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9
A WORLD BANK COUNTRY STUDY
Malaysia Enterprise Training, Technology, and Productivity
The World Bank United Nations Development Programme Government of Malaysia
Washington, D. C.
Copyright© 1997 The International Bank for Reconstruction and Development/THE WORLD BANK 1818 H Street, N.W. Washington, D.C. 20433, U.S.A. All rights reserved Manufactured in the United States of America First printing September 1997 World Bank Country Studies are among the many reports originally prepared for internal use as part of the continuing analysis by the Bank of the economic and related conditions of its developing member countries and of its dialogues with the governments. Some of the reports are published in this series with the least possible delay for the use of governments and the academic, business and financial, and d e v e lopment communities. The typescript of this paper therefore has not been prepared in accordance with the procedures appropriate to formal printed texts, and the World Bank accepts no responsibility for errors. Some sources cited in this paper may be informal documents that are not readily available. The World Bank does not guarantee the accuracy of the data included in this publication and accepts no responsibility whatsoever for any consequence of their use. The boundaries, colors, denominations, and other information shown on any map in this volume do not imply on the part of the World Bank Group any judgment on the legal status of any territory or the endorsement or acceptance of such boundaries. The material in this publication is copyrighted. Requests for permission to reproduce portions of it should be sent to the Office of the Publisher at the address shown in the copyright notice above. The World Bank encourages dissemination of its work and will normally give permission promptly and, when the reproduction is for noncommercial purposes, without asking a fee. Permission to copy portions for classroom use is granted through the Copyright Clearance Center, Inc., Suite 910, 222 Rosewood Drive, Danvers, Massachusetts 01923, U.S.A. Cover photos: Photos used by permission of the Malaysian Government. ISBN: 0-8213-4059-X ISSN: 0253-2123
TABLE OF CONTENTS FOREWORD FROM ECONOMIC PLANNING UNIT, GoVERNMENT OF MALAYSIA
vii
ABsTRACT
Viii
AcKNo�MENTs
oc
AcRoNYMs/ABBREVIATIONs
x
CHAPIER ONE: INTRODUCTION
1 1
The MITP Survey Analytic Approach
4
Overview of Report
6
CHAPTER Two: OvERVIEW OF TRAINING
10
Incidence of Training
10
Sources of Enterprise Training
12
Workers Getting Training by Source
14
Factors Shaping Training Decisions of Firms
17
Findings and Policy Implications
21
CHAPIER THREE: PRODUCTIVITY AND WAGE OUTCOMES
24
Estimating the Productivity Impact of Training
24
Productivity Effects of Training for Different Firms
25
Productivity Outcomes by Skill Group and Training Source
30
Firm-Level Wage Outcomes of Training
35
Compensation Policy and Labor Turnover
38
Findings and Policy Implications
43
CHAPTER FoUR: TRAINING PoLICIEs
46
Constraints on Training: An Employer Perspective
46
The Double Deduction Incentive for Training Scheme
48
Human Resource Development Fund
52
Findings and Policy Implications
61
CHAPIER FivE: TECHNOLOGY, QUALITY AND SKILLS
63
Technological Characteristics of Firms
63
IS0-9000 and Quality Assurance
70
IS0-9000 and Export Orientation
73
New Technology and Changing Skill Needs
77
Findings and Policy Implications
81
iii
CHAPTER SIX: FIRM EFFICIENCY AND ITS DISTRIBUTION
86
Measuring Technical Efficiency
87
Distribution of Efficiency by Firm Size
90
A Profile of Efficient Firms by Size
92
Ownership, Efficiency Difference and FDI Spillovers Findings and Policy Implications
99 105
CHAPTER SEVEN: CoNCLUSIONS AND REcoMMENDATioNs
108
Summary of Main Findings
108
Policy Recommendations
112
ANNExEs 2.1
Probit Estimates of the Likelihood of Formal Training
23
5.1
Introduction of New Technology and Training
83
5.2
Introduction of New Technology and Firm-Level Productivity
85
6.1
Stochastic Frontier Production Functions
107
NOTES
121
REFERENcES
125
TABLES 1.1
Key Variables in the MITP Survey
4
1.2
The MITP Sample and Response rates
5
2.1
Incidence of Training in Manufacturing and by Firm Size
11
2.2
Incidence of Training by Industry
11
2.3
Internal and External Sources of Training
12
2.4
Sources of Training by Firm Size
13
2.5
Workers Trained: Overall and by Firm Size
14
2.6
Number of Workers Trained by Industrial Sector
15
2.7
Workers Getting Formal In-House Training by Skill Group
16
2.8
Workers Trained from External Sources by Occupation
17
2.9
Marginal Effects of the Likelihood of Formal Training
18
3.1
Production Function Estimates by Firm Size
25
3.2
Production Function Estimates by Technology Level
28
3.3
Production Function Estimates by Export Orientation
30
and Ownership
3.4
Production Function Estimates with Predicted Training by Worker Groups
32
3.5
Production Function Estimates: In-house vs. External Training
33
3.6
Production Function Estimates: Training from External Sources
34
3.7
Productivity Effects oflncreased Training Intensity
35
iv
3.8
Wage Model Estimates with Training Indicator and Predicted Values 37
3.9
Wage Effects of Training by Technology, Exports
3.10
Occupation-Specific Wage Effects on Training
38
3.11
Summary Statistics on Quits and Compensation Policies
41
3.12
Compensation and Overall Quit Rates by Training Status
42
3.13
Compensation and Quit Rates by Occupation and
4.1
Reasons for Little or No Training: Overall and by Firm Size
48
4.2
Participation in DDIT by Industrial Sector
50
and Ownership
37
Training Status
43
4.3
Reason Given by Firms for Not Using DDIT
51
4.4
Reason for Not Using DDIT by Firm Size
52
4.5
Use of HRDF by MITP Firms , 1994
53
4.6
Eligible Firms Not Registered with HRDF by Size and Industry
54
4.7
Probit Estimates of Non-Compliance with HRDF
55
4.8
Registerd Firms Not Claiming from HRDF by Training Status
56
4.9
Probit Estimates of Not Claiming from HRDF
57 58
4.10
Training Centers and Training Plans in MITP by Firm Size
4.11
Joint Training Programs in MITP by Firm Size
58
4.12
Pro bit Estimates of Increased Training Under HRDF
60
4.13
