand shock (edt), respectively. The latter two New Keynesian models borrowed from Stock and Watson (2002) both include real GDP growth (Dyt) and inflation (pt) . Then, depending on the type of monetary policy regime and foreign exchange rate system in place, monetary aggregate growth (Dmt) or exchange rate change (Det) is added. In this context, I claim that these models better describe the real image of the Korean economy than the B-Q (1989) type models.7 A three-variable extension of Blanchard and Quah (1989) Blanchard and Quah (1989) understand a VAR system in an equivalent MAR (moving average representation) and levy additional long-run restrictions on disturbances and their lags.8 B-Q present a simple model based on Fisher (1977) and provides a solution in the form of longrun restrictions on demand and supply shocks. Instead of repeating the already famous B-Q setup, I explain how it is extended to a model with three variables and three shocks. As for shocks, I decompose the supply shock into two parts – the price shock (ept ) and the productivity shock (est) – and add them to the existing demand shock (edt). In particular, ept has a direct influence on price determination, while indirectly working against aggregate demand and employment. Aggregate demand (a combination of IS and LM curves): Yt 5 Mt 2 Pt 1 aq1,t Aggregate supply (assuming a CRS production technology):

(5.1)

The economic growth of Korea since the 1990s

149

Yt 5 Nt 1 q1,t

(5.2)

Pt 5 Wt 2 q1,t 2 q2,t

(5.3)

Price equation:

Wage equation: Wt 5 W 0 E

t21

[Nt ] 5N

5 W 0E

t21

, Ut ; N 2 Nt

[Ut ] 50

or Et21 [ Wt ] 5 Wt, Et21 [ Nt ] 5 N

(5.4)

All the shocks of this economy follow first-order autoregression (AR(1)) processes. Furthermore, demand shock (edt) supply shock (est), and price shock(ept ) are orthogonal to each other: Mt 5 Mt21 1 edt, q1,t 5 q1,t21 1 est, q2,t 5 q2,t21 1 ept

(5.5)

Manipulating (5.1)–(5.5) properly, I derive the following matrix, in which key macro variables,9 such as real GDP growth (DYt), inflation (pt), and unemployment rate (Ut)10 are represented as moving averages of exogenous shocks: (a 1 1) DYt £ pt § 5 £ 2 1 Ut 2a

1 0 21

2 1 est 2a d 1 § £ et § 1 £ a 1 ept 0

21 1 0

1 est21 2 1 § £ edt21 § 0 ept 21 (5.6)

By simply ignoring the subscripts t and summing the right-hand side of the SVMAR, I obtain the long-run restriction matrix C: (a 1 1) £ 21 2a

1 0 21

21 2a 1 § 1 £ a 1 0

1 5 £ (a 2 1) 2a

0 1 21

21 1 0 0 0§ 1

1 2 1§ 0

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The rise of China and structural changes in Korea and Asia

NA C 5 £ NA NA

0 NA NA

0 0 § NA

(5.7)

With these long-run restrictions, all the shocks are exactly identified. Their effects on the three key variables, both long-run and short-run, are summarized as follows. To begin with, demand shock (edt) has a temporary effect on real GDP whereas it has a permanent influence on price level and unemployment rate. Second, productivity shock (est) affects permanently all three of these macro variables. Third, price shock (ept ), such as oil price hikes, affects the real GDP and price level temporarily but has a permanent effect on the unemployment rate. An economy under inflation targeting rule and flexible exchange rate system Next, I introduce an open economy New Keynesian model, a substantial part of which is borrowed from Stock and Watson (2002). In the economy, the government carries out a monetary policy based on inflation targeting.11 The government adjusts the short-term interest rate in response to the anticipated inflation and GDP gap following the so-called Taylor rule. To assess openness, I define the trades of commodities, services and currencies across borders. Hence, I describe an equilibrium condition for the foreign exchange market and include the terms of trade12 (qt) as a determinant of the IS curve. IS curve:13 yt 5 krt 2 qt 1 qdt, qdt ; qdt21 1 edt, rt 5 Rt 2

1 k f a Et [ pt1j ] , qt 5 pt 2 (et 1 pt) k j51

(5.8)

New Keynesian Phillips curve (aggregate supply curve): `

pt 5 g a diEt [ ypt1i 2 yt1i ] 1 edt 1 eet

(5.9)

i50

A forward-looking Taylor rule: h

rt 5 bpEt [ pt1h ] 1 by a diEt [ ypt1j 2 yt1j ]

(5.10)

j51

An equilibrium condition in the foreign exchange market: Rt 5 Rft 1 Et [ et 11 2 et ] 1 eet

(5.11)

The economic growth of Korea since the 1990s

151

Equations (5.8)–(5.11) consist of orthogonal demand and exchange rate shock (edt, eet) and five variables (yt, Rt, pt, Et [ ypt1i 2 yt1i ] , et).14 Filling the gap between the numbers of shocks and variables, I define the GDP gap by an AR(1) process:15 Xt ; ypt 2 yt 5 rXt21 1 est, 0 , r , 1,

(5.12)

Then, equation (5.12) could be represented in moving averages:16 Xt (1 2 rL) 5 est 1 Xt 5

` est 5 a rjest2j 1 2 rL j50

(5.129)

Next, the equilibrium condition of the foreign exchange market is transformed into equation (5.13), which defines the exchange rate (et) to be the sum of interest parity (Rt2j 2 Rft2j) and the cumulative exchange rate shock (qet): et 5 (Rt21 2 Rft21) 1 et21 1 eet 5 (Rt21 2 Rft21) 1 (Rt22 2 Rft22) 1 et22 1 eet21 1 eet `

(5.13)

5 a (Rt2j 2 Rft2j) 1 qet j51 `

qet ; a eet2j j50

Now, I represent the four variables of real GDP (yt), inflation (pt), nominal interest rate (Rt), and the exchange rate (et) in linear functions of the three orthogonal shocks (est, edt, eet). First, I obtain the following expressions by plugging (5.12) to the righthand side of (5.9) and (5.10): `

pt 5 c a diEt [ rXt1i21 1 ext1i ] 1 edt 1 eet i50 `

5 c a diriXt 1 edt 1 eet 5 c i50

Xt 1 edt 1 eet 1 2 dr

` c j s d e 5 a r et2j 1 et 1 et , (0 # dr , 1) 1 2 dr j50

(5.14)

h h 1 2 rh 1 2 rh cr ` j s 5 a Et [ ypt1i 2 yt1i ] 5 a riXt 5 r Xt 5 a r et2j 12r 1 2 r 1 2 dr j50 i51 i51

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The rise of China and structural changes in Korea and Asia

Second, by plugging the above equations back to (5.10), we represent the real interest rate (rt) as a function of external shocks: h

rt 5 bpEt [ pt1h ] 1 by a Et [ ypt1j 2 yt1j ] j51

Xt1h 1 2 rh 1 edt1h 1 ceet1h d 1 byr X 5 bpEt cc 1 2 dr 12r t crh 1 2 rh 5 bp Xt 1 byr X 1 2 dr 12r t crh 1 2 rh 5 abp 1 byr bXt 1 2 dr 12r

(5.15)

Third, converting the expression on the real interest rate (rt) to that on the nominal interest rate (Rt) and combining the new expression with (5.13), I derive the following: 1 s a Et [ pt1j ] 5 AXt, s j51 crh 1 2 rh 1 cr 1 2 rs A ; bp 1 byr 1 s 1 2 dr 1 2 r 1 2 dr 12r Rt 5 r t 1

`

(5.16)

`

et 5 a (AXt2j 2 Rft2j) 1 qet, qet ; a (fjeet2j) j51

j50

Finally, by plugging the above equation to (5.8), I can also project real GDP as a function of external shocks: yt 5 krt 2 qt 1 qdt 5 BXt 2 qt 1 qdt, crh 1 2 rh B ; kabp 1 byr b 1 2 dr 12r

(5.17)

Combining all the equations so far derived, we can represent (yt, pt, et) as moving averages of (est, edt, eet). As for logarized real GDP (yt) and the exchange rate (et), I use the first-order differences for treating their nonstationarity. Accordingly, the first-order differences of the real GDP (Dyt) and the exchange rate (Det) are represented as follows: Dyt 5 BDXt 2 qt 1 qt 21 1 qdt 2 qdt21 5 BDXt 2 pt 1 (et 2 et 21) 1 pft 1 edt c 5 BDXt 2 X 2 eet 1 Det 1 pft, 1 2 dr t

The economic growth of Korea since the 1990s

153

DXt 5 (1 2 rL) Xt 2 (1 2 r) Xt21

(5.18)

5 est 2 (1 2 r) Xt 21 `

5 est 2 a rj (1 2 r) est21 2j j50

Det 5 et 2 et 21 `

`

`

5 a (ADXt2j 2 DRft2j) 1 a eet2j 2 a eet2j21 j50

j50

j50

When properly rearranged, the vector of (Dyt, pt, Det) is represented as an SVMAR (structural moving average representation) system of exogenous shocks (est, edt, eet).17 Furthermore, we can find 3 (5 k 3 (k 2 1) /2, k 5 3) ` restrictions on the coefficients of A` ; A (1) 5 g j50Aj. In other words, (5.19) is exactly identified. Dyt est est NA ` e e ° Det ¢ 5 A (L) ° et ¢ 5 a Aj ° et ¢ , A` 5 ° NA j50 pt edt edt NA

0 NA NA

0 0 ¢ (5.19) NA

The above long-run restriction matrix A` indicates the following properties of the model economy, which is also characterized by equations (1)–(5). First, the productivity shock (est) has a permanent impact on the real GDP, price level and exchange rate. Second, the demand shock (edt) has a permanent effect on the price level, but it has a transient effect on real GDP and the exchange rate. Third, the impact of the exchange rate shock (eet) has a permanent effect on the exchange rate itself and the price level. An economy under the monetary aggregate targeting rule and fixed exchange rate system The next model differs from the previous one in the selection of the monetary policy regime as well as the foreign exchange rate system. First, the monetary authority controls a monetary aggregate instead of adjusting the short-term interest rate based on the so-called Taylor rule. To rephrase, it is assumed that we watch the monetary aggregate (neither the anticipated inflation rate nor the GDP gap) and use the money growth (not the shortterm interest rate) as a monetary policy tool. Such a monetary aggregate targeting rule best describes the policy regime of the Bank of Korea before 1997. Second, the exchange rate is assumed to be fixed at a certain level by the government. In order to balance the capital account or clear the currency exchange market at the prespecified exchange rate, the interest rate differential with other countries is not allowed, and the monetary aggregate

154

The rise of China and structural changes in Korea and Asia

is constantly controlled for maintaining a zero interest rate differential. In this context, we could say that the central bank loses autonomy of monetary policy under the fixed exchange rate system. As in the case of monetary aggregate targeting, such a fixed or managed exchange rate system existed until the financial crisis in 1997. IS curve: IS IS IS yt 5 krt 2 qt 1 qIS t , qt 5 qt21 1 et , 1 k rt 5 Rt 2 a Et [ pt1j ] , qt 5 pt 2 (et 1 pft ) , k j51 pft ; pft 2 pft21 5 Sf,pXft f f f Xft ; yf,p t 2 yt 5 r Xt 21

(5.20)

LM curve: mt 2 pt 5 yt 1 bRt

(5.21)

Combining (5.20) and (5.21), we derive an aggregate demand schedule as follows:

yt 5

k k k (mt 2 pt) 2 a Et [ pt1j ] 2 qt b k j51 a1 1

ak b b

1 qdt, qdt ;

qIS t 5 qdt21 1 edt ak (5.219) 11 b

New Keynesian Phillips curve (aggregate supply curve):18 ` k pt 5 c a diEt [ ypt1i 2 yt1i ] 1 a1 1 bedt b i50

(5.22)

An equilibrium condition in foreign exchange markets: Rt 5 Rft, et 5 et, Rft 5 Sf,R Xft

(5.23)

mt 5 yt 1 bRft 1 pt

(5.24)

Money supply:

Equations (5.20)–(5.23) consist of the demand shock (edt) and four macro variables (yt, Rt, pt, mt). In order to reconcile the mismatch, we define the GDP gap to be an AR(1) process with a noise of est, which is in turn defined to be the productivity shock:

The economic growth of Korea since the 1990s

Xt ; ypt 2 yt 5 rXt21 1 est, 0 , r , 1 ` est Xt (1 2 rL) 5 est 1 Xt 5 5 a rjest2j 1 2 rL j50

155

(5.25)

Now, we represent the four variables of the real GDP (yt), inflation (pt), nominal interest rate (Rt), and the monetary aggregate (mt) as functions of supply shock and demand shock (est, edt) in the following procedure. First, by inserting the AR(1) representation of the potential GDP (Xt) to the right-hand side of (5.22), we can describe inflation (pt) to be a function of exogenous shocks: ` k pt 5 c a diEt [ rXt2i21 1 est1i ] 1 a1 1 bedt b i50 `

5 c a diriXt 1 a1 1 i50

5c

5

k d be b t

Xt k 1 a1 1 bedt 1 2 dr b

(5.26)

` c k rjest2j 1 a1 1 bedt (0 # dr , 1) a 1 2 dr j50 b

Then, considering the working mechanism of the fixed exchange rate system, we note that the domestic interest rate (Rt) has the following relationship with the inflation of the foreign economy (pft): Rt 5 Rft 5 Sf,RXft, pft 5 Sf,pXft

(5.27)

Now, I take the first order differences of the real GDP (yt) and the monetary aggregate (mt) in consideration of their non-stationarity: a1 1

c ak k k k rjXt bDyt 5 (Dmt 2 Dpt) 2 a b b k j51 1 2 rd 2a

c k k Xt 1 a1 1 bedt 2 Sf,pXft b 1 a1 1 bedt 1 2 rd b b

Dmt 2 Dpt 5 Dyt 1 bDRft

(5.28)

Then, combining the first-order differenced real GDP (yt) and monetary aggregate (mt) in the above, I represent real GDP growth (Dyt) and money growth (Dmt) to be the moving averages of the exogenous shocks: Dyt 5 kDRft 2

c c k k rjDXt 2 a X 2 Sf,pXft b a k j51 1 2 rd 1 2 rd t

156

The rise of China and structural changes in Korea and Asia

Dmt 5 Dyt 1 bDRft 1 pt Dqt 5

(5.29)

c c k k Xt 1 a1 1 bedt 2 pft 5 Xt 1 a1 1 bedt 2 Sf,pXft, 1 2 rd b 1 2 rd b `

DXt 5 (1 2 rL) Xt 2 (1 2 rL) Xt21 5 est 2 a rj (1 2 r) est21 2j, j50

Because they match, the two shocks (est, edt), (Dyt, pt) are picked out and rearranged in an SVMAR as below. According to A`, the productivity shock (est) has a permanent effect on real GDP only. In contrast, demand shock (edt) has a permanent effect on the price level and the monetary aggregate: a

` Dyt est est NA b 5 A (L) a d b 5 a Aj a d b, A` 5 a pt et et NA j50

0 b NA

(5.30)

As previously mentioned, in the fixed exchange rate system, the monetary authority cannot exercise its discretion in determining the interest rate and the monetary aggregate. Otherwise, a target exchange rate could not be maintained. Considering such a dilemma, a bivariate SVAR with the real GDP growth and inflation rate (not with the exchange rate change) is estimated for the period before the financial crisis.

5.4 5.4.1

ESTIMATION RESULTS Data

The data for real GDP, price index (GDP deflator), the exchange rate of the US dollar to Korean won, a monetary aggregate (M2), and the unemployment rate used in this chapter are obtained from the Bank of Korea. They cover the period between the first quarter of 1970 and the second quarter of 2007. As a pretest, I examine the existence of unit roots in these variables. Results from the Dicky-Fuller generalized least squares (DF-GLS) procedure (Eliot et al. 1996) exhibit that all the key variables, such as real GDP growth, inflation, the exchange rate change and the unemployment rate, do reject the existence of a unit root at the 1 percent significance level (see Table 5.2). Next, I run various lag-order selection tests. Both Table 5.3 and Table 5.4 report the test results for B-Q type or New Keynesian type models. According to these models, most of the lag order selection criteria prescribe longer lags than the data can accommodate. Thus, I take four lags in every SVAR estimation.19

The economic growth of Korea since the 1990s

Table 5.2

Unit root test results (DF-GLS) Test statistic (DF-GLS)

Dyt pt et Ut

1% level

5% level

10% level

−2.581 −2.581 −2.599 −2.581

−1.943 −1.943 −1.946 −1.943

−1.615 −1.615 −1.614 −1.615

−2.661 −2.712 −6.068 2.659

Table 5.3

157

Lag order selection criteria for B-Q type models

Variables

LR

FPE

AIC

HQIC

SBIC

(Dyt, ut) (Dyt, pt, ut)

78 79

33 22

76 38

76 38

76 38

Notes: 1. The covered period is 1970.1Q–2007.2Q. 2. LR is a likelihood ratio test, FPE is the final prediction error, AIC is Akaike’s information criterion, HQIC is the Hannan and Quinn information criterion, and SBIC is the Schwartz Bayesian information criterion.

Table 5.4

Lag order selection criteria for New Keynesian models

Periods

Variables

LR

FPE

AIC

HQIC

SBIC

2000.1Q–2007.2Q 1991.1Q–1997.3Q

(Dyt, Det, pt) (Dyt, pt)

35 48

2 12

60 36

60 36

60 36

5.4.2

Impulse Responses (IR) and Forecasting Error Variance Decomposition (FEVD)

I estimate SVAR models based on the long-run restrictions previously derived. In this section, I summarize and analyze the estimation results in the form of IR and FEVD. IR analysis tracks down the impact of a shock20 on an endogenous variable along the passage of time. On the other hand, FEVD measures the fraction of the error in forecasting the future value of a variable that is attributable to a shock. Blanchard and Quah’s (1989) original model (two variables and two shocks) To begin with, I demonstrate the IR and FEVD results for the period between 1Q1970 and 2Q2007 from my benchmark of B-Q’s (1989) original model. I also estimate the same model for the following four sub-periods: 1Q1970

158

The rise of China and structural changes in Korea and Asia Real GDP Supply shock

Demand shock

0.030

0.005

0.025

0.000

0.020

–0.005

0.015 –0.010

0.010

–0.015

0.005 0.000

0 2 4 6 8 10 12 14 16 18 20 22 24

–0.020

0 2 4 6 8 10 12 14 16 18 20 22 24

Unemployment rate Supply shock 0.003 0.002 0.001 0.000 –0.001 –0.002 –0.003 –0.004 –0.005 –0.006

Note:

0 2 4 6 8 10 12 14 16 18 20 22 24

0.008 0.007 0.006 0.005 0.004 0.003 0.002 0.001 0.000 –0.001 –0.002

Demand shock

0 2 4 6 8 10 12 14 16 18 20 22 24

The dotted lines are 95% confidence intervals.

Figure 5.2

Impulse response of the two-variable B-Q model (1970.1/4–2007.2/4)

to 4Q1979 (Period I), 1Q1980 to 4Q1989 (Period II), 1Q1990 to 4Q1999 (Period III), and 1Q2000 to 2Q2007 (Period IV). However, I will mention their results only if necessary. Such division of the time series is intended to treat structural changes, which arose from 1Q1970 to 2Q2007.21 IR results in Figure 5.2 show that supply shock has a permanent effect on both real GDP and unemployment, whereas demand shock affects real GDP temporarily, which is consistent with the corresponding longrun restrictions derived in the previous section. In detail, positive supply shock raises real GDP and temporarily (for the first 20 quarters) lowers unemployment. In contrast, positive demand shock in the form of money (M2) growth lowers real GDP, although temporarily (for the first 20 quarters).22 The results for FEVD in Figure 5.3 demonstrate that the relative contribution of supply shock compared with the demand shock to the fluctuations

The economic growth of Korea since the 1990s Changes in growth rate of real GDP 1.00 0.95 0.90 0.85 0.80 0.75 0.70 0.65 0.60

1

3

5

7

9

Supply shock

Figure 5.3

11 13 15 17 19 Demand shock

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

159

Changes in unemployment rate

1

3

5

7

9

Supply shock

11 13 15 17 19 Demand shock

Forecast error variance decomposition of the two-variable B-Q model (1970.1/4–2007.2/4)

of real GDP growth is roughly 80:20. Conversely, the relative contribution of demand shock to unemployment rate change is about 85:15. IR and FEVD results for the four previously defined subperiods are summarized as follows. First, IR results during Period I, compared with the whole sample period, show that the magnitude and the persistence of IRs become smaller and shorter (20 quartersS10 quarters). Furthermore, FEVD analysis shows that the relative contribution of supply shock to the movement of real GDP growth is reduced to 60:40 (compared with 80:20 for the whole sample period). Second, the magnitude of IRs during Period II is close to that during Period I. However, the persistence of a shock and FEVD results are closer to those of the whole sample period, as in Figure 5.2 and Figure 5.3. Third, in comparison with Periods I–II, the magnitude of IRs increased during Period III. In particular, the response to supply shock increased substantially, and the persistence of supply shock on the unemployment rate became longer, from 20 quarters to 30 quarters. On the other hand, the relative contribution of supply shock to the GDP growth rate change falls back to 1970s levels (60:40) whereas that of supply shock to the unemployment fluctuation rises to 70 percent. We suspect that these patterns are attributed to the 1997 financial crisis and its aftermath. It is surmised that the tightening and restructuring policy stance raised the contribution of demand shock while the responses to supply shock were magnified due to the collapse of credit channels after the financial crisis. Fourth, compared to the three preceding periods, the magnitude of IRs decreased for both demand and supply shocks during Period IV, which seems related to the reduced volatility since 2000 (see Table 5.1). On the other hand, the relative contribution of productivity shock to the movement of real GDP growth grew substantially.

160 –0.001 –0.002

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.00

0 2 4 6 8 10 12 14 16 18 20 22 24

Demand shock

–0.025

0.04

0.06

0.08

0.10

0.12

0.14

–0.006 0 2 4 6 8 10 12 14 16 18 20 22 24

0.02

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

–0.005

–0.02

–0.004

–0.003

–0.002

–0.001

0.000

0.001

0.002

0.003

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

Price index Supply shock

–0.020

–0.015

–0.010

–0.005

0.000

0.005

0.000

0.005

0.010

0.015

0.020

0.025

0.030

Real GDP

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

Unemployment

161

0 2 4 6 8 10 12 14 16 18 20 22 24

0.000

0.005

0.000 –0.001

0.001

0.002

0.003

0.004

0.005

0.006

0.007

–0.025 0 2 4 6 8 10 12 14 16 18 20 22 24

Price shock

–0.020

–0.015

–0.010

–0.005

Impulse response of the three variable B-Q model (1970.1/4–2007.2/4)

The dotted lines are 95% confidence intervals.

Figure 5.4

Note:

0.002 0.000 –0.002 –0.004 –0.006 –0.008 –0.010 –0.012 –0.014 –0.016 –0.018

0.010

0 2 4 6 8 10 12 14 16 18 20 22 24

162

The rise of China and structural changes in Korea and Asia

An extension of Blanchard and Quah (1989) (three variables and three shocks) Here I extend the original B-Q model to accommodate three variables (real GDP, unemployment rate and inflation) and three shocks (demand shock (edt), productivity shock (est) and price shock (ept )). Figure 5.4 and Figure 5.5 provide IR and FEVD results for the whole sample period (1Q1970–2Q2007). According to Figure 5.4, productivity, demand and price shocks have the biggest impact on real GDP, price levels and unemployment, respectively. In addition, Figure 5.5 shows that changes in real GDP growth, inflation and unemployment rate can be best explained by productivity, demand and price shocks. However, these patterns are not sustained for all the subperiods, which may be attributed to outbreaks of special events or changes in economic environment such as two oil shocks, the (so-called) three-low phenomenon23 and the financial crisis during the corresponding periods. First, most IRs in 1970s (Period I) with the exception of price level decreased in terms of not only magnitude but also persistence, which is consistent with the results from the original B-Q model. On the other hand, we could guess the impact of oil shocks on the Korean economy from the FEVD results that the relative contributions of price shock to the movements in real GDP growth and unemployment rate are greater than any other sources of shocks. Second, compared with Period I, the magnitude of IRs and persistence increased while the relative contribution of price shock to the growth rate change remained greater than that of any other shocks. These patterns could be at least partly explained by the favorable price shocks hitting the Korean economy in the mid-1980s (the so-called three-low phenomenon). Third, compared to Periods I and II, the responses of real GDP and unemployment increased. In particular, the unemployment rate responded more sensitively to productivity shock than in the past, which I infer is attributable to the drastic measures of corporate restructuring taken after the financial crisis in 1997. Fourth, the most notable point in the estimation results of Period IV (in the 2000s) is that the magnitude of IRs declined in comparison with Periods II and III. Furthermore, the persistence of IRs was shortened (mostly within 20 quarters). On the other hand, the relative contribution of productivity shock to the movement of real GDP growth grew substantially.

The economic growth of Korea since the 1990s

163

Real GDP growth 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 1

3

5

7

Supply shock

9

11

13

Demand shock

15

17

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Price shock

Inflation 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

1

3

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7

Supply shock

9

11

13

Demand shock

15

17

19

Price shock

Unemployment rate 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 1

3

5

7

Supply shock

Figure 5.5

9

11

13

Demand shock

15

17

19

Price shock

Forecast error variance decomposition (1988.1/4–1997.3/4)

164

The rise of China and structural changes in Korea and Asia

An economy under the inflation targeting rule and flexible exchange rate system The previous B-Q type models do not provide explicit descriptions of the foreign exchange market and the monetary policy regime. Remembering that the monetary policy regime switched from monetary aggregate targeting to inflation targeting, and the floating foreign exchange rate system was introduced after or around the 1997 financial crisis, I suggest two new Keynesian models. In the following two sections, I report their estimation results sequentially. To begin with, this section reports the estimation results of the SVAR model under the inflation targeting and flexible exchange rate system. Accordingly, the estimation covers the post-crisis period from the first quarter of 2000 to the second quarter of 2007. Figure 5.6 and Figure 5.7 summarize the estimation results of SVAR consisting of three endogenous variables (real GDP growth (Dyt), domestic inflation (pt), and the rate of change in the US dollar to Korean won exchange rate (Det)), and three exogenous shocks (productivity, demand and exchange rate shocks (est, edt, eet)). First, the IR graphs in Figure 5.6 demonstrate that productivity, demand and exchange rate shocks have the biggest impact on real GDP, price index and exchange rate, respectively. The impacts of shocks disappear completely after 30 quarters, but they become almost negligible after approximately 20 quarters. Second, the FEVD analysis confirms that productivity, demand and exchange rate shocks have the greatest forecasting power for changes in real GDP, inflation and exchange rate, respectively. In particular, the influence of exchange rate shock on the exchange rate (Korean won–US dollar) turns out to be more dominant than any other cases, which implies that the exchange rate is influenced more by foreign factors than domestic variables. An economy under the monetary aggregate targeting rule and fixed exchange rate system This section reports the estimation results of the SVAR model under the monetary aggregate targeting and fixed exchange rate system. Accordingly, the estimation covers the period between 1Q1988 and 3Q1997. Figure 5.8 and Figure 5.9 summarize the estimation results of SVAR24 consisting of two endogenous variables (real GDP growth (Dyt) and inflation (pt)). First, the IR graphs in Figure 5.8 demonstrate that the two variables respond sensitively to productivity shock, and it takes 30–40 quarters for IRs to phase out completely. Second, FEVD analysis shows

The economic growth of Korea since the 1990s

165

that productivity and demand shocks contribute more to the changes in real GDP and inflation, respectively. Combining the estimation results of the two new Keynesian models,25 I note the following two points. First, compared to the 1990s, the magnitudes of impulse responses become smaller in 2000. Second, FEVD results show that 70 percent of inflation and 80 percent of real GDP growth are explained by demand and productivity shocks, respectively, in the 2000s. These numbers contrast with the outcome that in the 1990s, 40 percent of inflation and 87 percent of real GDP growth are explained by demand and productivity shocks, respectively.

5.5

CONCLUDING REMARKS

Defining growth to be the accumulated responses of an economy to various internal and external shocks, this chapter identifies diverse impacts that gave rise to the current status of the Korean economy, and differentiates the relative contributions of those impacts. To that end, SVAR in the presence of long-run restrictions is applied to four economic models, two of which are borrowed from Blanchard and Quah (1989). The other two models are modified from a New Keynesian set-up seen in Stock and Watson (2002). In particular, the last two models26 are devised to reflect the recent changes in the determination of foreign exchange rates (from a fixed rate regime to a flexible rate system), as well as the monetary policy rule (from aggregate targeting to inflation targeting).27 When the assumed results are organized in the form of an impulse response and forecasting error variance decomposition, two common denominators are found. First, changes in the rate of economic growth are mainly attributable to the impact on productivity, and this trend has grown strong since the 2000s, which indicates that Korea’s economic growth since the 2000s has been closely associated with its potential growth rate. Second, the magnitude or consistency of impact responses tends to have subsided since the 2000s. Given Korea’s high dependence on trade, it is possible that low interest rates, low inflation, steady growth and the economic emergence of China as a world player have helped secure capital and demand for exports and imports, which therefore might have reduced the impact on the whole economy. Despite the fact that this analysis has incorporated a diverse mixture of model specifications and shock identifications, these two points are overall confirmed.28 Therefore, it can be concluded that Korea’s decreased

166

0.006 0.005 0.004 0.003 0.002 0.001 0.000 –0.001 –0.002 –0.003 –0.004

0.008 0.007 0.006 0.005 0.004 0.003 0.002 0.001 0.000 –0.001 –0.002 –0.003

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

Real GDP

0.00

0.01

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Exchange rate shock

0 2 4 6 8 10 12 14 16 18 20 22 24

0.006 0.004 0.002 0.000 –0.002 –0.004 –0.006 –0.008 –0.010 –0.012 –0.014

0.06

0.07

0.08

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Supply shock

Exchange rate

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

Price index

167

0.025 0.020 0.015 0.010 0.005 0.000 –0.005 –0.010 –0.015 –0.020

Demand shock

0 2 4 6 8 10 12 14 16 18 20 22 24

Impulse responses (2000.1/4–2007.2/4)

The dotted lines are 95% confidence intervals.

0 2 4 6 8 10 12 14 16 18 20 22 24

Figure 5.6

Note:

–0.006

–0.004

–0.002

0.000

0.002

0.004

0.006

0.008

0.000

0.002

0.004

0.006

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0.010

0.012

0

2

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8 10 12 14 16 18 20 22 24

168

The rise of China and structural changes in Korea and Asia Real GDP growth

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

Demand shock Exchange rate shock Supply shock

1

3

5

7

9

11

13

15

17

19

Change of the logarized exchange rate 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

Demand shock Exchange rate shock Supply shock

1

3

5

7

9

11

13

15

17

19

Inflation 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3

Demand shock Exchange rate shock Supply shock

0.2 0.1 0.0 1

3

Figure 5.7

5

7

9

11

13

15

17

19

Forecast error variance decomposition (2000.1/4–2007.2/4)

The economic growth of Korea since the 1990s

169

Real GDP Supply shock

Demand shock

0.020 0.018 0.016 0.014 0.012 0.010 0.008 0.006 0.004 0.002 0.000

0.002 0.000 –0.002 –0.004 –0.006 –0.008 –0.010 0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

Price Index Supply shock

0.030 0.025 0.020 0.015 0.010 0.005 0.000 –0.005 –0.010

Note:

0 2 4 6 8 10 12 14 16 18 20 22 24

Demand shock

0.020 0.018 0.016 0.014 0.012 0.010 0.008 0.006 0.004 0.002 0.000

0 2 4 6 8 10 12 14 16 18 20 22 24

The dotted lines are 95% confidence intervals.

Figure 5.8

Impulse responses (1988.1/4–1997.3/4)

Real GDP growth 1.00 0.95 0.90 0.85 0.80 0.75 0.70 0.65 0.60

1

3

5

7

9

Supply shock

Figure 5.9

11 13 15 17 19 Demand shock

Inflation 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

1

3

5

7

9

Supply shock

11 13 15 17 19 Demand shock

Forecast error variance decomposition (1988.1/4–1997.3/4)

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The rise of China and structural changes in Korea and Asia

rate of economic growth since 2000 appears to be on the same track as the decrease in Korea’s potential growth rate. These two findings are also consistent with the possibilities either that the inflation targeting rule and the flexible exchange rate system absorb shocks more before they reach the whole economy or that the size of the shocks themselves has diminished. In particular, compared to supply shocks, it seems that both the impact and the size of demand-originated shocks have diminished. In addition, the successful global coordination of the low interest rate regime led by the Federal Reserve Board (FRB)29 (at least until the mid-2000s) contributed to diminishing the magnitude of external shocks to a small open economy like Korea.

NOTES 1. 2.

3. 4.

5.

6. 7. 8. 9. 10. 11.

Blanchard and Quah (1989) admit that their model is only a example showing how a SVAR with long-run restrictions is estimated. Some of these changes were caused by the crisis but others happened to be made after (or around) the outbreak of the crisis. Here, however, it is not my immediate concern to verify their causalities with the crisis. Instead I focus on evaluating the macroeconomic consequences of these post-crisis changes on the Korean economy. In other words, Shim’s (2001) system of equations is simply reduced to a VAR with Cholesky ordering. Monetary aggregate targeting and inflation targeting diverge from each other in the treatment of a money supply schedule. Under monetary aggregate targeting, the LM curve is derived from money demand 5 money supply, whereas money supply is replaced by an interest rate setting rule, such as the Taylor rule, in the case of inflation targeting. Furthermore, autonomy of monetary policy is not guaranteed in a fixed exchange rate system because the domestic interest rate should always be equal to the foreign interest rate. Otherwise, the exchange rate would fluctuate. Oh (2007) assumes that domestic demand shocks have only a temporary effect while domestic supply shocks persist in the long run. He also assumes that world supply shocks increase world production and have a permanent effect on world demand for imports, whereas domestic supply shocks have only a temporary effect on the world demand for imports. Under such presumptions, the estimation results report that world supply shocks have a larger impact in contrast with the shrunken influence of domestic supply shocks after the financial crisis. It is also revealed that the impact of domestic demand shocks has been magnified in the short run. Price shocks represent situations like sudden hikes in oil prices and foreign exchange rates. By construction, they denote all the shocks from foreign economies. B-Q (1989) mention that the model in the paper is an example intended for explaining the use of SVAR with long-run restrictions. SVAR with short-run restrictions differs from B-Q (1989) in that it constrains only the relationships between contemporaneous disturbances. Most of the variables are logarized for scaling. In addition, all the other variables except the unemployment rate are used in differences for stationarity. The addition of nominal wage growth (DWt) to these three variables, however, would make the SVMAR (structural vector moving average representation) underdentified. Hence, I discard nominal wage growth (DWt) from the SVMAR. Fiscal policy, another pillar of economic policy, is not considered in the model, which

The economic growth of Korea since the 1990s

12. 13.

14. 15. 16.

17.

18. 19. 20. 21.

22.

23. 24.

25.

171

is partly due to the long-held (at least since the mid-1980s) fiscal stance of so-called ‘expenditure-within-revenue’. In addition, some empirical works report that fiscal stimuli through either increasing expenditure or reducing tax revenue have not been effective in boosting the Korean economy (Hur 2007). lnPt Pt 1 Qt 5 qt 5 pt 2 et 2 pft 1 lnQt 5 lnEtPft EtPft The IS curve is influenced by the accumulation of demand shocks (edt), qdt. It should be noted, however, that demand shock does not necessarily have a permanent effect on yt because yt is determined not only by the IS curve but also by its interactions with other equilibrium conditions. Based on the concept of a small open economy, I assume that interest rate (Rft), price level (pft ) and inflation (pft) of a foreign country are exogenously given. The author’s pretest using the quarterly data of Korea (1979–2001) shows that the GDP gap (; GDP minus (−) Hodrick–Prescott filtered GDP) follows a stationary AR(1) process (0 , r , 1). With equations (5.12) and (5.129) rearranged as ypt 5 yt 1 rXt21 1 est, we could say that this economy is a part of the Keynesian world in a sense that the potential GDP (ypt ) moves one-to-one with the aggregate demand or real GDP (yt). However, change in yt will not have any impact on ypt1j ( j . 0). Only est will have a persistent effect on ypt1 j Once the productivity shock is defined to have a permanent effect on the potential GDP, est in (5.12) and (5.129) will emerge as the most conceivable candidate for the productivity shock. Instead of taking the first-order differences of I(1) variables (such as real GDP (yt) and the exchange rate of US dollars to Korean Won (et)), we can adopt a structural vector error correction model (SVECM) with cointegrating equations, as suggested by King et al. (1991). In contrast, following B-Q (1989), I form a system of SVAR with longrun identifying restrictions, which consists of I(0) variables and first-order differences of (1) variables. A reason for not following King et al. (1991) is to avoid disentangling permanent shocks from transient shocks a priori. I set demand shock (edt) in the New Keynesian aggregate schedule to have a coefficient of (1 1 k/b) so that the long-run influence of edt on real GDP can converge to 0. The rationale for taking four lags is that all the data are gathered on a quarterly basis. The magnitude of a shock is one standard deviation, and 95 percent confidence intervals are calculated by bootstrappings (1000 trials each). Instead, I could take dummies for certain periods (for example, two oil shocks and the East Asian financial crisis) and measure the level changes in key macro variables induced by these events. But this method does not provide a perfect solution because the dummy variables cannot detect possible functional changes among the key variables. The observation that the unemployment rate rises significantly in response to positive demand shock is opposite to that of B-Q (1989), which may be attributed to the possibility that in Korea the effect of demand shock is transmitted faster through price and wage channels. In contrast, in the next model, which is a three-variable extension of B-Q, such a phenomenon is not sustained statistically. The three-low phenomenon points to the Korean economy in the mid-1980s during which time three favorable economic conditions, such as low oil prices, low interest rates and the low value of the Korean won to the Japanese yen facilitated an economic boom. It is important to remember that this model includes monetary aggregate targeting as well as the fixed exchange rate system. The long-run impulse-response matrix (A`) is overidentified. I find a log-likelihood c2(1) test statistic of 2.647 with a p-value of 0.104. Accordingly, I cannot reject a null hypothesis that additional restrictions are valid. An SVAR model with inflation targeting and the floating exchange rate system uses three variables (Dyt, pt, Det) whereas one with monetary aggregate targeting and the fixed exchange rate system uses two variables (Dyt, pt). Hence, the results from the two are not directly comparable.

172 26. 27. 28. 29.

The rise of China and structural changes in Korea and Asia Unlike B-Q type models, these new Keynesian models assume a small open economy, which is consistent with the heavy dependency of the Korean economy on international trade. These systemic reforms may have caused changes in shock transmission channels. These two patterns are also robust to the number of lags included in the estimation of SVAR systems. The price competitiveness of Chinese manufacturing sectors could be identified as a prop for the low interest rate regime in the early 2000s.

REFERENCES Blanchard, O.J. and D. Quah (1989), ‘The dynamic effects of aggregate demand and supply disturbances’, American Economic Review, 79, 655–73. Fisher, Stanley (1977), ‘Long term contracts, rational expectations, and the optimal money supply rule’, Journal of Political Economy, 85 (February), 163–90. Hur, S. (2007), ‘Measuring the effectiveness of fiscal policies in Korea’, in T. Ito and A. Rose, NBER-EASE series, vol. 16, Ch. 3, Chicago: University of Chicago Press, pp. 63–93. Kim, Kwon Sik (2005), ‘Impacts of foreign shocks on domestic macroeconomic fluctuations’, Policy References, no. 05-06, KIEP (in Korean). King, R., C. Plosser, J. Stock and M. Watson (1991), ‘Stochastic trends and economic fluctuations’, American Economic Review, 81, 819–40. Oh, Hyoung-Seok (2007), ‘Structural break in potential growth and business cycle after Korean Currency Crisis’, Working Paper, 21(1), Bank of Korea (in Korean). Shim, Jae Woong (2001), ‘Decomposing factors of post-crisis business cycle’, Research Paper Series, LGERI (in Korean). Stock, J. and M. Watson (2002), ‘Has the business cycle changed and why?’, NBER Macroeconomics Annual 2002, vol. 17, NBER, pp. 159–230.

PART III

Impacts on Korean Firms and Workers

6.

China’s rise and production and investment growth in Korean manufacturing industries: channels and the effects Chin Hee Hahn and Yong-Seok Choi

6.1

INTRODUCTION

China’s rapid economic growth as well as its integration into the world economy is probably one of the most important developments in the external economic environment surrounding Korea and other East Asian countries. Over the past several decades, China sustained rapid economic growth of about nearly 10 percent per annum accompanied by the rapid trade expansion. As a result, China has recently become the third-largest economy in terms of GDP and the second-largest in terms of trade.1 Since the 1990s, the bilateral trade between Korea and China expanded impressively as well, making China the largest trading partner of Korea. China’s share of Korea’s exports rose from 0.9 percent in 1990 to 22.7 percent in 2007, making China the largest export market of Korea. During the same period, China’s share of Korea’s imports increased from 3.2 percent to 17.7 percent, making China the second-largest importing partner of Korea. What are the effects of China on the economic growth of Korea? What are major channels which are empirically important? To answer these questions, this chapter attempts to examine how measures of various aspects of trade relationship between Korea and China are related to the production and investment growth of Korean manufacturing at three-digit industry level. We consider primarily three channels – import competition and third-market competition from China and exports to China – and try to evaluate the empirical importance of each channel through which Korean manufacturing industries are affected by the rise of China. One might expect, on the one hand, that Korean manufacturing industries could have been adversely affected by the increasing competition pressure from low-wage countries such as China, consistent with 175

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The rise of China and structural changes in Korea and Asia

the traditional comparative advantage theory of trade. In the case of the US, Bernard et al. (2002) shows that import competition from low-wage countries had adverse effects on the output and employment growth of labor-intensive manufacturing plants. In the case of Korea, however, manufacturing industries have faced increasing competition with China, not only in Korea’s domestic market but also in the global export market. So, we consider both import competition and third-market competition in assessing the effects of the rise of China. On the other hand, the rapid growth of China can also provide an opportunity for the growth of Korean manufacturing industries. Here, the primary channel is obviously exports to China. There is a growing body of literature which considers the spread of fragmentation of production as a distinguishing characteristic in the recent rapid growth of world trade (for example, see Feenstra 1998; Yi 2003; Irwin 2005; and Kimura and Ando 2005). Also, many authors point out that the formation of a regional production network, based on fragmentation of production as well as intraregional foreign direct investment, has been particularly noticeable in East Asia (for example, Athukorala and Yamashita 2006; Ando and Kimura 2005). In many of these studies, the increasing importance of intermediate goods trade is considered as a piece of evidence suggestive of the increasing importance of the fragmentation of production.2 So what specific types of exports mattered for the growth of manufacturing industries in Korea? To answer this question, we further disaggregate exports to China into several subcategories: consumption goods, capital goods and other intermediate goods. Then we assess the respective roles of intermediate and capital goods exports to China in the growth of Korean manufacturing industries.3 Also, we examine what role Korea’s outward foreign direct investment (FDI) to China played in each type of export to China. Most previous studies on the effects of China on the growth of other countries seem to have focused on the effects on exports. There are some studies which examine the trade structure of China and East Asian countries and suggest that China’s exports have been complementary to exports of East Asian countries (Lall and Albaladejo 2004; Li 2002; Shafaeddin 2002; Ianchovichina and Martin 2001, for example). By contrast, the World Bank (2007) examines the effects of third-market competition with China on exports of 19 East Asian countries and reports that adverse effects are pronounced for Korea, Taiwan and Singapore. As mentioned above, Bernard et al. (2002) shows that import competition from low-wage countries had adverse effects on the output and employment growth of labor-intensive manufacturing plants in the US. For Korea, Kim et al. (2006) shows that Korea’s outward FDI to China

China’s rise and Korean manufacturing industries

177

in Korean manufacturing promoted exports of parts and components to China, based on a survey data of some large firms. Kim (2006) examines the effects of the rise of China on the demand for labor, focusing on three channels: bilateral trade, third-market competition and FDI toward China. Our chapter tries to provide an integrated view of the effect of the rise of China on the growth of manufacturing industries in Korea, with a particular focus on the distinction between intermediate goods and capital goods exports to China. The rest of this chapter is organized as follows. Section 6.2 briefly overviews recent trends in the production and investment growth of Korean manufacturing. In section 6.3 we explain our basic regression specification and main explanatory variables. Section 6.4 provides our main regression results. Section 6.5 examines the relation between Korea’s outward FDI to China and subcategories of exports to China. The final section concludes.

6.2

OUTPUT AND INVESTMENT GROWTH OF KOREAN MANUFACTURING

In this section, we briefly overview trends in output and investment growth in the Korean economy, as well as in the manufacturing sector. We use both National Account (NA) data and Survey of Mining and Manufacturing (SMM) data to see whether broad trends in output and investment growth from SMM, which is employed in our analysis that follows, are similar to those from NA. The aggregate real GDP growth rate of the Korean economy has exhibited a downward trend since the 1980s (Table 6.1). Annual average GDP growth rate declined from 8.4 percent in the 1980s to 6.3 percent in the 1990s before the crisis that broke out in 1997. After the crisis, the growth slowed down further to a record 4.6 percent for the period from 2000 to 2006. Although the causes of the post-crisis growth slowdown in Korea have been a subject of heated debate, it should be noted that the growth slowdown had already been in progress during the pre-crisis period of the 1990s.4 Manufacturing GDP growth rate declined from 11.4 percent in the 1980s to 7.0 percent during the period from 1991 to 1997, but hardly declined further after the crisis. Based on SMM, the average production growth rate in manufacturing sector increased slightly, rather than declined, after the crisis. So it is suggested that the period when manufacturing GDP growth slowdown occurred was the pre-crisis 1990s, rather than after the crisis. The real equipment investment growth rate from NA has also shown a

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The rise of China and structural changes in Korea and Asia

Table 6.1

Growth rate of production and investment by periods

Real GDP growth rate (aggregate) Real GDP growth rate (manufacturing) Average production growth rate (manufacturing) Real equipment investment growth rate (aggregate) Real equipment investment growth rate (manufacturing) Note:

1981–90

1991–97

2000–2006

8.4

6.3

4.6

11.4

7.0

6.7

–

8.3

10.7*

12.5

6.4

2.2

–

4.2

0.2*

* Represents average figure for the period of 2000–2003.

declining trend since the 1980s. Contrasted with GDP growth, however, aggregate investment growth rate declined significantly after the crisis. In the manufacturing sector, the real investment growth rate, calculated from SMM, also declined significantly after the crisis. In sum, during the 1990s before the crisis, both output and investment growth in Korean manufacturing sector slowed down compared with the 1980s. In spite of the overall growth slowdown after the crisis, the output growth rate in manufacturing sector hardly declined after the crisis, although investment growth rate in manufacturing declined substantially. Below, we examine how the rise of China affected the growth of output and investment in the Korean manufacturing sector.

6.3 6.3.1

SPECIFICATION OF REGRESSION MODEL AND VARIABLE CONSTRUCTION Specification

As discussed in section 6.1, the main interest of this chapter is to investigate effects of the rise of China on the growth of Korea’s manufacturing industries and their main channels. We considered three different channels: export to China (which in turn could be divided into two major categories: capital goods and intermediate goods); import competition with China

China’s rise and Korean manufacturing industries

179

in Korea’s domestic market; and third-market competition with China. Thus, the basic specification of our regression model is as follows: DGi 5 a 1 b1XKi 1 b2XIi 1 g1MCi 1 g2XCi 1 dZi 1 ei

(6.1)

where subscript i denotes industry, DG either growth rate of real production or investment at industry level. For industry i, XK, XI, MC and XC represent measure of capital goods exports to China, measure of intermediate goods exports to China, measure of domestic import competition from China, and measure of third market competition with China, respectively, which are intended to capture various aspects of trade relation between Korea and China. Z is a vector of other control variables, such as capital intensity, skill intensity, average plant size and plant average of the industry, which are usually included in the related literature. The variables MC and XC capture the potentially adverse impact from the competition with China in Korea’s domestic market and in the world market. It is expected that the higher the competition with China either in domestic market or in the world market, the lower the growth rate of real output and investment since those industries may be losing its comparative advantage over China. Thus, we expect negative signs for g1 and g2. It is not easy to predict, a priori, what sign the coefficients of XK or XI will take. Given the rapid growth of China for the period analyzed here, if China’s imports from Korea mainly consisted of capital goods, then industries with a higher share of capital goods exports to China would have benefited more. Then, the coefficient of XK, b1, is likely to be positive, while it is not clear whether the coefficient of XI, b2, will be positive or negative. If, however, China’s imports from Korea mainly consisted of intermediate goods, then industries with a higher share of intermediate goods exports to China would have benefited more. Then, the coefficient of XI, b2, is likely to be positive, while it is not clear whether the coefficient of XK, b1,will be positive or negative.5 Thus, whether these two coefficients would have a positive or negative sign seems to be an empirical question.6 6.3.2

Data and Construction of Variables

We employed two main data sources. The first one is the Survey of Mining and Manufacturing conducted by the KNSO (Korea National Statistical Office). This survey covers all establishments with five or more employees in mining and manufacturing sectors and contains necessary information to construct variables used in this chapter at industry level, including output, employment, number of non-production and production workers,

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and tangible fixed assets. The other main data source is the Comtrade Database of the United Nations from which all international trade data have been extracted.7 Main variables in our analysis were constructed as follows. Firstly, the real production growth rate was calculated from the survey’s nominal industrial production deflated by a sectoral gross domestic product (GDP) deflator.8 Yearly nominal investment was calculated as an annual increase in tangible fixed assets (machinery, buildings, and vehicles), which were deflated by an investment deflator to give real investment. Secondly, the measure of capital goods exports to China (XK) and the measure of intermediate goods exports to China (XI) were calculated as a share of capital goods exports and intermediate goods exports to China out of total exports to China. We used the United Nations’ BEC (Broad Economic Categories) classification to measure capital goods and intermediate goods exports to China, as in Hummels et al. (1999). Based on BEC classification, it is possible to categorize exports reasonably clearly into consumption goods, machinery and capital goods (‘capital goods’ hereafter), and non-machinery and non-capital equipment intermediate goods (‘intermediate goods’ hereafter). Appendix Table 6A.1 shows the categorization of exports using BEC classification. The measure of import competition with China in the domestic market (MC) has been calculated following Schott (2006) and Bernard et al. (2002) as follows: MCi 5 VSHiC 3 PSHiC MiC PiC 5 3 Mi Pi This measure is a product of two different measures of import competition: value share (VSH) and product share (PSH). The value share is the share of imports from China in total imports in industry i. The product share is a product coverage ratio, which is the number of products in imports from China divided by the number of products in total imports at of industry i. So, this measure captures the imports competition from China in terms of both intensive and extensive margin. Thirdly, the index of competition with China in the world market was calculated as: XCi 5

MSiC MSiC 1 MSiK

where MSiC and MSiK are market shares of the Chinese and the Korean exports in the world market respectively (excluding the Chinese and Korean markets). As XC approaches zero, Korea has comparative

China’s rise and Korean manufacturing industries

181

30.0 25.0 20.0 15.0 10.0 5.0 0.0 1992

Figure 6.1

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

Capital intensity (High)

Capital intensity (Medium)

Capital intensity (Low)

Total

2003

Trends of MC by the level of capital intensity

advantage over China, while as it approaches one, China has comparative advantage over Korea in the relevant industry. Finally, capital intensity (KI) of an industry is measured as natural logarithm of per worker tangible fixed assets averaged over the period, while skill intensity (HI) is the ratio of non-production worker to production worker. Average plant size (SZ) is the natural logarithm of average level of plant employment of an industry, and average plant age (AG) is the natural logarithm of an average plant’s operating years since establishment. 6.3.3

Preliminary Analysis

In this subsection, we briefly review recent trends in the main explanatory variables, which measure various aspects of the trade relation between Korea and China. First of all, the measure of import competition from China has been increasing since the 1990s (Figure 6.1). The increase has been mostly driven by industries with low and medium capital intensity, although industries with high capital intensity have also contributed to the increase recently. Similarly, the competition between Korea and China in the world export market has been increasing as well (Table 6.2). This is primarily due to the rapid increase in China’s market share. Korea’s world market share has been fairly stable at around 3 percent. Next, the share of exports to China in Korea’s total exports has also increased rapidly since the 1990s (Table 6.3). It increased from 4 percent in 1992 to 32.1 percent in 2006. In addition, the composition of Korea’s

182

The rise of China and structural changes in Korea and Asia

Table 6.2

World market share and competition between Korea and China 1992

1995

1999

2003

2006

2.7 2.7 49.4

3.5 3.1 53.0

4.3 2.9 59.4

7.3 2.7 72.9

10.9 3.0 78.7

China’s world market share (%) Korea’s world market share (%) Competition between Korea and China (XC) Source:

UN Comtrade.

Table 6.3

Export share to China

Export to China / Total export (%)

1992

1995

1999

2003

2006

4.0

9.3

13.4

25.8

32.1

Export share to China by commodities Capital goods and Parts 16.3 & accessories (Capital goods) (8.5) (Parts & accessories) (7.8) Intermediate goods 82.0 Consumption goods 1.7

23.7

28.9

58.8

64.7

(13.2) (10.5) 73.2 3.1

(7.6) (21.3) 73.7 2.5

(27.3) (31.4) 39.4 1.8

(21.4) (43.3) 33.8 1.5

Total

100

100

100

100

100

exports to China has also undergone dramatic change. Above all, the share of capital goods exports to China has increased rapidly since the 1990s. It was 16.3 percent in 1992 and rose continuously since then to reach 64.7 percent in 2006. If we further divide capital goods into ‘parts and accessories’ (BEC Code 42 and 53) and other capital goods that are not ‘parts and accessories’, it turns out that the rapid increase in the share of capital goods exports to China has been mostly driven by the rapid increase in parts and accessories, although the other capital goods category also shows a generally increasing trend. By contrast, the share of intermediate goods exports to China, which was 82 percent in 1992, has declined substantially to record 33.8 percent in 2006. Meanwhile, Korea’s consumption goods export to China form a relatively small portion, less than 3 percent, of total exports to China for most years. In sum, Table 6.3 shows that the rapid increase in Korea’s exports to China is mostly driven by machinery and capital goods, which account for about two-thirds of total exports to China.

China’s rise and Korean manufacturing industries

Table 6.4

Correlation coefficients between main variables All periods (1993–2002) DY

Real production growth rate (DY) Real investment growth rate (DI) Capital intensity (KI) Human capital intensity (HI) Size (SZ) Age (AG) Import competition (MC) Export competition (XC) Share of capital goods exports (XK) Share of intermediate goods exports (XI) Note:

183

1.000

DI –

Pre-crisis (1993–97) DY 1.000

DI –

Post-crisis (1999–2003) DY

DI

1.000

–

0.716 (0.000)

1.000

0.653 (0.000)

1.000

0.063 (0.650)

1.000

0.122 (0.375) 0.105 (0.445)

−0.138 (0.314) −0.027 (0.846)

0.342 (0.011) 0.213 (0.119)

0.255 (0.060) 0.358 (0.007)

−0.180 (0.189) 0.063 (0.650)

−0.131 (0.341) −0.193 (0.159)

0.247 (0.069) −0.125 (0.364) −0.541 (0.000)

0.106 (0.439) −0.133 (0.334) −0.551 (0.000)

0.244 (0.073) −0.066 (0.634) −0.477 (0.000)

0.389 (0.003) 0.053 (0.702) −0.427 (0.001)

0.198 (0.147) −0.262 (0.053) −0.258 (0.062)

0.123 (0.372) 0.003 (0.986) −0.094 (0.501)

−0.438 (0.001)

−0.272 (0.046)

−0.339 (0.012)

−0.124 (0.372)

−0.220 (0.111)

−0.017 (0.904)

0.471 (0.000)

0.386 (0.004)

0.311 (0.023)

0.358 (0.008)

0.646 (0.000)

0.109 (0.431)

−0.240 (0.080)

−0.327 (0.016)

−0.079 (0.576)

−0.236 (0.088)

−0.438 (0.001)

−0.138 (0.318)

p-values for correlation coefficients are in parentheses.

Table 6.4 shows correlations of the main explanatory variables averaged over the period from 1993 to 2003 with production and investment growth rates for the same period at three-digit industries. The table also shows correlations of the same variables for two subperiods: before (1993–97) and after (1999–2003) the crisis. Firstly, import competition (MC) as well as third-market competition (XC) is negatively correlated with both production and investment growth. The correlation coefficients

184

The rise of China and structural changes in Korea and Asia

are more strongly negative for the pre-crisis period than for the post-crisis period. Secondly, the share of capital goods exports (XK) is strongly positively correlated with production growth for the whole period as well as for each of the two subperiods. Finally, the correlations between the share of intermediate goods exports (XI) and production or investment growth were negative, although their significance varied depending on the period of analysis.

6.4 6.4.1

MAIN REGRESSION RESULTS Production Growth

Table 6.5 shows cross-section regressions of production growth of industries for the whole sample period: 1993–2003. As expected, the measure of import competition from China enters all regressions with significantly negative coefficients, suggesting that an industry exposed to higher import competition from China experienced an adverse effect on production growth. Although the coefficients on third-market competition with China are also negative, however, this loses significance with the inclusion of the capital goods exports variable. It is notable that the capital goods exports variable (XK) is estimated to be significantly positive while the intermediate goods exports variable (XI) is not statistically significant. This result implies that industries with a higher share of capital goods exports destined for China experienced faster growth. In other words, it is the capital goods exports channel, rather than the intermediate goods exports channel, through which China’s rise contributed to the production growth of Korean manufacturing industries. Also, this result is consistent with the patterns shown in Table 6.3. In order to see whether there are differences in the effects of various explanatory variables between the pre- and post-crisis periods, we also ran pooled regressions by dividing the sample period into two subperiods: 1993–97 and 1999–2003. The explanatory variables in these regressions are the same explanatory variables measured for each subperiod interacted with pre-crisis (Db) or post-crisis dummy variable (Da).9 In Table 6.6, import competition from China has a negative effect on the production growth of Korean manufacturing industries, with the effect strongly significant before the crisis. However, there was no strong evidence suggesting that third-market competition with China had an adverse effect on the production growth of industries. If anything the third-market competition had a negative effect during the pre-crisis period, although insignificant.

China’s rise and Korean manufacturing industries

Table 6.5

185

Cross-section regression for real production growth (1993–2003)

Variables

(1)

(2)

(3)

(4)

Capital intensity (KI) Human capital index (HI) Size (SZ) Age (AG) Import competition (MC) Export Competition (XC) Capital goods share (XK) Intermediate goods share (XI) Constant

0.0185 (0.0210) 0.0338 (0.0491) 0.0201 (0.0129) −0.1718** (0.0779) −0.3593*** (0.0755)

0.0162 (0.0211) 0.0368 (0.0509) 0.0171 (0.0152) −0.1635** (0.0801) −0.3399*** (0.0821) −0.0250 (0.0517)

0.0312 (0.0220) 0.0369 (0.0455) 0.0056 (0.0144) −0.1432* (0.0800) −0.2752** (0.1026) −0.0210 (0.0495) 0.0510** (0.0223)

0.3097** (0.1157)

0.3231** (0.1207)

0.2473* (0.1294)

0.0220 (0.0274) 0.0398 (0.0431) 0.0073 (0.0150) −0.1346 (0.0843) −0.2828** (0.1109) −0.0202 (0.0501) 0.0646* (0.0395) 0.0227 (0.0444) 0.2373* (0.1363)

Observations Adjusted-R2

53 0.391

53 0.380

53 0.430

53 0.423

Notes: Heteroskedasticity-consistent standard errors are in parentheses. *, ** and *** denote that the estimated coefficients are significant at 10%, 5% and 1% level, respectively.

Also, the regression results suggest that the positive effect from capital goods exports to China tends to become stronger after the crisis. In both regression (3) and (4), the estimated coefficients on the XK variable are larger in absolute value and more significant after the crisis than before the crisis. Figure 6.2 shows the partial residual plot between production growth rate and capital goods exports to China after the crisis, based on regression model (3), which shows that some industries with an extremely large share of capital goods exports or some outlier industries do not drive the result. By contrast, intermediate goods export to China was not estimated to be significant in any subperiods. Overall, the regressions indicate that capital goods export was the main channel through which Korean manufacturing industries benefited from China’s rise, and that this effect became stronger over the crisis.

186

Table 6.6

The rise of China and structural changes in Korea and Asia

Cross-section regression for real production growth (pre-crisis and post-crisis)

Variables Db x KI Da x KI Db x HI Da x HI Db x SZ Da x SZ Db x AG Da x AG Db x MC Da x MC

(1)

(2)

(3)

0.0937** (0.0414) −0.0241 (0.0252) 0.0910 (0.0590) 0.0198 (0.0467) 0.0114 (0.0181) 0.0335*** (0.0105) −0.2492*** (0.0830) −0.0835 (0.0619) −0.3414*** (0.1143) −0.1248* (0.0737)

0.0909** (0.0409) −0.0149 (0.0242) 0.0955 (0.0597) 0.0165 (0.0465) 0.0070 (0.0229) 0.0382*** (0.0134) −0.2317** (0.0900) −0.1261** (0.0614) −0.3039** (0.1292) −0.1642* (0.0882) −0.0410 (0.0730) 0.0595 (0.0580)

0.1133** (0.0440) 0.0040 (0.0180) 0.0962 (0.0582) 0.0071 (0.0347) −0.0050 (0.0195) 0.0186 (0.0119) −0.2133** (0.0907) −0.0925* (0.0536) −0.2126* (0.1180) −0.1119 (0.0806) −0.0242 (0.0653) 0.0600 (0.0493) 0.0658** (0.0328) 0.0855*** (0.0255)

0.2359** (0.0927)

0.2451** (0.0974)

Db x XC Da x XC Db x XK Da x XK Db x XI Da x XI Constant

Observations Adjusted-R2

106 0.302

106 0.295

0.1428 (0.1053) 106 0.382

(4) 0.1063** (0.0481) −0.0069 (0.0224) 0.0987* (0.0559) 0.0137 (0.0321) −0.0038 (0.0199) 0.0208* (0.0122) −0.2072** (0.0945) −0.0901 (0.0549) −0.2227* (0.1338) −0.1124 (0.0836) −0.0232 (0.0652) 0.0608 (0.0507) 0.0761 (0.0485) 0.1094*** (0.0392) 0.0168 (0.0493) 0.0397 (0.0439) 0.1359 (0.1082) 106 0.375

Notes: Heteroskedasticity-consistent standard errors are in parentheses. *, ** and *** denote that the estimated coefficients are significant at 10%, 5% and 1% level, respectively.

China’s rise and Korean manufacturing industries

187

0.2

e (DY | X)

0.1

0

–0.1

–0.2 –1

–0.5

0

0.5

1

e (DaXCAP_CH | X) Note:

Coef. = .8554522, (robust) se = 02553653, t = 3.35.

Figure 6.2 Partial residual plot between production growth rate and capital goods exports to China after the crisis (Model 3 of Table 6.6) 6.4.2

Investment Growth

In this subsection, we discuss investment growth regression results. For the whole sample period from 1993 to 2003, the import competition from China was estimated to have negative and significant coefficients for all regressions considered here (Table 6.7). So, industries with higher import competition from China exhibited a lower investment growth rate. As shown in pooled regressions for the two subperiods (Table 6.8), the strong negative effect was obtained for the pre-crisis period but it became weaker after the crisis. Thus, import competition from China might be a factor behind the slowdown in investment growth in Korean manufacturing during the 1990s before the crisis, which was shown in Table 6.1. The coefficient on import competition from China after the crisis was still negative, but not significant. Other than import competition from China, none of the variables considered in this chapter could explain the investment growth of industries. 6.4.3

Further Breakdown of Export Channel

So far, we have considered only two types of exports to China – capital goods exports (XK) and intermediate goods exports (XI) – in our analysis.

188

Table 6.7

The rise of China and structural changes in Korea and Asia

Cross-section regression for real investment growth (1993–2003)

Variables

(1)

(2)

(3)

(4)

Capital intensity (KI) Human capital index (HI) Size (SZ) Age (AG) Import competition (MC) Export Competition (XC) Capital goods share (XK) Intermediate goods share (XI) Constant

−0.0748*** (0.0254) −0.0522 (0.0435) 0.0132 (0.0139) −0.0171 (0.0597) −0.6112*** (0.1521)

−0.0759*** (0.0261) −0.0508 (0.0465) 0.0117 (0.0165) −0.0130 (0.0611) −0.6016*** (0.1757) −0.0123 (0.0662)

−0.0691** (0.0294) −0.0507 (0.0444) 0.0065 (0.0174) −0.0037 (0.0603) −0.5720*** (0.1987) −0.0105 (0.0653) 0.0233 (0.0248)

0.3166*** (0.1070)

0.3233*** (0.1164)

0.2887** (0.1291)

−0.0685** (0.0300) −0.0509 (0.0455) 0.0064 (0.0175) −0.0043 (0.0638) −0.5715*** (0.2010) −0.0106 (0.0660) 0.0224 (0.0344) −0.0014 (0.0329) 0.2893** (0.1346)

Observations R2

53 0.492

53 0.481

53 0.479

53 0.467

Note: Heteroskedasticity-consistent standard errors are in parentheses. *, ** and *** denote that the estimated coefficients are significant at 10%, 5% and 1% level, respectively.

We have shown that capital goods exports, rather than intermediate goods exports, have been an important channel through which the rise of China promoted the growth of Korean manufacturing industries. We mentioned earlier that the increasing importance of intermediate goods trade is considered in previous literature as a piece of evidence suggestive of the increasing importance of the fragmentation of production. So, one caution to be raisied here is that the above empirical results should not be interpreted as evidence either in favor of, or against the hypothesis that intermediate goods exports to China or fragmentation of production played no role in growth of Korean industries. The primary reason for this is that the category name ‘intermediate goods’ in the above analysis refers to non-machinery and non-capital-goods intermediate goods, so it excludes intermediate goods in the machinery and

China’s rise and Korean manufacturing industries

Table 6.8

Variables Db x KI Da x KI Db x HI Da x HI Db x SZ Da x SZ Db x AG Da x AG Db x MC Da x MC

Cross-section regression for real investment growth (pre-crisis and post-crisis) (1)

(2)

(3)

(4)

0.0023 (0.0430) −0.0868 (0.0581) 0.0747 (0.0735) −0.1493* (0.0804) 0.0251 (0.0186) 0.0098 (0.0359) −0.1690* (0.0929) 0.0389 (0.1069) −0.4910*** (0.1574) −0.2479* (0.1483)

−0.0009 (0.0441) −0.0870 (0.0670) 0.0811 (0.0775) −0.1486* (0.0836) 0.0202 (0.0208) 0.0085 (0.0473) −0.1561 (0.1006) 0.0345 (0.1706) −0.4564*** (0.1695) −0.2469 (0.2029) −0.0405 (0.0936) −0.0091 (0.2023)

0.0149 (0.0458) −0.0795 (0.0713) 0.0851 (0.0735) −0.1528* (0.0819) 0.0099 (0.0204) 0.0010 (0.0470) −0.1467 (0.1000) 0.0543 (0.1667) −0.3871** (0.1785) −0.2234 (0.2154) −0.0334 (0.0913) −0.0060 (0.2049) 0.0489 (0.0387) 0.0356 (0.0490)

0.2939** (0.1198)

0.3146** (0.1303)

0.2564* (0.1516)

0.0171 (0.0527) −0.0634 (0.0771) 0.0850 (0.0769) −0.1627* (0.0846) 0.0093 (0.0214) −0.0023 (0.0466) −0.1501 (0.0978) 0.0518 (0.1680) −0.3837** (0.1895) −0.2223 (0.2166) −0.0351 (0.0924) −0.0069 (0.2051) 0.0446 (0.0590) 0.0004 (0.0534) −0.0062 (0.0752) −0.0589 (0.0592) 0.2640* (0.1497)

Db x XC Da x XC Db x XK Da x XK Db x XI Da x XI Constant

Observations Adjusted-R2

189

106 0.134

106 0.117

106 0.110

106 0.096

Notes: Heteroskedasticity-consistent standard errors are in parentheses. *, ** and *** denote that the estimated coefficients are significant at 10%, 5% and 1% level, respectively.

190

The rise of China and structural changes in Korea and Asia

70 60 50 %

40 30 20 10 0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2004 2006 China’s investment growth rate Capital goods export share Parts and accessories export share Capital goods and parts & accessories export share

Figure 6.3

China’s investment growth rate and Korea’s exports to China

capital goods sector.10 In fact, there seems to be no clear way to separate intermediate goods trade from the UN Comtrade database based on BEC classification, since it does not classify products according to an intermediate–final goods division. Nevertheless, in this subsection, we further break down capital goods exports to China into parts and accessories of machinery and capital goods (‘parts and accessories hereafter’, BEC Codes 42 and 53), and machinery and capital goods excluding parts and accessories (‘final capital goods’ hereafter, BEC Codes 41 and 521), using BEC classification. With this breakdown, we construct two additional explanatory variables as before – final capital goods export to China (XKF) and parts and accessories export to China (XKP). Although the ‘final’ capital goods categorized here may not correspond exactly to final capital goods in the economic sense, Figure 6.3 shows that final capital goods export to China (XKF) moves closely together with the growth of China’s aggregate investment, which is a component of final demand. So, we go on to use the term ‘final capital goods’ to denote machinery and capital goods excluding parts and accessories. The primary reason for this additional breakdown is that we want to understand which type of exports to China can better explain cross-industry variations of production and investment growth. The separation of parts and accessories from other machinery and capital goods seems to be a natural way to go.11 Table 6.9 shows production growth regressions based on pooled data.

China’s rise and Korean manufacturing industries

Table 6.9

191

Cross-section regression for real production growth (pre-crisis and post-crisis)

Variables

(1)

(2)

Db x MC

−0.2126* (0.1180) −0.1119 (0.0806) −0.0242 (0.0653) 0.0600 (0.0493) 0.0658** (0.0328) 0.0855*** (0.0255)

−0.2965** (0.1281) −0.1638* (0.0892) −0.0351 (0.0734) 0.0719 (0.0621)

Da x MC Db x XC Da x XC Db x XK Da x XK Db x XKF

Db x XKP Da x XKP

Observations Adjusted-R 2

−0.2334* (0.1209) −0.1068 (0.0739) −0.0423 (0.0609) 0.0254 (0.0545)

0.0131 (0.0282) 0.0373 (0.0393)

Da x XKF

Constant

(4)

0.1428 (0.1053) 106 0.382

0.2239** (0.1069) 106 0.287

0.0904 (0.0553) 0.0977*** (0.0257) 0.1954* (0.0986) 106 0.381

Notes: Heteroskedasticity-consistent standard errors are in parentheses. *, ** and *** denote that the estimated coefficients are significant at 10%, 5% and 1% level, respectively.

The table shows that it is parts and accessories (XKP) that has a positive effect on the production growth of Korean manufacturing industries. The final capital goods (XKF) category also has a positive coefficient after the crisis, but it was not significant. The coefficients on all other explanatory variables are qualitatively similar to previous regressions, except for the third-market competition measure. In this case, it was estimated to be negative and significant before the crisis. In the case of investment growth regressions, the results are somewhat mixed. That is, both final capital goods (XKF) and parts and accessories

192

The rise of China and structural changes in Korea and Asia

(XKP) are estimated to have some positive effects depending on the period. Final capital goods export to China has a positive effect on investment growth in the post-crisis period, while parts and accessories export to China has a positive effect in the pre-crisis period. In sum, parts and accessories export to China had a positive effect on both production and investment growth, depending on the period, while final capital goods export to China had a positive effect only on investment growth in the post-crisis period. So, if we focus on production growth, exports of parts and accessories (of machinery and capital goods) to China seem to have been more important to the growth of Korean manufacturing industries.12

6.5

KOREA’S OUTWARD FDI TO CHINA AND EXPORTS

In the previous sections, we examined the effects of the rise of China on the growth of Korean manufacturing industries, taking various trade linkages between Korea and China into account. With regard to exports to China in particular, we considered several subcategories of exports to China – intermediate goods exports, (machinery and capital) parts and accessories, and final capital goods exports – and analyzed their effects. In this section, we examine how the outward FDI to China by Korean manufacturing industries is related to those sub-categories of exports to China.13 As is well known, the rise of China, together with the formation of a regional production network in East Asia, provided Korea with not only a low-cost production opportunity but also China’s large domestic market. To utilize this opportunity, Korean firms rapidly increased FDI in China. As Table 6.10 shows, China’s share of Korea’s total outward FDI in the manufacturing sector has been rapidly increasing since the 1990s, although there are some fluctuations, from about 30 percent in 1992 to about 70 percent in 2003. For most of the period Korea’s outward FDI to China was concentrated in industries with low to medium capital intensities, not only in terms of absolute value but also as a share of industrial production or domestic equipment investment. However, the table also indicates that the share of industries with high capital intensity has been rapidly increasing since the crisis. Table 6.11 shows regressions of subcategories of exports to China considered in previous sections – XI, XKP, XF – on each industry’s outward FDI to China, with and without the control of capital and skill intensity and average plant size and age of industries. Here, the FDI variable is nominal outward FDI to China divided by nominal production

China’s rise and Korean manufacturing industries

Table 6.10

193

Outward FDI in Korean manufacturing

Total outward FDI (billion dollars) FDI to China (billion dollars) FDI to China / Total FDI(%)

1992

1995

1999

2003

0.65

2.01

1.68

2.18

0.12

0.71

0.29

1.46

29.8

51.7

32.6

69.5

FDI to China by subgroup of industries (by capital intensity) Industries Low capital intensity Medium capital intensity High capital intensity MFG total

Industry composition (%) 58.3

32.4

34.5

26.7

33.3

35.2

51.7

45.9

8.3

32.4

13.8

28.1

100.0

100.0

100.0

100.0

FDI to China/Production (%) Low capital intensity Middle capital intensity High capital intensity MFG total

0.06

0.13

0.06

0.16

0.03

0.10

0.07

0.22

0.01

0.06

0.01

0.09

0.02

0.09

0.04

0.15

FDI to China/Equipment investment Low capital intensity Medium capital intensity High capital intensity MFG total Source:

1.7

4.2

2.8

7.8

0.4

1.3

1.0

3.5

0.1

1.1

0.3

3.8

0.4

1.6

0.9

4.2

Author’s own calculations based on data from Korea Eximbank.

194

54 −0.019

Observations Adjusted-R2

54 0.338

0.5549*** (0.0964) −0.0213 (0.2302) −0.2062*** (0.0483) −0.0398 (0.3918) 0.8419** (0.3396) −0.5806 (0.5616) 54 0.005

−0.3376 (0.2151) 0.1759*** (0.0517)

XKF

54 0.098

−0.1693* (0.0903) −0.0400 (0.1435) 0.0676 (0.0430) −0.1381 (0.1706) −0.7287** (0.2995) 0.8260*** (0.2914)

Notes: Heteroskedasticity-consistent standard errors are in parentheses. *, ** and *** denote that the estimated coefficients are significant at 10%, 5% and 1% level, respectively.

Constant

−0.0275 (0.3854) 0.4729*** (0.0754)

XI

Dependent variables

Regressions of exports to China on FDI: cross-section

FDIY_CH

AG

SZ

HI

KI

Variables

Table 6.11

54 0.016

−0.5054** (0.2342) 0.2492*** (0.0591)

XKP

54 0.190

−0.1338 (0.1043) −0.0933 (0.1723) 0.1777*** (0.0592) −0.3825 (0.2388) −0.8685*** (0.3178) 0.9098** (0.3582)

China’s rise and Korean manufacturing industries

195

(FDIY_CH), averaged over the period from 1992 to 2003. The first row of the table denotes dependent variables. Meanwhile, Table 6.12 shows similar regressions on pooled data based on two subperiods. The first two columns of Table 6.11 show that outward FDI to China promoted (non-machinery and non-capital goods) intermediate goods exports to China. Although the coefficient on FDIY_CH is insignificant in the simple regression, it became significantly positive with the inclusion of capital and skill intensity variables. The positive and significant coefficient on the capital intensity variable indicates that the share of intermediate goods exports to China was higher in industries with a higher capital– labor ratio. Table 6.12 shows that the positive effect of outward FDI to China on intermediate goods exports to China is observed particularly in the pre-crisis period. However, we do not observe a positive effect of outward FDI to China on final capital goods exports (XKF) or (machinery and capital goods) parts and accessories exports (XKP). In fact, the coefficients on FDIY_CH in these regressions are estimated to be significantly negative, even controlling for the capital and skill intensities. We do not have a clear interpretation of the significantly negative coefficient. One possibility might be that these results reflect the fact that outward FDI to China was concentrated on low and medium capital intensity industries, such as apparel, leather and furniture, which have a low share of machinery and capital goods exports to China. Overall, these results suggest that outward FDI to China promoted intermediate goods exports to China especially before the crisis. However, given our previous result that intermediate goods exports to China do not explain cross-industry variations of production or investment growth, it is suggested that outward FDI to China cannot explain cross-industry variations of growth systematically.14

6.6

SUMMARY AND CONCLUDING REMARKS

In this chapter, we have examined what effects the rise of China had on the growth of production and investment of Korean manufacturing industries. In doing so, we considered three main aspects of the trade relation between Korea and China: import competition, third-market competition and exports to China. In addition, we further divided exports to China into capital goods exports and (non-machinery and non-capital equipment) intermediate goods exports. From various regression results, we could obtain both positive and negative effects from China’s rise on the production and investment growth of Korean manufacturing

196

Da x AG

Db x AG

Da x SZ

Db x SZ

Da x HI

Db x HI

Da x KI

Db x KI

Variables

Table 6.12

XI 0.5727*** (0.1066) 0.3836*** (0.1004) −0.1848 (0.2752) −0.2485 (0.1760) −0.2043*** (0.0473) −0.1824*** (0.0476) 0.0343 (0.2794) 0.2541 (0.2796)

XKF −0.1845* (0.0960) −0.0908 (0.0844) −0.0836 (0.1433) 0.1230 (0.1928) 0.0588 (0.0466) 0.0658 (0.0424) −0.0346 (0.1406) −0.2450 (0.1988)

Dependent variables

Regressions of exports to China on FDI: pooled

XKP −0.1460 (0.1063) −0.0815 (0.0968) 0.0114 (0.1837) 0.0125 (0.1911) 0.1781*** (0.0611) 0.1600*** (0.0562) −0.3450* (0.1835) −0.3614 (0.2511)

197

107 −0.019

Observations Adjusted-R2

107 0.309

0.6563** (0.2909) 0.2809 (0.3821) −0.6434* (0.3599) 107 −0.001

−0.2943** (0.1212) 0.0621 (0.3010) 0.1572*** (0.0373) 107 0.053

−0.6243*** (0.2214) 0.0462 (0.4074) 0.6803*** (0.2187)

Notes: Heteroskedasticity-consistent standard errors are in parentheses. *, ** and *** denote that the estimated coefficients are significant at 10%, 5% and 1% level, respectively.

Constant

Da x FDIY_CH

0.0505 (0.3030) −0.0270 (0.2682) 0.4690*** (0.0510)

Db x FDIY_CH

107 0.015

−0.4247*** (0.1474) −0.3527** (0.1428) 0.2450*** (0.0404)

107 0.158

−0.5620*** (0.2061) −0.4628** (0.2257) 0.7461*** (0.2521)

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The rise of China and structural changes in Korea and Asia

industries. On the one hand, capital goods exports to China, rather than intermediate goods exports, were estimated to have positive effects on the production growth of Korean manufacturing industries, especially during the period after the crisis. Results based on further division of capital goods into two subcategories reveals that in particular exports of parts and accessories of machinery and capital equipment to China promoted growth of industries. Although we obtained some evidence that outward FDI to China promoted intermediate goods exports to China, particularly before the crisis, we were not able to find evidence that it promoted exports of parts and accessories (of machinery and capital equipment). On the other hand, import competition from China was estimated to have negative effects on both the production and the investment growth of Korean manufacturing industries, especially before the crisis. Overall, the regression results suggest that the positive effects from China’s rise on the growth of Korean manufacturing industries have been strengthened after the crisis. Although we have tried to understand better the effects of the rise of China on the economic growth of Korea, we think the issues raised in this chapter need further scrutiny. With regard to the channel of exports to China, for example, it might be useful to distinguish between intermediate goods and final goods. The export of the final goods, which has been of major interest in traditional trade theory, is more likely to be related to Chinese domestic demand, such as domestic investment demand. So, if this type of export is important for the growth of the Korean exporters, it means that China’s domestic market is important as an export destination. Then, autonomous changes in China’s domestic market condition could have an important influence on Korean manufacturing industries. By contrast, if exports of intermediate goods to China are important to the growth of Korean industries, it means that China is more important to Korea as a low-cost production location. In this case, autonomous changes in China’s domestic market condition might have a less important role. Better data might be required to examine this issue further. Also, we were not able to find empirical evidence suggesting that outward FDI to China promoted (machinery and capital goods) parts and accessories exports to China, which were found to have positive effects on the production and investment growth of Korean manufacturing industries. One could conjecture that this result might be related to either the very small outward FDI to China, relative to either the production or investment, or to the concentration of outward FDI to China on industries with low and medium capital intensities. However, this issue seems to be in need of further scrutiny.

China’s rise and Korean manufacturing industries

199

NOTES 1.

2.

3. 4. 5.

6.

7.

8. 9. 10.

11.