Changes in Training Levels Over Past Three Years: Frims Registered with HRDF and Unregisterd Firms
60
5.1
Technology Characteristics by Firm Size and Ownership
64
5.2
Technology Characteristics by Industry
66
5.3
Quality Control and Precision in Production
67
5.4
IS0-9000 Status and Quality Control Systems
71
5.5
IS0-9000 by Firm Size and Ownership
72
5.6
IS0-9000 and Export Orientation
73
5.7
IS0-9000 and Export Propensity by Principal Markets
75
5.8
Introduction of New Technology since 1992
76
5.9
Effects of New Technology on Skill Needs and Employment
76
5.10
New Technology and Changes in Training since 1992
77
5.11
Impact of New Technology on Training
78
5.12
Impact of New Technology on Productivity by Firm Size
80
6.1
Stochastic Frontier Production Function Estimates
89
6.2
Distribution of Efficiency by Firm Size and Economy
90
6.3
Stachastic Frontier Production Function Estimates
6.4
Stochastic Frontier Production Function Estimates with
by Ownership
101
FDI Spillovers
104
v
FIGURES 3.1
Quit rates and Wage Policies: Training and Non-Training Firms
39
5.1
Quality Control Systems by Firm Size and Ownership
68
5.2
IS0-9000 and Exports
74
6.1
Distribution of Efficiency by Economy
91
6.2
Malaysia- Distribution of Efficiency by Firm Size
92
6.3
Technology Attributes of Efficient and Inefficient Firms
93
6.4
Training Attributes of Efficient and Inefficient Firms
94
6.5
Quality Control in Efficient and Inefficient Firms
95
6.6
Quits and Compensation in Efficient and Inefficient Firms
96
6.7
Technology and Training in Past Three Years
97
1.1
Cross-National Enterprise Training Study
BoXES 3.1
Enterprise Training and Productivity in Developing Countries
3.2
Technology Raises the Productivity of Training in Taiwan, China
2 25 27
5.1
Use of External Sources of Technical Support by Firms
69
5.2
Diffusion and Impact ofiS0-9000 in Brazil
70
6.1
Mexico's Proactive Approach to SMI Support
100
6.2
Promoting SMI Networks in Chile
103
vi
FoREWORD FRoM THE EcoNOMIC PLANNING UNIT, GOVERNMENT OF MALAYSIA
The quality of a nation's workforce is the key ingredient to economic growth. Increasing labor productivity and upgrading the skills and flexibility of workers through training and retraining are essential strategies for developing a quality labor force to support sustained growth and economic development of the country. To achieve the status of a fully developed industrialized country by the year 2020, Malaysia has made human resource development one of its major development strategies. The govern ment has, and will continue to, play a strong role in strengthening the educational and workforce skills of the population. But the government cannot do it on its own. Most technological innovations now enter Malaysia through industries; furthermore, learning is a lifelong pro cess, and relevant skills are best acquired in the workplace. This means that employers who have the expertise and technical know-how to train-will have to assume greater re sponsibility for training and upgrading the existing skill levels of their employees to meet the skill requirements of new technology. For its part, the government has introduced the Human Resource Development Fund, to encourage and promote enterprise training in industry, as well as complementary research and development (R&D) incentives and policies to assist small and medium industries (SMis). This report, which is based on a large survey of enterprise training, technology and produc tivity in the manufacturing sector, is written for policy makers and company executives who have to make critical decisions and design training policies. It provides the first broad based look at the existing level and incidence of private sector-led training in Malaysia, and it relates training efforts to corporate strategies on R&D, technology licensing, and quality control, as well as the effects of training on productivity and wages in companies. The analyses reported here can be used to support formulation of more effective public policies and corporate strategies for strengthening industrial training to meet the challenges of sus tained economic growth and globalization. It is hoped that this report will encourage the private sector to play a greater role in developing the country's skill abilities to support Malaysia's strategic vision of attaining our Vision 2020. Tan Sri Dato' Seri Ali Abul Hassan b. Sulaiman Director General Economic Planning Unit Prime Minister's Department Government of Malaysia
vii
ABsTRAcT This report presents the findings of a study of enterprise-based training in Malaysia's manufacturing sector which was jointly sponsored by the World Bank, the United Nations Development Programme, and the Economic Planning Unit, Prime Minister's Department. Using data from a survey of 2,200 companies, the study investigates the incidence and productivity outcomes of employer-sponsored training in in-house com pany programs and from external training providers, and the role of government poli cies and incentives in encouraging private sector training. The study also looks more broadly at technology in firms, their use of quality control systems, and the skill re quirements associated with the use of new technology and organizational change . The report concludes that while some firms, especially the larger, more technologically progressive ones and the multi-national companies do provide training, in general, most Malaysian firms underinvest in employee training. It documents the primacy of the private sector as the most important source of in-service training, and suggests that existing public sector training institutions need to become more demand responsive. It demonstrates that training firms are also making complementary investments in new technology, and that the productivity of local firms lags behind that of foreign-owned firms, in large part because local firms invest relatively less in training and new tech nology. The report also offers recommendations on improving collection and dissemi nation of training information, making training and technology policies more effective, and developing better coordinated, proactive policies to support small and medium industries.