There are many studies which document that the composition of China’s exports is much more sophisticated than can be expected by its level of development, or that it is rapidly changing from labor-intensive low-tech products to capital-or skill-intensive high-tech products. See Lall and Albaladejo (2004), Rodrik (2006), Schott (2006), Kim et al. (2006), for example. Irwin (2005) explains that technological progress that enabled the phenomenon of fragmentation of production has driven a rapid increase in international trade. He points to vertical specialization and outsourcing as two tendencies reflecting this phenomenon. Here, vertical specialization refers to firms purchasing intermediate goods or parts in the market which have been previously produced within the firms. Outsourcing refers to the movement of the production processes abroad. As will be shown later, Korea’s consumption goods exports to China are a relatively minor proportion of the total exports. Hahn and Shin (2007) discusses the sources of the post-crisis growth slowdown based on growth accounting analysis and evaluates the post-crisis growth performance of the Korean economy from a cross-country perspective. In fact, even if China’s imports from Korea mainly consisted of capital goods, for example, the expected sign on capital goods exports may not be clear. For example, it is plausible that the exports of capital goods from Korea to China could change China’s comparative advantage in such a way that the competition between Korea and China increases in industries where the share of capital goods exports from Korea to China is high. However, we hope to control for this effect by the inclusion of the two competition measures. One might be temped to think of an alternative interpretation of the coefficients, as the following: that is, if the coefficient of capital goods exports is positive while the coefficient of intermediate goods exports is not, then China’s domestic demand, rather than low-cost production opportunity in China, is important to the growth of Korean manufacturing industries, and vice versa. However, we caution against this interpretation because the distinction between intermediate and capital goods may not be the same as the distinction between intermediate and final goods. This point will be discussed later in this chapter. All the variables in the chapter were measured at the three-digit industry level according to the KSIC. Thus we needed to match the five-digit SITC (Standard International Trade Classification) of the Comtrade Database with the three-digit KSIC. Since there exists no official matching table between the KSIC and SITC provided by the KNSO, this matching table was constructed by the authors and is available upon request. Sectoral GDP deflators are available for 37 manufacturing sectors and were obtained from Kim (2006). The results from separate regressions for each subperiod are very similar to this approach, so we do not report them here. Also, our empirical analysis is not a test of the hypothesis that the fragmentation of production promoted growth of Korean manufacturing industries. Irwin (2005) explains that both vertical specialization and outsourcing, which underlie fragmentation of production phenomenon, promote greater specialization in production, leading to efficiency enhancement. Although previous studies indicate that fragmentation of production has been most noticeable in the machinery sector (for example, Feenstra 1998), we believe one still cannot be sure that the machinery and capital goods excluding parts and accessories truly reflect final goods exports, since parts and accessories may or may not be equal to intermediate goods in the economic sense. Indeed, at least some of the ‘parts and accessories’ might be intermediate goods. For example, a hard disk drive for a desktop computer would be an intermediate good. But it is possible that some other parts and accessories are final capital goods. For example, exports of parts of a sewing machine

200

12.

13. 14.

The rise of China and structural changes in Korea and Asia for maintenance purposes, which is being used to make T-shirts, are not intermediate goods exports but final capital goods. Inasmuch as parts and accessories exports correspond to ‘intermediate goods’ in the economic sense, it is suggested that intermediate goods export, rather than final goods export, to China has been a more important channel through which China’s rise benefited Korean manufacturing industries. However, as discussed above, we should be careful about this interpretation. Although outward FDI to China can affect the growth of Korean manufacturing industries through various channels, in this chapter we do not try to consider all those channels here but focus on its effect on several types of exports to China. Indeed, when we included FDIY_CH in regressions in Tables 6.5–6.8, it was not significant at all.

REFERENCES Ando, Mitsuyo and Fukunari Kimura (2005), ‘The formation of international production and distribution networks in East Asia’, in Takatoshi Ito and Andrew Rose (eds), International Trade in East Asia, NBER-East Asia Seminar on Economics, Chicago: University of Chicago Press, pp. 177–216. Athukorala, Prema-Chandra and Nobuaki Yamashita (2006), ‘Production fragmentation and trade integration: East Asia in a global context’, North American Journal of Economics and Finance, 17(3), 233–56. Bernard, Andrew, J. Bradford Jensen and Peter K. Schott (2002), ‘Survival of the best fit: exposure to low-wage countries and the (uneven) growth of US manufacturing plants’, NBER Working Paper, no. 9170. Feenstra, Robert C. (1998), ‘Integration of trade and disintegration of production in the global economy’, Journal of Economic Perspectives, 12(4), 31–50. Hahn, Chin Hee and Seok Ha Shin (2007), ‘Accounting for the growth slowdown of the Korean economy since the 1990s’, in proceedings of 2007 EWC/KDI conference on Reforms for Korea’s sustained growth, Honolulu, Hawaii. Hummels, David, Jun Ishii and Kei-Mu Yi (1999), ‘The nature and growth of vertical specialization in world trade’, Staff Reports no. 72, Federal Reserve Bank of New York. Ianchovichina, Elena and Will Martin (2001), ‘Trade liberalization in China’s accession to the World Trade Organization’, Journal of Economic Integration, 16(4), 421–44. Irwin, Douglas A. (2005), ‘Trade and globalization’, in Michael M. Weinstein (ed.), Globalization: What’s New, New York: Columbia University Press, pp. 19–35. Kim, Dae-Il (2006), ‘China’s impact on the labour market in Korea’, in In-Seok Shin and Chin Hee Hahn (eds), Structural changes in the Korean Economy after the Economic Crisis, Korea Development institute Research Monograph, 2006–07, Seoul: Korea Development Institute, pp. 195–244. Kim, Dong-Seok (2005), ‘Empirical study on the polarization in the manufacturing sector’, in Kim Joo Hoon (ed.), The Role of SMEs in the Innovation-driven Economy, Korea Development Institute Research Monograph 2005–05, Seoul: Korea Development Institute, pp. 109–74. Kim, Joon-Kyung, Yangseon Kim and Chung H. Lee (2006), ‘Trade, investment and economic integration of South Korea and China’, Korea Development Institute Working Paper no. 2006–01.

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Kimura, Fukunari and Mitsuyo Ando (2005), ‘Two-dimensional fragmentation in East Asia: conceptual framework and empirics’, International Review of Economics and Finance, 14(3), 317–48. Lall, Sanjaya and Manuel Albaladejo (2004), ‘China’s competitive performance: a threat to East Asian manufactured exports?’, World Development, 32(9), 1441–66. Li, Yuefen (2002), ‘China’s accession to WTO: exaggerated fears’, Discussion Papers, No. 165, Geneva: UNCTAD. Rodrik, Dani (2006), ‘What’s so special about China’s exports?’, NBER Working Paper, no. 11947. Schott, Peter K. (2006), ‘The relative sophistication of Chinese exports’, NBER Working Paper, no. 12173. Shafaeddin, S.M. (2002), ‘The impact of China’s accession to WTO on the exports of developing countries’, Discussion Papers, No. 160, Geneva: UNCTAD. World Bank (2007), An East Asian Renaissance: Ideas for Economic Growth, Washington, DC: World Bank. Yi, Kei-Mu (2003), ‘Can vertical specialization explain the growth of world trade?’, Journal of Political Economy, 111(1), 52–102.

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APPENDIX Table 6A.1

UN’s BEC code and intermediate/capital/consumption goods

Broad Economic Classification

Categories

1

Food and Beverage 11 Primary 111 Mainly for industry 112 Mainly for household consumption 12 Processed 121 Mainly for industry 122 Mainly for household consumption

– – Intermediate goods Consumption goods – Intermediate goods Consumption goods

2

Industrial Supplies, n.e.s. 21 Primary 22 Processed

– Intermediate goods Intermediate goods

3

Fuels and Lubricants 31 Primary 32 Processed 321 Motor spirit 322 Other

– Intermediate goods – Intermediate goods Intermediate goods

4

Machinery, Capital Equipment (except transport) and accessories thereof 41 Machinery and other capital equipment except transport 42 Parts and accessories

– Capital goods Capital goods

5

Transport Equipment and accessories thereof 51 Passenger motor cars 52 Other 521 Industrial 522 Non-industrial 53 Parts and accessories

– Consumption goods – Capital goods Consumption goods Capital goods

6

Consumer goods, n.e.s. 61 Durable 62 Semi-durable 63 Non-durable

– Consumption goods Consumption goods Consumption goods

7

Goods, n.e.s.

Note:

n.e.s. = not elsewhere specified.

–

7.

The impact of outward FDI on export activities: evidence from the Korean case* Siwook Lee

7.1

INTRODUCTION

In recent years, the world has witnessed a remarkable proliferation of foreign direct investment (FDI) across borders, largely spurred by the accelerated liberalization trend of national FDI policies and the expansion of the global production network. Between 1980 and 2005, worldwide FDI outflows grew about 14.5-fold, while trade flows and gross domestic product (GDP) have increased by around 5.3 and 4.1 times, respectively. Nowadays, multinational corporations (MNCs) account for two-thirds of the world trade, of which a half is in fact intra-firm trade, an in-house transaction between parent firms at home and their subsidiaries in foreign lands. Korea had been traditionally a government-led, export-oriented economy with little emphasis on FDI. Consequently, Korea had been relatively closed off from world markets in terms of both inward and outward foreign direct investment. Since the mid-1990s, however, the situation has been drastically changed. In the course of massive restructuring and downsizing efforts since the financial crisis in 1997, Korea’s leading companies, especially in major exporting sectors such as semiconductors, IT and automobiles, pursued new business strategies with a special emphasis on outsourcing and offshoring. This indicates that the rapid increase of recent Korean outward FDI can be attributed in large part to the globalization of businesses, such as in establishing global vertical production and distribution networks. Facing the surge of outbound FDI, increasing attention has been paid to the impacts of the FDI-mediated corporate globalization on exports from the home country. Some argue that the expansion of outward FDI could sharpen the corporate competitive edge and encourage exports through reduced production costs and enhanced market access in target countries. On the other hand, others have raised concerns that the rapid 203

204

The rise of China and structural changes in Korea and Asia

relocation of manufacturing facilities toward foreign countries through FDI could shrink exports, and at the same time the imports of those goods would also contract domestic production activities. While the existing theories of international trade and multinational firms remain inconclusive about the FDI–exports nexus, most empirical works indicate a complementary relationship between the two. However, recent studies have increasingly shown that empirical evidence critically depends on the level of data aggregation, the FDI types in focus and the empirical methodology. In particular, recent evidence suggests that the oft-found complementary relationship in the current literature is largely attributable to the high level of data aggregation. For example, using US import data from Organisation for Economic Co-operation and Development (OECD) countries, Swenson (2004) finds less substantial complementarities, and even substitution effects, as one moves from more aggregated industry FDI data to less aggregated data. In a similar vein, but in a different context, Arndt et al. (2007) compare the existing empirical studies on the linkage between FDI and domestic investment, and discuss limitations on the aggregate-level and firm-level analyses. They argue that an aggregate-level analysis does not allow light to be shed on the sources of complementarities between foreign and domestic investment. On the other hand, a firm-level analysis does not allow the examination of interaction between firms, notably between FDI firms and the other domestic firms. Arndt et al. (2007) claim that an industry-level study is most appropriate for verifying the impacts of FDI on domestic activities, but such a study still does not fully provide information on a precise channel through which FDI-mediated corporate globalization affects intra-firm trade activities. The main goal of this chapter is to examine the relationship between FDI and exports in the case of Korea. In particular, this chapter empirically investigates the issue by using three-tiered Korean data, comprising of aggregate, industry and individual firm levels. We test each level separately and check whether different qualitative implications arise among the three levels of data aggregation. While there exists a growing body of literature focusing on the aggregation issues of product data, there is little research that checks for the FDI–export linkage for different scopes of economies at the same time in a concrete way. At each level of analysis, careful attention is paid to endogeneity issues in estimation, which are another source of potential bias in estimating the FDI–exports nexus. Since the data characteristics differ, such that time-series data and balanced panel data are used at the aggregate level and at the micro level, respectively, different empirical methodologies are adopted accordingly to take care of endogeneity issues.

The impact of outward FDI on export activities

205

The rest of the chapter is organized as follows. Section 7.2 introduces the existing literature on the relationship between outward FDI and exports. Then section 7.3 briefly presents the recent pattern of Korean FDI and exports. Section 7.4 outlines the estimation framework and describes the data, and section 7.5 presents empirical results. Finally, section 7.6 concludes the paper.

7.2

LITERATURE REVIEW

This section introduces a brief overview of the current literature on the FDI–export linkage. In the theoretical perspective, the existing literature suggests both substitution and complementarity relationship. For example, within the traditional Heckscher–Ohlin framework, international trade is generated by differences in factor endowments and factor prices across countries. In the absence of factor mobility, commodity movement is a driving force to equalize factor prices across countries. As factors of production become mobile across borders, however, these differences become smaller and thus factor movement leads to a reduction in the volume of international trade. Similarly, the standard theory of multinational firms regards FDI and exports as alternative strategies to serve foreign markets. More specifically, a firm establishes its own production or distribution facility abroad when there are sufficient costs to external transaction such as exporting or licensing. It is often difficult to appropriate properly rents from intangible assets specific to the firm, such as technology and managerial skills, via contract with a third party. On the contrary, there are several convincing theoretical arguments to suggest FDI–export complementarity as well.1 First, as suggested in Helpman (1984) and Markusen et al. (1996), FDI can lead to an increase in the volume of trade, mainly driven by increased specialization within an industrial sector. For example, a skilled-labor-abundant country may concentrate on headquarters activities and let other countries concentrate more on final production through outward FDI. In this case, direct investment can lead to an increase in the volume of trade and produce a strong tendency toward factor-price equalization. Second, complementarity can be expected when the presence of one of a firm’s products in a foreign market may increase the total demand for all products of that firm. FDI leads to the acquisition of important assets such as brand names and distribution networks, which helps to increase the firm’s knowledge about the market and tilt consumer preferences in the firm’s favor.

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The rise of China and structural changes in Korea and Asia

As such, the existing theories of international trade and multinational firms remain inconclusive for the FDI–export linkage, but most empirical works interestingly indicate a complementary relationship between the two. For example, Clausing (2000) finds that multinational activity and trade are complementary activities, particularly multinational activity and intra-firm trade for US multinational firms. Lipsey and Weiss (1981), Graham (2000) and Hejazi and Safarian (2001), among many others, also suggest that affiliate sales are positively correlated with exports at the aggregate or industry level. However, recent studies increasingly suggest that empirical evidence on the FDI–exports nexus differs, depending on the levels of data aggregation. For example, using US import data from OECD countries, Swenson (2004) shows evidence on substitution between exports and FDI when import data are matched to foreign investments that have been disaggregated to the individual product level, while the complementary relationship emerges at higher levels of aggregation. In a similar vein, Blonigen (2001) emphasizes the importance of adopting the level of data aggregation appropriate for the hypothesis being tested. In addition, the empirical studies in search of the trade–FDI nexus can be broadly classified into macro and micro or firm-level studies. The macro studies have predominantly adopted an FDI-augmented gravity model. As Mitze (2007) convincingly argues, special attention should be paid to controlling for a possible simultaneity bias between variables of interest. Simultaneity may occur due to a spurious inference between trade and FDI when there are common exogenous factors that would affect both of these variables. Once controlling for simultaneity bias in gravity model estimation, Mitze (2007) recently found a substitutive relationship between exports and FDI for EU countries, while imports and FDI are found to complement each other. In sum, the current theoretical and empirical literature still does not provide a clear-cut relationship between export and FDI. As far as empirical estimation is concerned, the existing studies suggest the importance of controlling for aggregation and endogeneity bias in the estimation process.

7.3

RECENT PATTERNS OF KOREAN OUTWARD FDI AND TRADE

As shown in Figure 7.1, the size of outward FDI by Korean firms remained relatively small until the mid-1980s, but since then it has grown steadily, especially for the periods after the year 2000. As a result, the share of

The impact of outward FDI on export activities

207 12000

6000 Total investment

5000

10000

4000

8000

3000

6000

2000

4000

1000

2000

($ million)

Number of affiliates

0

0 1981

1986

Figure 7.1

1991

1996

2001

Korean outward FDI, 1981–2006

35

1990

30.7% 30

2006

2000

2006

26.1%

%

25 20

18.0% 13.9%

15 10.3%

10

5.3%

5

Source:

el

a re

D

ev

Ko

g op

in

n pa Ja

S U

ed D

ev

el

W

op

or

ld

0

Author’s calculations, based on UNCTAD, World Investment Report, 2007.

Figure 7.2

Outward FDI stock per GDP

total FDI stocks in GDP increased from 0.2 percent (1980) to 5.3 percent (2006), even though it is still well below that of the United States (18 percent) or of most countries around the world (26.1 percent on average), as depicted in Figure 7.2. One of the distinctive features in the recent surge of Korean outward FDI is that the share of China as a destination of Korean FDI has been rapidly increasing. As depicted in Figure 7.3, China now accounts for 23.9 percent of total cumulative investment, followed by the United States, Asia and Europe. Investments destined for China have concentrated in

208

The rise of China and structural changes in Korea and Asia 13.4%

23.9%

2.1% 15.5%

22.9% 22.2%

China

Figure 7.3

US

Asia

Europe

Japan

Others

Korean cumulative outward FDI by destination (as of March 2008)

manufacturing (80.8 percent of the total outstanding investment into China up to March 2008). On the other hand, for the United States, Korean FDI into service sectors has a relatively bigger share (60.7 percent) than FDI going into manufacturing (35.6 percent), as shown in Figure 7.4. Another noticeable characteristics of the recent Korean outward FDI is that high-tech industries account for the lion’s share in outward FDI into manufacturing. For example, in 2007, about half of the manufacturing FDI is in transport equipment, electronic components and information and communication technology (ITC) equipment. On the other hand, low-tech industries, such as food and beverages, textiles, wood and paper products, account for less than 10 percent of the total FDI in manufacturing. In line with the recent surge of outward FDI, the importance of intrafirm trade via FDI activities has grown remarkably. Figure 7.5 presents the shares of related-party exports, or intra-firm exports, into the US by selected countries.2 For the period of 1992–2007, the relative share of intrafirm exports has remained between 45 and 48 percent of the total exports; the share of Korean intra-firm exports relative to total exports into the US has steadily increased from 26.8 percent in 1992 to 62.1 percent in 2007. Table 7.1 contains the recent trend of total and intra-firm exports estimated by Lee and Lim (2007).3 The annual growth rate of intra-firm exports by Korean firms is, on average, 45.6 percent for the period of 1999–2005, while the other type of exports grew only by 7.2 percent per annum. Consequently, the proportion of intra-firm exports of listed companies out of Korea’s total exports increased from 9 percent in 1999 to 32 percent in 2005. One of the interesting findings is that about 80 percent of intra-firm

The impact of outward FDI on export activities China

209 US

4000

4000

3000

3000

2000

2000

1000

1000

0

0 1990

1995

2000

2005

3000

3000

2000

2000

1000

1000

1995

2000

2005

ASEAN

4000

EU

4000

1990

0

0 1990

1995

2000

2005

1990

1995

2000

2005

Agriculture, forestry, fishery and mining Manufacturing Service Source: Author’s calculations, based on EXIM Bank, Overseas Direct Investment Yearbook, various issues.

Figure 7.4

Outward FDI by sector and by destination, 1990–2007(US$ millions)

exports identified in the data are concentrated in the six large conglomerates, including Samsung Electronics and Hyundai Motor Company. Furthermore, among their intra-firm exports, the share of exports to their wholesale foreign affiliates amounts to between 64 and 98 percent, showing that the intra-firm exports of major Korean companies are mostly exports through distribution channels Applying a gravity model for the sample of Korean listed companies that have foreign affiliates, Lee and Lim (2007) also suggest that outward FDI generally encourages intra-firm trade. More specifically, a 1 percent increase in FDI stock led to 0.21–0.27 percent increase of intra-firm exports between 2002 and 2005. A greater degree of intra-firm exports is

210

The rise of China and structural changes in Korea and Asia

100% 80% 60% 40% 20% 0% 1992 World

Note: Source:

1994

1996

Canada

1998 Japan

2000

2002

Mexico

2004 China

2006 Korea

The share is relative to each country’s total exports into the US. US Census Bureau.

Figure 7.5

The share of related-party exports into the US

found in exporting activities with non-G7 countries and in manufacturing sectors relative to the others. Table 7.2 contains information on intra-firm and arm’s-length transaction by Korea as of 2006. This comes from the Korea Export–Import Bank of Korea (2007), which collects and analyzes financial statements of foreign affiliates for Korea multinationals. In 2006, local sales accounted for 54.7 percent of the total sales by Korean subsidiaries, and exports to Korea and to the third countries 15.9 percent and 29.4 percent, respectively. On the other hand, imports from Korea consisted of the largest share (46.4 percent) of the total purchases by Korean affiliates. In fact, most of these imports came from related parties in Korea, including parent firms. Furthermore, as presented in Table 7.2, 61.1 percent of the purchases by foreign affiliates originated from related parties all around the world. Such dominance of intra-firm transactions over arm’s-length transactions by Korean multinationals is seemingly quite exceptional, for example compared to the Japanese case. According to Ando and Kimura (2006), about 36.6 percent of the purchases by Japanese manufacturing affiliates in foreign countries were originated from related parties all around the world in 2001, and this share has been declining since the early 1990s. One possible explanation for such dominance of intra-firm transactions

The impact of outward FDI on export activities

Table 7.1

Recent trend in Korean exports by type (US$ billion) Total exports (A)

1999 2000 2001 2002 2003 2004 2005 Annual growth rate Source:

144 172 150 162 194 254 284 12.9%

Other exports

13 29 22 34 50 79 91 45.6%

131 144 129 128 144 175 193 7.2%

9% 17% 14% 21% 26% 31% 32% –

Intra-firm and arm’s-length transactions by Korean affiliates (2006) (US billion $, %) Local sales

Exports to Korea

Exports to 3rd markets

Related parties

Arm’slength

Related parties

Arm’slength

Related parties

Arm’slength

25.3 10.3%

109.1 44.4%

34.5 14.0%

4.6 1.9%

31.2 12.7%

41.2 16.8%

Local Purchases

Amount Share

Intra-firm exports (B)

B/A %

Lee and Lim (2007).

Table 7.2

Amount Share

211

Imports from Korea

Imports from 3rd markets

Related parties

Arm’slength

Related parties

Arm’slength

Related parties

Arm’slength

9.7 4.6%

45.7 21.6%

92.1 43.6%

6.0 2.8%

27.2 12.9%

30.6 14.5%

in the Korean case over the Japanese one is that the Export–Import Bank of Korea (2007) data cover both manufacturing and services, while Ando and Kimura’s (2006) are only for manufacturing. One of the main purposes of FDI into service sectors is to facilitate sales of exported goods through establishing distribution channels within the recipient economics of FDI. Finally, according to a survey by the Export–Import Bank of Korea (2007), promoting exports of domestically-produced goods is one of the most important motivations for Korean firms to invest abroad. This

212

The rise of China and structural changes in Korea and Asia

indicates a seemingly strong nexus between outward FDI and exporting activities in the Korean case.

7.4

EMPIRICAL STRATEGY AND DATA

As aforementioned, the current literature suggests that empirical evidence on the FDI–exports nexus may differ, depending on the levels of data aggregation. In this context, this chapter examines the FDI–export linkage using three-tiered Korean data, comprising of aggregate, industry and individual firm levels. We test them separately and check whether different qualitative implications arise among three levels of data aggregation. The basic hypothesis to test at each level of data is whether higher FDI stock induces higher export performance or not: EXt 5 f (FDIout t , Wt) where EXt is the amount of total exports at period t, FDIout is outward t FDI stock at t and Wt is a set of other control variables. Given that the current studies emphasize the importance of controlling for endogeneity bias, careful attention is paid to this at each level of analysis. Because of different data structures, each analysis adopts a slightly different estimation method to control for endogeneity bias. 7.4.1

Aggregate-Level Empirical Model

In the macro-level analysis, I employ an error correction model to study the FDI–exports nexus. I construct quarterly time-series data for Korea covering the periods from 1988/Q1 through 2007/Q4. Assuming that the volume of exports is determined by the foreign real GDP of major trading partners, unit export price, real effective exchange rates and outward FDI stocks in the long run, I perform Johansen tests for cointegration relationships among these variables. According to the test results, the null hypothesis of no cointegration is strongly rejected. In addition, I fail to reject the null hypothesis of at most one cointegrating equation. Thus, I accept the null that there is a single cointegrating long-run equation. Given a cointegration relationship among variables in the long-run equation, I allow that the short-run changes of variables in any period are related to the previous period’s gap from long-run equilibrium, using an error correction model. Thus, my specification is as follows: Dln (EXt) 5 b0 1 b1Dln (FDIout t ) 1 b2Dln (EXt21) 1 b3Dln (FGDPt) 1 b2Dln (XPt) 1 b3Dln (REERt) 1 b4ECt21 1 b5dumcrisis 1 xT 1 nt

(7.1)

The impact of outward FDI on export activities

213

where EXt is the amount of total exports at period t, FDIout t is outward FDI stock, FGDPt is real foreign GDP,4 XPt is unit export price, and REERt is real effective exchange rate. dumcrisis is a dummy for the financial crisis periods (1997/3–1998/4) and T is a vector of quarterly time dummies to control for seasonality. Finally, ECt21 is an error-correction term. 7.4.2

Industry-Level Model

Consider the following regression specification: out Dln (EXjt) 5 a0j 1 a1Dln (FDIout jt ) 1 a2Dln (FDIjt21) 1 LYjt21 1 xT 1 wt (7.2)

where D is a change between t and t 1 1, EXt is the amount of total exports for an industry j at time t and FDIout t is industry j’s outward FDI stock. Yjt21 is a vector of industry j’s specific variables including industry size, capital intensity, research and development (R&D) intensity and the wage ratio between non-production and production workers. a0j captures industry j’s unobserved fixed effect affecting export growth and T is a vector of year dummies reflecting various changes in the macroeconomic environment. Finally, wt is a white noise error term. Following Eaton and Tamura (1994), I include one-year lagged growth rate of outward FDI stock in estimation equation (7.2). Eaton and Tamura (1994) show that Japanese outward FDI is more correlated with later exports and thus it may indeed have a ‘beachhead’ effect in promoting subsequent Japanese exports.5 We would like to test if this holds for the Korean case as well. In order to address endogeneity of FDI with respect to exports, I explicitly control for industry fixed effects as well as industry-specific characteristics in estimation. Despite such consideration, it may be still possible that my estimation suffers from some other potential endogeneity problems. For example, export growth and regressors in estimation could be driven by some common factors omitted in estimation. In my estimation, industry fixed-effects are considered, but it is still plausible that some time-varying factors may not be completely controlled for. Furthermore, the nexus between FDI and exports could represent in large part reverse causation running from export to FDI. In this respect, I adopt the system generalized method of moments (GMM) estimator proposed by Blundell and Bond (1998). The system GMM estimator combines the standard set of equations in first differences with suitably lagged levels as instruments, with an additional set of level equations with lagged first-differences as instruments. Specifically, I

214

The rise of China and structural changes in Korea and Asia

pursue the following procedure. First, I take first differences of variables in equation (7.2) to eliminate the time-invariant industry fixed effects, a0j. By doing so, I have a double-differenced equation. Then, I simultaneously estimate this double-differenced equation with the original equation (7.2) using suitable sets of instruments. For estimation, I construct industry-level balanced panel data of 70 manufacturing sectors for the periods of 1992–2003. This dataset has three sources of information: the Annual Report on Mining and Manufacturing Survey (Korean National Statistical Office) for industry-level production data, the Overseas Direct Investment Statistics Yearbook (Export–Import Bank of Korea) Bank for industry-level FDI data, and the UN Commodity Trade Statistics Database (United Nations Statistics Division) for export data. 7.4.3

Firm-Level Model

In this section, I present an empirical strategy for the firm-level analysis. I balanced panel data of Korean multinationals by combining financial data of Korean parent companies extracted from the Korea Information Service Database with those of their overseas affiliates collected by the Export–Import Bank of Korea. The data consist of 62 Korean multinationals and their foreign subsidiaries for the periods of 2001–05.6 Even though the sample is confined to a relatively small number of firms, these firms are in fact large and account for a significant portion of domestic production activities, including exports. Due to double dominance (Belderbos 1992) of these firms in both FDI and domestic production, the worry that direct investment abroad by these large firms would crowd out domestic production is frequently raised by the public. The regression specification here is almost the same as that used in the industry-level analysis, except for the following: first, I exclude the oneyear lagged growth rate of FDI, due to the relatively short time span. Second, the wage gap between production and non-production workers is also dropped due to lack of relevant data. Third, parent dummies as well as sector dummies for foreign affiliates are included in the estimation to control for firm-specific unobserved characteristics. Finally, but most importantly, I could not obtain any reliable data for total exports of parent companies. On the other hand, financial statements of foreign affiliates contain detailed information on sales and purchase activities by foreign affiliates. Using these, I could extract information on intra-firm transactions among related parties around the world. This allowed me to examine a more detailed channel through which direct investment affects exporting activities.

The impact of outward FDI on export activities

215

In particular, I could analyze how foreign direct investment to foreign affiliates affects intra-firm trade from and to related parties (including parent firms) in Korea. The expansion of foreign production through FDI can play an important role in promoting exports from related parties by increasing demands for intermediates such as parts and accessories and capital goods produced by related parties in foreign production. Furthermore, FDI can lead to the acquisition of important assets such as brand names and distribution networks, which helps to increase the firm’s knowledge about the market and thus exports to host countries. As for estimation methodology, unlike the aforementioned industrylevel analysis, the system GMM estimation method employed cannot be adopted here to control for endogeneity bias, due again to the short time span of the sample. Instead, I employ here the two-stage least squared (TSLS) estimation recently proposed by Desai et al. (2007). An instrumental variable, which predicts direct investment, but does not directly affect exports, could help to identify the relationship between FDI and exports. Desai et al. (2007) use information on the firm’s initial distribution of FDI among foreign countries to construct an instrumental variable in the two-stage least squared estimation. They argue that multinationals with prior local experience would have an advantage in properly expanding foreign production because they have better knowledge about the local market. Therefore, when a host country grows, then multinationals with prior investment experience like to expand foreign production accordingly in that country. On the other hand, a firm’s initial distribution of FDI is likely to be exogenous from the standpoint of subsequent changes in exports. In this context, I take the GDP growth rates of foreign affiliates’ host countries and then aggregate them using weights equal to a parent company’s initial outstanding investment share in each of the host countries, relative to the total outstanding investment. The empirical procedure here is as follows: in the first-stage estimation, I regress FDI growth rates on firm-specific weighted averages of foreign GDP growth rates, where the weights correspond to the beginning period’s distribution of foreign investment stock. Then, in the second-stage estimation, I run the regression of the growth rates of parent’s capital stock on the instruments derived from the first stage and other firm-specific variables. Unlike Desai et al. (2007), I also account for firm-specific fixed effects in the estimation.

216

The rise of China and structural changes in Korea and Asia

Table 7.3

D ln (FDI ) out t

Dln (FGDPt) Dln (XPt) Dln (REERt) DummyCrisis Dln (EXt21) ECt21

No. of obs. R-Squared

Aggregate-level analysis: regression results All sample

Before crisis

After crisis

0.345 (0.231) −0.209 (0.102)** 1.347 (0.206)*** 0.067 (0.112) 0.009 (0.021) −0.174 (0.095)* −0.089 (0.056)

1.202 (0.391)*** −0.130 (0.108) 1.104 (0.307)*** −0.107 (0.329) –

0.110 (0.392) 0.121 (0.542) 1.227 (0.246)*** −0.143 (0.216) –

−0.204 (0.154) −0.121 (0.115)

0.184 (0.147) −0.078 (0.062)

78 0.7987

36 0.8994

36 0.7979

Notes: The dependent variable is the logarithm of exports in value. Quarterly time dummies are included in all of the regressions. *, ** and *** indicate significance at a 10%, 5% and 1% level, respectively.

7.5 7.5.1

EMPIRICAL RESULTS Aggregate-Level Results

Table 7.3 reports estimation results based on equation (7.1). For the sample of the whole periods for 1988–2007, estimation results indicate that there is no statistical evidence that outward FDI stock either helps to expand or contract the exporting activity. Among regressors, unit export price is strongly positively correlated with the export volume (at value term). The estimated coefficient for unit export price is statistically significant at the 1 percent level. By dividing the sample periods into before and after the financial crisis, I further examine whether any structural change between two periods occurs. The results indicate that outward FDI in fact complements exports before the financial crisis. Specifically, if outward FDI stock increases by 1 percent, then exports are raised by 1.2 percent. On the other hand, the coefficient for outward FDI becomes statistically insignificant for the

The impact of outward FDI on export activities

Table 7.4

Industry-level analysis: regression results I OLS

a

DFDI b FDIout jt

a

217

out

DFDIout b FDIout jt21

Sizejt21

0.011 (0.014) – 0.026+

Capital_Intensityjt21 Wage_Ratiojt21 R*D_Intensityjt21

Industry Dummies Year dummies No. of obs. R-Squared (within) (between) Arellano-Bond test AR(1) AR(2)

Fixed effect

GMM

0.018 (0.012)

0.016 (0.014)

0.023 (0.013)*

0.022 (0.013)*

0.021 (0.013)

0.027 (0.010)***

−0.062 (0.124) −0.122 (0.235) −0.461 (0.290) 0.186 (0.981)

0.016 (0.021) −0.015 (0.032) −0.186 (0.224) 10.523 (0.316)***

0.009 (0.033) 0.076 (0.135) 10.327 (0.536)**

0.016 (0.031) −0.014 (0.039) −0.214 (0.152) 10.544 (0.521)***

No Yes

No Yes

609 0.1104 – –

543 0.0957 – –

– –

– –

Yes Yes 543 0.0267 (0.0950) (0.0009)

– –

Yes Yes 543 – – – (P-value) 0.018 0.930

Notes: The dependent variable is the annual growth rate of exports. Standard errors corrected for heteroskedasticity and serial correlation in parentheses. *, ** and *** indicate significance at a 10%, 5% and 1% level, respectively.

after-financial crisis period. Later in this chapter, I compare this result with that from the industry-level analysis. 7.5.2

Industry-Level Results

Table 7.4 contains the industry-level regression results based on equation (7.2), using an ordinary least squares (OLS), fixed effect model and the system GMM estimator. First of all, according to OLS estimation, contemporaneous FDI activities neither complement nor substitute exports.

218

The rise of China and structural changes in Korea and Asia

But, as found in Eaton and Tamura (1994) for the Japanese case, the oneyear lagged growth rate of outward FDI seems to be positively associated with the current exports. If inward FDI per GDP is higher by 1 percent, then Korean exports increase by 0.02 percent. However, this beachhead effect of FDI on exports disappears once I control for industry-specific fixed effects. As aforementioned, exports and FDI could be driven by some common factors omitted in OLS or fixed-effects estimation. Even the nexus between FDI and exports could represent, in large part, reverse causation running from exports to FDI. When equation (7.2) is re-estimated by the system GMM method to take care of endogeneity bias, I find evidence for a strong FDI–exports linkage. The results suggest that not only does FDI contemporaneously complement the current period’s exports, but also it promotes subsequent exports. Specifically, other things being equal, a 1 percent increase of outward FDI per GDP leads to 0.02 percent and 0.03 percent of export growth for the current and next year, respectively. This, when converted into currency, implies that if outward FDI increases by $1, then exports of the given year and the year after rise approximately by $2.40 and $2.80, respectively. For other control variables, the coefficients for industry size, capital intensity and wage gap between non-production and production workers all turned out to be statistically insignificant in estimation. On the other hand, the results show that higher R&D intensity helps to promote exports in the Korean case. Similarly to the aggregate-level estimation, I also estimate equation (7.2) separately for the before- and after-financial crisis sample. As shown in Table 7.5, the FDI–export nexus becomes conspicuous after the financial crisis, contrary to aggregate-level results reported in Table 7.3. For the after-financial crisis sample, the results from the fixed-effects estimation support the beachhead effect of FDI on exports, while the system GMM estimation indicates the significant contemporaneous nexus as well. Table 7.6 contains the estimation results for high-tech and low-tech industries separately.7 The results suggest that the positive relationship between FDI and exports is mainly coming from high-tech industries. For these industries, FDI does promote exports, while this is not the case for the low-tech industries. Neither the fixed-effects model nor the system GMM estimator produces evidence of the FDI–exports linkage for lowtech sectors. These results are consistent with those reported in Table 7.5, in the sense that Korean outward FDI after the financial crisis is largely concentrated in high-tech sectors in which vertical specialization across countries prevails. In fact, as depicted in Figure 7.6, outward FDI in high-

The impact of outward FDI on export activities

Table 7.5

219

Industry-level analysis: regression results II Before the crisis (1992–1996) Fixed effect

GMM

After the crisis (1997–2003) Fixed effect

GMM

a

DFDI b FDIout jt

−0.052 (0.067)

0.015 (0.062)

0.025 (0.017)

0.023 (0.013)*

a

DFDIout b FDIout jt21

−0.052 (0.064)

0.032 (0.057)

0.031 (0.015)**

0.032 (0.009)***

−0.208 (0.288) 0.270 (0.339) −0.096 (0.316) 0.901 (1.743)

0.002 (0.067) −0.003 (0.103) 0.140 (0.357) 1.625 (1.169)

out

Sizejt21 Capital_Intensityjt21 Wage_Ratiojt21 R*D_Intensityjt21

No. of obs. R-Squared (within) (between) Arellano-Bond test AR(1) AR(2)

140 0.000 (0.1933) (0.0146)

– –

140 – – – (P-value) 0.127

−0.182 (0.167) −0.090 (0.300) −0.650 (0.385)* 0.126 (0.963) 403 0.0055 (0.0974) (0.0150)

– –

0.025 (0.018) −0.036 (0.039) −0.257 (0.281) 0.808 (0.613) 403 – – – (P-value) 0.018 0.583

Notes: The dependent variable is the annual growth rate of exports. Industry dummies and time dummies are included in all of the regressions. Standard errors corrected for heteroskedasticity and serial correlation in parentheses. *, ** and *** indicate significance at a 10%, 5% and 1% level, respectively.

tech industries, notably IT, communication equipment and automobiles among many others, has revealed rapid growth. Consequently, the share of high-tech industries in total FDI stock increased from 34.1 percent in 1992 to 61.0 percent in 2003. In sum, I can conclude that FDI leads to an increase in the volume of trade, mainly driven by increased specialization within high-tech industrial sectors after the financial crisis. Furthermore, my results suggest that Korean outward FDI is closely correlated with later exports and thus it plays an important role in promoting subsequent Korean exports.

220

The rise of China and structural changes in Korea and Asia

Table 7.6

Industry-level analysis: regression results III High-tech industry

Low-tech industry

Fixed effect

GMM

Fixed effect

GMM

a

DFDIout b FDIout jt

0.006 (0.010)

0.013 (0.007)*

0.138 (0.139)

0.116 (0.117)

a

DFDIout b FDIout jt21

0.006 (0.010)

0.015 (0.006)**

0.081 (0.069)

0.017 (0.079)

0.074 (0.077) −0.199 (0.148) −0.139 (0.262) 0.557 (0.907)

0.026 (0.016) −0.031 (0.0310 0.083 (0.091) 0.904 (0.364)**

−0.469 (0.261) −0.057 (0.352) −1.180 (0.481)** −10.984 (9.599)

−0.003 (0.019) −0.012 (0.039) −0.474 (0.294) −10.088 (5.792)*

304 0.0034 (0.1666) (0.0336)

304

Sizejt21 Capital_Intensityjt21 Wage_Ratiojt21 R*D_Intensityjt21

No. of Obs. R-Squared (within) (between)

239 0.1707 (0.2451) (0.2236)

Arellano-Bond test AR(1) AR(2)

– –

239 – – – (P-value) 0.037 0.885

– –

– – – (P-value) 0.027 0.436

Notes: The dependent variable is the annual growth rate of exports. industry dummies and time dummies are included in all of the regressions. Standard errors corrected for heteroskedasticity and serial correlation in parentheses. *, ** and *** indicate significance at a 10%, 5% and 1% level, respectively.

7.5.3

Firm-Level Results

In this section, we examine specific channels through which outbound FDI contributes to the export performance of Korean multinationals. As aforementioned, we do not have reliable data for total exports of parent companies. However, using extensive financial data of parent companies in Korea and their foreign affiliates, we investigate more detailed channels through which direct investment by multinational corporations (MNCs) affects exporting activities. Table 7.7 presents the correlation coefficients between various aspects

The impact of outward FDI on export activities

(0.1 billion $)

120

Low-tech

100

221

High-tech

80 60 40 20 0 1992

1994

1996

1998

2000

2002

Source: Author’s calculations, based on EXIM Bank, Overseas Direct Investment Yearbook.

Figure 7.6

Table 7.7

Korean FDI stock by sector

Correlation between parent companies’ and subsidiaries’ activities

Tangible assets growth (subsidiaries)

Capital stock growth (parent)

Fixed assets growth (parent)

R&D investment growth (parent)

Employment growth (parent)

−0.002 (0.012)

1.571 (0.971)*

0.047 (0.093)

11.546 (1.786)

−0.026 (0.015)*

157 0.0017

Intangible assets growth (subsidiaries)

0.017 (0.008)**

0.837 (1.259)

Assets growth (subsidiaries)

0.052 (0.037)

6.281 (2.335)***

0.458 (0.459)

0.280 (0.214)

Sales growth (subsidiaries)

0.023 (0.039)

1.948 (1.685)

0.351 (0.307)

0.195 (0.141)

−0.004 (0.073)

0.703 (2.694)

0.638 (0.448)

0.360 (0.202)*

Outward FDI growth (Parent)

Notes: Each coefficient is estimated by running a simple regression. Standard errors corrected for heteroskedasticity and serial correlation in parentheses. *, ** and *** indicate significance at a 10%, 5% and 1% level, respectively.

222

The rise of China and structural changes in Korea and Asia

of production activities of parent companies in Korea and those of their foreign affiliates. These coefficients are estimated by running simple OLS regressions. The results show that there exists a positive correlation between tangible asset (or total asset) growth of foreign subsidiaries and fixed asset growth of their parent companies. Similar relationships are found between intangible assets of foreign affiliates and capital stocks of their parents. On the other hand, the growth of outward FDI is not correlated with increases in capital stock, fixed asset or research and development (R&D) investment in parent companies. However, these results indicate a simple correlation relationship instead of causation. Furthermore, it is highly plausible that a growing parent firm also tends to expand investment in its foreign subsidiaries. Therefore, it is necessary to control for firm-specific characteristics in the estimation process in order to avoid spurious inference. As aforementioned, I employ the two-stage least squared (TSLS) estimation proposed by Desai et al. (2007). In the first-stage estimation, I regress FDI growth rates on firm-specific weighted averages of foreign GDP growth rates, where the weights correspond to the beginning period’s distribution of foreign investment stock. Then, in the second-stage estimation, I run the regression of the growth rates of the parent’s capital stock on the instruments derived from the first stage and other firmspecific variables. Before introducing the estimation results, let us examine the relationship between foreign GDP growth and production activities of Korean multinationals. The foreign GDP growth rates specific to firms are defined as a weight-sum of the GDP growth rates of their foreign affiliates’ host countries, where weights are equal to a parent company’s initial outstanding investment share in each of the host countries, relative to the total outstanding investment. According to the results obtained by simple regressions, as reported in Table 7.8, foreign GDP growth is positively associated with the growth of capital stock of the parent firms, with total asset growth of foreign subsidiaries, and with sales growth of foreign subsidiaries. Table 7.8 also reports the correlation relationship between foreign GDP growth and changes in sales (and in purchases) by foreign affiliates. It is necessary to note here that the foreign GDP growth not only leads to the increase of sales in local markets, but also creates new opportunities for international trade through various channels via foreign affiliates. As depicted in Table 7.8, when host countries are growing, then intra-firm trade among related parties is also expanding. Tables 7.9–7.10 contain my estimation results obtained by the TSLS estimation. First of all, I find evidence that the FDI–exports nexus mainly works through intra-firm exports from parent companies to foreign

The impact of outward FDI on export activities

Table 7.8

Correlations between foreign GDP growth and firms activities Capital stock growth (parent)

Foreign GDP growth (weighted sum) No. of obs. R-Squared

0.200 (0.106)*

274 0.0018 Local Sales growth (subsidiaries)

Foreign GDP growth (weighted sum) No. of Obs. R-Squared

0.501 (0.280)*

239 0.0025

Total assets growth (subsidiaries) 0.796 (0.391)*

275 0.0293 Total export growth (subsidiaries) 0.846 (0.378)**

203 0.0106

Total import Local growth purchase (subsidigrowth aries) (subsidiaries) Foreign GDP growth (Weighted sum) No. of Obs. R-Squared

223

–0.019 (0.481)

191 0.0000

0.591 (0.238)**

199 0.0052

Tangible fixed assets growth (subsidiaries)

Intangible fixed assets growth (subsidiaries)

0.935 (1.033)

11.546 (1.786)

267 0.0063

157 0.0017

Sales growth (subsidiaries) 0.575 (2.74)**

270 0.0066

To relatedparties in Korea

To other parties in Korea

To the 3rd markets

1.408 (0.354)***

2.888 (1.611)*

0.453 (0.216)**

156 0.0103

181 0.0330

160 0.0030

From relatedparties in Korea

From other parties in Korea

From the 3rd markets

1.043 (0.316)***

0.571 ( 0.272)**

0.815 (0.245)***

179 0.0066

193 0.0020

138 0.0095

Notes: Each coefficient is estimated by running a simple regression. The foreign GDP growth rates are calculated by taking a weight-sum of the GDP growth rates of their foreign affiliates’ host countries, where weights are equal to a parent company’s initial outstanding investment share in each of the host countries, relative to the total outstanding investment. Standard errors corrected for heteroskedasticity and serial correlation in parentheses. *, ** and *** indicate significance at a 10%, 5% and 1% level, respectively.

224

Table 7.9

The rise of China and structural changes in Korea and Asia

Firm-level analysis: regression results I Import growth from parent company

Instrument Firm size R&D intensity Capital intensity No. of obs. R-Squared

1.508 (0.896)* −0.053 (0.515) −0.001 (0.086) −0.231 (0.321) 139 0.1048

Import growth from Korea in total 0.574 (0.781) 0.092 (0.475) −0.016 (0.051) −0.040 (0.285) 148 0.1180

Import growth from 3rd market

Purchase growth from local market

0.684 (1.109) −0.149 (0.1260) 0.013 (0.041) 0.435 (0.265)

0.581 (0.929) −0.300 (0.275) −0.071 (0.089) −0.137 (0.486)

107 0.1716

154 0.1641

Notes: Each estimation includes parent dummies and sector dummies for foreign affiliates. Standard errors corrected for heteroskedasticity and serial correlation in parentheses. *, ** and *** indicate significance at a 10%, 5% and 1% level, respectively.

Table 7.10

Firm-level analysis: regression results II Export growth to related-parties in Korea

Instrument Firm size R&D intensity Capital intensity No. of obs. R-Squared

1.239 (0.893) 0.468 (0.775) −0.132 (0.088) 0.402 (0.500) 124 0.2457

Export growth to Korea in total

Export growth to 3rd market

Sales growth to local market

2.833 (0.977)*** 0.156 (0.963) −0.043 (0.202) −0.805 (0.826)

0.849 (0.645) 0.167 (0.088)* −0.038 (0.050) 0.512 (0.387)

2.031 (1.115)* 0.046 (0.446) 0.042 (0.059) −0.898 (0.509)*

138 0.3021

122 0.1655

183 0.2971

Notes: Each estimation includes parent dummies. Sector dummies for foreign affiliates are not included, basing on F-statistic. Standard errors corrected for heteroskedasticity and serial correlation in parentheses. *, ** and *** indicate significance at a 10%, 5% and 1% level, respectively.

The impact of outward FDI on export activities

Table 7.11

Instrument Firm size R&D intensity Capital intensity No. of obs. R-Squared

225

Firm-level analysis: regression results III Capital stock growth (parent)

Employment growth (parent)

Sales growth (parent)

Asset growth (parent)

R&D investment growth (parent)

0.101 (0.053)* −0.135 (0.130) 0.033 (0.044) 0.123 (0.105)

0.900 (0.264)*** −1.413 (0.208)*** −0.023 (0.045) −0.023 (0.331)

0.777 (0.363)** −0.165 (0.285) −0.082 (0.060) −0.332 (0.482)

0.905 (0.444)** −0.136 (0.249) −0.033 (0.038) 0.411 (0.489)

1.165 (0.714) 0.021 (0.542) −0.598 (0.187)*** −0.115 (0.827)

205 0.3976

202 0.3029

204 0.0268

204 –

201 0.3441

Notes: Each estimation includes parent dummies and sector dummies for foreign affiliates. Standard errors corrected for heteroskedasticity and serial correlation in parentheses. *, ** and *** indicate significance at a 10%, 5% and 1% level, respectively.

affiliates. The impact of FDI on the imports from parent companies, which is intra-firm exports in my terminology, is proven to be positive and statistically significant. On the other hand, I could not find similar results for exports from non-related parties in Korea or in other countries. My TSLS results also suggest that an FDI increase leads to the expansion of foreign affiliates’ exports to Korea as well as local sales in host countries. It is interesting that the estimated coefficient of FDI is greater on foreign affiliates’ exports to Korea than on intra-firm exports from their related parties in Korea. Specifically, when FDI increases by 1 percent, then exports from foreign affiliates to Korea increase by 2.8 percent, while intra-firm exports from their related parties in Korea rise by 1.5 percent. Finally, Table 7.11 reports the estimation results regarding the impacts of FDI on firms’ performance variables other than exports. Overall, there is no evidence that the expanded FDI replaced domestic production activities of parent companies in Korea. 7.5.4

The Rise of China and its Implications on the FDI–Export Nexus

Before closing the chapter, I briefly examine the implications of the Chinese emergence on the relationship between FDI and exporting

226

The rise of China and structural changes in Korea and Asia

activities. Specifically, I am interested in whether or not the complementary relationship between the Korean outward FDI and exporting activities will continue to hold as the importance of China as a destination of Korean FDI continues to increase. One plausible explanation of the strong FDI–exports nexus found in the chapter is that the presence of the wholesale affiliates, mainly of the Korean large corporations, contributes to promote exports through the enhanced distributional channels. Indeed, according to Lee and Lim (2007), about 80 percent of the Korean intra-firm exports are made by six major corporations, such as Samsung Electronics and Hyundai Motor Company. And, of their intra-firm exports, the share of exports to their wholesale affiliates in foreign countries amounts to between 64 and 98 percent. On the other hand, as shown in Figure 7.4, the Korean FDI in China has concentrated mostly in manufacturing, rather than in wholesaling. In the case of the FDI in manufacturing, the extent of the FDI–exports nexus greatly depends on the demand of foreign affiliates on products, such as parts and components, made at home. If the relocation of manufacturing facilities toward a foreign country proceeded without increasing such demand, then the expansion of outward FDI would not contribute to promote exports from home. Hence, it may be possible that the emergence of China as a major FDI destination alters the nature of the overall relationship between FDI and export activities. As depicted in Table 7.12, as of 2006, more than 95 percent of the Korean exports into China were intermediate and capital goods. Among them the shares of parts and components as well as of capital goods have increased since the 1990s. In addition, it is known that more than half of the Korean exports into China are directed towards the FDI firms in China. Therefore, we can infer that the rapid growth of exports into China is closely related to the manufacturing activities of the FDI firms in China. Table 7.13 compares the structures of sales and purchases of the Korean affiliates by FDI destination. The share of sales to third markets has substantially increased for the case of affiliates in China, while the Korean affiliates in the US sell most of their products (86.1 percent as of 2005) to the local market. On the purchase side, one distinct feature is that the importance of purchases from Korea by foreign affiliates has been declining both for those in China and in the US. In the case of China, the share of sales to Korea has also decreased, from 27.4 percent in 2001 to 10.8 percent in 2005. Another interesting finding is that for the Korean affiliates located in other regions, purchases from Korea have drastically increased. In fact, their share in total purchases increased from 32.7 percent in 2001 to 53.5 percent, as shown in Table 7.13.

The impact of outward FDI on export activities

Table 7.12

227

Composition of the Korean exports into China 1997 (%)

Raw materials

2000 (%)

20006 (%)

0.3

0.4

0.1

Intermediates

Semi-processed Parts & components

72.3 10.3

62.2 19.7

44.0 35.9

Final goods

Capital goods Consumers goods

11.2 5.9

9.9 4.8

16.7 3.3

Source:

UN Comtrade database.

Table 7.13

Composition of sales and purchases by Korean affiliates (%)

FDI destination

Sales To local market

To Korea

Purchases To the 3rd markets

From local market

From Korea

From the 3rd markets

China

2001 2005

42.7 45.5

27.4 10.8

29.9 43.6

39.2 40.4

44.7 27.4

16.2 32.3

US

2001 2005

88.6 86.1

6.7 6.9

4.7 7.0

14.2 24.9

79.3 65.0

6.5 10.1

Others

2001 2005

48.3 52.2

17.9 16.0

33.8 31.8

38.7 18.8

32.7 53.5

28.7 27.7

Total

2001 2005

64.5 61.0

14.1 12.8

21.4 26.2

28.0 23.0

53.9 54.3

18.1 22.7

These observations can be summarized in the following way. First of all, the linkage between FDI activities and the Korean trade with China seems to be relatively weakened in the 2000s. At the same time, however, such linkage with other regions, notably in Association of South East Asian Nations (ASEAN) areas, has strengthened over the same period. This indicates that Korean firms are actively participating in and benefiting from international production networks through diversifying FDI activities across the world.

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The rise of China and structural changes in Korea and Asia

However, since China is a major destination of Korean FDI and its importance is expected to be ever increasing, the trend of a weaker linkage between FDI activities and the Korean trade with China needs careful investigation. As Chinese industry advances and its exports require highvalue-added items, the demand for technology-intensive core components and materials will increase, serving as an ample opportunity for Korea exporting firms. Therefore, we can conclude that, to keep up with the strong FDI–export nexus, it is important for Korea to make great efforts to enhance the industrial structure and secure its competitive edge in advanced high-tech products and core components.

7.6

CONCLUDING REMARKS

Considering the recent trend of fast-spreading international division of labor, it is expected that FDI is going to have a growing influence on the domestic economy. In order for Korean companies to survive successfully in international competition, it is often suggested that Korean companies should actively participate in the international division of labor through FDI. At the same time, however, there exist some concerns that the rapid relocation of manufacturing facilities toward foreign countries through FDI could shrink exports, and at the same time the imports of those goods would also contract domestic production activities. According to my results, there is little evidence that the expanded FDI of Korean companies has replaced exports or other domestic production activities. Generally, I find that FDI complements exporting activities, and such a relationship is most apparent in the high-technology industries and in the period after the financial crisis. My industry-level analysis, which is useful in identifying the net effect of FDI on overall manufacturing, further suggests that Korean outward FDI has a so-called ‘beachhead effect’ and thus it plays an important role in promoting subsequent Korean exports. In addition, as for Korean multinationals, the estimation results indicate that the FDI–exports nexus mainly works through intra-firm exports from parent companies to foreign affiliates.

NOTES *

Paper prepared for presentation at the 2008 KDI International Conference on Growth and Structural Changes of the Korean Economy after the Crisis, 21–22 July Seoul, Korea.

The impact of outward FDI on export activities

229

1. There are also some studies suggesting that FDI can either complement or substitute trade. For example, Kojima (1985) argues that FDI creates trade if capital moves from comparatively disadvantageous sectors at home to comparatively advantageous ones in foreign countries. On the contrary, if capital moves from comparatively advantageous industries at home, then FDI would reduce trade. In a different context, Baldwin and Ottaviano (2001) suggest that non-zero trade costs reduce intervariety competition across firms since they shift production location to foreign affiliates. Then FDI replaces some exports, but it also creates trade through reverse imports of final goods. 2. The ‘related-party exports’ include exports from US foreign subsidiaries to parent companies in the US and exports from foreign parent companies to their subsidiaries in the US. 3. They define ‘intra-firm exports’ as sales of intermediate or final goods of a parent company operating in Korea to its foreign affiliates. 4. I add up the real GDPs of 11 major Korean trading partners to construct FGDPt. 5. O’Sullivan (1993) also finds that FDI this year increases the next year’s exports in the Irish time-series data. 6. The Export–Import Bank of Korea collects financial data only for foreign subsidiaries of which the amount of outstanding direct investment exceeds US$ 1 million. 7. I follow Hatzichronoglou’s (1997) approach in classifying manufacturing sectors according to technology intensity. High-tech industry includes information technology (IT) equipment, pharmaceuticals, aircraft, electric and electronic machineries, transportation equipment, chemicals, and so on.

BIBLIOGRAPHY Ahn, S., S. Lee and C. Woo (2008), ‘The internationalisation of firm activities and its economic impacts: the case of South Korea’, in J.J. Palacios (ed.) (2008), Multinational Corporations and the Emerging Network Economy in Asia and the Pacific, London: Routledge, pp. 139–62. Arndt, C., C.M. Buch and M. Schnitzer (2007), ‘FDI and domestic investment: an industry-level view’, mimeo. Ando, M. and F. Kimura (2006), ‘Fragmentation in East Asia: further evidence’, mimeo. Baldwin, R. and G. Ottaviano (2001), ‘Multi product multinationals and reciprocal FDI dumping’, Journal of International Economics, 54, 429–48. Belderbos, R.A. (1992), ‘Large multinational enterprises based in a small economy: effects on domestic investment’, Weltwirtschaftliches Archiv, 128(3), 543–57. Blonigen, A.B. (2001), ‘In search of substitution between foreign production and exports’, Journal of International Economics, 53, 81–104. Blundell, R. and S. Bond (1998), ‘Initial conditions and moment restrictions in dynamic panel data models’, Journal of Econometrics, 87(1), 115–43. Braunerhjelm P., L. Oxelheim and P. Thulin (2005), ‘The relationship between domestic and outward foreign investment revisited: the impact of industryspecific effects’, Electronic Working Paper Series, no. 35. Chen, Y., J. Ishikawa and Z. Yu (2004), ‘Trade liberalization and strategic outsourcing’, Journal of International Economics, 63, 419–36. Clausing, A.K. (2000), ‘Does multinational activity displace trade?’, Economic Inquiry, 38(2), 190–205. Desai, M.A., C.F. Foley and J.R. Hines Jr (2005), ‘Foreign direct investment and the domestic capital stock’, American Economic Review, 95(2), 33–8.

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Desai, M.A., C.F. Foley and J.R. Hines Jr (2007), ‘Foreign direct investment and the domestic activity’, mimeo. Eaton, J. and A. Tamura (1994), ‘Bilateralism and regionalism in Japanese and US trade and direct foreign investment patterns’, NBER Working Paper, no. 4758. Egger, H. and P. Egger (2004), ‘On the relationship between international outsourcing and price–cost margins in European industries’ Review of Industrial Organization, 25, 45–69. Export–Import Bank of Korea (2007), Annual Report on Business Performances of Korea Overseas Enterprises 2007, Seoul: Export–Import Bank of Korea. Faeth, I. (2006), ‘Consequences of FDI in Australia: causal links between FDI, domestic investment, economic growth and trade’, mimeo. Feldstein, M. (1994), ‘The effects outbound foreign direct investment on the domestic capital stock’, NBER Working Paper, no. 4668. Feldstein, M. and C. Horioka (1980), ‘Domestic savings and international capital flows’, Economic Journal, 90, 314–29. Goedegebuure, R.V. (2006), ‘The effect of outward foreign direct investment on domestic investment’, Investment Management and Financial Innovations, 3(1), 9–22. Graham, E.M. (2000), ‘On the relationships among direct investment and international trade in the manufacturing sector: empirical results for the United States and Japan’, in D. Encarnation (ed.), Does Ownership Matter? Japanese Multinationals in East Asia, London: Oxford University Press. Grossman, G.M. and E. Rossi-Hansberg (2006), ‘The rise of offshoring: it’s not wine for cloth anymore’, mimeo. Hatzichronoglu, T. (1997), Revision of the High-technology Sector and Product Classification, Paris: OECD. Helpman, E. (1984), ‘Multinational corporations and trade structure’, Review of Economic Studies, 92(3), 451–71. Hejazi, W. and P. Pauly (2003), ‘Motivations for FDI and domestic capital formation’, Journal of International Business Studies, 34, 282–9. Hejazi, W. and A.E. Safarian (2001), ‘The complementarity between US foreign direct investment stock and trade’, Atlantic Economics Journal, 29(4), 420–37. Herzer, D. and M. Schrooten (2007), ‘Outward FDI and domestic investment’, Discussion Papers, German Institute for Economic Research. Kojima, K. (1985), ‘Japanese and American direct investment in Asia: a comparative analysis’, Hitotsubashi Journal of Economics, 26, 1–35. Lee, S. and K. Lim (2007), ‘Impact of corporate globalization on intra-firm exports’, KDI Economic Outlook, 2009(1), 158–67. Lee, S. and S. Shin (2007), ‘Analysis on the primary factors for recent export growth’, KDI Economic Outlook, 2009(2), 145–55. Lipsey, R. and M.Y. Weiss (1981), ‘Foreign production and exports in manufacturing industries’, Review of Economics and Statistics, 63(4), 488–94. Lipsey, R. and M.Y. Weiss (1984), ‘Foreign production and exports of individual firms’, Review of Economics and Statistics, 66(2), 304–8. Mankiw, N.G. and P. Swagel (2006), ‘The politics and economics of offshore outsourcing’, mimeo. Marchant, M.A. and S. Kumar (2005), ‘An overview of US foreign direct investment and outsourcing’, Review of Agricultural Economics, 27(3), 379–86.

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Mitze, T. (2007), ‘Determining trade–FDI linkages for Germany: evidence from a simultaneous equation approach using panel gravity models’, mimeo. Matsubara, K. (2004), ‘FDI with reserve imports and hollowing out’, mimeo. Markusen, J.R., A.J. Venables, D.E. Konan and K.H. Zhang (1996), ‘A unified treatment of horizontal direct investment, vertical direct investment, and the pattern of trade in goods and services’, NBER Working Paper No. 5696. O’Sullivan, P.J. (1993), ‘An assessment of Ireland’s export-led growth strategy via foreign direct investment: 1960–1980’, Weltwirtschaftliches Archiv, 129(1), 139–58. Stevens, G.V.G. and R.E. Lipsey (1992), ‘Interaction between domestic and foreign investment’, Journal of International Money and Finance, 11, 40–62. Swenson, D.L. (2004), ‘Foreign investment and the mediation of trade flows’, Review of International Economics, 12(4), 609–29. Swenson, D.L. (2005a), ‘Overseas assembly production choices’, Contemporary Economic Policy, 23(3), 394–403. Swenson, D.L. (2005b), ‘Overseas assembly and country sourcing choices’, Journal of International Economics, 66, 107–30.

8.

The rise of the Chinese economy and Korea’s job growth* Dae Il Kim

8.1

INTRODUCTION

The Korean economy has heavily relied on international trade since the 1960s when the economy commenced fast growth. As of 2004, the ratio of international trade to gross domestic product (GDP) was 0.64 in Korea, much higher than that of the US or Japan.1 Such a high ratio implies that the labor demands and job growth potentials in Korea are more strongly affected by the changes in trade patterns and volumes.2 In particular, the ratio to the GDP of trade with China alone is as high as 0.14 as the trade with China accounts for 21.9 percent of the total trade volumes of Korea. Consequently, the effects of the trade with China on Korea’s labor market must have been substantial. Goods trade is just one of many important aspects of Korea’s economic trade with China. The Chinese economy went through rapid industrialization during the 1980s and 1990s, which has led China to become one of the major competitors to Korea in the world market. Kim et al. (2006) show that the exports of China shifted from labor-intensive products such as textiles, apparel and shoes toward skill-intensive products such as electronics and information technology (IT)-related products through the 1990s.3 As these have been among Korea’s main exports, the world market share of Korea in these products has accordingly been suppressed. Another important aspect in the two countries’ economic trade that could have affected Korea’s job growth potential has been Korea’s foreign direct investment (FDI) into China. There have been many causes that have induced Korea’s FDI, but it is generally agreed that most of the FDI into China has been motivated by relatively lower labor costs. To the extent that the FDI has targeted lower labor costs, such outflow of capital is likely to have affected Korea’s job growth potential negatively. This chapter measures how the labor demand and job growth potential of Korea have been affected by the increased economic trade with the growing Chinese economy. The analysis focuses on three channels: the 232

The rise of the Chinese economy and Korea’s job growth

233

increase in goods trade; the increase in competition in the world market arising from the export growths of China; and the increase in direct investment of the Korean firms in China. The effect through each channel is measured by utilizing the input–output relationship among the Korean industries. It is important to understand that the effects measured in the analysis are not the actual contribution of economic trade with China to Korea’s employment. Instead, it is more appropriate to consider the effects as representing the changed demand for labor (or labor disaggregates), given that other things are held constant including wages. Such changes in demand, or alternatively pressure on labor demands, may show up in employment changes or wage changes in the economy depending on various factors including labor supply elasticity. The main empirical results of the chapter can be summarized as the following. First, Korea has maintained a large trade surplus during the 1988–2004 period, which has contributed positively to its overall domestic labor demand. However, the effects have been skill-biased, favoring bettereducated workers. Second, the increased competition with China in the world market has had a negative effect on Korea’s domestic labor demand, almost offsetting the positive effect of trade surplus. Third, Korea’s FDI into China has suppressed domestic labor demand, but the magnitude has been relatively small. When put together, the effects on aggregate labor demand appear small, but the relative decline in demand for less-educated workers in Korea has been non-trivial, accounting for a substantial portion of rising wage inequality during the latter half of the 1990s in Korea.

8.2 8.2.1

INCREASED TRADE, COMPETITION AND INVESTMENT WITH CHINA Economic Growth of China and Increased Trade

The economic growth of China during the 1990s was quite remarkable. The GDP of China increased three times from $503.7 billion in 1990 to $1652.8 billion in 2004, and the nominal growth rate was 9 percent per annum. China’s growth was accompanied by equally fast industrialization: industrial outputs increased by almost 300 percent between 1993 and 2004, and investments increased by 460 percent. International trade also increased fast. China’s exports have increased from $84.5 billion in 1992 to $587.4 billion in 2004, and the imports from $80.6 billion to $552.7 billion during the same period. Such fast growth placed China among the five largest economies in the world by 2005.

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The rise of China and structural changes in Korea and Asia

70

Exports Imports

60 50 40 30 20 10 0 1988 Source:

1990

1992

1994

1996

1998

2000

2002

2004

UN Comtrade data set, 1988–2004.

Figure 8.1

Trade volumes of Korea with China (current price, $ billion)

During the period of fast economic growth of China, goods trade between China and Korea also expanded rapidly. As shown in Figure 8.1, Korea’s exports to China have increased from $3.6 billion in 1988 to $66.3 billion in 2004, and Korea’s imports from China from $0.6 billion to $31.5 billion during the same period. In particular, trade expansion has been more pronounced during the post-crisis period of Korea; the average nominal growth rate of Korea’s exports to China jumped from 9.8 percent during the 1988–97 period to 23.3 percent during the 1998–2004 period; that of Korea’s imports from China also jumped from 15.3 percent to 29.5 percent between the two periods.4 Consequently, the shares of trade with China in Korea’s total exports and imports reached 27 percent and 14 percent in 2004, respectively, exceeding the shares of trade with the US or Japan.5 As the trade volume with China has increased, the pattern of traded goods has also changed. Figure 8.2 shows the changes in export and import patterns defined by worker skill content during the 1988–2004 period. The top 30 percent of the wage distribution among the Korean workers is defined as high-skilled workers, and the industries (and goods) are classified according to the share of high-skilled workers in total employment into high-skill, medium-skill and low-skill intensive sectors of an equal size. The figure shows that in Korea’s exports to China, the sectors of all skill intensities have increased similarly. In contrast, the imports of lowskill intensive goods from China have increased faster. Kim et al. (2006) showed that the trade with China has shifted from agricultural products and raw materials toward intra-industry trade of manufactured parts and

The rise of the Chinese economy and Korea’s job growth

235

(a) Exports 18

Low skill intensive Medium skill intensive High skill intensive

16 14 12 10 8 6 4 2 0 1988

1990

1992

1994

1996

1998

2000

2002

2004

1996

1998

2000

2002

2004

(b) Imports 30

Low skill intensive Medium skill intensive High skill intensive

25 20 15 10 5 0 1988

1990

1992

1994

Source: UN Comtrade data set, 1988–2004; Wage Structure Survey, the Ministry of Labor, Korea.

Figure 8.2

Trade volumes with China by skill intensity (current price, $ billion)

machines, and the results in the figure suggest that the imports of parts and manufactured goods from China are still relatively low-skill-intensive. Goods trade with China is expected to have affected Korea’s labor demand or job growth potential in two ways. First, as previously shown in Figure 8.1, Korea has recorded a substantial surplus in trade with China, and this trade surplus has had a positive impact on Korea’s domestic job growth. The magnitude of the impact depends on the relative labor

236

The rise of China and structural changes in Korea and Asia

Table 8.1

1992–94 2002–04 Source:

Increased export competition between Korea and China (A) Number of products with Korea’s export greater than $1m

(B) Number of products among (A) with China’s export greater than $.5m

Ratio (%) = (B)/(A)

1502 1871

1299 1802

86.5 96.3

UN Comtrade data set, 1992–2004.

intensities of the export and import sectors of Korea, however. To the extent that Korea’s exports are capital-intensive while its imports are labor-intensive, the positive effect of trade surplus on employment will be smaller in Korea. Second, the shift in sectoral structures in exports and imports may have differential effects on variously skilled workers’ employment. To the extent that Korea imports a greater amount of unskilled labor intensive products from China, Korea’s domestic demand for unskilled workers is likely to be suppressed. 8.2.2

Increased Competition in the World Market

As the Chinese economy has increasingly integrated into the world market, many Chinese products have emerged as potentially very strong competitors against the Korean products. Such competition between the Korean and Chinese products has intensified both at the external and internal margins. Table 8.1 indicates that the Chinese exports to the world market have increased rapidly among the major exports of Korea. In 1992, among the 1502 products classified by a five-digit commodity code that Korea sold to the world market over $1 million, the Chinese exports exceeded $0.5 million in 1299 products, or 86.5 percent. However in 2004, out of 1871 products whose exports of Korea exceeded $1 million, the Chinese exports exceeded $0.5 million in 1802 products, or 96.3 percent. The share of the products whose exports of Korea exceeded the Chinese exports was 33.5 percent in 1992, but had fallen to 21.9 percent by 2004. That is, China has emerged as a strong competitor for Korea in the world market in the increasing number and share of products. Competition has also similarly intensified at the intensive margin. Figure 8.3 shows the change in relative world market shares of China to Korea in 70 three-digit industries. The relative market share (zjt) of industry j at year t is defined as the following:

The rise of the Chinese economy and Korea’s job growth

237

1

2002–04 average

0.8 0.6 0.4 0.2 0 0

Source:

0.1

0.2

0.3

0.4 0.5 0.6 1992–94 average

0.7

0.8

0.9

1

UN Comtrade data set, 1992–2004.

Figure 8.3

Increase in relative market shares of the Chinese products

zjt 5

XChina jt XKorea 1 XChina jt jt

(8.1)

In the above, Xcjt is the export of industry j at year t of country c. A zjt close to 0 implies that China does not compete with Korea in the market of product j at year t, and a zjt close to 1 implies that China takes away almost all of the Korea’s share in the market of product j at year t. In the figure where zjt of the 2002–04 period is plotted against zjt of the 1992–94 period for each industry j, 58 out of 70 industries are located above the 45-degree line, which implies that 82.9 percent of Korea’s exporting industries have lost their market shares to the Chinese competitors. At the same time, out of 26 industries in which Korea’s exports exceeded China’s during the 1992–94 period, Korea’s exports still exceeded China’s in only 11 industries, or 42.3 percent, in the 2002–04 period. In contrast, Korea’s exports exceeded China’s only in two industries in the 2002–04 period out of 44 industries in which China’s exports exceeded Korea’s in the 1992–94 period. Increased competition from China’s manufacturing is expected to have suppressed the demand for Korea’s manufactured goods and thus its labor input demands. One also must consider, however, the indirect effect such as the demand increase for Korea’s products put to use as intermediate goods by the Chinese exporting firms. To the extent that such indirect effects are large, the downward pressure on the overall demands for the Korean products and labor will be at least partly offset by them. The total

238

The rise of China and structural changes in Korea and Asia

effect on the demand for Korean products and Korea’s domestic labor, therefore, is an empirical question, which will be estimated later in this chapter. 8.2.3

Direct Investment into China

China has been one of the major countries into which Korea’s foreign direct investment has flown since the 1990s, and more recently an increasing number of Korean firms have invested in China for its less expensive labor. Shin and Nam (2004) report that 42.8 percent of the Korean firms which have invested in China cite lower labor costs as the number one incentive for such investment. Kim et al. (2006) report that the share is similarly high among the firms which have invested in South American countries (46.2 percent), but it is much lower among the firms investing in North American countries (7.1 percent) or Europe (3.7 percent). To the extent that FDI targets for natural resources or exporting platform, the negative effect on domestic labor demand arising from capital outflow is unlikely to be large. But the above survey results indicate that cheap labor has been the most important cause for capital outflow, and the resulting impact on domestic labor demand is expected to be non-trivial.6 Figure 8.4 indicates that Korea’s FDI has been increasing since the 1990s. In 1990, total FDI reached $954.3 million all over the world, among which $20.9 million, or 2.2 percent, was directed to China. In 2004, the total FDI increased to $5197.3 million, among which $2060.7 million, or 39.6 percent, was directed to China. In other words, China has risen to be one of the largest capital recipients from Korea through foreign direct investment. Figure 8.5 shows the trend of Korea’s cumulative capital stock invested in China through FDI between 1990 and 2004 estimated from the investment series shown in Figure 8.4. In the estimation, each year’s investment is converted into the 2000 price and discounted by 4.6 percent per annum, considering depreciation.7 Reflecting past FDI, the estimates have been continuously increasing, reaching 1.12 billion Korean won as of 2004 at the 2000 price. Such capital stock amounts to approximately 0.6 percent of Korea’s total domestic capital stock. The FDI into China is considered to have negatively affected Korea’s labor demand because it could have helped create new jobs if it had been invested on domestic soil. In particular, the share of investments by small or medium-sized firms in Korea’s total FDI into China increased sharply between 1998 and 2004 from 9.6 percent to 51.9 percent. Given that smaller firms in Korea are more labor-intensive, the overall effect on employment is expected to be non-trivial.

The rise of the Chinese economy and Korea’s job growth 6000

239

China World

5000 4000 3000 2000 1000 0 1990 Source:

1992

1994

1996

1998

2000

2002

2004

The Export–Import Bank of Korea.

Figure 8.4

Korea’s FDI by destination (current price, $ million)

12 10 8 6 4 2 0 1990 Source:

1992

1994

1996

1998

2000

2002

The Export–Import Bank of Korea.

Figure 8.5

Korea’s capital stock through FDI in China (2000 price, W100 million)

2004

240

8.3 8.3.1

The rise of China and structural changes in Korea and Asia

ESTIMATION OF THE EFFECTS OF CHINA ON KOREA’S LABOR DEMAND Methodology and Caveat

As mentioned before, this chapter focuses on three channels through which the rise of China may have affected Korea’s employment – goods trade, increased competition and foreign direct investment. There are undoubtedly other channels, but they are too complicated to be analyzed completely and have been left for future researches. The base model for the analysis is the trade framework of Heckscher– Ohlin–Vanek (‘HOV model’ hereafter). The HOV model deals with the long-term equilibrium in which trading partners differ in factor endowments but share the same technology. Katz and Murphy (1992) and Feenstra and Hanson (2000) similarly used the HOV framework to analyze the effects of international trade and outsourcing on the domestic labor demands in the US, and this chapter follows them. Under the HOV framework, I interpret a dollar import of a certain product as the decline in the demand for domestic factors utilized to produce the dollar amount of the product. In calculating the factor contents of imports that would have been put to use if the good were produced domestically, I consider the input–output table as in Feenstra and Hanson (2000) and Kim and Mieszkowski (2006). The analysis presented here is only a partial approach in several senses. First, the effect of increased economic trade with China is not measured in a general equilibrium framework in which these economic trades are endogenously determined. Instead, the analysis here takes the economic trade as given and converts the increase in economic trade into the effects on domestic labor demands. Consequently, the analysis here is rather silent on the underlying causes for the increased economic trade between Korea and China. Second, China and Korea are assumed to share the same technology or labor because, under the assumption, the HOV model allows a simple framework in which trade and other economic exchanges between the two countries are easily converted into the shifts in factor demands.8 The assumption is convenient as the analysis here estimates, for example, the labor inputs that would have been put to use if the imported goods had been produced domestically. This is a strong assumption, but not an unreasonable one. Although complete factor price equalization has not taken place between the two countries, the recent increase in wage inequality in Korea is regarded as having at least partly reflected the pressure for equalization. To the extent that the same technology assumption is violated, the labor demand effects are likely to be underestimated.9

The rise of the Chinese economy and Korea’s job growth

241

Third, the analysis here ignores the rest of the world and thus some potentially important indirect channels through which the increased economic trade between China and Korea may affect Korea’s domestic labor demand. For example, China’s economic growth may induce an increase in Korea’s exports to China, and also to the rest of the world, through income effects and also through the international network of production divisions. Such additional effects can be considered in a general equilibrium model of the world economy, but it is beyond the scope of the current analysis as it is not yet determined what the exogenous variables have been behind the growth of the economic trade between the two countries. Finally, as mentioned previously, what is being estimated is the potential change in labor demand derived from the increase in direct economic trade between China and Korea. The estimate in demand shift would have coincided with the actual change in employment only if labor supply were perfectly elastic in Korea. However, as labor supply is not perfectly elastic in Korea, the demand shift is likely to have affected both employment and wages. Therefore, it would be more practical to regard the estimates as the net pressure on Korea’s domestic labor demand. Based on these estimates for ‘pressures’, the potential effects on wage inequality will be considered as well. 8.3.2

Effects of Goods Trade

The effects of goods trade between China and Korea on Korea’s labor market (E1t ) can be estimated in the following manner: E1t 5 a a (Xit 2 Mit) aij j

(8.2)

i

In the above, Xit represents Korea’s exports of industry i at year t to China, and Mit represents Korea’s imports of industry i at year t from China. Thus the difference between Xit and Mit represents Korea’s net exports of industry i at year t to China. aij 5 njTRij holds where nj is the labor input per value-added in industry j and TRij is the total requirement of industry j required for a dollar delivery final demand of industry i. Consequently, aij represents the labor input required in industry j to produce intermediate inputs for a dollar delivery of final demand of industry i. If no intermediate goods are purchased from industry j for the production of industry i (TRij 5 0), aij will be zero accordingly. The information on aij is obtained from the 2000 input–output table produced by the Bank of Korea (2001). The counterfactual estimates of the annual effects of trade with China on Korea’s employment (e1t ) can be calculated as below:

242

The rise of China and structural changes in Korea and Asia

0.014 0.012 0.010 0.008 0.006 0.004 0.002 0 –0.002 –0.004 Source:

1988

1990

1992

1994

1996

1998

2000

2002

2004

UN Comtrade data set, 1988–2004; Bank of Korea.

Figure 8.6

Employment effects of the trade with China

e1t 5

E1t Nt 2 E1t

(8.3)

In the above, Nt is the actual employment at year t. Figure 8.6 shows that the effect has been positive except for in the early 1990s. In particular, the effects are estimated to be quite large in 2004, reaching 1.1 percent (or 255 000 jobs). The estimates in Figure 8.6 are the labor demand effect relative to that under no trade with China. An alternative way to consider the effect of trade with China would be the counterfactual estimate relative to when Korea’s trade with China has remained flat relative to the GDP level. Here I consider the case where the ratio of exports and imports to GDP in Korea has remained at the 1992 level, or 2.6 percent of the GDP for the exports and 1.4 percent of the GDP for the imports. The estimates indicate that if Korea’s exports and imports with China had remained at the above level, Korea’s domestic labor demand would have been lower by 0.9 percent in 2004. The overall positive effects on labor demand are attributable mainly to trade surplus. As indicated in Figure 8.7 which compares the composite labor contents between the exporting and importing industries of Korea, the importing industries are much more labor-intensive. Thus balanced trade would have resulted in a decline in labor demands. One notable point is that the labor intensity gap between the exporting and importing industries is narrowing, which appears to have also contributed to the increase in the labor demand effects in the recent years.

The rise of the Chinese economy and Korea’s job growth 20

243

Export sectors Import sectors

18 16 14 12 10 8 6 4 2 0 1991

1993

1995

1997

1999

2001

2003

Note: The composite employment coefficients measure the induced job growth in the entire economy from the delivery of final demand worth 1 billion Korean won. Source:

UN Comtrade data set, 1988–2004; Bank of Korea.

Figure 8.7

8.3.3

Composite employment coefficient of export and import sectors of Korea (men)

Effects of Increased Competition

China has also emerged as a strong competitor to Korea in the world market for many manufactured goods as mentioned before. Such increased competition is likely to have limited the exports of the Korean products to the world market, and therefore Korea’s labor demand as well. In order to estimate the effects, one needs to estimate the extent of the world market share of each Korean product taken away by the Chinese products. The following reduced form regression attempts to identify the empirical relationship between the Korean and Chinese exports of each product in the world market: XjtKorea 5 aj 1 bjzjt 1 qjt 1 ejt

(8.4)

In the above, XKorea is Korea’s export of industry j at year t measured at jt the 2000 price, and zjt is the relative market share of China and Korea in industry j at year t in the world market as previously defined in equation (8.1). An increase in zjt implies that the Chinese export of industry j has grown faster than that of Korea, and bj captures the extent of China’s encroachment on the Korean share in the world market for the industry. The time variable t is included in the regression to capture any unrelated trend to China in Korea’s exports.