viii
AcKNOWLEDGMENTS This report was prepared as part of the Malaysian Industrial Training and Productiv ity (MITP) Study, a joint project of the World Bank, the United Nations Develop ment Programme (UNDP), and the Economic Planning Unit (EPU), Prime Minister's Department. The project, directed by Hong Tan, was conducted by several teams -- a World Bank team, including Hong Tan and Geeta Batra; a local team including Professors Rajah Rasiah, Osman Rani, and Anwar Ali from Universiti Kebangsaan Malaysia; and staff from the Human Resource Section of EPU, especially Puan Faizah Mohd. Tahir (Director), Dato Zainol Abidin Rashid (former Director), Yap
Kim Lian, Asri Hamidon, Mohd. Hanafi Sakri and Muhd. Fikri Nawawi. The MITP survey was fielded by Survey Research Malaysia (SRM) under the able direction of Eugene Wong, Cheah Swee Kit and Christine Kwan. The MITP survey relied on a sampling frame provided by the Department of Statistics (DOS), and used a survey instrument developed by the World Bank and adapted for the MITP Study by the project team and SRM. This report was written by Hong Tan and Geeta Batra of the Private Sector Development Department. This MITP Study would not have been possible without the financial support of UNDP, the World Bank Research Committee (RPO
678-39), and EPU. We thank
Ameerah Haq, Neil Buhne, and Selva Ramachandran of UNDP for their support. We gratefully acknowledge the active support of Dato Annuar Ma'aruf, Deputy Director General ofEPU, and the many insightful comments provided by members of the project's Steering Committee, including representatives from EPU (Human Resources, Industry and Social Sections), the Ministry of Human Resources, Minis try ofintemational Trade and Industry, Malaysian Industrial Development Author ity, Human Resources Development Council, Ministry of Science, Technology and theEnvironment, and the Federation of Malaysian Manufacturers. We benefited from interactions with numerous individuals and both public and pri vate sector groups. In particular, we acknowledge the staff of DOS, especially Dorothy Robert, Mat Noh b. Russin, Lok Chung Lee and Tan Hoe Seng for their invaluable assistance with surveys and data; and Mr. Yau De Piyau and his staff at HRDC for data and insights into the operation of the Human Resource Develop ment Fund. We gained many insights from interviews with the Penang Develop ment Corporation, the Penang Skills Development Center, Standards and Industrial Research Institute of Malaysia, National Productivity Center, and the National Vo cational Training Council. Finally, we acknowledge the many companies that con tributed their time generously to participate in the MITP Survey; we trust that you will find the research and policy recommendations in the Report useful in formulat ing your skills and technology development strategies.
ix
AcRoNYMs/ABBREVIATIONS APITD
Action Plan for Industrial Technology Development
ClAST
Center for Industrial and Advanced Skills Training
DDIT
Double Deduction Incentive for Training
DOS
Department of Statistics
EPU
Economic Planning Unit
FDI
Foreign Direct Investment
GMI
German-Malaysia Institute
GTS
Group Training Scheme
HRDC
Human Resource Development Council
HRDF
Human Resource Development Fund
IKM
Institute Kemahiran Mara
IMP
Industrial Master Plan
ITI
Industrial Training Institute
JMI
Japan-Malaysia Institute
JTS
Joint Training Scheme
MASTIC
Malaysian Science and Technology Information Center
MFI
Malaysia-France Institute
MIDA
Malaysia Industrial Development Authority
Mill
Ministry of International Trade and Industry
MITP
Malaysia Industrial Training and Productivity Survey
MLFS
Malaysia Labor Flexibility Survey
�
Multi-national Corporation
NPC
National Productivity Corporation
NVTC
National Vocational Training Council
OJT
On the Job Training
Q:C
Quality Control Circles
QIP
Quality Improvement Practices
soc
Skill Development Center
SIRIM
Standards and Industrial Research Institute of Malaysia
SMI
Small and Medium Scale Industry
SMIDEC
Small and Medium Industrial Development Corporation
SPC
Statistical Process Control
SRM
Survey Research Malaysia
1NA
Training Needs Analyses
UNDP
United Nations Development Programme
VEf
Vocational Education and Training
VIE
Vocational and Technical Education
YIC
Youth Training Center
X
CHAPTER ONE: INTRODUCTION This report seeks to inform policy discussions on
employers' technology- whether they invest in re
private sector-led training through a survey offinns
search and development (R&D) or purchase their
and rigorous analyses of their responses.
technology through licensing agreements, whether
The Malaysia Industrial Training and Productivity
relate to training strategies. It characterizes the dis
they have quality control systems- and how these (hereafter MITP) survey, was fielded to 2,200 manu
tribution of employers' technical efficiency levels
facturing firms in 1994 and 1995. The MITP sur
relative to the best-practice frontier, and identifies
vey elicited infonnation on firm-sponsored training,
the key training and technological factors associated
and on a wide range of firms' attributes including
with high efficiency levels.
size, industry, local or foreign ownership, equip ment, technology, quality control systems, markets and exports, work force characteristics, wages and
The MITP Survey
other compensation and production. The firm-level data needed to study private sector These data allow us to document, for the first time,
training do not currently exist in Malaysia. A primary
the incidence and characteristics of training in Ma
data collection effort was deemed necessary to
laysian industry, throughout finns of different sizes,
develop the requisite data from a statistically
ownership, and industrial sector. The data also pro
repre s e n t a tive s a m p l e of m a n u f a c t u ri n g
vide unique insights into where firms get their train
enterprises. The MITP project team adapted, to
ing- from in-house training programs, from private
Malaysian conditions, a survey instrument
sector providers, and from different government
developed by the World Bank as part of its cross
training institutions; which groups of workers get
national study of Enterprise Training and
training and how much; and what are the outcomes
Productivity (see Box 1.1).
of training on firm-level productivity and wages.
Survey Questions This report addresses the issue of whether firms in
Table l.llists the main types of questions asked in
Malaysia under-invest in training. It asks employ
the MITP survey. It elicits a variety of information
ers about why they do little or no training, and in
about the attributes of the enterprise; its market and
vestigates the factors which shape employers'
technology, including research and development,
training decisions. It evaluates the efficacy of dif
technology licensing, equipment, and quality con
ferent training incentives in promoting in-service
trol systems; its work force structure, skills and
training, and suggests ways of overcoming their limi
compensation system; its training facilities and
tations.
worker training by source and type; and produc tion inputs and outputs.
It investigates the links between training and firm level productivity, a critical issue not only for firms
The MITP survey asked detailed questions about
but also for policymakers. It addresses this issue by
employer-sponsored training. The multifaceted
estimating the productivity and wage outcomes of
nature of training makes it notoriously difficult
different kinds of training provided to different
to quantify. It can either be provided informally
groups of workers.
on-the-job through instruction from co-workers and supervisors, or formally through structured
Finally, the report studies the role of new tech
courses of classroom instruction combined with
nology in raising skill requirements. It looks at
on-the-job training.