244

The rise of China and structural changes in Korea and Asia

The equation is applied to 70 industries classified by the Korean Standard Industry classification Code (KSIC), respectively, and the estimated bjs are found to be negative in 53 industries.10 Among the 17 industries whose bjs are positive, only two estimates are statistically significant, implying that China and Korea compete against each other in most of the 70 industries.11 Out of the 53 industries whose bjs are negative, 31 industries are found to have statistically significant estimates. They include somewhat high-tech products such as electronic components (KSIC 321), computers and office machines (300), electric components (312), automobile parts (343) and optical instruments (333).12 The extent of Korea’s export market share taken away by China is estimated for each year at industry level, as below, based on the estimates in equation (8.4): X^ jt 5 b^ j (zjt 2 zjt21)

(8.5)

X^ jt above represents the difference between Korea’s actual and counterfactual exports in industry j at year t where the counterfactual exports are defined as the level that would have resulted if there were no change in the relative market share of China to Korea in the world market. Figure 8.8 shows the competition effect based on the estimates of (8.5) over the 1992–2004 period, where the effect (x^ t) is obtained in the following way: ^ a Xjt x^ t 5

j

Xt 2 a X^ jt

(8.6)

j

Xt is the actual export of Korea and is the sum of the lost exports to China over all industries. The effect, therefore, is the ratio of the reduced exports of Korea to the level that would have resulted if there were no increase in competition. The average effect during the 1993–2004 period is 26.9 percent. Though the time series is not sufficiently long and shows cyclical fluctuations, a simple OLS indicates that the absolute value of the effect is on an increasing trend at a rate of 0.36 percentage points per annum. The rising trend is consistent with the observation by Kang (2006) and Kim et al. (2006) that China has caught up fast with Korea in Korea’s major exporting industries such as electronics and automobile parts. The expansion of China’s exports, though it tends to take market share away from Korea, also has the effect of increasing China’s imports from Korea through two channels. First, China will import more parts and intermediate goods from Korea that are put into the production of its

The rise of the Chinese economy and Korea’s job growth

245

0 –0.02 –0.04 –0.06 –0.08 –0.10 –0.12 –0.14 –0.16 –0.18 Source:

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 UN Comtrade data set, 1992–2004.

Figure 8.8

The estimated loss of Korean exports’ market share

exports. Second, China’s higher income from its greater exports will lead to an increase in imports of consumption goods from Korea. Thus these two effects need be considered to estimate more precisely the net effect of competition. These are, however, not easily estimated because the information on the Chinese input–output tables and the income elasticity of the Chinese demands for Korea’s products is not readily available. Though not perfect, I utilize the Korean input–output table to estimate the effect by assuming that the input–output relationship is the same between Korea and China. I have not been able to find any reliable information on the income elasticity of goods demand in China, and I could not help ignoring the income effect. Given that an increase in income in China is likely to induce greater imports from Korea, ignoring the income effect will result in overestimation of the effect of competition. The induced demands for China’s imports from Korea arising from an ^ t) can be calculated in the following increased use of intermediate goods (M way under the assumption that Korea and China share the same input– output relationship: M^ t 5 2S IM X^ t

(8.7)

In the above, X^ t is the vector of the competition effects on Korea’s exports whose jth element represents industry j. IM is the import-requirement matrix whose i 2 jth element is the amount of imports of industry i’s

246

The rise of China and structural changes in Korea and Asia

0.004 0.003 0.002 0.001 0 –0.001 –0.002 –0.003 –0.004 –0.005 –0.006 –0.007

1992

Source:

UN Comtrade data set, 1988–2004; Bank of Korea.

Figure 8.9

1994

1996

1998

2000

2002

2004

Employment effects of the increased competition from China

products required to produce a dollar delivery of final goods of industry j. Finally, S is a diagonal matrix with zero off-diagonal elements. The jth diagonal element of S is the share of imports from Korea in China’s total imports of industry j’s products.13 When denoting the jth element in M^ t as m^ jt, one can calculate the labor demand effect of competition from China (E2t ) in the following: E 2t 5 a a (X^ jt 1 m^ jt) aij j

(8.8)

i

Figure 8.9 shows the labor demand effect as a fraction of total employment (e2t ) as defined below: e2t 5

E2t Nt 2 E2t

(8.9)

The effects in the figure resemble the time-series pattern of the effects on Korea’s exports previously shown in Figure 8.8. The employment effect was 20.3–20.4 percent on average during the 1992–2004 period, and its absolute value has also been on a rising trend at 0.04 percentage points per annum. Similarly as before, another counterfactual estimate can be calculated. I consider as the baseline the case where the relative market share has remained at the 1992 level while the two countries’ export volumes have grown proportionately. The actual employment in 2004 is smaller by 879 000 compared to the baseline estimate, which indicates that Korea’s

The rise of the Chinese economy and Korea’s job growth

247

aggregate domestic labor demand is suppressed in 2004 by 3.8 percentage points. This estimate is much greater than that in Figure 8.8 because it is a sort of cumulative effect. That is, the estimate represents the gap between the actual and counterfactual labor demands in Korea where the counterfactual estimate is based on the assumption that the relative market share has remained the same level in 2004 as in 1992. 8.3.4

Effects of Foreign Direct Investment

Korea’s direct investment in China has mostly been induced by lower wages in China, and thus the investment is likely to have been concentrated in labor-intensive sectors. Such capital outflow is expected to negatively affect Korea’s domestic labor demand in two ways in Korea: first, the jobs that could have been directly created if the capital had been invested domestically have not been created; and second, the demand for domestic intermediate goods that could have been induced if not for the capital outflow was not induced. These two effects, again, can be jointly estimated by using the input–output table. The labor demand effect of Korea’s direct investment in China can be estimated as in the following: E 3t 5 2 a a Y^ itaij j

`

where

Y^ it 5 yi a (1 2 d ) sKit2s (8.10)

i

s50

In the above, Kit2s is the amount of capital outflow into China at year t 2 s ` invested in industry i, and d is the depreciation rate. Thus g s50 (1 2 d) sKit2s represents the discounted stock of capital directly invested in China by the Korean firms in industry i.14 yt is the output–capital ratio of industry i and aij represents the labor input needed to produce total requirements of industry j’s output for a dollar delivery of industry i’s final demand as previously defined.15 Foreign direct investment, unlike goods trade or increased competition, has a lasting effect on employment and thus I use ` the accumulated capital stock (g s50 (1 2 d) sKit2s) instead of investment (Kit) to identify the employment effect. The percentage effect can be defined as below: e3t 5

E3t Nt 2 E3t

(8.11)

Figure 8.10 shows that, when accumulated, Korea’s FDI into China has had an increasingly negative effect on Korea’s labor demand. The increasing pattern reflects not only the ‘accumulated’ effects, but also the increasing pattern of annual FDI into China. In 1990, for example, $21 million were invested in China, suppressing the job growth in Korea

248

The rise of China and structural changes in Korea and Asia

0.001

0

–0.001

–0.002

–0.003

–0.004 1990 Source:

1992

1994

1996

1998

2000

2002

2004

UN Comtrade data set, 1988–2004; Bank of Korea.

Figure 8.10

Employment effects of FDI into China

by 0.01 percent, but the investment had risen to $2.1 billion by 2004, suppressing the job growth by 0.08 percent. This annual effect has been rising at a rate of 0.005 percentage points a year. As a result, the FDI into China during the 1990–2004 period had an accumulated effect of suppressing the labor demands by 81 000 jobs, or 0.4 percent of total employment. 8.3.5

Overall Effects and Comparison among Worker Groups

This section compares all the three effects considered in the preceding sections and decomposes the effects into those on several worker groups. First, the three effects, when put together, can be denoted as below to represent the overall effects: et 5

E1t 1 E2t 1 E3t Nt 2 E1t 2 E 2t 2 E3t

(8.12)

Figure 8.11 shows that the overall employment effects of the rise of the Chinese economy on Korea were positive during the mid-1990s and the mid-2000s. The effects were negative, however, during the early 1990s and the early 2000s. The time-series pattern of the employment effects is mostly determined by the trade and competition effects. The two main effects tend to have offset each other, but not entirely so. The positive employment

The rise of the Chinese economy and Korea’s job growth 0.015

249

Total Trade Competition FDI

0.01

0.005

0

–0.005

–0.01 1992 Source:

1994

1996

1998

2000

2002

2004

UN Comtrade data set, 1988–2004; Bank of Korea (2001).

Figure 8.11

Overall employment effects of the rise of China

effect through continued trade surplus was relatively large during the mid-1990s and the mid-2000s, when the overall effect was positive. The negative effect through increased competition was large in absolute value during the early 2000s, when the overall effect was negative. That is, when competition from China was rather weak, Korea enjoyed a large trade surplus, while the opposite was true when competition was strong. The third effect, the cumulative effect through FDI, has been steadily increasing and has become another offsetting factor of the positive effect of trade surplus. These employment effects can be decomposed into the effects on various worker groups in the following way. The effects on workers of type k through the three channels are: E1kt 5 a a (Xit 2 Mit) aijsjk j

E2kt 5 a a (X^jt 1 m^ jt) aijsjk j

(8.29)

i

(8.89)

i

E3kt 5 2 a a Y^ itaijsjk j

(8.109)

i

In the above, Sjk is the share of type k workers in total employment of industry j in Korea. Thus the above framework assumes that the employment effects are distributed among workers of various types proportionately within each industry. Then the percentage effects can be defined similarly as before:

250

The rise of China and structural changes in Korea and Asia

(A) Men 0.015 0.01 0.005 0 –0.005 –0.01 1992

1994

1996

1998

2000

(B) Women

2002

2004

Total Trade Competition FDI

0.015 0.01 0.005 0 –0.005 –0.01 1992 Source:

1994

1996

1998

2000

2002

2004

UN Comtrade Data Set, 1988–2004; Bank of Korea (2001).

Figure 8.12

Overall employment effects of the rise of China by gender ekt 5

E1kt 1 E2kt 1 E3kt Nkt 2 E 1kt 2 E2kt 2 E3kt

(8.129)

Figure 8.12 compares the effects between male and female workers. The time-series patterns are similar between men and women, and the results are not surprising because the industry-level effects are assumed to be distributed proportionately among workers. The magnitudes, however, differ somewhat. The effects of goods trade and FDI have been greater in absolute values among men, while the effects of competition are rather similar

The rise of the Chinese economy and Korea’s job growth

Table 8.2

251

Average employment effects by gender and education, 1992–2004 Men

High school

High school

High school

2-yr college

4-yr college

Total −0.004 0.001 0.002 −0.001 −0.001 Trade −0.003 0.006 0.010 0.007 0.002 Comp. 0.000 −0.003 −0.005 −0.005 −0.002 FDI −0.001 −0.002 −0.004 −0.003 −0.001

0.000 0.006 −0.005 −0.001

0.000 0.004 −0.002 −0.001

0.001 0.004 −0.002 −0.001

Source:

High school

2-yr college

Women 4-yr college

UN Comtrade Data Set, 1988–2004; Bank of Korea (2001).

among men and women. The result partly reflects that men are more likely to work in manufacturing sectors than women in Korea. However, competition with China appears to have intensified more in the sectors where women are relatively more represented. Table 8.2 compares the effects among workers defined by gender and education. For expositional simplicity, the average of each effect during the 1992–2004 period is shown in the table. When grouped by gender and education, the overall employment effects are found to be significantly negative among the least-educated men, while the effects on other groups are relatively small. The pattern masks important differences, however. The effects from trade surplus show a strong pattern of skill bias; despite trade surplus, the least-educated men in Korea have lost out in terms of labor demand. The competition effect, however, is found to be more pronounced among bettereducated men, and so is the effect of FDI. Although these two opposing effects tend to offset each other, the skill pattern still remains in the aggregate effects as the demand for the least-educated men has been suppressed.

8.4

ESTIMATED EFFECTS ON WAGE INEQUALITY

The estimated employment effects in the preceding sections measure the pressure on domestic labor demand. If labor supply is perfectly elastic among various worker types, the estimated effects will closely resemble the actual employment changes, but in reality, labor supply is nor perfectly elastic. This implies that the estimated employment (labor demand) effects are likely to show up, at least partly, in wage changes. As the estimated employment effects sometimes have a skill pattern, they are converted into relative wage effects in this section.

252

The rise of China and structural changes in Korea and Asia

The following equation is estimated for each worker group in order to identify the factor price elasticity (Hamermesh 1986) defined over worker groups. Factor price elasticity is needed to convert the relative shift in labor demands into relative wage changes: loga

K Njt Wkt b 5 ak 1 a bkjloga b 1 ekt Wt Nt j51

(8.13)

In the above, Wkt is the wage of worker type k at time t and Wt is the average wage at time t. Similarly, Nkt is the employment of worker type k at time t and Nt is the aggregate employment at time t. Eight gender and education groups are considered in the regression (four education groups for men and women), and the equation is estimated from the time series of wages obtained from the Wage Structure Survey administered by the Ministry of Labor.16 Table 8.3 reports the estimation results under homogeneity restriction. Own price elasticity is correctly signed and often significant for all educational groups among men, and for two groups among women. Given that both female employment and relative wages have been on an increasing trend, the positive estimates for own price elasticity appear to be the result of incomplete control for demand shift. Based on the estimates of factor price elasticity in Table 8.3 and the estimates of employment effects in Table 8.2, the relative wage effects are estimated in Table 8.4. During the 1995–2004 period considered in the table, the wages of the least-educated men relative to the average wages fell by 0.689 percent while those of college graduate men rose by 1.056 percent.17 Among women, the relative wages rose in all educational groups except for two-year college graduate women, reflecting the general increase in relative demand for women during the period. Two things are notable regarding the predicted wage effects in Table 8.4. First, the increased economic trade with China appears to have a skill-biased effect on relative wages among men. As indicated in the row labeled ‘total’, the predicted effects are a decline in relative wages by 0.445 percent among the least-educated men, while they are an increase in relative wages by 0.473 percent among the college graduate men. Second, the predicted changes in relative wages account for a lot of the actual changes among men. They account for 65 percent of the actual changes among the least-educated men, 11.2 percent among the high-school graduate men, and 44.6 percent among the four-year college graduate men. In sum, the increased economic trade with China appears to have a substantial skillbiased effect among men’s wages and employment. The accountability of the predicted relative wage changes for the actual changes is much weaker among women, however. The predicted changes

253

59.97 0.000

F(7, 9) Prob>F

24.92 0.000

−0.091 (0.031) −0.001 (0.075) −0.034 (0.042) 0.086+ (0.026) 0.091+ (0.032) −0.056 (0.031) 0.029 (0.031) −0.024 (0.019)

+

High school

47.24 0.000

0.039 (0.039) 0.042 (0.093) −0.071 (0.052) 0.101+ (0.032) −0.081* (0.040) 0.005 (0.051) −0.012 (0.038) −0.023 (0.024)

2-yr college

Source:

50.00 0.000

0.233 (0.081) 0.035 (0.194) 0.008 (0.108) −0.183+ (0.068) −0.264+ (0.084) 0.255+ (0.107) −0.156 (0.079) 0.073 (0.049)

+

4-yr college

210.38 0.000

−0.267 (0.112) 0.204 (0.190) −0.191* (0.107) 0.136* (0.068) 0.255+ (0.093) −0.065 (0.104) 0.023 (0.086) −0.095 * (0.049)

+

High school

Estimates from the Wage Structure Survey (1978–2004), the Ministry of Labor.

Notes: Standard errors are in the parentheses. + significant at 5 percent, *significant at 10%. Homogeniety restriction is imposed on all equations.

−0.224 (0.071) −0.082 (0.169) 0.025 (0.094) 0.147+ (0.059) 0.266+ (0.073) −0.168* (0.093) 0.090 (0.069) −0.055 (0.043)

+

High school

Men

Estimates of factor price elasticity

Men <12 Men =12 Men 2 yr col. Men 4 yr col. Women <12 Women =12 Women 2 yr col. Women 4 yr col.

Table 8.3

28.17 0.000

0.246 (0.077) −0.064 (0.130) 0.050 (0.074) 0.019 (0.047) −0.080 (0.063) −0.283+ (0.072) 0.151+ (0.059) −0.039 (0.033)

+

High school

9.95 0.000

0.674 (0.137) −0.439* (0.232) 0.327+ (0.132) −0.078 (0.083) −0.321+ (0.113) −0.086 (0.128) −0.033 (0.105) −0.042 (0.059)

+

2-yr college

Women

9.41 0.000

0.177 (0.209) −0.282 (0.353) 0.519+ (0.200) −0.547+ (0.127) 0.084 (0.172) −0.337* (0.194) 0.287* (0.160) 0.100 (0.090)

4-yr college

254

Source:

Note:

−0.689 −1.002 0.457 0.105 −0.445 64.9

−1.163 −0.349 0.194 0.026 −0.130 11.2

High school −1.092 0.144 0.054 0.060 0.258 −23.8

2-yr college 1.056 0.908 −0.324 −0.108 0.473 44.6

4-yr college 7.073 −0.854 0.394 −0.061 −0.525 −7.2

High school 1.155 1.734 −0.932 −0.014 0.772 66.4

Estimates based on Tables 8.2 and 8.3.

−5.621 3.100 −1.094 0.169 2.145 −39.2

2-yr college

Women High school

The relative wages are measured as the ratio of each group’s wage to the aggregate average wages.

Actual Trade Competition FDI Total Total/Actual (%)

High school

Men

Actual and predicted relative wage changes (1995–2004)

Relative wage changes (%)

Table 8.4

0.514 1.024 −1.405 −0.129 −0.005 −101.6

4-yr college

The rise of the Chinese economy and Korea’s job growth

255

are often in an opposite direction to the actual changes. This reflects that female wages are determined more by non-trading sector jobs such as service and retail trades where women are much more frequently found.

8.5

CLOSING REMARKS

This chapter empirically investigates the effect of increased economic trade with China on Korea’s job growth potential. Although Korea’s trade surplus from its trade with China has helped job growth in Korea except for the least-skilled men, the rapid increase in competition in the world market is likely to have reduced Korea’s job growth potential. Further, the latter effect is expected to grow in the future as China’s industrialization continues and its industrial structure becomes more similar to Korea’s manufacturing. These results suggest that the overall labor demands, or the job growth potential of Korea, are likely to be squeezed in the future, not just for unskilled workers but for skilled workers as well. The surplus from trade with China, though having positively affected Korea’s job growth, is likely to decrease as China’s industrial structure becomes similar to Korea’s. Competition is likely to intensify between the two countries in the world market, suppressing the export potential of Korea to other countries. Although the products in which China’s exports have rapidly grown (electronics and IT-related products) are not labor-intensive, the employment effect of increased competition appears to be quite large due to the spillover effects through the input–output relationship. At the same time, rising wages in Korea are also likely to accelerate Korea’s outflow of capital into China to the extent that the wage rates in China still remain attractive to the Korean producers. The considered effects on labor demand have jointly shown some degree of skill pattern in favor of better-educated workers. Given that labor supplies of variously skilled workers are not perfectly elastic, the skill pattern in labor demand effects is likely to show up in relative wage changes, at least partly. The estimates based on the factor price elasticity indicate that the skill pattern in labor demand effects arising only from the increased economic trade with China can account for up to 50 percent of the actual increase in wage inequality between college graduate men and high-school dropouts during the latter half of the 1990s and the early half of the 2000s in Korea. A caveat applies, however. The analysis in this chapter is only partial, in the following sense. The analysis here is silent on, for example, the effect of the oil price hike since 1998 that is at least partially attributable to the

256

The rise of China and structural changes in Korea and Asia

fast growth and industrialization of China. Income effects have also been ignored throughout the analysis. Further, China’s capital inflow into Korea is not taken into account either, although its magnitude has not been large.18 As China continues to grow, it is not unrealistic to assume that the FDI will grow and will have a non-trivial impact on Korea’s job growth. Despite being a partial analysis, the results bear an important implication for the Korean economy. China may have helped Korea in terms of job growth during the past few decades, but it is quite likely that China will emerge as a strong competitor in the world market rather than a trade surplus provider for Korea. Given that, it will be critical for Korea to develop comparative advantage in new products and industries in order to keep its growth engine running. At the same time, skill upgrading of the workforce is another important issue because the increasing trade with China and the rest of the world is expected to keep producing the skillbiased labor demand effects.

NOTES *

1. 2.

3. 4. 5. 6. 7. 8. 9.

An earlier version of this paper was originally prepared for the KDI publication titled Structural Changes in the Korean Economy after the Economic Crisis. The author is grateful to Inseok Shin, Gyeongjoon Yoo, Moon-Joong Tcha, Dongsuk Kim, and Dong-Chul Cho, and also to the seminar participants at Seoul National University for their helpful comments. All remaining errors are mine. The ratio was approximately 0.25 in the US and Japan. Borjas and Ramey (1994), Leamer (1994), and Wood (1995), for example, argue that international trade has strongly affected the domestic labor demands in the US resulting in an upward pressure on skill differentials. Lawrence and Slaughter (1993) offer an opposite view based on the observation that skill intensity of labor inputs has changed in a wrong direction in the US. Also there are views that trade volume is too small relative to the GDP to account for the expansion of skill differentials during the 1980s in the US. See Cline (1997) for a complete survey on the effect of trade on the skill differentials in the US. The share of IT-related products in China’s exports was below 6 percent in 1992 but grew to 24 percent by 2003 (Kim et al. 2006). The growth in trade between the two countries also reflects increased intra-industry trade and outsourcing (Kim et al., 2006). The share of exports to the US (Japan) in Korea’s total exports was 8.3 percent (4.1 percent), and that of imports from the US (Japan) in Korea’s total imports was 6.7 percent (10.6 percent) in 2004. Feenstra and Hanson (1996), for example, also report a strong negative effect on domestic labor demand in the US arising from the outsourcing from Mexico. The depreciation rate of 4.6 percent per annum is based on Pyo et al. (2005). Deardorff and Staiger (1988) show that a valid factor-contents model requires a production technology and utility function to satisfy certain conditions. It is implicitly assumed in this chapter that both are of the Cobb–Douglas type. The effects are likely to be underestimated because Korea imports labor-intensive goods while exporting capital-intensive goods in its trade with China.

The rise of the Chinese economy and Korea’s job growth 10.

11.

12. 13. 14. 15.

16. 17. 18.

257

Equation (8.4) is a time series and thus subject to autocorrelation. When tested, AR(1) process is not rejected in only four out of the 70 industries. Thus a simple ordinary least squares (OLS) is applied to the remaining 66 industries and the Cochrane–Orcutt method is applied to the four industries. One possible explanation for a positive estimate is that the products of Korea and China are complementary with each other, not necessarily competing against each other in the world market: Such a possibility arises when both countries produce parts that are used jointly in certain products. Numbers in the parentheses are the Korean Standard Industry Codes. Thus I am assuming that any increased demand for intermediate goods imports in China is proportionately distributed among the countries China imports from. As for the depreciation rate, 4.6 percent per annum is chosen following Pyo et al. (2005). The output–capital ratio is obtained from the firm data provided by Korea Information Service, Inc. The average output–capital ratio among the firms that invested in China is 0.6, which is greater than the average of all firms, 0.3. This implies that the foreign direct investment by Korea into China has been concentrated in relatively labor-intensive sectors. The survey is an annual establishment survey that covers firms with five or more regular employees in non-agricutural sectors. It carries the information on individual workers in the survey firms such as their education level and wages. The chosen as the starting year for which wage effects are considered is 1995, because it is when wage inequality started to grow in Korea’s labor market. Mah (2003) shows that the overall inflow of foreign capital into Korea during the 1975–95 period has not had a large impact on jobs and wages, but this may change in the future as the amounts of inflowing capital increases.

REFERENCES Bank of Korea (2001), The Input–Output Table 2000, Seoul: Bank of Korea Press. Borjas, George J. and Valerie A. Ramey (1994), ‘The relationship between wage inequality and international trade’, in Jeffrey H. Bergstrand (ed.), The Changing Distribution of Income in an Open US Economy, Amsterdam: North-Holland, pp. 217–41. Cline, William R. (1997), Trade and Income Distribution, Washington, DC: Institute for International Economics. Deardorff, Alan V. and Robert W. Staiger (1988), ‘An interpretation of the factor content of trade’, Journal of International Economics, 24(1), 93–107. Feenstra, Robert C. and Gordon H. Hanson (1996), ‘Globalization, outsourcing, and wage inequality’, American Economic Review, 86(2), 240–45. Feenstra, Robert C. and Gordon H. Hanson (2000), ‘Aggregation bias in the factor content of trade: evidence from US manufacturing’, American Economic Review, 90(2), 155–60. Hamermesh, Daniel S. (1986), ‘The demand for labor in the long run’, in Orley Ashenfelter and Richard Layard (eds), Handbook of Labor Economics, Vol. 1, Amsterdam: North-Holland, pp. 429–71. Kang, Doo Yong (2006), The Effect of the Rise of China on the Economic Growth of Korea, Seoul: Korea Institute for Industrial Economics and Trades (in Korean).

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Katz, Lawrence F. and Kevin Murphy (1992), ‘Changes in relative wages, 1963– 1987: supply and demand factors’, Quarterly Journal of Economics, 107(1), 35–78. Kim, Dae Il (2006), ‘The effect of increased trade with China on Korea’s labor market’ (in Korea), in Inseok Shin (ed.), Structural Changes in the Korean Economy after the Crisis, Seoul: Korea Development Institute Press, pp. 195–244. Kim, Dae Il and Peter Mieszkowski (2006), ‘The effects of international trade on the wage structure in US’, Korean Economic Journal, 45(2), 153–179. Kim, Joon-Kyung, Yangseon Kim and Chung H. Lee (2006), ‘Trade, investment and economic integration of South Korea and China’, unpublished manuscript, Korea Development Institute and University of Hawaii. Leamer, Edward E. (1994), ‘Trade, wages, and revolving door ideas’, Cambridge, MA: National Bureau of Economic Research. Lawrence, Robert Z. and Matthew J. Slaughter (1993), ‘Trade and US wages: great sucking sound or small hiccup?’, Brookings Papers on Economic Activity, 2, 161–226. Mah, Jai S. (2003), ‘A note on globalization and income distribution: the case of Korea, 1975–1995’, Journal of Asian Economics, 14, 157–164. Pyo, Hak K., Keunhee Lee and Bong-Chan Ha (2005), ‘Sources of industrial growth and productivity estimates in Korea (1984–2002)’, Journal of Korean Economic Analysis, 11(1), 109–60. Shin, Hyun Soo and Jang-Keun Nam (2004), The Analysis of Korea’s Manufacturing based on Firm Survey, Seoul: Korea Institute for Industrial Economics and Trades (in Korean). Wood, Adrian (1995), North–South Trade, Employment and Inequality: Changing Fortunes in a Skill-Driven World, New York: Oxford University Press.

PART IV

Impacts on Other Countries

9.

The rise of China and the sustained recovery of Japan* Shin-ichi Fukuda

9.1

INTRODUCTION

After the crash of the stock market in the early 1990s, the Japanese economy experienced a prolonged stagnation. The problems became especially serious in the late 1990s when several major financial institutions became insolvent. Japan’s economy recovered from the crisis in the first half of the 2000s and recorded sustained growth until October 2007. Tremendous structural changes during and after the financial crisis were one of the main driving forces for the recovery. However, dramatic increases in exports were another factor. In particular, increases in Japanese exports to China were substantial in the 2000s and supported the recovery of the Japanese economy on the demand side. An exogenous increase of exports can be a big push that raises aggregate output directly and indirectly.1 Figure 9.1 shows Japan’s exports since 1993. The amount of Japan’s monthly total exports, which had been stable at around 4 trillion yen until the end of 2001, started to show dramatic increases after 2002. These increases were accompanied by an equally dramatic rise in exports to China.2 The amount of Japan’s monthly exports to China, which was only 250 billion yen in the early 2000s, exceeded 1 trillion yen in 2007. China is about to surpass the United States as Japan’s top export destination. The starting point of these dramatic increases in exports nearly coincides with that of the sustained recovery of the Japanese economy from prolonged recessions. Figure 9.2 shows business conditions in Japan based on the Coincident Composite Index. Japan’s business cycles witnessed a trough in January 2002 and had seen continuous recovery since that time. The length of the recovery became the longest in history after World War II.3 The non-performing loan ratio, which had peaked in March 2002, dropped dramatically. Based on the definition of the Financial Reconstruction Law, the ratio of non-performing loans for all banks, which peaked at 8.4 percent in March 2002, declined to 2.5 percent in 261

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March 2007. These trends point to a link between increased exports to China and the significant recovery of the Japanese economy after 2002. The purpose of this chapter is to examine what role the exports to China played in Japan’s recovery in the 2000s. Exogenous increases in exports have positive multiplier effects on aggregate production in Japan. To the extent that the roles of Japan and China are complementary, the increased dependence on the Chinese economy has benefited Japanese firms in the 2000s. This is particularly true for Japanese firms that have intra-firm

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international trade with China. However, if the substitution effect exists, the increased dependence might not have benefited all Japanese firms. The increased role of China would have had highly heterogeneous impacts on Japanese firms, depending on the industry and firm size. In particular, China’s economic growth led to higher external demand for certain manufacturing industries with advanced technology. Significant increases were noted in exports of electric equipment, including semiconductors and other electronic parts, and high-end digital cameras, reflecting a global trend towards multifunctional and advanced computers and digital home appliances. However, China also decreased the competitiveness of other Japanese firms in several international markets. Increased imports from China overtook market shares in the domestic market. This negative impact was especially felt among labor-intensive small firms. Figure 9.3 shows the Indices of Industrial Production (IIP), Indices of Industrial Production of Small and Medium Size Enterprises (SIP), and Indices of Tertiary Industry Activity (ITA).4 All of these indexes are normalized to 100 in year 2000. The IIP shows that recovery after 2002 was strong and substantial for industry production. However, the SIP indicates that the recovery was slow and limited for small and medium-sized firms. Tertiary industry activity, which has an upward trend throughout the period, showed no conspicuous upward deviation from the trend around 2002.

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Figure 9.4

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Diffusion index of Tankan Business Survey

The slow recovery among small firms was a unique feature that had not been observed in previous recovery phases of Japanese business cycles. Figure 9.4 shows the Diffusion Index of the Short-term Economic Survey of Enterprises in Japan (TANKAN) by the Bank of Japan from 1983 to 2007. This is a quarterly survey that solicits enterprises for their opinions on general business conditions, primarily in light of their profits or business performance. Responses are aggregated into the Diffusion Index (DI).5 The DI moves procyclically and shows the booms and recessions over the business cycles. Cyclical changes had been commonly observed not only for large manufacturing firms but also for non-manufacturing firms, as well as for small firms until the late 1990s. However, the recovery of DI, which was clearly observed for large manufacturing firms, could not be observed for small firms even after 2002. In the following analysis, I explore what impacts the increased total exports had on various industries in Japan during the last 15 years. Using the method of vector autoregression (VAR), I investigate whether or not exports to China had significant impacts on production in various industries.6 The results show that Japanese industrial production, which could be explained in the form of exports to the United States until the mid-1990s, would later be more strongly linked to exports to China after the late 1990s. However, the impacts were highly heterogeneous across industries. The increased exports to China were beneficial in high-tech manufacturing sectors such as electrical machinery, precision instruments, electronics and information and communication equipment. Exports also

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had strong positive impacts on iron and steel and general machinery. However, the increase in exports had a smaller impact on other industries. These industries include not only labor-intensive industries such as textiles, pulp–paper, plastic products, and foods–tobacco, but also industries with standardized technology such as fabricated metals, non-ferrous metals, ceramics, chemicals and petroleum products. I also find that the effects were limited among small and nonmanufacturing firms. Small labor-intensive firms with less advanced technology could not compete in international markets. Nor did nonmanufacturing firms producing non-tradable goods benefit from increased external demand from China. Consequently, the sustained growth in the last several years was accompanied by widening inequalities across firms. Using industry-level data, I explore which Japanese firms gained and which firms did not from increased exports to China. There has been a growing body of literature that discusses the effects of China’s international trade (see, for example, Rodrik 2006; Feenstra and Wei forthcoming). In particular, several studies investigate the impact of the rise of China’s international trade on other Asian economies. These contributions include Ahearne et al. (2003, 2006), Eichengreen et al. (2004) and Ianchovichina and Walmsley (2005). They support the view that the effects of China’s increased international trade vary between developed and less-developed Asian countries. While Japan and the newly industrialized economies (NIEs) (Hong Kong, Korea, Singapore and Taiwan) have experienced a positive effect with the increase in exports of high quality products to China, other Association of South East Asian Nations (ASEAN) economies (Vietnam, the Philippines, Thailand, Indonesia and Malaysia) have not benefited because of the ensuing decline in the export competitiveness of labor-intensive manufacturers in these countries. My empirical results mirror the conclusions of these studies in that the increase in China’s international trade had very different effects across industries. In Japan, increases in exports to China had a large positive effect on industries producing high-quality products. But they had no significant effect on industries that produce labor-intensive products. Overall, the effect was positive in the 2000s. My results, however, contrast with those of more recent studies focusing on the impact of increased imports from China on the Japanese economy.7 To support the sustained recovery of the Japanese economy, the role of increased exports to China had been indispensable in the early 2000s. The sustained recovery in the 2000s was accompanied by widening inequalities across firms in Japan not only because of increased imports from China, but also because of increased exports to China. The chapter proceeds as follows. Section 9.2 investigates the impact of

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increased exports on aggregate manufacturing production and discusses how exports changed in the past decades. Section 9.3 compares the effects of increased exports to China on production across 16 manufacturing industries. Section 9.4 explores the impact of increased exports to China on small firms’ production, and section 9.5 examines the impact on tertiary industry activities. Section 9.6 investigates the effects of increased imports from China on aggregate manufacturing production. Section 9.7 summarizes my main results and discusses their implications.

9.2

THE IMPACTS ON AGGREGATE MANUFACTURING PRODUCTION

The purpose of the following sections is to estimate the effects of exports on production in Japan. I estimate the following vector autoregression (VAR) that consists of three macro variables: production index (Yt), price index (Pt), and the amount of exports (EXt). 4

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ΔYt 5 constant 1 a i51a1,iΔYt–i 1 a i51a2,iΔPt–i 1 a i51a3,iΔEXt–i 1 u1,t, (9.1) 4 4 4 ΔPt 5 constant 1 a i51b1,iΔYt–i 1 a i51b2,iΔPt–i 1 a i51b3,iΔEXt–i 1 u2,t, (9.2) 4 4 4 ΔEXt 5 constant 1 a i51g1,iΔYt–i 1 a i51g2,iΔPt–i 1 a i51g3,iΔEXt–i 1 u3,t, (9.3) Except for the data, I follow the standard estimation method of VAR. We use METI’s Indices of Industrial Production (IIP) for the production index, the Bank of Japan’s Corporate Goods Price Index (CGPI, the 2005 base) for the price index, and the Ministry of Finance’s Trade Statistics of Japan for the amount of exports. All of the data series are monthly. The data series for production and exports are seasonally adjusted. I use the logged difference of these variables and take four lags for all variables. Assuming that changes in exports are exogenous, the Cholesky factor dictates the order of the series to be exports, production index and price index. I first explore what different impacts the exports had on aggregate manufacturing industrial production (IIP) before and after 1995. Using the total exports, the exports to China and the exports to the United States, I estimate VARs with three variables for two alternative sample periods: January 1980 to December 1994 and January 1995 to December 2007. The former period is a period when the exports to the United States were dominant in Japan’s exports, while the latter period is a period when the exports to China increased dramatically.

The rise of China and the sustained recovery of Japan

Table 9.1

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(1) Sample: 1980M06 1994M12 Total export Export(−1) Export(−2) Export(−3) Export(−4) Adj. R-squared

0.02 [0.072] 0.124 [3.500]** −0.03 [−0.078] −0.006 [−0.181] 0.331

Export China −0.012 [−1.244] 0.009 [0.862] 0.003 [0.310] 0.003 [0.325]

Export US −0.008 [−0.378] 0.065 [2.904]** 0.018 [0.763] 0.009 [0.431]

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Export China

Export US

0.047 [1.223] 0.075 [1.917] 0.019 [0.467] 0.055 [1.430]

0.039 [3.025] 0.058 [4.037] 0.016 [1.075] 0.005 [0.349]

−0.020 [−0.875] −0.001 [−0.061] −0.009 [−0.371] 0.012 [0.541]

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Note: The estimated coefficients of the other explanatory variables are not shown in the table to economize the space.

Table 9.1 reports the estimated coefficients of the lagged exports in equation (9.1). If some of the a3,is are statistically significant, we can conclude that exports caused production based on Granger causality. When I use total exports, the estimated coefficients of exports with a two-month lag are significantly positive in both periods. These results suggest that even after taking into consideration the two months needed to diffuse the impacts, exports serve as one of the most important determinants of Japan’s business cycles throughout the two alternative periods.8 However, when I use exports to the United States, the estimated coefficients of the exports with a two-month lag were significantly positive in the former period, while none of the estimated coefficients of the exports were significant in the latter period. In contrast, when I use exports to China,

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Accumulated impulse responses on manufacturing IIP to the exports to the USA

the estimated coefficients were close to zero in the former period, while the estimated coefficients of the exports with one- and two-month lags were significantly positive in the latter period. The results suggest that exports to the United States were a determinant of Japan’s business cycles until the mid-1990s, but that their role has been replaced by exports to China since the late 1990s.

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(c) 0.008 0.007 1980–1994

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Figure 9.5 reports the accumulated impulse responses of manufacturing IIP to total exports, to exports to China, and to exports to the US based on the estimated VARs for the two alternative sample periods. When I use the exports to China, the impulse responses, which are computed for ten periods, show very different features between the two periods (Figure 9.2). The responses were close to zero and statistically insignificant for the period from January 1980 to December 1994. But they exceeded 0.006 and were statistically significant for the period from January 1995 to December 2007. The comparison of the two impulse responses clearly shows that the role of China increased dramatically in explaining Japanese business cycles during the late 1990s and the 2000s. In contrast, when I use exports to the US, the impulse responses show significantly positive responses in both periods (Figure 9.3). However, the accumulated responses are around 0.006 for the period from January 1980 to December 1994 and around 0.005 for the period from January 1995 to December 2007. In explaining Japanese business cycles, the role of the exports to the US may have declined during the late 1990s and the 2000s. Similarly, when I use total exports, the impulse responses show significantly positive responses in both periods (Figure 9.1). However, the accumulated responses are around 0.006 for the period from January 1980 to December 1994 and exceed 0.01 for the period from January 1995 to December 2007. The impulse responses in the latter period were magnified by the increased role of China in explaining Japanese business cycles after 2002.

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The rise of China and structural changes in Korea and Asia

THE IMPACTS ON INDUSTRY-LEVEL PRODUCTION

The increased dependence on the Chinese economy might have benefited several exporting sectors in Japan during the late 1990s and the 2000s, but not all Japanese firms. The increased role of China has had highly heterogeneous impacts on Japanese firms, depending on the industry. The purpose of this section is to investigate what impacts the exports to China have had on production among manufacturing industries. I investigate 16 manufacturing industries: iron and steel; non-ferrous metals; fabricated metals; ceramics, stone and clay products; general machinery; electrical machinery; transport equipment; information and communication equipment; electronics parts and devices; precision instruments; textiles; pulp–paper products; plastic products; foods–tobacco; chemicals; and petroleum products. For each of these industries, I estimate VAR with three variables: industry-level production index (Yj,t), industry-level price index (Pj,t) and the aggregate exports to China (EXt): 4

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ΔYj,t 5constant 1 a i51a1,iΔYj,t–i 1 a i51a2,iΔPj,t–i 1 a i51a3,iΔEXt–i 1 v1,t, (9.4) 4 4 4 ΔPj,t 5constant 1 a i51b1,iΔYj,t–i 1 a i51b2,iΔPj,t–i 1 a i51b3,iΔEXt–i 1 v2,t, (9.5) 4 4 4 ΔEXj,t5 constant 1 a i51c1,iΔYj,t–i 1 a i51c2,iΔPj,t–i 1 a i51c3,iΔEXt–i 1 v3,t, (9.6) where j is the index of the industry. Except for the data, the estimation method remains the same as that in the last section. The monthly data series are based on industry-level IIP for the production index and industry-level CGPI for the price index. However, aggregate exports are used for the exports to China. This is because my focus is to explore what impacts the growth of the Chinese market has had on each industry not only directly but also indirectly. The sample period is from January 1998 to December 2007.9 The data series of production and exports are seasonally adjusted. Figure 9.6 reports the accumulated impulse responses of each industry’s production to exports to China. The largest impacts were observed in general machinery, including semiconductor and flat-panel display manufacturing equipment, exceeding 0.015.10 The second-largest impacts were observed in electrical machinery and electronics, where the impulse responses exceed 0.008. The responses were also big in iron and steel, precision instruments, and information and communication equipment, where the accumulated impulse responses were around 0.006. These

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industries represent advanced technology, where Japanese firms have long enjoyed a comparative advantage in international markets. The rise of China increased external demand in these industries. However, the accumulated impulse responses were small in the other ten industries. These industries include not only labor-intensive industries such as textiles, pulp–paper products, plastic products, fabricated metals, non-ferrous metals, and foods–tobacco, but also industries with standardized technology such as ceramics, stone and clay products, chemicals, and petroleum products. Although we still observe statistically significant responses in some industries, the impacts were around 0.002 in these industries. China’s economic growth deteriorated the competitiveness of some firms in international markets. In addition, increased imports from China took over some other firms’ market shares in the domestic market. Despite sustained recovery of aggregate production, the recovery was limited in these industries with China’s growth.