2
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Training can take place in company training centers
Employer responses can be used to characterize,
or be provided by a variety of external sources in
for the first time, the incidence and intensity of
cluding public and private training institutes, in
in-service training in Malaysia: how much in
dustry associations, foreign joint-venture partners,
service training goes on in Malaysia; where are
and buyers and suppliers.
employers training their workers, in company training programs or through external training
The content of training can vary, from machinery
providers; which external training sources are
operation to statistical process control to production
most in demand - public training institutions such
management. Training provided to different occupa
as ITis or IKMs, skil l development centers
tional groups can differ, both in the numbers trained
(SDCs) or advanced training institutes, or other
and in the types and sources of training provided.
private sector providers? They will also allow us
Other dimensions of training- duration, intensity,
to identify which of the firms train and which
cost, and the quality of instruction- are also impor
do not, and which groups of workers are being
tant, but are poorly measured in the MITP survey.
trained.
Box 1.1 Cross-National Enterprise Training Study
This study was based on five developing economies. Three countries-- Columbia, Indonesia, and Malaysia -- fielded surveys of manufacturing firms based on a World Bank survey instrument. A fourth country, Mexico, used a survey instrument developed jointly by the Secretariat of Labor and Social Welfare and the International Labor Organization (ILO), with input from the World Bank to ensure its comparability with the other surveys. Tawain, China was included in this sample because key training, technology and production information was elicted in its 1986 Census of Manufacturing. It was also attractive both for its large sample size and as a benchmark for the other developing economies. Table 1.2 presents some summary statistics on these economies. The five economies in the sample represent considerable diversity in the level of per capita income, stage of industrialization, and export performance. The World Development Report (1995) classifies Indonesia and Columbia as lower middle income economies. In1986, the year for which we have data, Taiwan, China would have been ranked as being higher-middle income by this classification system. These economies experienced strikingly different growth patterns over the 1980s and early 1990s, with stagnant or low groth of per capita GNP and manufacturing output in Mexico and Columbia, and rapid growth in Indonesia, Malaysia and Taiwan, China. Characteristics of Economies in the Enterprise Training Study
Developing Economy
GNP per Capita US$ 1993
GNP Growth 1980-93
Manufactures 1980-93
Export 1980-93
Indonesia
$740
4.2
11.8
6.7
Columbia
$1,400
1.5
3.5
11.0
Malaysia
$3,140
3.5
10.3
12.6
Mexico
$3,610
-0.5
2.1
5.4
Taiwain, China
$3,6878
7.6b
12.7b
6.2b
Notes: For Taiwan, China, a refers to 1986 and b refers to the 1980-86 period. Sources: World Development Report, 1995; Taiwan Statistical Yearbook, 1988. See Tan and Batra, Enterprise Training in Developing Countries, World Bank (1995)
INTRODUCTION
3
The survey included a comprehensive set of ques
vey, this information provides an unprecedented
tions about the attributes of the enterprise. These
opportunity to explore the critical inter-dependen
variables- total employment size, research and de
cies that exist between key strategic variables, and
velopment spending, licensing of technology, for
that ultimately determine the productivity levels
eign capital participation, exports, use of automatic
and competitiveness of firms in the economy.
equipment, quality control system, education and sex composition of the work force, and labor tum
The Sampling Frame
over- are critical for understanding why firms train.
The design of the MITP sampling frame reflected several considerations. First, we wanted a large, na
They allow us to address questions of how skill and
tionally representative sample of manufacturing en
training requirements are influenced by firm size,
terprises.
by the technology and quality control system used,
representative of the composition of the manufac
While the overall sample would be
by foreign capital participation either as joint ven
turing sector, it would be stratified by three firm
tures or as wholly foreign-owned firms, and by the
sizes with larger firms being over-sampled relative
characteristics of its workforce. The survey elicited information on production and compensation, data critical to understanding the eco nomic motive for why firms train and how these
to their true weight in the population. A sample size of approximately 2,200 was thought to be ad equate for ensuring adequate representation in each industry-firm size cell.
investments in training affect firm-level productiv
Second, we wanted to build in the potential for link
ity and the wages paid to employees. Information
ing the MITP
survey
to the 1988 Malaysia
on production inputs and outputs allow us to esti
LaborFlexibility Survey (MLFS). While its fo
mate production functions and, after accounting for
cus was on labor market adjustment, the MLFS also
differences in capital, labor and other firm attributes,
elicited relevant information, such as skill com
to relate investments in training to improvements
position of employees, and adoption of new tech
in firm-level productivity. This ability to relate training to productivity out comes is important since different types and sources of training may have different effects on productiv ity, with implications for where and how policymakers and enterprises should allocate their
nology. To this end, two samples of firms were created- respondents of the 1988 MLFS still pre sumed to be in existence in 1994, the "survivors" sample; and firms not in the MLFS that began op eration between 1989 and 1994, the "new entrants" sample.
training resources. Similarly, the ability to relate
The MITP survey was carried out by Survey Re
training to wages will allow us to address the issues
search Malaysia (SRM), using a sampling frame pro
of how the productivity benefits of training are
vided by the Department of Statistics (DOS), and
shared with workers, and if the factors that shape
with participation of the local research team, the Eco
training changes, (such as adoption of new technol
nomic Planning Unit (EPU), and the World Bank.
ogy) what are the consequences for income distri
The fieldwork involved several activities: track
bution and inequality?
Finally, many variables elicited in the survey are also important in their own right. They represent key elements of private sector firms' innovation,
ing down firms in the DOS list, verifying the de mise or continued existence of firms and conducting pilot interviews to field-test and refine the MITP survey instrument.
human resource, organization, and marketing strat
The survey enumeration was carried out over a pe
egies as well as important areas of government
riod of four and a half months between December
policymaking. When brought together in one sur-
1994 and May 1995. Questionnaires were mailed to
4
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 1.1 Key Variables in the MITP Survey
Firm attributes Firm characteristics
Types of questions asked Single or multi-plant firm, age of enterprise Foreign capital by country of origin Principal product and exports by destination market
Markets and Technology
Prior growth and future growth expectations Capital stock-automation, vintage,
investment plans
R&D as% of sales, any technology licenses Quality control system, IS0-9000 certification Workforce and Compensation
Education and worker attributes by broad occupation Wages, fringe and statutory benefits by occupation Recruitment and labor turnover by occupation
Training system
Training facilities and training specialists Informal OJT vs formal, structured training Numbers trained in-house and mode by occupation Numbers trained by detailed external source Reasons for low investments in worker training
Production and Inputs
Value of output, capacity utilization rate Cost of intermediate inputs and energy
each firm that could be located, accompanied by a
sponse rates being in the Wilayah Persekutuan area.