9.4

THE IMPACTS ON SMALL FIRMS’ PRODUCTION

In the last section, we found that the increased role of China had highly heterogeneous impacts across industries. However, it is also likely that the impacts are heterogeneous among different-sized Japanese firms. China might have pumped up external demand for the large manufacturing industries. At the same time, however, the competitiveness of small firms in both the international and domestic markets declined. The purpose of this section is to investigate what impacts total exports to China had on the production of small Japanese firms in each manufacturing industry. As in the last section, I estimate VAR with three variables. Except when using industry-level production of small and medium-sized enterprises, the estimation method and the variables remain the same. The data for industry-level production is based on industry-level SIP, which provides the same industry classification as IIP. As in the last section, I investigate the production indexes of 16 manufacturing industries. The sample period is from January 1998 to December 2007. Figure 9.7 reports the accumulated impulse responses of small firms’ production to the total exports to China in each industry. As in Figure 9.6, the largest impacts were observed in general machinery. However, the impulse responses, which were around 0.013, are smaller than those in Figure 9.6. This implies that the exports to China had a smaller positive impact on small firms than on large firms in general machinery. The

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1

2

3

4

5

6

Figure 9.7

9

10

8

9

10

0.016 0.014 0.012 0.01 0.008 0.006 0.004 0.002 0 –0.002

–0.002

Accumulated impulse responses of small firms’ production

7

General machinery

Dotted lines denote ±s respectively.

0.02 0.018 0.016 0.014 0.012 0.01 0.008 0.006 0.004 0.002 0

-0.002

Note:

8

0 7

0 6

0.002

0.002

5

0.004

0.004

4

0.006

0.006

3

0.008

0.008

2

0.01

0.01

1

0.012

Electrical machinery

0.012

1

1

2

2

4

5

6

3

4

5

6

Precision instruments

3

Transport equipment

7

7

8

8

9

9

10

10

278

8

9

10

8

9

10

–0.002

–0.002

0 7

0 6

0.002

0.002

5

0.004

0.004

4

0.006

0.006

3

0.008

0.008

2

0.01

0.01

1

0.012

Petroleum products

–0.002

0.012

–0.002

0 7

0 6

0.002

0.002

5

0.004

0.004

4

0.006

0.006

3

0.008

0.008

2

0.01

0.01

1

0.012

Chemicals

0.012

1

1

3

4

5

6

7

8

9

2

3

4

5

6

7

8

9

Information and communication equipment

2

Electronics parts and devices

10

10

279

7

8

9

10

8

9

10

Figure 9.7

–0.002

(continued)

–0.002

0 7

0 6

0.002

0.002

5

0.004

0.004

4

0.006

0.006

3

0.008

0.008

2

0.01

0.01

1

0 –0.002

0.012

Pulp–paper

6

0.012

–0.002

5

0.002

0.002

4

0.004

0.004

3

0.006

2

0.008

0.006

1

0.01

0.01

0.008

0

0.012

Textiles

0.012

1

1

2

2

3

3

4

4

6

5

6

Food–tobacco

5

7

7

Plastic products

8

8

9

9

10

10

280

The rise of China and structural changes in Korea and Asia

second-largest impacts were observed in electrical machinery and precision instruments, where the impulse responses are close to 0.01. In contrast to general machinery, these industries had impulse responses greater than those in Figure 9.6. The responses were also big in iron and steel, electronics, and information and communication, where the accumulated impulse responses were almost similar to those in Figure 9.6. In these industries, even small firms possessed advanced technology so that China’s growth might have benefited Japanese firms regardless of firm size. As in Figure 9.6, the accumulated impulse responses were small in the other ten industries. The impulse responses are similar to those in Figure 9.6 in industries such as ceramics, stone and clay products, chemicals, and petroleum products. However, the responses are smaller than those in Figure 9.6 in industries such as fabricated metals, non-ferrous metals, textiles, pulp–paper, plastic products, and foods–tobacco. These industries are labor-intensive, thereby reducing the competitiveness of Japanese firms in both the international and the domestic market as a result of China. The smaller impacts may suggest that China did not benefit small firms in these industries.

9.5

THE EFFECTS ON TERTIARY INDUSTRY ACTIVITY

The preceding sections explored the effects of increased exports to China on manufacturing production in Japan. This analysis is significant because manufacturing production is a major part of the Japanese business cycle. However, the share of total manufacturing industry in gross domestic product (GDP) has declined to nearly 20 percent in Japan. The share of tertiary industry activity in GDP, in contrast, has exceeded 70 percent (see Table 9.2). Exploring the impacts on tertiary industry activity is critical to understanding a primary driver behind the overall business cycle in Japan. Although the effects were heterogeneous, the increased role of China increased external demand in the manufacturing industries and improved their profitability in the 2000s. However, the dramatic increase in external demand from China is perhaps less relevant to non-manufacturing firms because they produce non-tradable goods. The purpose of this section is to investigate what impacts exports to China had on tertiary industry activity and production in Japan. As in the last section, I estimate VAR with three variables. For the production index, I use either overall tertiary industry activity (TIA) or production of service industry based on METI’s Indices of Tertiary Industry Activity. For the price index, I use the total price index in the Bank of

The rise of China and the sustained recovery of Japan

Table 9.2

281

Gross domestic product classified by economic activities (at current prices) (% distribution)

Items

1996

2001

2006

1.

93.5 1.9 0.2 23.2 8.2 2.7 15.0 6.2 10.8 7.0 18.4 8.6 1.8

92.7 1.7 0.1 20.9 7.1 2.8 14.0 6.4 11.8 6.9 20.8 9.3 1.8

91.7 1.5 0.1 21.3 6.3 2.2 13.5 6.9 11.9 6.6 21.4 9.3 2.1

100.0

100.0

100.0

Industries (1) Agriculture, forestry and fishing (2) Mining (3) Manufacturing (4) Construction (5) Electricity, gas and water supply (6) Wholesale and retail trade (7) Finance and insurance (8) Real estate (9) Transport and communications (10) Service activities 2. Producers of government services 3. Producers of private non-profit services to households Gross domestic product

Notes: Year is based on calendar year. Tertiary industry activities are the sum of (4), (5), (6), (7), (8), (9) and (10).

Japan’s Corporate Services Price Index (CSPI, 2000 base). The sample period is from January 1995 to December 2007. Figure 9.8 reports the accumulated impulse responses of tertiary industry activity to exports to China. For the purpose of comparison, the figure also reports the corresponding responses of aggregate production of all manufacturing enterprises and those of small and medium-sized enterprises. The responses in small manufacturing firms are smaller than those in the manufacturing industry. However, the responses in tertiary industry activity are even smaller. These results do not change even when I use production of the service industry for the production index. This finding suggests that the exports to China had the least positive impact on non-manufacturing firms – most of which produce non-tradable goods. In Japan’s sustained recovery, dramatic increases in external demand had no significant impact on non-manufacturing firms. However, when compared with Figure 9.7, the accumulated impulse responses in tertiary industry activity are not so different from those in labor-intensive small manufacturing firms. The exports to China had the least positive impacts not only on non-manufacturing firms, but also on

282

The rise of China and structural changes in Korea and Asia

0.008 Industrial production 0.006 0.004

Small firms’ production

0.002 0

Tertiary industry activity 1

–0.002

Figure 9.8a

2

3

4

5

6

7

8

9

10

Accumulated impulse responses of TIA

0.008 Industrial production 0.006 0.004 Small firms’ production 0.002 Services

0 1

2

3

4

5

6

7

8

9

10

Note: Dotted lines denote ±s for the impulse responses to tertiary industry activity and services respectively.

Figure 9.8b

Accumulated impulse responses of services

small labor-intensive manufacturing firms during Japan’s economic recovery of the 2000s.

9.6

THE EFFECTS OF IMPORTS FROM CHINA

The preceding sections researched the impacts of increased exports from China on the Japanese economy. China’s economic growth, however, increased not only exports from Japan to China but also imports of Japan from China. The purpose of this section is to examine what impacts increased imports from China had on aggregate industrial production in Japan. I estimate the following VAR that consists of four macro variables: production index (Yt), price index (Pt), the amount of total exports to China (EXt) and the amount of total imports from China (IMt).

The rise of China and the sustained recovery of Japan

Table 9.3

283

The effects of exports to China and imports from China Dependent variable = aggregate manufacturing IIP

Explanatory var.

Export to China

Imports from China 0.015 [1.015] −0.018 [−0.857] 0.006 [0.283] 0.012 [0.833]

0.039 [3.083]** 0.052 [3.585]** 0.017 [1.156] 0.005 [−0.103]

Lag1 Lag2 Lag3 Lag4 Adj.R-squared

0.213

Note: The estimated coefficients of the other explanatory variables are not shown in the table to economize on space.

With the exception of imports from China added as an additional variable, the estimation method and the data are the same as those in section 9.2. I use the Ministry of Finance’s Trade Statistics of Japan for the amount of imports from China. All of the data series are monthly. Except for the price index, the data series are seasonally adjusted. I use the logged difference of these variables and take four lags for all variables. The sample period is from January 1995 to December 2007. Assuming that Japan’s imports are endogenously determined by income and prices, the order of the series based on the Cholesky factor is exports, production index, price index and imports from China. Table 9.3 reports the estimated coefficients of lagged exports and imports in the following equation: 4

4

4

ΔYt 5 constant 1 a i51d1,iΔYt–i 1 a i51d2,iΔPt–i 1 a i51d3,iΔEXt–i 4

1 a i51d4,iΔIMt–i 1 et,

(9.7)

If some d4,js are statistically significant, we can conclude that the imports from China led to production based on the Granger causality. Even when I include the imports from China as explanatory variables, the estimated coefficients of the exports to China are significantly positive with one- and two-month lags. However, none of the estimated coefficients of the imports from China are statistically significant. These results suggest that in contrast to exports to China, imports from China did not have significant impacts on Japan’s business cycles during the late 1990s and the 2000s.

284

The rise of China and structural changes in Korea and Asia 0.008 Exports to China

0.006 0.004 0.002 0 –0.002

Imports from China 1

2

3

4

5

6

7

8

9

10

–0.004

Note:

Dotted lines denote ±s for the impulse responses to the imports from China

Figure 9.9

Accumulated impulse response of IIP to exports to China and imports from China

Figure 9.9 reports the accumulated impulse responses of aggregate industrial production to the imports from China. For the purpose of comparison, the figure also reports the accumulated impulse responses to exports to China. It is easy to see that the responses to imports from China are much smaller than the responses to exports to China. Like the exports to China, imports from China have increased dramatically in Japan during the late 1990s and 2000s. The accumulated impulse responses, however, suggest that unlike the exports to China, the imports from China had no significant impact on aggregate manufacturing production in Japan during the late 1990s and 2000s. Increased imports from China may have negative effects on Japan’s production through substitution of production in labor-intensive industries. However, increased imports from China may benefit Japanese firms, which import cheap intermediate goods from China. This is particularly true for Japanese firms that have intra-firm international trade with China. My results imply that these positive and negative effects offset each other and have had ambiguous impacts on aggregate production in Japan in the late 1990s and 2000s.

9.7

CONCLUDING REMARKS

In this chapter, I have examined the role of Japanese exports to China in Japan’s economic recovery in the 2000s. The dependence of the Japanese export sectors on the Chinese economy has risen during the late 1990s and 2000s. The VARs show that Japanese production, which had been driven by exports to the United States until the mid-1990s, increased as a result of rising exports to China after the late 1990s. However, the effects

The rise of China and the sustained recovery of Japan

285

on production differed significantly across sectors. The increase in exports to China benefited the recovery of large firms in manufacturing industries with advanced technology. This trend also had a beneficial impact on small firms with advanced technology. Exports to China did not, however, assist in the recovery of labor-intensive small firms and those in the nonmanufacturing sectors. Consequently, the sustained growth of exports and the Japanese economy during the last several years was accompanied by widening inequalities across sectors. The results suggest that China’s growth serves as an opportunity for several large firms with advanced technology but can actually pose a threat to other Japanese firms – particularly those that are small and labor-intensive. The heterogeneous effects across firms in different industries and of different firm sizes could also be problematic in terms of income distribution. Even with regard to resource allocation, the heterogeneous effects may cause efficiency losses if sectoral adjustment costs exist. Sectoral adjustment costs actually magnify the threat that China’s economic growth presents to the Japanese economy. A policy that mitigates the adjustment costs may increase the complementarities between the Chinese economy and Japanese economy.

NOTES *

1. 2.

3.

4. 5. 6.

7. 8.

An earlier version of this chapter was presented at the KDI conference on ‘Growth and Structural Changes of the Korean Economy after the Crisis: Coping with the Rise of China’ that was held in Seoul on 21–22 July 2008. I would like to thank S. Urata and other participants for their helpful comments. There are a large number of studies that discuss the role of exports in economic growth. See, for example, Frankel and Romer (1999). Fukuda and Toya (1995) discussed the special role of exports in East Asia. The correlation between total exports and exports to China, which was 0.75 for the sample period from January 1993 to December 2001, rose to 0.98 for the period from January 2002 to December 2007. This is in comparison to the correlation between total exports and exports to the United States of 0.91 for both periods. Based on the Working Group of Indexes of Business Conditions, the ESRI (Economic and Social Research Institute), Cabinet Office of the Japanese government, which determines when a peak and a trough in business cycles occurred for the Japanese economy. It announced that the recovery continued until October 2007. The IIP and ITA are from the Ministry of Economy, Trade, and Industry (METI), while the SIP is from the Small and Medium Enterprise Agency. The DI is defined as percentage share of enterprises responding ‘favorable’ minus Percentage share of enterprises responding ‘unfavorable’. There are a number of papers that explore the determinants of Japanese business cycles by VAR. They include Bayoumi (2001), Braun and Shioji (2006), Miyao (2005), Shioji (2000) and Nakashima (2006). However, these studies did not explore the impact of exports on production. For example, see Weinstein and Broda (2008) and Kiyota (2008). The variance decomposition of the VAR shows that shocks to the total exports explain

286

9. 10.

The rise of China and structural changes in Korea and Asia 18.1 percent of ten period production variations in the former period and 14.2 percent in the latter period. I start from January 1998 because there was discontinuity in data for industry classification. Note that the unit of the vertical axis in general machinery is different from those in other industries.

REFERENCES Ahearne, Alan, John Fernald, Prakash Loungani and John Schindler (2003), ‘China and emerging Asia: comrades or competitors?’, Seoul Journal of Economics, Summer, special issue on The Post-Crisis Macroeconomic Adjustment in Asia. Ahearne, Alan G., John G. Fernald, Prakash Loungani and John W. Schindler (2006), ‘Flying geese or sitting ducks: China’s impact on the trading fortunes of other Asian economies’, Board of Governors of the Federal Reserve System, International Finance Discussion Papers no. 887. Bayoumi, Tamim (2001), ‘The morning after: explaining the slowdown in Japanese growth in the 1990s’, Journal of International Economics, 53(2), 241–59. Braun, R. Anton and Etsuro Shioji (2006), ‘Monetary policy and the term structure of interest rates in Japan’, Journal of Money, Credit, and Banking, 38(1), 141–62. Eichengreen, Barry, Yeongseop Rhee and Hui Tong (2004), ‘The impact of China on the exports of other Asian countries’, NBER Working Paper, no. 10768. Feenstra, Robert and Shiang-Jin Wei (eds) (forthcoming), China’s Growing Role in World Trade, Chicago: University of Chicago Press. Frankel, Jeffrey A. and David Romer (1999), ‘Does trade cause growth?’, American Economic Review, 89(3), 379–99. Fukuda, Shin-ichi and Hideki Toya (1995), ‘Conditional convergence in East Asian countries: the role of exports in economic growth’, in T. Ito and A.O. Krueger (eds), Growth Theories in Light of the East Asian Experience, Chicago: University of Chicago Press, pp. 247–62. Ianchovichina, Elena and Terrie Walmsley (2005), ‘Impact of China’s WTO accession on East Asia’, Contemporary Economic Policy, 23(2), 261–77. Kiyota, Kozo (2008), ‘Are US exports different from China’s exports? Evidence from Japan’s imports’, working paper. Miyao, Ryuzo (2005), ‘Use of money supply in the conduct of Japan’s monetary policy: reexamining the time series evidence’, Japanese Economics Review, 56(2), 165–87. Nakashima, Kiyotaka (2006), ‘The Bank of Japan’s operating procedures and the identification of monetary policy shocks: a reexamination using the Bernanke– Mihov approach’, Journal of the Japanese and International Economics, 20, 406–33. Rodrik, Dani (2006), ‘What’s so special about China’s exports?’, NBER Working Paper, no. 11947. Shioji, Etsuro (2000), ‘Identifying monetary policy shocks in Japan’, Journal of the Japanese and International Economies, 14, 22–42. Weinstein, David E. and Christian Broda (2008), ‘Exporting deflation? Chinese exports and Japanese prices’, NBER Working Paper, no. 13942.

10.

East Asian production networks and the rise of China* Fukunari Kimura

10.1

RISE OF CHINA AS AN INTERNATIONAL PLAYER

The growth performance of China has truly been remarkable. With its massive size, China has continuously attained 10 percent plus growth rates for years. Although some scholars predict a number of risks and challenges that China may face, the existence of vigorous economic dynamism is obvious. Furthermore, the Chinese economy has actually become increasingly open and international, though the splendid growth of China’s domestic economy often overshadows it. China’s international trade has grown much faster than its gross domestic product (GDP). In other words, in the analogy of astrophysics, the Chinese economy is not collapsing by its own gravity like a white dwarf star but is expanding its size just like a reddish giant star. We have observed the unprecedented development of international production networks in East Asia since the beginning of the 1990s, particularly in machinery industries (Ando and Kimura 2005; Kimura 2006). China has increasingly become an important participant in such networks. China is a ‘lumpy’ country (Courant and Deardorff 1992) in the sense that factor prices and location advantages across regions within the country differ widely and present a variety of comparative advantages at the same time. The lumpiness pulls down the proportion of machinery trade in China to some extent. However, the absolute magnitude of transactions in machinery industries has recently grown at an explosive pace. China has quickly become a focal point of production networks in East Asia. What would be the implications of the rise of China for Japan and Korea? Japanese and Korean companies have expanded global operations, and the fragmentation of production with China taking advantage of geographical proximity has steadily advanced. We can assess that both Japan and Korea have overall enjoyed great success, in spite of numerous 287

288

The rise of China and structural changes in Korea and Asia

failure examples, in enhancing efficiency and competitiveness through production and distribution networking with China. However, location advantages in China have recently started changing drastically. Wage hikes in the coastal area and steady evaluation of the yuan break the myth of unlimited supply of labor from inland, and losing competitiveness in labor-intensive industries seems to be being realized steadily. Reconsideration of the investment incentive scheme by the Chinese government further enhances the uneasiness of labor-intensive operations by Japanese and Korean firms. On the other hand, China has continuously tried to foster its human capital and improve its investment climate, and some of the consequences are observed in its enhanced capability for research and development (R&D) activities. In other words, China has gradually gained competitiveness in the type of industries or economic activities suitable for advanced countries. With such recent drastic changes in location advantages in China, can production and distribution networks be resilient? Can Japan and Korea retain domestic activities while extending production and distribution networks? The issue is not necessarily on the location of whole operations; production processes can be fragmented and located in both Japan/Korea and China under certain conditions. The issue is not necessarily the competition between Japan/Korea and China, either; Japanese/Korean multinationals may optimize their location patterns of production processes across national borders in order to maximize their profits rather than maximizing the national welfare of Japan/Korea. The implication of globalizing corporate activities heavily depends on the mechanics and actual functioning of production networks. Although the possibility of losing competitiveness and hollowing-out at home has long been discussed, the issue is becoming more serious and urgent than ever. This chapter discusses the impact of rising China, particularly as an important player in international production networks, on Japan and Korea. The next section provides an overview of international trade data and confirms the presence of China in international production and distribution networks. The third section reviews the mechanics of international production and distribution networks along the fragmentation theory and extracts some key elements that make production and distribution networks viable. The fourth section discusses the resilience of production and distribution networks developed by Japanese and Korean firms facing recent drastic changes in location advantages in China. The last section concludes the chapter.

East Asian production networks and the rise of China

10.2

289

THE PRESENCE OF CHINA IN PRODUCTION AND DISTRIBUTION NETWORKS

Although we observe production fragmentation in various industries such as textiles and garment, chemical industry, and software, machinery industries are by far the most important sector, both quantitatively and qualitatively, in formulating production and distribution networks. Machines typically consist of a large number of parts and components, and production processes are multilayered. Each production process requires diversified resource inputs and different technologies, and thus the most sophisticated networks are necessarily observed in machinery industries. East Asian countries host multinational enterprises with various firm nationalities, allow them to form cross-border production and distribution networks, and try to make indigenous firms and entrepreneurs penetrate into the international division of labor. Table 10.1 presents the pattern of machinery exports by East Asian countries. Countries and economies are classified into four: Japan newly industrialized economics – NIEs3 (Korea, Hong Kong and Singapore), ASEAN-4 (Malaysia, Thailand, the Philippines and Indonesia), and China. In addition to values of exports in 1990, 2001, 2003 and 2005, commodity composition, shares in total East Asian exports and annual average growth rates in nominal prices are tabulated. Machinery here includes HS84-92, that is, general machinery, electric machinery, transport equipment and precision machinery. Machinery products are further classified into machinery parts and components, and machinery finished products. The proportion of machinery exports in total exports, particularly that of machinery parts and components exports, is a good indicator for judging the degree of participation in international production and distribution networks. In the process of joining with international production and distribution networks, both exports and imports of machineries increase, though the export side changes much more drastically. Commodity composition figures in Table 10.1 vividly indicate the evolution of international production and distribution networks among East Asian countries. Japan was already a key country for machinery industries as of 1990 and maintained a very large proportion of machinery exports in total exports, that is, more than 70 percent. NIEs3 became significant players in international production and distribution networks by 2000; machinery parts and components in particular occupy a large share in total exports.1 ASEAN-4 also grew up as active players in back-and-forth transactions of machinery parts and components. And China is rapidly catching up with other East Asian countries, enhancing the proportion of machinery exports after 2001.2

290

Machinery: 77 138 parts & components Machinery: 141 421 finished products Machinery: 218 559 total All 286 947 commodities

Machinery: 43 875 parts & components Machinery: 61 532 finished products Machinery: 105 407 total All 253 116 commodities

NIEs3

1990

190 074

150 024

340 098 566 720

120 786

264 148

463 254

471 996

403 364

143 363

344 062

183 186

156 814

295 815

160 877

2003

139 002

2001

Export values (US$ million)

806 189

500 162

199 623

300 539

594 941

419 052

219 448

199 604

2005

73.3

38.9

34.5

2001

72.9

38.8

34.1

2003

Commodity composition (%)

70.4

36.9

33.6

2005

57.0

26.1

30.9

60.0

26.5

33.5

62.0

24.8

37.3

100.0 100.0 100.0 100.0

41.6

24.3

17.3

100.0 100.0 100.0 100.0

76.2

49.3

26.9

1990

Machinery exports by East Asian economies

Japan

Table 10.1

36.0

29.5

28.0

32.0

40.8

61.3

64.4

56.2

1990

33.7

33.8

31.7

35.8

29.4

37.9

41.2

34.7

2001

32.2

33.2

29.9

36.4

26.8

33.6

36.6

30.8

2003

Shares in East Asian total (%)

31.7

33.9

27.9

39.5

23.4

28.4

30.7

26.2

5.6

8.7

6.3

11.4

3.1

2.8

0.9

5.5

10.6

13.5

11.4

15.1

8.2

7.8

8.1

7.6

19.3

21.3

15.4

25.7

12.3

10.4

9.5

11.4

2005 1990– 2001– 2003– 2001 03 05

Annual average growth rates (nominal, %)

291

Machinery: parts & components Machinery: finished products Machinery: total All commodities

118 611

241 584

16 846

78 197

59 339

102 723

266 098

10 238

15 968

84 940

43 384

43 918

6293

5 685

74 693

10 553

438 228

201 032

118 878

82 154

282 327

137 682

49 012

88 670

761 953

378 816

224 112

154 704

377 954

178 245

72 387

105 858

49.1

18.2

30.9

48.8

17.4

31.4

47.2

19.2

28.0

38.6

22.3

16.3

45.9

27.1

18.7

49.7

29.4

20.3

100.0 100.0 100.0 100.0

18.8

12.1

6.7

100.0 100.0 100.0 100.0

21.5

8.0

13.5

12.1

4.5

4.7

4.1

11.1

4.7

2.9

7.7

19.4

13.1

15.6

10.8

17.6

15.2

11.5

18.7

24.9

19.7

23.7

15.7

16.0

13.5

9.8

17.0

30.0

25.7

31.3

20.3

14.9

12.1

10.1

13.9

13.5

23.0

21.5

25.3

10.8

19.4

19.3

19.5

28.3

39.9

41.5

37.6

8.1

7.7

5.6

9.0

31.9

37.3

37.3

37.2

15.7

13.8

21.5

9.3

Source:

UN Comtrade.

Note: ‘East Asia’ here includes Japan, NIEs3, ASEAN-4, and China. Due to lack of data available from UN Comtrade: (1) Taiwan is not included in East Asia; (2) data for China in 1992 and Hong Kong in 1993 are used in calculating intra-East Asian trade in 1990; (3) data for the Philippines in 1996 are used in calculating intra-East Asian trade in 1995; and (4) data for the Philippines and not included in calculating intra-East Asian trade in 1990.

China

ASEAN-4 Machinery: parts & components Machinery: finished products Machinery: total All commodities

292

The rise of China and structural changes in Korea and Asia

Export shares of each country or country group in total East Asian exports have also changed significantly since 1990. Japan’s shares in machinery exports dropped from above 60 percent in 1990 to around 30 percent in 2005. NIEs3 shares were kept at around one-third. ASEAN-4’s share reached 15 percent in 2001 though slowly declining after that. The most drastic changes are found for China; China’s share in machinery exports was merely 5 percent in 1990, grew to 13 percent in 2001, and then explosively enhanced up to 20 percent in 2003 and 26 percent in 2005. China has no doubt become one of the major players in production and distribution networks in East Asia. These changes are confirmed by annual average growth rates. Growth rates of machinery trade are considerably high in Japan, NIEs3 and ASEAN-4, compared with their growth rates of GDP. However, annual average growth rates of machinery exports by China are truly amazing; 23 percent in 1990–2001 and almost 40 percent in 2001–05. Table 10.2 presents more detailed exports data, classifying exports by destination: intra-East Asia and inter-regional, with separately tabulating exports to the US. East Asia is here defined as the sum of Japan, NIEs3, ASEAN-4 and China. As for Japan’s machinery parts and components exports, intra-East Asia exports increased their share from 28 percent in 1990 to 47 percent in 2005, indicating Japan’s deepening involvement with international production and distribution networks in East Asia. As for machinery finished products exports, inter-regional exports are continuously dominant and account for around 80 percent. A similar pattern is observed for NIEs3. Intra-East Asia ratios for machinery parts and components exports grew from 54 percent in 1990 to 68 percent in 2005 while inter-regional ratios for machinery finished products stayed around 70 percent. ASEAN-4 also presents similar changes. China has recently caught up with other East Asian countries in its trade pattern; intra-East Asia exports of machinery parts and components reached around 55 percent of total machinery parts and components exports, and inter-regional exports of machinery finished products had a 67–69 percent share in total machinery finished products exports. Table 10.3 is a more detailed table for China in 2003–06. Note that the role of Hong Kong as a destination for reshipment is still large, though it is gradually declining over time. However, a considerable portion of exports to Hong Kong are supposed to have East Asia as their final destination, particularly in the case of machinery parts and components. The relative importance of the US market as a destination of East Asian exports has steadily declined. In the case of machinery parts and components exports, the share of the US market is naturally reducing due to the development of regional production and distribution networks. What I

293 27 649 129 165 60 832 156 814 83 446 212 370 100 023 295 815 131 772 271 591 122 591 403 364

44 078 174 480 76 373 218 559

69 431 217 517 90 944 286 947

55 797 83 205 39 191 139 002

2001

22 861 118 560 49 971 141 421

21 217 55 921 26 401 77 138

1990

180 469 291 527 117 539 471 996

115 974 228 088 95 001 344 062

39 330 143 856 59 307 183 186

76 645 84 232 35 694 160 877

2003

Export values (million US$)

234 354 360 587 135 947 594 941

140 214 278 389 109 598 419 052

45 886 173 562 67 512 219 448

94 328 105 277 42 085 199 604

2005

Intra-East Asia and inter-regional exports of machineries

Japan Machinery: parts & components Intra-East Asia Inter-regional (US) Total Machinery: finished products Intra-East Asia Inter-regional (U.S.) Total Machinery: total Intra-East Asia Inter-regional (US) Total All commodities Intra-East Asia Inter-regional (US) Total

Table 10.2

24.2 75.8 31.7 100.0

20.2 79.8 34.9 100.0

16.2 83.8 35.3 100.0

27.5 72.5 34.2 100.0

1990

32.7 67.3 30.4 100.0

28.2 71.8 33.8 100.0

17.6 82.4 38.8 100.0

40.1 59.9 28.2 100.0

2001

38.2 61.8 24.9 100.0

33.7 66.3 27.6 100.0

21.5 78.5 32.4 100.0

47.6 52.4 22.2 100.0

2003

Shares by destination (%)

39.4 60.6 22.9 100.0

33.5 66.5 26.2 100.0

20.9 79.1 30.8 100.0

47.3 52.7 21.1 100.0

2005

294

1990

34 740 86 046 32 909 120 786 119 363 144 785 53 790 264 148 213 351 249 903 92 466 463 254

42 017 63 390 26 936 105 407

104 639 148 478 61 841 253 116

84 623 58 739 20 881 143 363

2001

282 712 284 008 96 642 566 720

172 447 167 651 57 576 340 098

48 111 101 913 36 329 150 024

124 336 65 738 21 247 190 074

2003

Export values (million US$)

18 499 43 033 17 336 61 532

23 518 20 357 9600 43 875

(continued)

NIEs3 Machinery: parts & components Intra-East Asia Inter-regional (US) Total Machinery: finished products Intra-East Asia Inter-regional (US) Total Machinery: total Intra-East Asia Inter-regional (US) Total All commodities Intra-East Asia Inter-regional (US) Total

Table 10.2

420 707 385 482 111 862 806 189

266 935 233 227 67 381 500 162

61 747 137 876 39 429 199 623

205 188 95 351 27 952 300 539

2005

41.3 58.7 24.4 100.0

39.9 60.1 25.6 100.0

30.1 69.9 28.2 100.0

53.6 46.4 21.9 100.0

1990

46.1 53.9 20.2 100.0

45.2 54.8 20.4 100.0

28.8 71.2 27.2 100.0

59.0 41.0 14.6 100.0

2001

49.9 50.1 17.1 100.0

50.7 49.3 16.9 100.0

32.1 67.9 24.2 100.0

65.4 34.6 11.2 100.0

2003

Shares by destination (%)

52.2 47.8 13.9 100.0

53.4 46.6 13.5 100.0

30.9 69.1 19.8 100.0

68.3 31.7 9.3 100.0

2005

295 55 848 62 763 27 110 118 611 114 181 127 404 47 819 241 584

40 548 37 649 13 594 78 197

4218 1468

China Machinery: parts & components Intra-East Asia Inter-regional 24 374 19 010

15 005 28 912 12 776 43 918

2 187 4 107 2 004 6 293

7 570 9 276 5 166 16 846

40 842 33 851 14 335 74 693

5 383 5 170 3 162 10 553

ASEAN-4 Machinery: parts & components Intra-East Asia Inter-regional (US) Total Machinery: finished products Intra-East Asia Inter-regional (US) Total Machinery: total Intra-East Asia Inter-regional (US) Total All commodities Intra-East Asia Inter-regional (US) Total

46 069 36 084

140 831 141 497 48 835 282 327

70 217 67 466 28 259 137 682

17 129 31 883 15 157 49 012

53 087 35 583 13 102 88 670

85 633 69 071

193 097 184 858 62 104 377 954

91 568 86 677 36 394 178 245

26 563 45 824 21 065 72 387

65 005 40 853 15 329 105 858

74.2 25.8

51.9 48.1 17.4 100.0

44.9 55.1 30.7 100.0

34.8 65.3 31.8 100.0

51.0 49.0 30.0 100.0

56.2 43.8

47.3 52.7 19.8 100.0

47.1 52.9 22.9 100.0

34.2 65.8 29.1 100.0

54.7 45.3 19.2 100.0

56.1 43.9

49.9 50.1 17.3 100.0

51.0 49.0 20.5 100.0

34.9 65.1 30.9 100.0

59.9 40.1 14.8 100.0

55.4 44.6

51.1 48.9 16.4 100.0

51.4 48.6 20.4 100.0

36.7 63.3 29.1 100.0

61.4 38.6 14.5 100.0

296

Source:

Note:

46 344 56 379 30 590 102 723 119 804 146 294 70 050 266 098

11 603 4366 1332 15 968

55 848 29 092 8599 84 940

Same as Table 10.1.

Please refer to notes for Table 10.1.

21 970 37 369 23 572 59 339

7385 2898 872 10 283

2001 7018 43 384

1990

182 185 256 043 92 626 438 228

85 867 115 165 45 340 201 032

39 798 79 080 32 841 118 878

12 500 82 154

2003

Export values (million US$)

460 5685

(continued)

(US) Total Machinery: finished products Intra-East Asia Inter-regional (US) Total Machinery: total Intra-East Asia Inter-regional (US) Total All commodities Intra-East Asia Inter-regional (US) Total

Table 10.2

291 663 470 290 163 180 761 953

155 904 222 912 83 751 378 816

70 271 153 841 60 905 224 112

22 846 154 704

2005

65.7 34.3 10.1 100.0

72.7 27.3 8.3 100.0

71.8 28.2 8.5 100.0

8.1 100.0

1990

45.0 55.0 26.3 100.0

45.1 54.9 29.8 100.0

37.0 63.0 39.7 100.0

16.2 100.0

2001

41.6 58.4 21.1 100.0

42.7 57.3 22.6 100.0

33.5 66.5 27.6 100.0

15.2 100.0

2003

Shares by destination (%)

38.3 61.7 21.4 100.0

41.2 58.8 22.1 100.0

31.4 68.6 27.2 100.0

14.8 100.0

2005

297

65 525 13 425 44 304 6190 33 198 4916 7796 3489 1586 1471 1250 52 264 17 732 34 532 117 790

54 317 16 001 33 881 4619 25 732

Machinery: finished products Intra-East Asia 39 798 Japan 12 876 NIEs3 23 798 Korea 2738 Hong Kong 18 659

2004

Machinery: parts & components Intra-East Asia 46 069 Japan 10 248 NIEs3 29 998 Korea 3919 Hong Kong 23 065 Singapore 3015 ASEAN-4 5823 Malaysia 2798 Thailand 1311 The Philippines 850 Indonesia 864 Intra-regional 36 084 US 12 500 Others 23 585 Total 82 154

2003

70 271 18 487 46 169 5660 35 870

85 633 16 110 59 255 7725 45 267 6263 10 267 4871 2119 1587 1689 69 071 22 846 46 224 154 704

2005

Export values (million US$)

Table 10.3 By-destination machinery exports by China

87 698 19 375 60 903 6126 47 566

107 191 18 702 75 862 10 685 56 965 8212 12 627 6301 2716 1851 1759 94 266 30 549 63 717 201 457

2006

33.5 10.8 20.0 2.3 15.7

56.1 12.5 36.5 4.8 28.1 3.7 7.1 3.4 1.6 1.0 1.1 43.9 15.2 28.7 100.0

2003

31.9 9.4 19.9 2.7 15.1

55.6 11.4 37.6 5.3 28.2 4.2 6.6 3.0 1.3 1.2 1.1 44.4 15.1 29.3 100.0

2004

31.4 8.2 20.6 2.5 16.0

55.4 10.4 38.3 5.0 29.3 4.0 6.6 3.1 1.4 1.0 1.1 44.6 14.8 29.9 100.0

2005

Shares by destination (%)

30.6 6.8 21.2 2.1 16.6

53.2 9.3 37.7 5.3 28.3 4.1 6.3 3.1 1.3 0.9 0.9 46.8 15.2 31.6 100.0

2006

298

2402 3124 1000 816 490 818 79 080 32 841 46 239 118 878

85 867 23 124 53 769 6656 41 724 5416 8947 3798 2127 1340 1682

Machinery: total Intra-East Asia Japan NIEs3 Korea Hong Kong Singapore ASEAN-4 Malaysia Thailand The Philippines Indonesia

2003

Singapore ASEAN-4 Malaysia Thailand The Philippines Indonesia Intra-regional US Others Total

Table 10.3 (continued)

119 843 29 427 78 186 10 809 58 930 8447 12 231 4930 2797 2135 2369

3531 4434 1441 1210 664 1119 115 763 47 284 68 478 170 080

2004

155 904 34 597 105 424 13 385 81 137 10 902 15 882 6732 3872 2267 3012

4639 5615 1861 1752 679 1322 153 841 60 905 92 936 224 112

2005

Export values (million US$)

194 889 38 077 136 765 16 812 104 531 15 422 20 047 8706 5082 2681 3578

7211 7420 2405 2366 830 1819 198 940 75 556 123 383 286 637

2006

42.7 11.5 26.8 3.3 20.8 2.7 4.5 1.9 1.1 0.7 0.8

2.0 2.6 0.8 0.7 0.4 0.7 66.5 27.6 38.9 100.0

2003

41.6 10.2 27.2 3.8 20.5 2.9 4.2 1.7 1.0 0.7 0.8

2.1 2.6 0.8 0.7 0.4 0.7 68.1 27.8 40.3 100.0

2004

41.2 9.1 27.8 3.5 21.4 2.9 4.2 1.8 1.0 0.6 0.8

2.1 2.5 0.8 0.8 0.3 0.6 68.6 27.2 41.5 100.0

2005

Shares by destination (%)

39.9 7.8 28.0 3.4 21.4 3.2 4.1 1.8 1.0 0.5 0.7

2.5 2.6 0.8 0.8 0.3 0.6 69.4 26.4 43.0 100.0

2006

299

Source:

239 290 73 509 141 368 27 812 100 869 12 688 24 413 8086 5802 4269 6256 354 036 125 149 228 887 593 326

168 027 65 016 103 011 287 870

291 663 8986 176 213 35 108 124 473 16 632 31 464 10 606 7819 4688 8350 470 290 163 180 307 110 761 953

222 912 83 751 139 161 378 816

353 128 91 623 223 017 44 522 155 309 23 185 34 489 13 537 9764 5738 9450 615 807 203 801 412 006 968 936

293 206 106 106 187 100 488 094

41.6 13.6 24.0 4.6 17.4 2.0 4.0 1.4 0.9 0.7 1.0 58.4 21.1 37.3 100.0

57.3 22.6 34.7 100.0

Same as Table 1.1.

‘East Asia’ here includes Japan, NIEs3, and ASEAN-4. Taiwan is not included in East Asia.

182 185 59 409 105 233 20 095 76 274 8864 17 543 6141 3828 3093 4482 256 043 92 626 163 416 438 228

All commodities Intra-East Asia Japan NIEs3 Korea Hong Kong Singapore ASEAN-4 Malaysia Thailand The Philippines Indonesia Intra-regional US Others Total

Note:

115 165 45 340 69 824 201 032

Intra-regional US Others Total

40.3 12.4 23.8 4.7 17.0 2.1 4.1 1.4 1.0 0.7 1.1 59.7 21.1 38.6 100.0

58.4 22.6 35.8 100.0

38.3 11.0 23.1 4.6 16.3 2.2 4.1 1.4 1.0 0.6 1.1 61.7 21.4 40.3 100.0

58.8 22.1 36.7 100.0

36.4 9.5 23.0 4.6 16.0 2.4 4.0 1.4 1.0 0.6 1.0 63.6 21.0 42.5 100.0

60.1 21.7 38.3 100.0

300

The rise of China and structural changes in Korea and Asia

would like to stress is that the significance of the US market is gradually dropping even for machinery finished products. The heavy dependence of East Asian economies on the US market has often been claimed in various contexts, but is steadily declining over time. This would be important information for discussing the issue of subprime loans and the possibility of decoupling.

10.3

THE MECHANICS OF PRODUCTION AND DISTRIBUTION NETWORKS

Once we admit that China is an important player in production and distribution networking in East Asia, the understanding of the mechanics of such networks becomes crucial in analyzing the implication of the rise of China. Fragmentation of production processes provides an additional degree of freedom for a corporate firm to optimize its location of production activities. To take advantage of different location advantages in different places such as Japan/Korea and China, a firm can cut out production blocks and separately place them in appropriate places. The viability of such fragmentation, however, requires a certain set of conditions; otherwise, a firm must make a location decision for the whole operation. Fragmentation accelerates the trend of globalizing corporate activities. In the globalization era, the competitiveness of Japanese/Korean firms and the strength of Japan/Korea as industrial locations do not necessarily coincide any more, so that having stronger firms does not automatically mean higher welfare of nationals. These are all related to the mechanics of international production and distribution networks. The fragmentation theory initiated by Jones and Kierzkowski (1990) and its extension neatly explain the mechanics of fragmentation in East Asia. Figure 10.1 illustrates the original idea of fragmentation. Suppose that this is an electronics company and the whole production from downstream to upstream are originally located in a developed country. If we closely look at the factory, however, it includes various production processes in terms of technologies, required factor inputs, and others. Hence, if we can separate production processes into production blocks and relocate them to remote places with different location advantages, the total production costs may be reduced. Such fragmentation of production processes becomes viable if: (1) production costs per se are saved in fragmented production blocks; and (2) the additional cost of connecting remotely located production blocks, that is, service link costs, is not prohibitively high. Condition (1) means that the larger differences in location advantages

East Asian production networks and the rise of China

301

Before fragmentation Old big factory

After fragmentation PB

SL

PB

SL

SL PB

PB SL

PB

SL PB: production block SL: service link

Figure 10.1

Fragmentation of production processes: an illustration

between two countries or regions, the more likely it is that fragmentation is viable. In this sense, China has been an ideal country as a partner to Japan and Korea in production networking. On the other hand, if the components of location advantages are converging, the benefit of fragmentation may gradually decline. In fragmentation, the ability of a firm properly separating production processes into production blocks is also important. Wage levels of unskilled labor are no doubt one of the important determinants of location choices but do not fully represent multidimensional components of location advantages. Whether a firm can cleverly cut out production blocks is crucial for taking advantage of niches in location advantages. Such decision-making by a firm is also a function of service link costs including transport costs, telecommunication costs, various coordination costs, and others. To accommodate the sophistication of production and distribution networks in East Asia, Kimura and Ando (2005) expand the concept of fragmentation into two dimensions: fragmentation in terms of geographical distance and fragmentation in terms of the disintegration of corporate activities (see Figure 10.2). The latter is particularly important in the context of East Asia, which explains the proliferation of arm’s-length (that is, interfirm) transactions including various classes of outsourcing such as subcontracting, OEM (original equipment manufacturing or original equipment manufacturer) or ODM (original design manufacturing or original design manufacturer) contracts, EMS (electronics manufacturing service) firms, foundries, and Internet auction. The development of

302

The rise of China and structural changes in Korea and Asia

Disintegration Internet auction

Competitive

Domestic arm’s length fragmentation

EMS

Cross-border arm’s length fragmentation

OEM contracts Subcontracting

Outsourcing

(Boundary of firm) Domestic intra-firm fragmentation

Original position

Source:

Cross-border intra-firm fragmentation

(National border)

Distance

Kimura and Ando (2005).

Figure 10.2

Fragmentation in a two-dimensional space

arm’s-length transactions in production and distribution networks, in addition to intra-firm transactions, is compatible with recent innovative business models in which the concentration of resources to core competences and the choice of business architecture, that is, modular versus total integration, are crucial. Furthermore, the introduction of disintegration-type fragmentation is also essential to explaining the simultaneous advancement of firm-level fragmentation and industry- or macro-level agglomeration. Arm’s-length transactions, particularly in tight just-in-time (JIT) systems, are highly sensitive to geographical distance, which generates geographical concentration of vertical arm’s-length transactions. This is one of the economic forces that accelerate the formation of industrial agglomeration. Such mechanisms are particularly important in the context of examining the relationship between Japan/Korea and China. Once industrial agglomeration starts working, it also becomes an important element of location advantages, particularly in counterbalancing wage hikes as economic development proceeds.3 Industrial agglomeration also provides ample opportunities for local firms and entrepreneurs to penetrate into production and distribution networks developed by multinationals.

East Asian production networks and the rise of China

10.4

303

IMPLICATIONS FOR JAPAN AND KOREA

Outsourcing and offshoring to developing countries is often criticized by both journalistic and academic literature in North America and Europe, on the grounds that it may end up causing a reduction of domestic employment and domestic economic activities in developed countries.4 However, such criticism or sentiment seems to be relatively weak in East Asia. East Asians intuitively know that the formation of international production and distribution networks in East Asia, particularly in the manufacturing sector, can be a source of efficiency and competitiveness for corporate firms as well as the higher welfare of nationals. Whether both developed and developing countries can gain from production networking, however, depends on the nature and characteristics of networks. In the era of globalization, corporate firms optimize the geographical placement of production and distribution processes as well as setting up the boundary of the firm by effectively utilizing outsourcing in order to maximize their profits and gain competitiveness. Firms may not ultimately be patriotic in the sense that they are not necessarily maximizing employment in their home country or retaining maximal operations at home. Hence, policy-makers in developed countries may want to take care of the proper business environment to enable multinationals to place or retain a certain amount of economic activities at home. Ando and Kimura (2007, 2008) employ firm-level panel data of Japanese firms after 1998 and statistically investigate the relationship between the expansion of activities in East Asia in terms of the number of affiliates and domestic operations. The manufacturing sector in Japan as a whole has a secular trend of reducing domestic employment over time. The regression analysis, however, finds that manufacturing firms expanding operations in East Asia are more likely to maintain or sometimes even increase domestic employment than other manufacturing firms.5 These firms tend to reduce the number of domestic establishments and affiliates relative to other firms, suggesting their successful reshuffling of domestic operations. They also intensify export and import activities, presenting a positive association between trade and foreign direct investment. These results imply that despite losing competitiveness in the manufacturing sector as a whole, firms expanding operations in East Asia tend to utilize complementarity between domestic and foreign activities and retain or expand domestic operations. This tendency seems to be even stronger in machinery industries. Fragmentation provides flexibility in the location of corporate activities. With fragmentation as a choice, a firm does not have to decide whether the whole operations should be located at home (say, in Japan

304

The rise of China and structural changes in Korea and Asia

or Korea) or abroad (say, in China). To seek efficiency and competitiveness, it can split production processes into separate production blocks and place them partially at home and partially abroad, together with systematically reshuffling operations. A large number of Japanese and Korean firms have obviously attained considerable success in Chinese operations with effective fragmentation while retaining or even generating domestic operations. Table 10.4 presents machinery exports to China by Japan and Korea, with the disaggregation of machinery parts and components into HS84 (general machinery), HS85 (electric machinery), HS86-89 (transport equipment) and HS90-92 (precision machinery). Commodity composition is similar overall for both countries, particularly in the dominance of parts and components exports. Parts and components of electric machinery occupy more than 20 percent of total exports to China by Japan and Korea. Parts and components of general machinery have a slightly larger proportion in the case of Japan than Korea, while parts and components of precision machinery present the opposite pattern. Korean exports to China are growing at a higher pace than Japanese exports to China, indicating Korea’s rapidly increasing commitment to China. However, recent changes in the Chinese economy may shake the foundation of production and distribution networks developed by Japanese and Korean firms. In particular, changes in location advantages in the coastal area of China are drastic, and firms seem to be responsive. An annual questionnaire survey for Japanese manufacturing multinationals by the Japan Bank for International Cooperation (JBIC) (JBIC Institute 2007)6 confirms that firms operating in China think less of the inexpensive labor supply or investment incentives as strong points in China than before. Wage hikes are regarded as one of the most serious issues in operating in China. China continues to be the most promising country for Japanese firms to invest in, but their interest is increasingly diversified across other parts of the world. Although a number of firms are still moving their production plants from other parts of the world to China, a considerable number of firms are now getting out of China and placing their plants in other countries. The Chinese market is also regarded as a very competitive market; the competitors for Japanese firms are not only Korean or Taiwanese firms but also Chinese indigenous firms, particularly for generic products. To be internationally competitive, Japanese firms place the enhancement of R&D capability as the first priority. What sort of production and distribution networks could be resilient against changes in location advantages, maintaining overall competitiveness and domestic operations at home? The fragmentation theory suggests three possible directions in which to go. First, to retain some economic

East Asian production networks and the rise of China

Table 10.4

Machinery exports to China by Japan and Korea Export values (million US$)

Japan Machineries: parts & components HS84 HS85 HS86-89 HS90-92 Machineries: finished products Machineries: total All commodities

Commodity composition (%)

2003

2004

2005

2006

2003

2004

2005

2006

23 068

29 140

31 824

36 924

40.2

39.4

39.7

39.8

5856 12 977 1856 2380 12 716

7679 15 644 2464 3354 15 775

8619 16 611 2675 3920 14 540

9467 20 088 3535 3834 17 089

10.2 22.6 3.2 4.1 22.1

10.4 21.2 3.3 4.5 21.3

10.8 20.7 3.3 4.9 18.2

10.2 21.7 3.8 4.1 18.4

35 784

44 915

46 365

54 013

62.3

60.7

57.9

58.2

57 415

73 939

80 074

92 770

100.0

100.0

100.0

100.0

19 899

27 798

30 175

33.7

40.0

44.9

43.4

5086 10 699 1657 2457 7064

4399 15 720 2604 5075 7450

5221 16 753 2570 5631 8437

9.7 19.5 2.5 2.0 17.7

10.2 21.5 3.3 4.9 14.2

7.1 25.4 4.2 8.2 12.0

7.5 24.1 3.7 8.1 12.1

26 963

35 248

38 612

51.4

54.2

56.9

55.6

49 763

61 915

69 456

100.0

100.0

100.0

100.0

Korea Machineries: 11 824 parts & components HS84 3413 HS85 6845 HS86-89 866 HS90-92 700 Machineries: 6208 finished products Machineries: 18 032 total All 35 110 commodities Source:

305

Same as Table 10.1.

activities in Japan or Korea, some distinctive production blocks appropriate for the location advantages of Japan and Korea must be created. Examples of such production blocks include headquarters functions, R&D laboratories, pilot plants, and capital- and human capital-intensive production processes. If the investment climate of developing countries improved and domestic activities were about to lose critical mass, firms

306

The rise of China and structural changes in Korea and Asia

should start thinking of relocating the whole operation to developing countries. To keep some operations at home, location advantages of developed countries must be strengthened for distinctive production blocks. Second, to accommodate changes in location advantages in China, various types of location advantages other than low-wage workers must be explored. In particular, effectively utilizing industrial agglomeration is necessary in order to cancel out wage hikes. As industrial agglomeration grows, both positive and negative agglomeration effects emerge. On the positive side, an economic environment desirable for arm’s-length transactions is realized. On the negative side, congestion effects take place in the form of wage hikes, shortage of human capital, traffic jams, pollution, and others. Whether positive or negative agglomeration effects dominate is crucial to firms’ decisions on maintaining their operations or not. Third, low service link costs help firms retain international production and distribution networks. Important components of service links include logistics services. In the context of production and distribution networks, logistics services must be evaluated in three dimensions: monetary fees, time costs and reliability. Logistics services in China have a lot of room for improvement, particularly on their reliability; firms operating in China still typically hold over-large amounts of parts and products inventories. How do Japanese and Korean firms meet these conditions? Japanese and Korean firms share a wide range of common characteristics, particularly in their Chinese operations. At the same time, we may point out some differences. First, although investment destinations of Korean firms are more diversified worldwide than those of Japanese firms (Chang and Delios 2006), the investment pattern in China is rather highly concentrated in Shandong and the Northeast Region (Kimura et al. 2008), utilizing low service link costs due to geographical proximity and ethnic ties. Production networks of Korean firms are in general better planned, simpler and more efficient than those of Japanese firms, which are sometimes redundantly complicated. However, Korean networks may be less resilient against changes in location advantages than Japanese networks. Second, except for extremely competitive giants in high-tech, laborintensive operations still dominate the activities of Korean multinationals in China. Benefits from industrial agglomeration are less utilized than in the case of Japanese firms. Japanese firms have made a lot of effort in the formation of a vertical division of labor in industrial agglomeration through inviting investment by small and medium-sized enterprises, and fostering local parts producers. Using positive agglomeration effects is the best way to counteract wage hikes.7 Third, strengths in location advantages at home are essential for both Japan and Korea. The Korean government has recently made courageous

East Asian production networks and the rise of China

307

efforts to strengthen its R&D basis, and here Japan can learn from Korea. On the other hand, Japan has a thicker domestic industrial base, and recently new investment in the manufacturing sector is being conducted with the aim of retaining domestic operations. Keeping domestic operations will be a continuous challenge for both countries.

10.5

CONCLUDING REMARKS

When Krugman (1994) warned of dangerous confusion between corporate firms’ international competitiveness and a nation’s ‘competitiveness’, his argument was based on the traditional comparative advantage model without international factor movements, and the US-specific fact that international trade is tiny compared with the huge domestic economy. Neither of these two starting points holds in current East Asia, due to the rise of China as a great attractor of foreign direct investment. Fragmentation provides ample flexibility in firms’ location choices. With fragmentation, it is more likely for firms to enhance their efficiency and retain some economic activities back home. Japanese and Korean firms have effectively utilized fragmentation in their Chinese operations and have successfully conducted their business. But now, they must properly respond to drastic changes in the Chinese economy and reconsider their production and distribution networks. The deep understanding of the mechanics of production and distribution networks is more important than ever. The separation of firms’ competitiveness and a nation’s location advantages has become salient; because corporate activities are more and more globalized, strong firms do not automatically mean the high welfare of nationals any more. In the current globalizing world, policy-makers must pay attention not only to the competitiveness of firms but also to the location advantages, in order to keep some economic activities at home. Such effort is particularly important when a huge, attractive country like China is nearby.

NOTES *

The author would like to thank Dr Shujiro Urata and other participants in the KDI Conference held in July 2008 for constructive comments and suggestion. The author is also grateful to Mitsuyo Ando and Ayako Obashi for data preparation. 1. Note that exports of machinery parts and components may be magnified to some extent by multilayered trade: the same parts and components may be traded again and again in production and distribution networks. Yi (2003) points out such a possibility of

308

2. 3. 4. 5.

6.

7.

The rise of China and structural changes in Korea and Asia double- or triple-counting in parts and components trade. Also note that exports by NIEs3 (ASEAN-4) include trade among NIEs3 (ASEAN-4) countries. The contrast with other parts of the world is sharp. In Latin America, only Mexico and Costa Rica participate in international production networks. Eastern European countries also present an evolutionary pattern. See Ando and Kimura (2005). The literature of new economic geography also argues positive and negative agglomeration effects. See, for example, Baldwin et al. (2003). See, for example, Samuelson (2004) and Blinder (2006). Previous literature such as Blomstrom et al. (1997), Becker et al. (2005) and Brown and Spletzer (2005) looks at whether the expansion of foreign operations by multinational enterprises reduces domestic employment or not. A novelty of our papers (Ando and Kumura 2007, 2008) is to utilize the information on multinational enterprises not expanding foreign operations and non-multinational firms as a benchmark, and examine the differences of further globalizing firms in their domestic operations. This survey covers Japanese manufacturing firms that have three or more than three foreign affiliates including at least one manufacturing affiliate. The response ratios are above 60 percent. In the FY2007 survey, firms regard China as a promising country to invest in because of the future growth potential of local market (79.8 percent), the inexpensive source of labor (50.3 percent; this ratio is quickly declining over time), the current size of the local market (30.1 percent), good supply base for assemblers (28.3 percent), and inexpensive components and raw materials (24.7 percent). On the other hand, difficulties are found in the unclear execution of the legal system (64.9 percent), insufficient protection for intellectual property rights (54.5 percent), rising labor costs (53.5 percent; this ratio is rapidly rising over time), intense competition with other companies (44.9 percent), and the unclear execution of the tax system (39.1 percent). Some of the labor-intensive plants, say in the apparel industry, run by Koreans have moved out of China and are relocated in less-developed countries such as Cambodia, motivated by wage hikes in China as well as uncertainty in trade policies. Gawon Apparel Co. Ltd in Phnom Penh is such an example (see http://panjiva.com/gawon_ apparel_co_ltd). These plants have often lost any production links with Korea. Due to rapid changes in location advantages in China, such movements may be accelerated.

REFERENCES Ando, Mitsuyo and Fukunari Kimura (2005), ‘The formation of international production and distribution networks in East Asia’, in Takatoshi Ito and Andrew K. Rose (eds), International Trade in East Asia, NBER–East Asia Seminar on Economics, Volume 14, Chicago, IL: University of Chicago Press, pp. 177–213. Ando, Mitsuyo and Fukunari Kimura (2007), ‘Can offshoring create domestic jobs? Evidence from Japanese data’, CEPR Policy Insight, 16, available at http: //www.cepr.org/pubs/PolicyInsights/CEPR_Policy_Insight_016.asp (accessed December 2007). Ando, Mitsuyo and Fukunari Kimura (2008), ‘International production/distribution networks in East Asia and domestic operations: evidence from Japanese firms’, presented at Korea and the World Economy VII Conference held in Seoul, Korea 20–21 June, available at http://www.akes.or.kr/eng/papers/ Mitsuyo Ando and Fukunari Kimura.pdf. Baldwin, Richard, Rikard Forslid, Philippe Martin, Gianmarco Ottaviano and Frederic Robert-Nicoud (2003), Economic Geography and Public Policy, Princeton, NJ: Princeton University Press. Becker, Sascha, Karoline Elholm, Robert Jackle and Marc-Andreas Muendler

East Asian production networks and the rise of China

309

(2005), ‘Location choice and employment decisions: a comparison of German and Swedish multinationals’, Weltwirtschaftliches Archiv, 141(4), 693–731. Blinder, Alan S. (2006), ‘Offshoring: the next Industrial Revolution?’, Foreign Affairs, 85(2), 113–28. Blomstrom Magnus, Gunnar Fors and Robert E. Lipsey (1997), ‘Foreign direct investment and employment: home country experience in the United States and Sweden’, Economic Journal, 107(445), 1787–97. Brown, Sharon and James Spletzer (2005), ‘Labor market dynamics associated with movement of works overseas’, presented at the November 2005 OECD conference on The Globalisation of Production. Chang, Sea-Jin and Andrew Delios (2006), ‘Competitive interactions between global competitors: the entry behavior of Korea and Japanese multinational firms’, JCER Discussion Paper No. 97 (August), available at http://www.jcer. or.jp. Courant, Paul N. and Alan V. Deardorff (1992), ‘International trade with lumpy countries’, Journal of Political Economy, 100(1), 198–210. JBIC Institute, Japan Bank for International Cooperation (2007), ‘Survey report on overseas business operations by Japanese manufacturing companies – results of JBIC FY2007 Survey’, Outlook for Japanese Foreign Direct Investment (19th Annual Survey), available at http://www.jbic.go.jp/ autocontents/english/ news/2007/000150/index.htm (accessed November 2007). Jones, R.W. and H. Kierzkowski (1990), ‘The role of services in production and international trade: a theoretical framework’, in R.W. Jones and A.O. Krueger (eds), The Political Economy of International Trade: Essays in Honor of R.E. Baldwin, Oxford: Basil Blackwell, pp. 31–48. Kimura, Fukunari (2006), ‘International production and distribution networks in East Asia: eighteen facts, mechanics, and policy implications’, Asian Economic Policy Review, 1(2), 326–44. Kimura, Fukunari and Mitsuyo Ando (2005), ‘Two-dimensional fragmentation in East Asia: conceptual framework and empirics’, International Review of Economics and Finance, 14(3), special issue on Outsourcing and Fragmentation: Blessing or Threat, edited by Henryk Kierzkowski, 317–48. Kimura, Fukunari, Kazunobu Hayakawa and Zheng Ji (2008), ‘Are Korean firms doing well? Evidence from Shadong Province in China’, Journal of the Korean Economy, 9(1), 1–26. Krugman, Paul (1994), ‘Competitiveness: a dangerous obsession’, Foreign Affairs, 73(2), 28–44. Samuelson, Paul (2004), ‘Where Richard and Mill rebut and confirm arguments of mainstream economists supporting globalization’, Journal of Economic Perspectives, 18(3), 135–46. Yi, K.-M. (2003), ‘Can vertical specialization explain the growth of world trade?’, Journal of Political Economy, 111, 52–102.

11.

The rise of China and structural change in Thailand* Kanit Sangsubhan

11.1

INTRODUCTION AND SUMMARY

The prominent role of China in the world economy has been predicted for some time. Panitchpakdi and Clifford (2002) projected a significant rise in export share of China to the world market after accession to the World Trade Organization (WTO). Twenty-five years after the expansion of China began, exports have been far-reaching in all regions (see Table 11.1), especially in export penetration to the US market, while there are trade deficits to Japan and the rest of Asia. The rise of China has changed the economic pattern in Asia as well that of the rest of the world. In order to monitor the impact of China on Thailand, it is inevitable to observe the trade relationships between Thailand and ASEAN13 (China, Japan and South Korea) which were collectively influenced by Chinese demand, production and trade. For Thailand, the rise of China has had both direct and indirect impacts on trade and production patterns. Thailand and ASEAN member countries have been members of AFTA for some time. The current intra-trade flows between Thailand and ASEAN reflect division of labor and specialization among the member countries. Moreover, before the rise of China, Japan as well as South Korea exhibited a strong trade–investment relationship with ASEAN and Thailand. Their trade–investment–production ties have been sustained for more than 30 years, long before China pursued a market-led economy. The recent rise of China, therefore, would induce changes directly to Thailand via the trade and production relationship between Thailand and China. In this light, the main impact would have come from China’s influences on changes in trade and production of ASEAN, South Korea and Japan which in turn have induced change to Thailand indirectly. In 2002, 41.4 percent of Thailand’s exports went to satisfy demand in ASEAN13. The analysis in section 11.2 shows that exports of ASEAN and Thailand moved towards ASEAN13 demand: 310

The rise of China and structural change in Thailand

Table 11.1

Bilateral trade balance between China and selected economies

Billion US$ United States European Union Japan Rest of Asia Others Total Source:

●

●

311

2000

2004

62 20 −14 −65 −3

110 49 −40 −143 −41

0

−65

UNCTAD (2008).

ASEAN’s export share to ASEAN13 increased from 48.5 percent in 2002 to 55.6 percent in 2007. While the intra-ASEAN trade expanded from 22.6 percent to 25.2 percent, the major expansion came from exports to the Plus Three (PR China, South Korea and Japan) whose share increased from 25.9 percent to 30.4 percent during the same period. Thailand’s export share to ASEAN13 increased from 41.4 percent to 45 percent during the same period.

At first glance, the production and trade of ASEAN and Thailand were biased towards intra-regional trade of the ASEAN13. However, the biasness came directly from China’s demand. ASEAN increased its export share to China from 8.1 percent in 2002 to 14.4 percent in 2007. Meanwhile, Thailand’s export share to China had increased from 5.2 percent to 9.7 percent during the same period. The same conclusion can be applied to the imports. Thailand expanded its import share from China from 7.7 percent to 11.8 percent during the same period. The trade expansion of China with Thailand came at the expense of Japan, the US and the EU, while the share of South Korea remained almost unchanged. So far, Thailand did not gain trade surplus to China, but experienced a slight trade deficit by US$ 1.4 billions in 2007. Since export to China has been on the rise, the balance of trade between China and Thailand will be sustained. The analyses indicate that Thailand has to adjust its production structure to accommodate the impacts from the rise of China. First, the production of labor-intensive manufacturing (HS 50–67), especially textiles and footwear imports, has to compete with the labor-intensive goods from China. The imports from China in these categories increased by more than 18 percent a year during 1998–2007. The impact on labor, in the case of

312

The rise of China and structural changes in Korea and Asia

Thailand, was minimal since Thailand continued to be in a labor shortage situation for years. Unemployment has been low, at the rate of 1.5 percent. On the other hand, the competition in labor-intensive production would increase efficiency in these products. The rise of the wage rate, relative to ASEAN, would not produce much gain to Thailand, but would benefit other ASEAN member countries like Cambodia and Vietnam, where their wage rates are relatively low compared to the rate in Thailand. Second, the cooperation between industries has been increased. The intermediate products and necessary base metal (HS 68–81) imported from China by the Thai industries grew at the rate of more than 45 percent during 1998–2007. Moreover, the imports of parts and components of electronics greatly increased, by more than sevenfold, during 2002 to 2007. At the same time, the Thai exports of electronics, tool machine and vehicles to China and others countries expanded as well. As a result, the rise of China has put Thailand closer with regard to its co-operation in the regional value chain of industries. The distance of transportation (gravity model) would have caused the regional bias of the trade and value chain. However, the strengthening of the relationships was enhanced by the free trade area (FTA) and the intra-firm trading of multinational corporations (MNCs). Third, there was trade creation between Thailand and China in the agricultural sector. The early harvest liberalization of HS 0-8 (edible fruits and nuts: peel of citrus fruit or melons) under the ASEAN–China FTA opened a new frontier of exchange. The rice, rubber and tropical fruits from Thailand were exchanged for cold-climate fruits from China, substituting similar products from the US, Australia and Japan. Fourth, the agricultural demand from China and the effects from becoming closer in the regional production networks have induced production changes structurally. The share of the agricultural sector in the gross domestic product (GDP) expanded from 9 percent in 2000 to 11.4 percent in 2007. Meanwhile, the manufacturing sector (food processing and other manufacturing) had not diminished but slightly expanded its share from 33.6 percent of GDP in 2000 to 34.9 percent in 2007. Fifth, there was a hypothesis that the rise of China would crowd out foreign direct investment (FDI) from ASEAN. In the case of Thailand, however, there was no such claim. The FDI to Thailand maintains its course, depending on the economic situation domestically. In fact, as Thailand has experienced surpluses in both current and capital accounts, Thailand has more savings than the ability to invest. There were no additional demands for foreign direct investment. The analyses in this chapter suggest that the rise of China produces benefits for Thailand. There are some sectors that have to adjust to new

The rise of China and structural change in Thailand

313

competition, but success depends on the adjustment mechanism that the country can provide.

11.2

TRADE PATTERNS OF ASEAN13 IN THE RISE OF CHINA

11.2.1

Intra- and Inter-Trade of ASEAN13

In East Asia, the progress of economic cooperation can be monitored from movements of ASEAN13. ‘ASEAN’ refers to ASEAN-10 which is composed of ASEAN-6 (Thailand, Malaysia, Singapore, Indonesia, the Philippines and Brunei) and the CLMV (Cambodia, Laos PDR, Myanmar and Vietnam). The ‘Plus Three’ refers to PR China, South Korea and Japan. After the burst of the dotcom bubble in 2001, the economic situation returned to normal and the trend of trade of ASEAN13 was re-established. The pattern of trade during 2002–07 can be summarized as follows (Table 11.2). Together, ASEAN13 generated intra-trade of about 36 percent and depended on outside demand for 64 percent. The ratio of intra-trade did not change much during the period of 2002 and 2007. The major change is in ASEAN, where the ASEAN intra-trade expanded from 49 percent in 2002 to 56 percent in 2007. The intra-trade of the Plus Three, however, has been relatively stable at around 28–29 percent even in the period when Chinese growth was phenomenally high. 11.2.2

Trade between ASEAN and the Plus Three

There has emerged a new pattern of trade between ASEAN and the Plus Three as follows (see also Table 11.3): ●

●

Generally, ASEAN secured intra-ASEAN exports amounting to about 25 percent of total exports, while ASEAN exports to the Plus Three market had a higher share at about 29 percent on average during 2002–07. In sum, ASEAN depended on an export demand within the ASEAN13 region of about 54 percent, compared to a 30 percent share of the US and EU markets, and 13 percent of the rest of the world, respectively. In fact, during 2000-2007, ASEAN increasingly moved its exports towards intra-trade and the Plus Three markets while reducing reliance on markets outside ASEAN13. The intra-trade share of total exports increased from 23 percent in 2002 to 25 percent in 2007. At

314

The rise of China and structural changes in Korea and Asia

Table 11.2

ASEAN+3 intra-trade (2002–07) (in US$ millions)

2002–07

ASEAN

Plus Three

ASEAN Plus Three ASEAN+3

139 293 151 364 290 656

163 060 304 008 467 068

2002–07

ASEAN

Plus Three

ASEAN Plus Three ASEAN+3

86 707 97 770 184 477

99 551 171 529 271 080

2002–07

ASEAN

Plus Three

ASEAN Plus Three ASEAN+3

189 177 220 019 409 196

228 525 430 147 658 673

Source:

Total export

Intraexport (%)

Interexport (%)

560 927 1 551 682 2 112 609

53.9% 29.3% 35.9%

46.1% 70.7% 64.1%

Total export

Intraexport (%)

Interexport (%)

383 854 905 277 1 289 131

48.5% 29.7% 35.3%

51.5% 70.3% 64.7%

ASEAN+3

Total export

Intraexport (%)

Interexport (%)

417 702 650 166 1 067 869

750 708 2 303 683 3 054 391

55.6% 28.2% 35.0%

44.4% 71.8% 65.0%

302 353 455 371 757 724 ASEAN+3

186 257 269 299 455 556

World Trade Atlas (2008).

Table 11.3 2002–07 ASEAN Plus Three 2002 ASEAN Plus Three 2007 ASEAN Plus Three Source:

ASEAN+3

Trade patterns of ASEAN and the Plus Three (2002–07) ASEAN (%)

Plus Three (%)

US & EU (%)

ROW (%)

Total (%)

24.8 9.8

29.1 19.6

30.0 37.3

16.1 33.4

100

22.6 10.8

25.9 18.9

35.0 39.9

16.5 30.3

100 100

25.2 9.6

30.4 18.7

27.4 35.8

17.0 36.0

100 100

World Trade Atlas (2008).

The rise of China and structural change in Thailand

Table 11.4

315

ASEAN export share to PRC, Korea and Japan (2002–07)

Export to:

PRC (%)

Korea (%)

Japan (%)

Total+3 (%)

2002–2007 2002 2007

12.3 8.1 14.4

4.3 4.3 4.4

12.4 13.5 11.6

29.1 25.9 30.4

Source:

●

●

●

●

World Trade Atlas (2008).

the same time, the export share to the Plus Three market moved up from 26 percent to 30 percent (see Table 11.4). It should be noted that the incremental share of ASEAN exports to the Plus Three came mainly from exports to China. The share of ASEAN exports to China increased from 8 percent to 14 percent during 2002–07, on average more than a 1 percent increase every year. As a result, ASEAN exports were quite resilient during this period as the Chinese economy was growing strongly. The Plus Three, to the contrary, did not move toward intra-trade within the Plus Three economies, as well as in ASEAN markets. The share of intra-trade in the Plus Three group was rather stable at around 18–19 percent during 2002–07, and the share to the ASEAN market was consistently around 10 percent. This might be because the size of ASEAN economy is relatively small, compared to total exports of the Plus Three. It should be noted that the export share of the Plus Three gained surprisingly in the rest of the world (ROW) markets. The share increased from 30 percent to 36 percent during 2002–07. It seems that the Plus Three moved to gain export diversification outside the major markets, and there is no evidence of ‘regional bias’ towards the ASEAN13 markets. The Plus Three’s export shares to ASEAN13; the US and the EU25; and the Row were about 30%, 37%, 33%, respectively. Perhaps the export diversification had reduced the risk of export earnings of the Plus Three economies. However, it is believed that expansion in the ASEAN market would directly benefit the Plus Three exporters due to their close proximity and the long-term relationships in Asia.

11.2.3

Intra-Trade of the Plus Three

As ASEAN gained market access to China, Japan and Korea did the same and at almost the same speed (see Table 11.5). As ASEAN gained an

316

The rise of China and structural changes in Korea and Asia

Table 11.5

Intra-trade of the Plus Three cross share on intra-export in the Plus Three

Export to

PRC (%)

Average 2002–07 PRC Korea Japan

20.2 13.3

2002 PRC Korea Japan

14.6 9.6

2007 PRC Korea Japan

22.1 15.3

Korea (%)

Japan (%)

Grand total (US$ m)

4.6

10.7 8.2

717 928 265 224 568 530

14.9 9.3

325 632 162 471 417 165

8.4 7.1

1 218 155 371 327 714 200

7.6

4.8 6.9

4.6

Source:

7.6

World Trade Atlas (2008).

incremental share of exports to China by 1 percent a year during 2002–07, the South Korean export share to China of 15 percent in 2002 increased to 22 percent in 2007 a 1.4 percent incremental share per year. Also, Japan’s export share to China increased from 9.6 percent in 2002 to 15 percent in 2007; a 1 percent of incremental share per year. Again, China became a new destination of export products from ASEAN as well as Korea and Japan. It should be noted that China reduced its share of exports to both Korea and Japan during the same period – meaning that China depends on markets outside the Plus Three region.

11.3

TRADE PATTERN OF THAILAND AND ASEAN13

Thailand’s exports between 2002 and 2007 increased by 1.4 times, or about 28 percent a year. The pattern of exports can be summarized as follows (see also Table 11.6): ●

The nominal value of exports increased in all markets but the share has increased in exports to CLMV (from 3 percent to 5 percent),

317

Source:

2002 Share 2007 Share Average 2002–07 Share

TH export to:

4.2%

11.8%

World Trade Atlas (2008).

2174 3.2% 7969 4.9% 4958

11 333 16.5% 26 910 16.5% 12 796

16.1%

13 507 19.7% 34 878 21.3% 17 394

Total ASEAN

13.2%

3544 5.2% 15 933 9.7% 14 317

PRC

0.8%

1391 2.0% 3181 1.9% 862

Korea

2.8%

9980 14.5% 19 444 11.9% 3001

Japan

16.8%

14 915 21.7% 38 558 23.6% 18 180

Total+3

Thailand’s exports by destination (2002–07) (in US$ millions)

ASEAN-6 CLMV

Table 11.6

15.3%

13 440 19.6% 20 620 12.6% 16 610

US

14.3%

10 529 15.3% 22 714 13.9% 15 448

EU

25.9%

16 203 23.6% 46 760 28.6% 28 088

ROW

100.0%

68 594 100.0% 163 529 100.0% 108 324

Grand total

318

●

●

The rise of China and structural changes in Korea and Asia

China (from 5 percent to 10 percent), and ROW (from 24 percent to 28 percent). Together they represent an 11 percent increase in export share to the so-called new markets. A reduction of export share appeared in the so-called traditional major markets (Japan from 15 percent to 12 percent, the US from 20 percent to 13 percent, and the EU from 15 percent to 14 percent). Thailand’s exports, therefore, exhibited a higher degree of ‘regional bias’, as it depended on ASEAN13 markets for around 45 percent of the total exports. If we include Thailand’s exports to other Asian nations – Hong Kong, Taiwan and South Asia (India, Pakistan, Sri Lanka, Bangladesh) – which accounted for 10.6 percent of the total exports in 2007, Thailand would depend on Asian markets by up to 51 percent.

While Thailand’s exports increased by 1.4 times, imports expanded by about 1.35 times or 27 percent a year. The pattern of imports by destination can be summarized as follows (see also Table 11.7): ●

●

●

The nominal value of exports increased in all markets but the share increased in imports from CLMV (from 2 percent to 2.8 percent), China (from 8 percent to 12 percent), and ROW (from 27 percent to 30 percent). Together they represent an 8 percent increase in import share of the so-called new markets. A reduction of import share appeared in the so-called traditional major markets (Japan from 23 percent to 21 percent, US from 10 percent to 7 percent and EU from 11 percent to 9 percent). Similar to exports, Thailand’s imports showed a higher degree of ‘regional bias’, as they depended on ASEAN13 markets by around 52 percent in 2002 and this increased to 54 percent in 2007. If we include Thailand’s exports to other Asian nations – Hong Kong, Taiwan, and South Asia (India, Pakistan, Sri Lanka and Bangladesh) – which accounted for 9.7 percent of the total imports in 2007, Thailand would depend on Asian markets by up to 64 percent, compared to 51 percent in the case of exports.

For Thailand, the rise of China means a shift of trade and production patterns that is reflected in the trade balance (see Table 11.8). First, Thailand’s imports and exports skewed towards China, reducing Thailand’s deficits in trade with the Plus Three. In 2007, Thailand reduced the trade deficit with the Plus Three by 5 percent of the total trade surplus. The deficit with the Plus Three was about 112 percent of the total trade surplus. Second, by importing more from China, especially raw materials

319

Source:

2002 Share 2007 Share Average 2002–07 Share

TH import from:

2.5%

15.4%

17.9%

10 880 17.1% 27 156 18.1% 18 629

World Trade Atlas (2008).

1 257 2.0% 4 242 2.8% 2 576

9 622 15.1% 22 914 15.3% 16 053

Total ASEAN

9.8%

4 920 7.7% 17 590 11.8% 10 255

PRC

3.8%

2 523 4.0% 5 724 3.8% 3 948

Korea

22.1%

14 877 23.4% 30 784 20.6% 23 042

Japan

35.7%

22 320 35.1% 54 098 36.1% 37 245

Total+3

US

7.7%

6 177 9.7% 10 305 6.9% 8 029

Thailand’s imports by destination (2002–07) (in US$ millions)

ASEAN-6 CLMV

Table 11.7

9.5%

7 272 11.4% 12 909 8.6% 9 876

EU

17.2%

13 449 21.1% 23 214 15.5% 17 905

Total US & EU

29.2%

17 005 26.7% 45 199 30.2% 30 465

ROW

100.0%

63 653 100.0% 149 666 100.0% 104 244

Grand total

320

Source:

2002 Share 2007 Share

916 18.5% 3727 26.9%

2627 53.2% 7723 55.7%

World Trade Atlas (2008).

1 711 34.6% 3995 28.8%

−1376 −27.9% −1657 −12.0%

PRC −1132 −22.9% −2543 −18.3%

Korea

Total+3

US

−4898 −7406 7263 −99.1% −149.9% 147.0% −11 340 −15 540 10 315 −81.8% −112.1% 74.4%

Japan

Thailand’s balance of trade (2002–07) (in US$ millions)

Trade ASEAN-6 CLMV Total balance ASEAN

Table 11.8

3257 65.9% 9805 70.7%

EU

10 520 212.9% 20 120 145.1%

Total US & EU

−802 −16.2% 1561 11.3%

ROW

4940 100.0% 13 863 100.0%

Grand total

The rise of China and structural change in Thailand

321

and finished products at low prices, Thailand managed to gain a greater trade surplus with CLMV, the EU and the rest of the world. As a result, the trade surplus continued to grow throughout the period of 2002–07. The rise of China and its current role has become a wake-up call for ASEAN, and Thailand, to adjust their strategy regarding international economic relationship for some time. Lately, the importance of China to Thailand has not only been focused on trade expansion and diversion, but has also extended to changing of trade patterns as well. At first, many people believed that China would mainly export labor-intensive manufacturing products, and import foods, energy and consumer products to serve the expansion of its domestic demand.1 However, in the late 1990s and 2000s, China has expanded production to cover a wider range of products, and ASEAN and China are now developing a complex production relationship in line with the movement of Asian production networks. In the case of Thailand, for example, the share of labor-intensive goods, especially textiles and footwear products (HS 50–67), expanded at an impressive rate of more than 18 percent a year during 1998–2007 (see Table 11.9). However, their share of total imports declined from 14 percent of total imports in 1998 to only 6 percent in 2007. Chinese exports were no longer dominated by labor-intensive goods. Meanwhile, the intermediate products and necessary base metal (HS 68–81) have moved to support production required by the Thai industries. The value of imports in the category of cement-ceramics-base metal (HS 68–81) grew at a rate of more than 45 percent and their share has increased from 10 percent to 20 percent during since 1999. This newly established pattern went far beyond predictions made in 1989. Moreover, in the detailed trade categories (HS six digits), the highest growth of imported commodities from China to Thailand during 2002 and 2007 were mainly parts and components of electronics (see Table 11.10). These 11 fast-growing commodities accounted for 15 percent of total imports from China in 2002, and expanded to 30 percent in the year 2007. By moving up the production ladder, the ‘Made in China’ products have been competing with exports previously taken by ASEAN. There has been a sign for years but, inevitably, the market forces and restructuring policies turned competition towards cooperation to reap benefits from China’s expansion. Thailand, for example, experienced a shift in export pattern with a bias towards China’s demand (see Table 11.11). First, the labor-intensive products such as textiles and footwear lost their share in exports to China, reducing from 4 percent to only 2 percent during 1998–2007. China has not required Thai labor-intensive products. Secondly, under the ASEAN and People’s Republic of China (PRC) Free Trade Agreement, Thailand took a

322

HS

Source:

8.4 52.9 1.3 100.0

9.5 53.5

1.5 100.0

Thai Customs Department (2008).