letter from the EPU explaining the purpose of the
All the analyses in this report are based on a sample
survey, assuring them of confidentiality, and arrang
of the first 2,200 firms that returned completed ques
ing for a face-to-face interview after respondents had
tionnaires. In the analyses, no distinction is made
an opportunity to assemble all relevant data. A sec
between the survivors and new entrants samples. 2
ond letter from the Human Resource Development Council was also sent out to emphasize the impor
Analytic Approach
tance of responding to the MITP survey. Our analytic approach is motivated by an economic Table 12 . shows the fmal composition of the MITP
model in which firms develop technological capa
sample and survey response rates by state. Out of
bilities through conscious investments in knowledge
the 4,583 names provided by DOS, SRM verified
generating activities.
and mailed out or delivered questionnaires to a to tal of3,373 firms; of these, a total of2,318 firms
Our definition of technological capability follows
returned completed and usable questionnaires.
Bell and Pavitt (1992), who distinguish between "production capacity" and "technological capability."
The overall response rate-68 percent-is extremely
The former concept measures the capacity of firms
high, especially given the length and complexity of
to produce output at given levels of efficiency, with
the MITP questionnaire. Response rates were some
existing inputs of capital, labor, and technology; the
what lower for the new entrant sample (66 percent)
latter incorporates the additional and distinct re
as compared to the survivor sample (71percent), and
sources needed to generate and manage technologi
varied considerably across states, with the lowest re-
cal change, including specialized managerial and
INTRODUCTION
5
technical skills, knowledge and experience, and in
firms operating in the local markets \Westphal
ter-firm linkages. Employers with these technologi
et al, 1984; Pack, 1992).
cal capabilities have a productivity advantage over
•
less capable firms.
ees. Whether importing foreign technology, or using, adapting and redesigning technol
Technological capabilities can be developed in
ogy through deliberate investments in R&D,
several ways. •
firms can build technological capacity by in vesting in the skills and training of the
Firms can invest in their own R&D or pur
workforce.
chase technology and know-how through li censing agreements with foreign firms. The
Several factors are at the heart of why education
evidence from developing countries suggests
and training are so critical to developing a firm's
that reverse engineering, imitation, and modi
technological capabilities. First, we know that the
fication of foreign technology are often more
productivity advantage of new technology is only
critical to developing technological capabili
attained through an intensive learning process. There
ties than investments in basic research and
is evidence from technology literature that much of
innovation (Pack, 1992). •
Firms can invest in the skills of their employ
the productivity gains from introducing a new in novation comes from making cumulative small
Firms can acquire relevant and best-practice technology through their links with foreign buy
modifications in it, essentially through an inten
ers of exported products as well as from foreign
sive learning-by-doing process (Bell and Pavitt,
Table 1.2 The MITP Sample and Response Rates DOS Sample
Number Surveyed
Response Rate %
State
NE
s
Johor
340
331
247
276
84
79
90
93
83
88
Kelantan
34
45
26
90 45
Malacca
69 38
70
51
50
88 76
91 78
57
37
53
95
91 100
Kedah
Negri Sembi ian
NE
s
NE
s
80
Pahang
38
65
29
60
86
Penang
218
284
186
265
70
76
Perak
150
272
91
224
91
94
Perlis
5
4
4
3
100
100
S elangor
346
517
263
418
63
56
Wilayah Per.
601
358
327
249
14
37
23
37
19
34
100
94
251
249
143
110
71
91
2,450
2,133
1,615
1,757
66
71
Trengganu Sabah/Sarawak
TOTAL
Note: NE = new entrant sample, S =survivor sample. Source: 1995 MITP Survey
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
6
1992; Enos, 1962). The challenge for employers
which its graduates bring to the employer - will
is to motivate and provide workers with incen
determine how cost effective it is for enterprises to
tives to learn about the new technology.
rely on outside training institutions rather than pro viding these skills in-house.
Second, innovative firms are more likely to use highly educated and skilled workers because they
The technology discussion suggests another set of
are more adept at critically evaluating new infor
determining factors. If the productivity advantage
mation, and thus learn more. Being more efficient
of technology is revealed only through learning by
learners, they are more productive when exposed to
doing, then innovative firms have an incentive to
new and unfamiliar information.
train in-house to internalize the new technology in the skills of its workforce.
Microeconomic case srudies have identified the criti cal role of educated workers in the innovation pro cess (Setzer,
1974; Pack, 1992). There is a large body
of substantiating evidence for these views.
In contrast, outside training providers are typically not well-prepared to impart skills associated with the most recent, and still evolving, technologies. They play an increasingly important role (and their
Human capital studies, have shown that educated
training services are utilized more intensively by
farmers and workers are more productive in a rap
firms), when technologies become standardized and
idly changing environment, and thus earn higher
their productive characteristics become well-under
incomes (Welch,
1970; Tan, 1980; Mincer, 1989).
stood.
There is evidence from industrialized and devel oping countries that industries experiencing rapid
These perspectives-on the relative importance of
technological change are more likely to train their
in-house company training when firms are en
workers, and that these training investments give rise to higher wages (Carnoy,
1990; Lillard and
gaged in innovation-are supported by the research of Lillard and
Tan(1992) and Tan et al (1992). In
1992; Tan et al, 1992). Finally, using frrm
their study of the sources of worker training in
level data from Taiwan, Aw and Tan (1994) show
high- and low-technology industries in the U.S., they
that worker training has a large positive impact
find that in-house training programs are empha
on firm-level productivity, and that this effect is
sized when employers are engaged in developing
larger when worker training is accompanied by
new technology.
Tan,
complementary investments in both R&D and for eign technology licenses.
These trends may be less pronounced in developing countries, such as Malaysia, where older, and more
To date, however, the literature has been relatively
standardized, technologies are in common use and
silent about the types of training that are most perti
frrms have limited in-house training capabilities.
nent to technological change. Employers must make decisions not only about whether to train, but also what kinds of training to provide. They may pro vide training in-house, or rely on outside training providers, depending upon their in-house training capabilities, and the vocational education and train ing (VET) system in the country. The VET system- its ability to meet the skill re quirements of enterprises, the quality of technical training provided, and the job relevance of skills
Overview of the Report The report is divided into two broad sections. The
first section, which comprises Chapters Two through Four, focuses on the incidence and productivity out comes of employer-sponsored training and on gov ernment policies and incentives designed to encourage training by employers. The second sec tion, Chapters Five and Six, looks more broadly at
INTRODUCTrON
7
technology in firms, the use of quality control sys
training are larger for small and medium size firms,
tems and IS0-9000 certification, and the skill re
who do relatively little training; for firms investing
quirements associated with the use of new
in new technology, especially through technology
technologies and organizational change. The report
licensing; and for export-oriented firms and firms
concludes in Chapter Seven with a summary of
with some foreign capital participation.
findings and policy recommendations. The production function analyses also revealed Chapter Two uses the MITP survey to paint a
marked differences in the productivity effects of
broad brush picture of enterprise training in the
training provided to different groups of workers and
manufacturing sector of Malaysia. It reports sum
training from different sources. The results show
mary statistics on the incidence of training across
that while skilled worker training leads to gains in
firms of different sizes and industries, and from in
productivity, training provided to unskilled work
ternal and external sources. The latter include
ers has no measurable productivity effects.
polytechnics, vocational schools, skill develop ment centers (SDCs), advanced training institutes
Among training sources, in-house company training
(ClAST), training institutions sponsored by dif
is most strongly associated with productivity gains
ferent government ministries (ITis, IKMs, and
except in local firms where training capabilities are
YTCs), and various private training institutes, buy
weak. The productivity effects of external training
ers and suppliers, joint venture partners, and train
varies by source for different firms, with SDCs and ClAST being most important for local firms and
ing overseas.
other private training providers for foreign firms. The key finding is that most firms either meet their skill needs in-house or through largely private sec
This chapter also analyzes the effects of training on
tor providers. With the exception of SDCs and
the average monthly wages of employees. The re
ClAST, other public training institutions play a rela
sults show that training leads to higher monthly
tively minor role in meeting the in-service training
wages. However, wage effects are smaller than pro
needs of private sector firms Though they currently
ductivity effects, suggesting that employers share
.
play a greater role in providing pre-employment
part of the productivity gains from training with
training, in future they will need to become more
their employees. The pattern of wage effects from
demand driven and work closely with the private
training parallels the productivity results, namely, that the wage effects of training are larger in firms
sector.
that make complementary investments in new tech Analyses of the determinants of firm training also
nology, in foreign-owned firms, and to a lesser ex
yielded other findings. They show that firms train
tent in firms that export. Like the productivity
ing decisions are shaped primarily by firm size, by
results, training provided to skilled workers results
the educational, skill and sex mix of employees, by
in wage gains but not training to unskilled workers.
'
its technology level, whether it exports, foreign own
Finally, it provides some evidence that firms can
ership, the type of equipment used and whether or
lower job turnover by the employees through high
not employers emphasize quality control. Chapter 1hree analyzes the productivity impacts of formal, structured training provided by employers. Using a production function framework, it shows
wage policies. Productivity gains from increased training that comes from greater job retention of trained workers can offset higher wage costs. Chapter Four motivates the discussion of training
that training has a positive impact on raising the pro
policies by reporting employer perspectives on why
ductivity levels of firms. Furthermore, it demon
they do little or no training. This reveals that while
strates that the beneficial productivity impacts of
most firms do not train because of the low skill re-
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
8
quirements of relatively simple, standardized tech
to invest in R&D and technology licenses than
nologies used, a large number of firms, small and
wholly foreign-owned firms of comparable size,
medium size employers in particular, also cited high
which may reflect the greater reliance of wholly
labor turnover, lack of knowledge about how to train,
owned subsidiaries on the technology stock and
and limited resources, as reasons for not training.
R&D of the parent MNC.
These latter responses, coupled with evidence from
This chapter also touches on IS0-9000, a voluntary
previous chapters about the low incidence of train
standard of the International Standards Organiza
ing and high potential returns, suggest that many
tion that Malaysia has adopted. Over ten percent
Malaysian firms under-invest in training, and that
of firms in the MITP survey had some level of
several market failures pose important constraints
IS0-9000 certification, and 33 percent expected
on training. The chapter then presents the results of
to be certified within the next three years. How
detailed analyses of two training policies designed
ever, IS0-9000 adoption will still be relatively
to encourage employers to train-the Double Deduc
low in micro, small and medium firms, and should
tion Incentive for Training (DDIT) and the Human
be an important area of focus-both in terms of dis
Resource Development Fund (HRDF).
semination a n d technical assista n c e - f o r policymakers. The analyses indicate that firms
It describes the limited use of the DDIT by firms
with IS0-9000 certification, or those actively
and the reasons why many firms did not use this
seeking it, are more successful in exporting to in
training incentive. It reports some teething problems
dustrialized country markets.
with the HRDF, including what appears to be seri ous noncompliance to register and contribute to the
Chapter Six draws together the analyses of training
HRDF, and failure to take advantage of training re
and technology by investigating firm-level tech
imbursements. It is too early to judge the efficacy of
nical efficiency and its distribution. Using a fron
HRDF, but there is some evidence that it has indeed
tier production function framework, it estimates
promoted training and skill upgrading among the
of how far each firm is from "best practice" tech
sample of firms that have registered with the Hu
nology, and what factors determine its level of
man Resource
Development Council.
efficiency. The overall results echo many of the main findings reported in previous chapters
Chapter Five shifts the focus to use of new technol
younger, export-oriented firms, firms that employ
ogy, quality control systems, and IS0-9000 certifi
a more educated workforce, and those that pro
cation in Malaysian firms, and their implications
vide training, skilled worker training in particu
for changing skill requirements. It provides a broad
lar, are more efficient.
overview of research and development, technology licensing, use of testing equipment, automation, and
The efficiency estimates are used to characterize
equipment age among furns by size, local and foreign
the size distribution of efficiency in the MITP
ownership, and industry.
sample. The results show that SMis are not nec
While the MITP survey reveals more private sector
efficient than many larger firms. Their low aver
R&D than the 1992 MASTIC survey, its R&D esti
age efficiency level, compared to larger firms, is
mates are still relatively low compared to other coun
due to the fact that a high proportion of SMis have
essarily inefficient -some SMis actually are more
It shows marked differences in these
low efficiency and a high proportion of larger
technology indicators across firms, withjoint ven
firms have high efficiency. If SMis are not in
tries.
tures and wholly foreign-owned firms being more
herently inefficient, then it follows that their ef
technologically advanced as compared to local furns.
ficiency levels can be improved through policy
It finds, however, that joint ventures are more likely
interventions.