14.0

2.1

2.5 13.7

2.6 18.5

1999 (%)

2.2 17.1

1998 (%)

0.7 100.0

52.7

10.0

14.8

2.0

3.0 16.9

2000 (%)

Imports from China (% share by HS group)

Food and Beverages 00–25 Ore-Mineral-Plastic- 26–40 Rubber Leather-Wood41–49 Paper Silk-Yarn-Textiles50–67 Footware Cement-Ceramics68–81 Base Metal Tools-Machinery82–95 Vehicles Others 96–100 Total

Imports share (%)

Table 11.9

0.6 100.0

57.6

7.7

13.0

2.2

2.3 16.6

2001 (%)

0.6 100.0

63.1

7.5

10.3

1.3

2.3 14.9

2002 (%)

0.6 100.0

62.0

9.6

10.1

1.3

2.7 13.7

2003 (%)

0.5 100.0

55.9

17.5

7.8

1.5

2.4 14.4

2004 (%)

0.5 100.0

58.2

18.9

6.6

1.6

2.0 12.3

2005 (%)

0.4 100.0

59.3

17.7

6.2

1.9

2.1 12.4

2006 (%)

0.4 100.0

56.0

18.3

6.1

2.0

2.4 14.9

2007 (%)

The rise of China and structural change in Thailand

Table 11.10

Selected imports from China (% share by HS six digits)

HS 6 digits

Description

847330

Parts & Accessories for Adp 415 Machines & Units Telephones for Cellular Networks 0 or for other Wireless Networks Portable Digital Automatic Data 14 Process Machines, not > 10 kg Silver, Semimanufactured 35 Pts, ex Antenna, for Trnsmssn, 30 Rdr, Radio, TV, etc Nesoi Articles of Iron or Steel Nesoi 40 Magnetic Media, O/T Cards 0 incorporating a Magnetic stripe Printed Circuits 31 Bars, Rodshot-Roll, Iron or Non6 Alloy Steel Coil Circ., <14mm Nesoi Eic Procsr & Cntlr, W/N combined 0 with Memories, Converters etc. Elect Appr f Prtct to Elect Circt 24 Nov 1000 V Nesoi

851712 847130 710692 852990 732690 852329 853400 721391

854231 853690

Total value (US$ m) Share to total imports Source:

323

Jan.–Dec. Jan.–Dec. Jan.–Dec. Jan.–Dec. 2002 2004 2006 2007

719 14.6%

694

1199

1443

0

0

726

90

312

447

150 58

227 255

319 285

97 0

176 0

264 255

72 44

145 120

216 192

0

0

120

45

81

115

1747 21.4%

3242 238%

5253 29.9%

Thai Customs Department (2008).

chance to exercise the early harvest package designated agricultural products of HS 0–8. As a result, trade values under the package (0–8 digits) between Thailand and PRC expanded at more than 30 percent a year during 2002– 07, and the share has been relatively stable albeit with tough competition in the agricultural markets. Combined HS 0–8 with rubber (HS40), which in the case of Thailand means natural rubber, the share of total exports to China was stable at around 20–22 percent during the late 1990s and 2000s. It is worth noting that there were three areas of development in this respect. First, the intra-trade expansion experienced in the HS 0–8 digits revealed cooperation rather than competition (see Table 11.12). Rice, rubber and tropical fruits were exchanged for cold-climate fruits such as apples and peaches from China, instituting imports from the US, Australia and Japan.

324

Source:

Total

2.2 41.1 11.0

68–81

82–95

96–100

Thai Customs Department (2008).

100

4.7

23.5 9.8 13.7 3.7

1988 (%)

50–67

00–25 40 26–39 41–49

HS

100

8.1

37.9

2.7

4.7

17.4 4.4 22.0 7.1

1999 (%)

100

12.3

36.9

4.0

4.0

10.0 116 27.3 5.5

2000 (%)

100

11.5

37.4

3.5

3.4

14.1 10.5 23.7 6.5

2001 (%)

Thailand’s exports to China (% share by HS group)

Food and Beverages Rubber Ore-Mineral-Plastic Leather-WoodPaper Silk-Yarn-TextilesFootware Cement-Ceramicsbased metal Tools-MachineryVehicles Others

Table 11.11

100

12.0

35.6

4.8

3.5

10.2 11.0 27.2 6.8

2002 (%)

100

14.3

39.1

5.2

3.2

7.7 13.7 24.8 5.7

2003 (%)

100

12.9

40.8

3.6

3.9

9.7 12.6 24.0 5.1

2004 (%)

100

11.0

44.5

4.4

3.2

8.5 10.7 24.2 4.0

2005 (%)

100

14.7

39.7

2.7

2.3

9.3 14.5 27.5 3.9

2006 (%)

100

13.8

45.0

2.8

1.9

7.1 13.7 25.7 3.6

2007 (%)

The rise of China and structural change in Thailand

Table 11.12

Thailand’s exports to China (HS 01–08)

HS

Description

01 02 03 04

Live Animals 3 Meat 9 Fish And Seafood 34 Dairy, Eggs, 1 Honey, Etc Other of Animal 1 Origin Live Trees And 1 Plants Vegetables 103 Edible Fruit And 34 Nuts

05 06 07 08

Sum of HS0 to HS8 Growth rate Share to total exports Source:

325

Jan.– Dec. 2002

Jan.– Dec. 2003

Jan.– Dec. 2004

Jan.– Dec. 2005

Jan.– Dec. 2006

Jan.– Dec. 2007

3 15 41 1

2 1 49 1

1 0 53 1

2 0 60 1

1 0 114 2

1

1

1

1

3

2

3

3

5

8

129 69

213 73

296 99

418 99

371 139

189

261

342

454

586

638

1.3 5.3%

39.9 4.6%

30.8 4.8%

32.7 5.0%

29.1 5.0%

8.9 4.0%

Thai Customs Department (2008).

Second, complaints that Chinese products crowded out the domestic production were offset by the restructuring program and help from the Free Trade Adjustment Fund. It should be noted that the most politically sensitive complaint of injury from the FTA with China were made by the poor farmers of red onions and garlic. The data showed that before the FTA the imported prices plus tariffs of both products were much lower than the domestic price. The FTA, therefore, is not the main culprit of lost competitiveness. Moreover, the FTA with quota and tariffication made imports more transparent with a protection system. However, the adjustment process came late and has been relatively ineffective, so the injuries were healed in time and brought about opposition to the FTA in general. Third, the non-tariff barrier (NTB) does exist when exporters trade with China due to provincial specific rules and regulations that many exporters have to deal with separately, while Chinese products were rather free with a single set of regulations at ports and at the provincial level. From the experiences of Thailand, the crucial domestic measure is to

326

The rise of China and structural changes in Korea and Asia

have an effective restructuring program that can heal the injury from existing and future competitive products from China. In the meantime, the restructuring program would mean producing value-added exports to serve needs in China. China at the same time has to unify its rules and regulations, which will help to reduce unintended NTBs.

11.4

FREE TRADE AGREEMENTS BETWEEN THAILAND AND THE PLUS THREE

11.4.1

AFTA and AEC

It is not an exaggeration to say that the ASEAN Free Trade Area (AFTA) was the ASEAN’s first response to the rise of China. In 1992, the leaders of ASEAN knew that China would become a key competitor, in intra- and inter-trade of ASEAN, as well as competing with ASEAN in receiving FDI. At that time, ASEAN generally perceived that China would probably be a new market for ASEAN exports as well. The AFTA, then, was aimed at reducing the tariffs in the region so that collectively the market size and mobilization of resources would draw the attention of FDI and make ASEAN products more competitive. The major argument at that time was that ASEAN nations produced similar products and were prone to compete rather than to cooperate. This was proved to be wrong. In fact, the AFTA has successfully led the ASEAN intra-trade to expand. For example, in the case of Thailand, the total trade (exports plus imports) to ASEAN increased from 17 percent in 1995 to 20 percent in 2007, and ASEAN became the largest trading partner of Thailand. In terms of FDI, Thailand as well as other ASEAN members did not run short of FDI and between 2003 and 2008 ASEAN experienced a surge of capital inflows, as current account surplus and portfolio investment. During this time, ASEAN seemed to have relatively low levels of investment, both individually and regionally (the exception might be in the case of Vietnam). However, in order to stay competitive in the globalizing world and in face of the rise of China, ASEAN needs to move further on restructuring and integrating. The ASEAN Economic Community (AEC) therefore represents the reaction towards global competition and maintaining balance of trade and investment in face of the rise of China. Under the AEC, ASEAN has agreed to extend cooperation towards a ‘single market’. The ASEAN summit meeting in Bali (7 October 2003) delivered the Declaration of ASEAN Concord II (or Bali Accord II) which integrates the AEC as one of three pillars of the ASEAN Community – adding to the

The rise of China and structural change in Thailand

327

existing Political and Security Pillar, and Socio-Culture Pillar. The major guidelines of the AEC are as follows: ● ●

●

The process of the AEC will be completed by 2015 (faster than the year 2020 agreed previously). The AEC’s principle is based on the concept of a single market and single production base which includes liberalization of goods, services, investment, capital and skilled labor. The liberalization will be speeded up by focusing on implementation in 11 sectors: tourism, air transport, agriculture, fisheries, automobiles, wood products, rubber, garments, electronics, information technology (IT), and healthcare business. The roadmap of 11 priority sectors was agreed.

11.4.2

ASEAN FTA with China (ACFTA)

At the Annual Summit in Bandar Seri Begawan on 6 November 2001, a closer trade relation between ASEAN and China began wherein both parties decided to undertake an unprecedented initiative aimed at establishing a bilateral free trade area in 2010. The Framework Agreement on Comprehensive Economic Cooperation was signed on 4 November 2002. The Framework Agreement served as the fulcrum for establishing the free trade area (FTA) by 2010 for the ASEAN-6 and 2015 for CLMV. The framework contained normal tariff reduction of goods and early harvest. Thailand pursued the early harvest of agricultural products under HS 01–08 and specific products (anthracite, coke and semi-coke of coal). The Framework also included trade in services sectors and investments for which the negotiations commenced in 2003. Since then, the agreements are still in the process of being drafted, with the principle of a positive list approach under the General Agreement on Trade in Services (GATS) (see details in Appendix 11.2). Generally, assessment of the ACFTA for Thailand anticipates that the agreement will create positive impacts on the Thai economy (GDP increases by 0.38 percent) and Thai consumers by providing a greater variety of products. It also indicates that the ACFTA will provide benefits to the Thai economy in various sectors such as rice, vegetables (cassava), tropical fruits, sugar, chemical products, rubber and related products, plastics, electronics, machinery, automotive and parts. On the other hand, the analysis estimates that various sectors will be negatively affected by this agreement: vegetables (onions, garlic, potatoes and tea), meat products, cement, fabrics and textiles, leather products, granite and ceramics.

328

11.4.3

The rise of China and structural changes in Korea and Asia

ASEAN FTA with Korea (AKFTA)

Assessments of the AKFTA for the Thai economy, quantitatively using the Global Trade Analysis Project (GTAP) model and qualitatively using competitiveness analysis and SWOT (strength, weakness, opportunities, threats) analysis by industry, reveal the conclusion that the AKFTA provides benefits in inducing investment and domestic demand expansion. Electronics, food products, machinery and equipment would gain direct positive impacts from the agreement. Some industry, plastic products, however, may have negative impacts from competition from Korea and ASEAN. In the short run, Thai industry has to understand the implications and benefits from the Rules of Origin (ROO) to create networks in ASEAN. The new ROO will lead the way for Thai industry to move into the ASEAN Production Network which is the key mechanism towards the ASEAN Single Market Economy. In this light, the movement will escalate ASEAN industries to a better competitive position in production from other regions. To be able to generate benefits from the network, the Thai agencies should give priority to technology improvement and to reducing tax abnormalities in the value chain. The analysis so far leads to a conclusion that the AKFTA provides a win–win situation for Thailand, ASEAN and Korea in terms of trade creation and the possibility of strengthening the production network in ASEAN. Turning to the service sectors, Thai industry may face intense competition from Korea. The government thus should be clear on which industries need to be liberalized in order to gain economic benefits from the FTA, and on the contrary, which industries rather need a gradual liberalization approach since they have a low ability to compete, or else for prudential reasons. Meanwhile, the AKFTA will increase the number of Korean companies investing in Thailand, which will create the benefits for consumers and for the Thai companies. In this regard, having strategic partners or Korean joint ventures can help build know-how and bring technological improvements to the real sector such as electronics, consumer products, telecommunication, IT, multi-media and entertainments. According to the ability of the Thai firms, the assessments also point out that Thailand will not be negatively affected by the AKFTA in other services sectors except financial services sectors, that is, tourism, hotel lodging services and health services sectors. Concerning the domestic laws and regulations, it should be noted that the proposed reforms of the Foreign Business Act may change the regulatory and business environment envisaged under the AKFTA.

The rise of China and structural change in Thailand

11.4.4

329

Japan–Thailand Economic Partnership Agreement (JTEPA)

The official negotiation of the JTEPA began in February 2004. It took three years of negotiation to launch the agreement officially in November 2007. According to the agreement, both sides will work quickly but allow for a period of adjustment: ●

●

●

●

Normal products from which tariffs will immediately be eliminated covered more than 90 percent for Japan but the tariff reduction in this group will be approximately around half of the total categories including shrimp, energy and fuel, and textiles. Normal products from which tariffs will be eliminated in five years include fisheries and chemicals on the Japanese side; and include vegetables, fruits, sugar, minerals, and electronics. Sensitive products from which tariffs will be eliminated in ten years include tea and coffee on the Japanese side; livestock, grains, hot rolling iron plate and automobile parts on the Thai side. Highly sensitive products from which tariffs will be eliminated in 15–20 years include chicken meat, pineapples, sugar and cane on the Japanese side; and all agricultural products under the World Trade Organization (WTO) on the Thai side.

The assessment of the JTEPA can be summarized as follows: ● ●

In general, Thailand will clearly gain from the JTEPA in terms of trade balance and welfare. At the sectoral level, the first four Thai industrial sectors that will be negatively affected by JTEPA are transportation equipment and parts (declining by 29 percent), mining (−8.2 percent), metal (−4.6 percent), chemicals (−2.7 percent). The industrial sectors that will gain positively are food processing (24.9 percent), grain (23.1 percent) and meat (17.1 percent).

For Japan, the JTEPA would create benefits in lower prices of agriculture and food products from Thailand. Moreover, the chemical sector, iron and steel, and machinery and equipment will also gain market access.

11.5

CHANGES OF TRADE AND PRODUCTION PATTERN IN THAILAND

Recently, there have been two major changes in the production structure of Thailand. The first one is the higher dependency on export demand

330

[5]= [10] [11] [12] [13] 41.1% 44.1

EX

Source:

8.1% 9.4

[6]

2.1% 4.3%

[7]

ASEAN PRC

Office of the National Economic and Social Development Board (2008).

Author’s calculation based on National Account data.

58.9% 55.9

[4] = [1] [2] [3]

DD

Note:

16.1% 16.1

[3 15.2%

I

100% 100%

7.6% 7.6

[2] 7.1%

[1] 36.6%

32.2% 32.2

G

C

Export demand to total supply (2002–07)

2002 2007

GDP+M

Table 11.13

0.8% 0.8%

[8]

6.0% 5.2%

[9]

[10] = [[6] [7] [8] [9] 17.0% 19.7%

Korea Japan ASEAN+3

6.3% 6.1%

[12

[11]

8.0% 5.6%

EU

US

9.7% 12.6%

[13]

ROW

The rise of China and structural change in Thailand

Table 11.14

1993 1994 1995 1996 1997 1998 1999 2000 2001r 2002r 2003r 2004r 2005r 2006p 2007p1

331

Gross national product (share in %)

Agriculture (%)

Non-Ag. (%)

Manufacturing (%)

Other non-ag. (%)

8.6 9.0 9.5 9.5 9.4 10.7 9.4 9.0 9.1 9.4 10.4 10.3 10.3 10.7 11.4

91.4 91.0 90.5 90.5 90.6 89.3 90.6 91.0 90.9 90.6 89.6 89.7 89.7 89.3 88.6

29.7 29.6 29.9 29.7 30.2 30.9 32.6 33.6 33.4 33.7 34.9 34.5 34.7 35.1 34.9

61.7 61.4 60.6 60.8 60.4 58.4 58.0 57.4 57.5 56.9 54.7 55.3 55.0 54.2 53.7

Notes:

Calculated from gross national products (current price-seasonal adjusted).

Source:

Office of the National Economic and Social Development Board (2008).

of ASEAN13. By using the standard relationship of total supply (GDP 1 imports) and search for the responsive source of demand, the results showed that Thailand depended more on external demand. The ratio of domestic demand to external demand moved up from 59:41 in 2002 to 56:44. The main reason was the shortfall of private consumption and investment due to political instability (see Table 11.13). The higher degree of export dependency and the ‘regional bias’ of the Thai exports towards ASEAN13 demand had increased the ratio of ASEAN13 exports to close to 20 percent of the total supply in 2007. Again the major contributors were China and ASEAN. Secondly, the rise of China, the above-mentioned trade agreements, and the rise in oil and agricultural prices, all impacted the production pattern in Thailand (see Table 11.14). From 2002 onward, the agricultural sector regained its momentum and its share increased to 11 percent in 2007. The continuous rise of demand from China played a major role in absorbing the surplus of rice, tapioca, tropical fruits and rubber from Thailand. This was added to by the severe shortfall of crops at the global scale that raised the price of most crops in world markets. In fact, Thailand has been the only country in Asia that has freely opened rice exports. If the global

332

The rise of China and structural changes in Korea and Asia

warming situation and Chinese expansion continue, the agricultural sector will gain more share in the GDP in the years to come. The change in production pattern shows that China’s expansion brings a crucial transition in the Thai economy. Putting this into the context of the regional production network, Thailand has developed manufacturing restructuring, in response to the structural changes in its production or gross national product (GNP). The restructuring consists of two important mechanisms. The first one is high competitive advantages in some industries such as food and beverages; tools, machinery and vehicles; and parts and components of electronics and automobiles. Thailand has experienced shift in export pattern, a bias towards China’s demand. The Thai manufacturing sector has expanded in order to serve increasing demand from China and to reinforce the production network. It is empirical that Thailand’s exports to China have increased over time, especially in the tools, machinery and vehicles industry. The second mechanism relates to trade restructuring. Evidently, there are exports and imports back and forth between Thailand and China. Thailand imported more parts and accessories of electronics from China (Table 11.9) in order to serve its local demand and the needs of Thai manufacturing sector for exports. At the same time, the exports of tools, machinery and vehicles to China have increased (Table 11.11). In conclusion, Thailand has managed well to put itself in the regional production network as an exporter and importer. The rise of China not only creates markets for selling, but also the sources of inputs. Thailand’s manufacturing sector still maintains its course, albeit against high competition in exports as well as substituting imports. There are both pros and cons from the emergence of China; it actually depends on how well Thailand can cope with all the changes. As far as I am concerned, the rise in China still has positive effects on Thailand’s economic growth. Although the imports from China have expanded, the exports to China are still growing gradually. Also, the manufacturing sector is still growing (Table 11.14).

11.6

CHANGES IN INVESTMENT AND EMPLOYMENT STRUCTURE IN THAILAND

Turning to the FDI partners of Thailand, although the US and the EU have invested significant amounts of FDI, the net flows of FDI from these two regions are not as stable as those from Japan. More than half of the total FDI still comes from ASEAN13 while Singapore is the major FDI investor from ASEAN (see also Table 11.15).

The rise of China and structural change in Thailand

Table 11.15

ASEAN Share% Japan Korea Chian Plus Three Share % ASEAN+3 Share % Total Note: Source:

333

Thailand’s foreign direct investment (share in %) 2007

2006

2005

2004

2003

1 245 16.7% 2 492 35.6 8.54 2 536 30.4% 3 781 50.7% 7 451

4 073 40.6% 2 584 50.78 43.9 2 678 26.7% 6 751 67.3% 10 031

1 101 16.9% 2 927 29.51 11.55 2 968 45.6% 4 069 62.6% 6 503

689 13.9% 2 750 93.53 −3.82 2 840 57.3% 3 528 71.2% 4 956

1 060 20.5% 2 298 23.83 23.83 2 345 45.4% 3 406 65.9% 5 165

Author’s calculation from the balance of payments. Bank of Thailand (2008).

The pattern of FDI inflows has changed its structure post-crisis, with less in financial institutions, construction and real estate – while increasing in machinery, transportation equipment and services. For China, the FDI is substantial but fluctuating where Thailand fills its need of raw materials and intermediate products. However, Thailand does not mainly consider FDI in terms of money, because of the country’s twin surpluses. It rather prefers to increase FDI that improves production bases and technology transfer, especially from Japan. Thailand has belatedly shifted its attention to technology matters and human resource development, and hopefully on ways in which FDI can be leveraged more strongly to support these objectives. In this light, the Board of Investment (BOI) announced in November 2007 that it would end incentives for labor-intensive, low-quality and low-technology sectors in 2008. Special incentives are provided to those companies that invest in certain key industries such as electronics, infrastructure, and sectors relating to environmental protection, machinery and information technology. Looking at FDI outflows, Thailand has increased its outward orientation over the years with expansion of outward FDI particularly concentrated on electrical appliances. The pattern of Thailand outward FDI in Asia is largely Japanese in origin. Considering the employment structure, Thailand’s labor force was estimated at 36.9 million in 2007. The employment structure in Thailand is characterized by the large share of the agricultural sector, which still accounts for more than half of total employment. About 37 percent were

334

The rise of China and structural changes in Korea and Asia 5.0

1 400

4.5

1 200

4.0

3.6

1 000

3.5

3.3

3.0

800 2.4 600

2.2

2.5

2.1 1.8

1.5

2.0 1.5

400

1.4

1.5 1.0

200

0.5 2000

2001

2002

2003

Unemployed, 000s Source:

2004

2005

2006

2007

39 569

Unemployment rate, %

National Statistical Office (2008).

Figure 11.1

Thailand’s unemployment situation

employed in the services sector while industry accounted for 14 percent. The unemployment rate has retracted from the record high of 4.4 percent of the labor force in 1998 to 2.2 percent in 2003, and subsequently to 1.5 percent in 2007. In the situation of intense international competition, particularly from other Asian nations that offered lower-cost labor and more abundant resources, such as China, India, Indonesia, the Philippines and Vietnam, Thailand gradually lost its competitive position in labor-intensive exports because of rapid wage increases until the economic crisis struck in mid1997. However, this does not imply inequality due to the cheap labor of China or the above-mentioned Asian nations, since Thailand itself lacks low-cost labor. As Figure 11.1 illustrates, Thailand has experienced a very low unemployment rate, which indicates that the Thai labor force has been mobilized from labor-intensive sectors to other sectors, such as service sectors, with replacement of lower-cost labor from other countries. For years, Thailand has continued to promote the export role of service sectors or subsectors where the country has strong comparative advantage. After the financial crisis, sectors like transportation, telecommunications, construction and financial services have also become relatively larger with the entry and higher degree of foreign penetration.

The rise of China and structural change in Thailand

335

NOTE *

This chapter was prepared for the seminar on Growth and Structural Changes of the Korean Economy after the Crisis: Coping with the Rise of China. The author would like to thank Dr Cholachit Vorawangso and Dr Pitchaya Sirivunnabood for their assistance. 1. UNCTAD (2008) summarized China’s trade policy in ‘Key issues in China’s economic transformation’ as the following: ‘Prior to its accession to the WTO, China’s trade policy was very industry-selective, with extensive import restrictions, in order to support industrial restructuring: First, gradual and phased trade liberalization enabled imports of technology which China would not otherwise have access to and which were essential for structural changes in Chinese industry. Second, foreign trade allowed the export of surplus production, without which these structural changes, based on a combination of a large surplus of labor and rapidly increasing investment, would not have been sustainable. Exporting firms benefited from various pricing, tax and loan privileges, as well as support for technological upgrading. With the deepening of its economic reforms and, in particular, the decentralization of foreign trade, which has led to a massive entrance of private enterprises, many of the incentives have been phased out, non-tariff barriers have been gradually dismantled, and tariff barriers have been significantly lowered.’

REFERENCES Bank of Thailand (2008), Balance of Payment Statistics (various years), available at http://www.bot.or.th. Fiscal Policy Research Institute (2008), A Research on Assessing the Impact of AKFTA to Thailand, Bangkok (Thai version). National Statistical Office (2008), Labor Force Survey, available at http://www. nso.go.th. Office of the National Economic and Social Development Board (2008), National Account and Gross National Products Statistics, available at http://www.nesdb. go.th. Panitchpakdi, S. and Mark L. Clifford (2002), China and the WTO: Changing China, Changing World Trade, Singapore: John Wiley & Sons (Asia). Thai Customs Department (2008), Trade Statistics, available at http://www. customs.go.th. UNCTAD (2008), ‘Key issues in China’s economic transformation’, available at http://www.unctad.org/TEMPLATES/Page.asp?intItemID54064&lang51. World Trade Atlas (2008), World Trade Atlas, Internet Edition.

336

The rise of China and structural changes in Korea and Asia

APPENDIX 11.1

ASSESSMENT OF THE ACFTA FOR THAILAND

At the Annual Summit in Bandar Seri Begawan on 6 November 2001, a closer trade relation between the Association of South East Asian Nations (ASEAN) and the People’s Republic of China (PRC) began, whereby both parties decided to undertake an unprecedented initiative aimed at establishing a bilateral free trade area in 2010. On 4 November 2002 during the ASEAN–China Summit in Phnom Penh, Cambodia, the leaders of ASEAN and China signed the Framework Agreement on Comprehensive Economic Cooperation. The Framework Agreement, which contains a preamble and 16 Articles, provides the legal instrument for enhancing the ASEAN–China economic, trade and investment relations from the short term to the long term. It will serve as the turning point for establishing the Free Trade Area (FTA) by 2010 for the six original ASEAN states – Brunei, Indonesia, Malaysia, the Philippines, Singapore and Thailand – and by 2015 for less-developed ASEAN members like Cambodia, Laos, Myanmar and Vietnam. Trade in goods involves two areas of tariff reduction: (1) tariff reduction for specific products under the Early Harvest program and (2) tariff reduction for products under the Normal Track. Early Harvest involves three groups of products that will reduce the most favoured nation (MFN) applied rates (Table 11A.1). Table 11A.1

Schedules of tariff reduction in the ASEAN-China FTA

China and ASEAN-6

New-ASEAN 4

Group 1 product that has MFN > 15% Group 2 product that has MFN 5–15% Group 3 product that has MFN < 5%

product that has MFN > 30% product that has MFN 15–30% product that has MFN < 15%

with the schedule of commitment of tariff reduction as: China and ASEAN-6 2004 10% 5% 0%

2005 5% 0% 0%

New-ASEAN 4 2006 0% 0% 0%

No specific timeframe and MFN start rates but tariff reduction to 0% for Early Harvest in 2010

The rise of China and structural change in Thailand

337

Immediate Tariff Reduction ●

● ● ● ●

Agricultural products under HS-01-08 (all products at 8/9 digit level in HS Chapters 1–8 including Live Animals, Meat & Edible Meat Offal, Fish, Dairy Products, Other Animal Products, Live Trees, Edible Vegetables, and Edible Fruit & Nuts). Specific products: Thailand and China have a specific agreement to reduce tariffs on anthracite, coke and semi-coke of coal. Normal Track: which aims to achieve tariff reduction to 0 percent in 2010 (extension has been applied to some products to 2012). Sensitive Track: limits to less than 400 products and tariff reduction to 0–5 percent in 2018. Highly Sensitive Track: limits to less than 100 products and tariff reduction to 50 percent in 2015.

Trade in Services Sectors and Investments The negotiations started in 2003. The process of drafting the agreements according to the principle of a positive list approach under GATS is still ongoing. Projected Economic Benefits of the ASEAN–China FTA The ASEAN–China FTA is the world’s biggest free trade area, comprising approximately 1.7 billion consumers, a combined gross domestic product (GDP) of around US$2 trillion, and total international trade of US$1.23 trillion. Generally, the assessment of the ACFTA to Thailand anticipates that the agreement will create positive impacts on the Thai economy (GDP increases by 0.38 percent) and Thai consumers by providing a greater variety of products. It also indicates that the ACFTA will provide benefits to the Thai economy in various sectors such as rice, vegetables (cassava), tropical fruits, sugar, chemical products, rubber and related products, plastics, electronics, machinery, automotive and parts. On the other hand, the analysis estimates that various sectors will be negatively affected by this agreement: vegetables (onions, garlic, potatoes and tea), meat products, cements, fabrics and textiles, leather products, granite and ceramics).

338

AKFTA

1. Enhance international relationship between Korea and Thailand. 2. Express international political relations in moving towards larger ASEAN Economic Community. 3. Express impartial political will in cooperation with ASEAN under the fierce competition situations among China, Japan, India and the US.

International relationships 1. Receive extension periods of tariff reduction in 128 products (from end of 2010/2012 to 1 April 2016/ 1 January 2017). 2. Thai exports will gain the benefits from ROO when import inputs from ASEAN countries and Korea.

Market access: goods

Impacts on sectoral level 1. Thai producers in various sectors are expected to receive benefits from increased production and exports (i.e., electronics, food products, machinery and equipment).

Overall impacts on the Thai economy 1. Anticipate positive impacts on the Thai economy (GDP increases by 0.2%). 2. Thai producers will get cheaper intermediate inputs which induce private investment by 0.8%.

Market access: services and investments 1. Create the opportunities for Thai tourism and travelrelated sectors to invest in Korea (i.e., hotel lodging services, restaurant services, travel agencies and tour operators services).

Summary of the assessments of the benefits of the AKFTA to the Thai economy

ASSESSMENT OF THE BENEFITS OF THE AKFTA TO THAILAND

Benefits to the Thai economy

Table 11A.2

APPENDIX 11.2

339

Source:

NoAKFTA

1. Loss of opportunities to be part of ASEAN Production Network which would affect the FDI in Korean high-technology industry.

Fiscal Policy Research Institute (2008).

1. Loss of cooperations under TKAFTA and among ASEAN countries. 2. Compared to other member countries, Thailand would be negatively affected by asymmetric information.

1. Loss of opportunities to gain greater market access in various Korean services than the WTO Revised Offer.

1. Decrease in Korean FDI which hence negatively effects the overall Thai economy and employment.

1. Thai plastics and textiles producers will face competition from imports from Korea and ASEAN countries.

Index ACFTA (ASEAN FTA with China) 83–4, 327, 336–7 AEC (ASEAN Economic Community) 326–7 AFTA (ASEAN Free Trade Area) 326 aggregate GDP growth, Korea 106–7 aggregate manufacturing production, Japan impacts of exports to China 266–9 impacts of imports from China 282–4 agricultural sector, Thailand 312, 331–2 Ahn, S. 111 AKFTA (ASEAN FTA with Korea) 328, 338–9 Ando, M. 210, 301, 303 Arndt, C. 204 ASEAN and China 82–6 ASEAN Economic Community (AEC) 326–7 ASEAN Free Trade Area (AFTA) 326 ASEAN FTA with China (ACFTA) 83–4, 327, 336–7 ASEAN FTA with Korea (AKFTA) 328, 338–9 ASEAN+3 313–16 and Thailand 316–26 Asian Currency Crisis 3–4, 20 Baldwin, R. 229 Bernard, A. 176 Blanchard, O.J. 142, 148, 157–9 Blanchard and Quah model 142, 148–50, 157–9 Blonigen, A.B. 206 Blundell, R. 213 Bond, S. 213 Bosworth, B.P. 112

capital goods exports, Korea 182, 185, 187–92 measurement 180 capital growth rate per worker 117–18 Korea 117–18, 123 capital markets rise, China 69 CEPA (Closer Economic Partnership Arrangement) 85 China challenges of economic growth 58–9, 88 as competitor 57–8, 236–8 and East Asian economies 75–92 and East Asian production networks 56–7, 287–307 FDI inflows 50–52, 192–5, 207–8, 238 growth 4–5, 44–9, 65–71, 233 as growth engine 20, 53–4 as import market 54–6 and Japan 261–5 and Korean job growth 232–56 and Korean manufacturing growth 175–98 poverty reduction 26–30 and Thailand 310–34 trade 49–50, 233–5 China–ASEAN Free Trade Area 83–4 Chung, D.-K. 129 Clausing, A.K. 206 Clifford, M.L. 310 Collins, S.M. 112 competition, China 57–8 effect on Korean labour market 236–8, 243–7 complementarity, FDI and exports 205–6 consumption and economic growth, China 87 currency revaluation, China 69

341

342

Index

demand shocks 147–8 and Korean economy 158–65 dual estimates, TFP growth, Korea 106–7 dual growth accounting approach 102–3 East Asia economic growth 19–40, 71–2 effect of China’s growth 79–82, 89–92 flying geese development pattern 6, 72 intra-regional FDI 72, 75 and poverty reduction 26–30 production networks and rise of China 287–307 sources of growth 30–34 trade patterns 35–8, 71–2 East and Southeast Asia, growth 19–40 Easterly, W. 113 Eaton, J. 213 economic growth, see growth Eichengreen, B. 129 environmental problems, China 58–9 export competition from China 176–7, 181–4 export-led strategy, China 49–50, 59–60 exports China 49–50, 59–60, 68 Japan, to China, effect on production 261–85 Korea, to China 176, 181–2, 187–95 Korea, effect of FDI 192–5, 203–28 machinery 289–300 Thailand 316–18 external demand shocks 147 FDI, see foreign direct investment Feenstra, R.C. 240 firm-level analysis, FDI and exports 214–15, 220–25 fixed exchange rate and monetary aggregate targeting 153–6, 164–5 flexible exchange system and inflation targeting 150–53, 164 flying geese pattern 6, 72 forecasting error variance decomposition (FEVD) 157–9, 162–5

foreign direct investment (FDI) China, inflows 50–52, 53, 68–9, 79 China, outflows 57 and exports 205–6, 212–28 intraregional 72, 75 Korea, outflows to China 192–5, 207–8, 238, 247–8 effect on exports 192–5, 203–28 Thailand 312, 332–3 and trade 55 foreign GDP growth and Korean multinationals production 222 fragmentation of production 1–2, 300–302, 303–4 free trade agreements, Thailand 326–9 free trade area, China–ASEAN 83–4 GDP growth ESE Asia 19 foreign, and Korean multinational production 222 Korea 106–8, 143–4, 177 per worker 113–17, 120 gender and employment, Korea 250–51 goods trade, China–Korea, and Korea’s labour market 241–2 Graham, E.M. 206 growth China 4–5, 44–9, 65–71, 233 East Asia 71–5 Japan 20, 71–2 Korea 97–129, 143–5, 177–8 impact of shock 145–70 growth accounting, Korean economy 101–20 aggregate GDP growth 106–7 international comparison 112–26 per capita GDP growth 107–8 per worker growth rate 113–18 sectoral growth 108–11 total factor productivity growth rate 118–20 growth decompositions, ESE Asia 31–5 growth sources 113–20 ESE Asia 30–34 Korea 101–11, 113–20 growth sustainability, China 86–8 Hahn, C.H. 130 Hanson, G.H. 240

Index

343

Heckscher–Ohlin–Vanek (HOV) model 240 Hejazi, W. 206 Helpman, E. 205 high-tech industries, Korean FDI 208 Hong, K.-S. 130, 131 Hsieh, C. 102

Japan–Thailand Economic Partnership Agreement (JTEPA) 329 job growth, see labour demand Jones, R.W. 300 Jorgensen, D. 30 JTEPA (Japan–Thailand Economic Partnership Agreement) 329

import competition from China, effect on Korea 181, 184, 187 measurement 180 imports from China, effects on Japanese economy 282–4 Thailand 318 impulse responses (IR), Korean economy 157–65 income and poverty 19–20, 26–30 industry cooperation, Thailand 312 industry-level FDI–export linkage, Korea 213–14, 217–19 industrial production, Japan 266–84 small firms 271–80 tertiary industry 280–82 inflation targeting and flexible exchange rate system 150–53, 164 infrastructural investment, China 87 inter-trade, ASEAN+3 313 internal demand shocks 147 intra-firm trade and FDI, Korea 208–11 intra-regional FDI 72, 75 intra-regional trade 72 intra-trade, ASEAN+3 313, 315–16 investment China 47–8, 87 manufacturing, Korea 177–8, 187 see also foreign direct investment Irwin, D.A. 199

Katz, L.F. 240 Kierzkowski, H. 300 Kim, D.-I. 177 Kim, J.-I. 97 Kim, J.-K. 176–7, 232, 234, 238 Kim, K.S. 145–6 Kimura, F. 210, 301, 303 Koh, Y.-S. 129 Kojima, K. 229 Korea economic growth 97–129, 143–5, 177–8 impact of shocks 145–70 exports to China 176–7, 181–2, 185, 187–92, 304 FDI destinations 207–8 FDI to China effect on exports 192–5, 203–28 effect on labour demand 238, 247–8 labour market, effect of China’s growth 232–56 machinery exports to China 304 manufacturing growth 177–8 effects of rise of China 175–98 post-crisis growth, international perspective 112–26 production and distribution networks 303–7 sources of growth 101–11, 113–20 structural reforms 99–100 wage inequality effects of trade with China 251–5 Krugman, P. 4, 30, 307

Japan economic recovery 261–2 effects of imports from China 282–4 exports 261 impact on production 262–85 growth 20, 71–2 impact of China’s rise 75–8 machinery exports 292, 304 production and distribution networks 303–7

labour demand, Korea effect of competition from China 236–8, 243–7 effect of FDI into China 238, 247–8 effect of trade with China 235–6, 241–2 labour market, Thailand 311–12, 333–4

344

Index

Lau, L.J. 97 Lee, S. 209, 226 Lim, K. 209, 226 Lipsey, R. 206 Lucas, R.E. 131 machinery exports 289–300, 304 Mankiw, N. 129 manufacturing GDP growth rate, Korea 177 manufacturing production, Japan and exports 266–80 and imports from China 282–4 manufacturing restructuring, Thailand 332 market opening policy, China 47 market role, China 54–6 Markusen, J.R. 205 Mitze, T. 206 monetary aggregate targeting and fixed exchange rate system 153–6, 164–5 Murphy, K. 240 Nam, J.-K. 238 Nanxun effect 65 NIEs (newly industrialized economies) 72 Oh, H.-S. 146 open economy New Keynesian model 150–53 Ottaviano, G. 229 output growth, see production growth Panitchpakdi, S. 310 per capita GDP growth, Korea 107–8 per worker capital accumulation, Korea 117 per worker capital growth East Asia 117–18 Korea 117–18, 123 per worker GDP growth, Korea 113–17, 120 poverty 20, 26–30 primal growth accounting approach 101–2 production, Korea, and foreign GDP growth 222 production and distribution networks and China 289–300

fragmentation theory 300–302 and Japan and Korea 303–7 production growth, Korea 177–8 impact of China 184–5 measurement 180 production network role, China 56–7 production patterns, Thailand 329–32 purchasing power parity 19–20 Pyo, H.K. 111 Quah, D. 142, 148, 157–9 real GDP growth, Korea 177 regional economic integration, effect of China’s foreign trade 81–2 regional gaps, China 60–61 regional impact of China’s rise 75–86 renminbi revaluation 69 Roland-Holst, D. 55–6 rural reform, China 44–5 Safarian, A.E. 206 sectoral growth, Korea 108–11 Shim, J.W. 145 Shin, H.S. 238 shocks, effect on economy 146–8 Korea 157–65 models 148–56 small firms, Japan 263–4, 271–80 small and medium enterprises, China 47 sources of growth, see growth sources state-owned enterprise (SOE) reform, China 45–7 Stock, J. 148, 150 structural reforms East Asian economies 89–90 Korea 99–100 subprime crisis 3–4 subregional cooperation, China 85–6 substitution relationships, FDI and exports 205 supply shocks 147–8 Korean economy 158–65 Swenson, D.L. 204, 206 Tamura, A. 213 Tamura, R. 131 tariff liberalization, China–ASEAN FTA 83

Index tertiary industry, Japan, impacts of exports to China 280–82 TFPG, see total factor productivity growth Thailand 310–34 and ASEAN+3 310–12, 316–26 employment structure 333–4 exports 316–18 free trade agreements 326–9 imports 318 investment structure 332–3 production structure changes 311–13 third-market competition with China 176 Korea 179–84 total factor productivity growth (TFPG) controversy 97–9 Korea 106–7, 118–20, 126 trade, China and Korea 234–5 effect on labour market 241–2

345

trade, intra-regional 72 trade patterns 35–8 ASEAN+3 313–16 effect of China’s growth 80–82 trade restructuring, Thailand 332 Treaty of Amity and Cooperation (TAC) 85 United States as destination of East Asian exports 292, 300 share of Korean FDI 207–8 Vu, K. 4, 30 wage inequality, Korea 251–5 Watson, M. 148, 150 Weiss, M.Y. 206 WTO accession, China 65–6 Young, A. 4, 30, 97, 101, 102, 103, 104, 130

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