INTRODUCTION
9
Potentially important areas for policy are sug
Finally, Chapter Six reports some preliminary analy
gested by the profile of efficient firms by size.
ses of efficiency spillovers to local firms from linkages
Highly efficient firms tend to have technology li
with joint ventures and foreign firms. The results in
censes but not necessarily R&D; they export and/
dicate that a higher foreign presence is associated with
or; have some foreign capital equity; they pro
efficiency improvements for local firms and that part
vide formal structured training to both skilled
of these gains come from the R&D done by joint ven
and unskilled workers, and do not rely only on
tures, and part comes from the training that wholly for
informal OJT. Efficient firms emphasize qual
eign-owned firms give their employees.
,
ity, especially statistical process control; they use precision measuring instruments and do not rely
The report concludes with Chapter Seven. It sum
on visual inspection and are more likely to be
marizes the main findings and draws out their policy
seeking IS0-9000 certification. Highly efficient
implications in five areas: (i) collection and dissemi
firms have formed work organizations that seek
nation of training information; (ii) expanded role
to reduce job turnover, using high-wage policies
of education and training institutions; (iii) more ef
and compensation that includes severance pay,
fective training policies; (iv) technology diffusion
profit-sharing and bonuses to attract and retain
and promotion; and (v) better coordinated and pro
workers.
active SMI policies.
CHAPTER Two: OVERVIEW oF TRAINING In this chapter, the MITP Survey is used to paint a
training nor formal training; those that rely exclu
broad picture of enterprise training in the manufac
sively on informal on-the-job training from co-work
turing sector. We describe the incidence of training
ers and supervisors; and those that provide formal
by firm size and industry. We present estimates on
training, either in-house or from external sources.
training provided by employers and by a variety of external training institutions, both in terms of the
The figures on training are adjusted using sampling
proportions of employers using each training source
weights constructed from the 1988 industrial survey
and in terms of the number of workers trained. We
whenever aggregate figures are reported for the
use employer responses to gain insights into why a
manufacturing sector as a whole or by industry .1 The
substantial proportion of firms provide little or no
data are not weighted when figures are reported by
formal training to their employees. Finally, we esti
size since the MITP survey is already stratified by
mate regression models to identify the important fac
size. For the purposes of this report, we define four
tors which shape company decisions to train
firm size categories-micro firms (with 15 or fewer
different groups of workers and to rely on in-house
workers), small finns (with 16-100 workers), medium
versus external training providers.
firms (101-250 workers) and large firms (with more than 250 workers).
Incidence of Training
Table 2.1 shows the incidence of enterprise-spon sored formal training for the manufacturing sector as
The MITP Survey elicited a wealth of information
a whole and by firm size. Two points stand out. First,
on training. It asked a limited number of questions
a very high fraction of firms either provide their
about informal on-the-job training provided by co
workers with no training (32 percent), or they rely
workers and supervisors, and detailed questions
exclusively on informal, on-the-job training (48 per
about formal, structured training-the number of work
cent). Only 2 1 percent of all employers provide
ers getting formal training over the past year, by
their workers with any formal, structured training.
broad occupational group and by source of training.
Secondly, there are very marked differences in the
It distinguished between formal training provided
incidence of training by firm size. The proportion
in-house by the employer, and formal training ob
of firms that do not provide any training is highest
tained from a variety of external training institutions,
among the micro finns (34 percent) and lowest among
both public and private. The public training institu
the largest size firms (four percent). Conversely,
tions included polytechnics, vocational and techni
formal training is most common among the large finns
cal schools, advanced skills training institutes
(71 percent) and lowest among the smallest firms (10
(ClAST), Industrial Training Institutes (ITI), Insti
percent). Most firms which provide formal training
tute Kemahiran Mara (IKM), Youth Training Cen
also have informal on-the-job training, a point that is
ters (YTC), Skill Development Centers (SDC), and
apparent from a comparison of the last two rows of
other government institutes. The private training
Table2.1.
sources include buyers and material suppliers, joint venture partners, and private sector training institutes.
Table 2.2 presents the corresponding estimates of
We can broadly characterize training incidence by
reveal considerable cross-industry variation in the
classifying firms into three groups: thosethat provide
proportion of firms that do no training and those that
no training of any kind, neither informal on-the-job
provide formal training.
training incidence by 16 industrial sectors. They
OVERVIEW OF TRAINING
11
First, consider the industries where large numbers
electrical machinery, iron and basic metals, trans
of firms do no training. These include such tradi
port equipment, textiles, apparel, and rubber indus
tional domestic-oriented industries as wood and fur
tries are relatively training-intensive, with over 35
niture, paper and printing, glass and pottery,
percent reporting formal training.
fabricated metals, machinery, and food products where only 10-25 percent of firms provide formal
The high proportion of firms providing formal
training to their employees. On the other hand, the
training in electrical machinery, transport equip-
Table 2.1 Incidence of Training in Manufacturing and by Firm Size Mean Characteristics
Overall
Micro
Small
2,200
247
959
%Firms not training
31.8
33.6
14.8
5.2
3.7
% Firms with only informal training
47.6
56.3
58.7
43.6
25.6
% Firms doing formal training
20.7
10.1
26.5
51.2
70.7
% Firms formal & informal training
17.0
6.9
24.5
48.4
66.5
Number of firms with training data
Notes:
Medium
Large
535
454
Overall estimates are weighted; estimates by firm size are not weighted micro
=
15 or fewer workers;
small= 16-100 workers; medium = 101-250 workers;
large= over 250 workers. Source: 1995 MITP Survey
Table 2.2 Incidence of Training by Industry Industry
All Industries
#Firms
%Firms
with Training
not
only Informal
Data
Training
Training
%Firms
%Firms with Formal Training
2,195
31.8
47.6
20.7
265
34.2
40.4
25.4
Beverages & tobacco
152
30.0
68.5
1.5
Textiles
107
23.6
17.7
58.7
Food
Apparel
116
13.8
49.2
37.0
Wood & Furniture
306
58.1
31.1
10.7
Paper & Printing
126
55.5
26.8
17.6
90
16.9
57.5
25.6 35.1
Chemicals Rubber
131
32.1
32.8
Plastics
133
10.4
77.5
12.1
Glass & Pottery
143
36.4
42.2
21.4
Basic Metals Fabricated Metals Machinery
71
6.1
30.9
63.0
110
43.3
38.8
86
38.8
45.9
17.9 15.3
213
1.8
50.2
Transport equipment
78
9.8
41.1
48.0 49.1
Other Industries
73
23.9
68.1
7.9
Electric Machinery
Note: Estimates by industry are weighted using 1988 Industrial Survey weights. Source: 1995 MITP Survey
12
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
ment, iron and basic metals is not surprising since these capital-intensive industries tend to be quite technology-intensive.2 Electrical machinery, along with rubber and apparel are also major export oriented industries, and we speculate that export ers have greater incentives to train so as to produce high-quality products for international markets.3 In summary, these data appear to substantiate con
ventional beliefs about training in Malaysia, namely, that the larger firms are more likely to train their employees than smaller employers, and that enter prise training is related to capital intensity, technol ogy and export-orientation of industries. However, what is especially striking is the presence of large numbers of firms without any system of worker train ing at all, formal or informal. This shouldbe of con cern to Malaysian policymakers, given the critical role that skills play in technology acquisition and de velopment, and their presumed beneficial effects on productivity and wages. (These links are quantified in Chapters Three and Five.) Also worrisome is the high proportion of employers (48 percent) that rely exclusively on informal on the-job training (OIT). Informal OJT, while an inte gral part of the skill acquisition process, typically involves fairly basic skills such as familiarizing new hires with the firm's equipment and operating pro cedures-the "how to" -rather than the "why. " It excludes the higher-level problem-solving skills that can come from structured training courses grounded in theory. Both kinds of skills are needed; indeed, as noted earlier, most firms that provide formal training also train informally. What is of concern is that firms which rely only on informal training develop few of the critical problem-solving skills needed to acquire and master new technologies and improve productiv ity. This fact, coupled with evidence indicating that informal OJT has no measurable impact on wages or fum-level productivity,4leads us to focus on formal structured training in the remainder of this report.
Sources of Enterprise Training
Table 2.3 shows the different ways in which firms provide formal in-service training. It distinguishes between formal in-house company training and external sources of training, both public and pri vate. Of the 21 percent of employers that train formally, about an equal proportion of them ( 13 percent) use in-house resources as external train ing providers. The bottom panel of Table 2.3 shows the relative importance of each external training source as re ported by enterprises. Conditional on the employer providing external training, the most commonly cited external sources are private training insti tutes (34.9 percent), followed by Skills Develop ment Centers (25. 8 percent), A dvanced Skills Training Institutes (21.3 percent), and their buy ers and material suppliers (11 percent).
Table 2.3 Internal and External Sources of Training Percentage of Firms
Source of Training• %Any Formal Training
b
20.7
% Internal Formal Training
12.6
% External Formal Training
13.0
External Sources of Training c Polytechnics Vocationalffechnical Schools
4.0
Advanced Skills Training Institutes
3.2 21.3
Skills Development Centers (SDC)
25.8
Institute Kemahiran Mara (IKM)
1.2
Industrial Training Institute (ITI)
5.3
Youth Training Centers (YTC)
0.5
Other Government Institutes
8.2
Joint Venture Partners Buyers/Material Suppliers Private Training Institutes Overseas Training
3.6 11.0 34.9 4.6
The numbers are weighted using 1988 Industrial Survey weights. Includes firms that train formally either inside the firm or from external sources. Conditional on doing external training. Source: 1995 MITP Survey
OvERVIEW oF TRAINING
13
It is plausible that these are external providers with
skills, not for the intermediate or advanced-level skills
capabilities to flexibly provide higher-level skills
that are needed after entering employment.
training to firms. The high proportion of firms that report using skill development centers (SDCs) is strik
For policymakers, the issue is whether these public
ing, especially since most of them (other than the
institutions should continue to limit their training ac
Penang SDC) were only established in the past three
tivities to pre-employment training, or whether they
years. The least commonly cited external sources
also have a role to play in post-employment skills
of training are government-run training institu
upgrading. One aspect of this issue-the limited in
tions-theYouth Training Centers (0.5 percent), IKM
service training provided by these institutions-can
institutes
be studied (see C hapter Three); however, the
(1.2 percent), vocational and technical schools (3.2 percent), and other government insti tutes (8.2 percent).
broader issue can only be addressed by a different study and is beyond the scope of this report.
The relatively small role of government training in
Table 2.4 disaggregates the different sources of train
stitutes reflec� their focus on pre-employment train
ing by firm size. The top panel shows the propor
ing, not in-service training that is the subject of the
tions of firms that provide formal training in-house
survey. The exceptions are the public agencies in
and externally. In general, the use of both training
the "other" category, such as SIRIM and NPC which
sources rises with firm size, with a higher proportion
provide a variety of training and other services di
of small and medium firms training in-house than us
rectly to the private sector. 5 This orientation towards
ing external training providers.
pre-employment training is borne out by data on National Vocational Training Council (NVTC) ad
The bottom panel shows, for the firms that train ex
ministered trade tests taken by graduates from dif
ternally, the proportion of employers citing each
ferent public training institutes. Most YTC, m, and
external source of training. (Note that figures for the
IKM graduates are tested for competencies in basic
micro firm size group are not reliable since less than
Table 2.4 Sources of Training by Firm Size Source of Training
Micro
Small
9.1 5.2 5.2
18.2 13.5 7.6
% Firms training formally % Firms training in-house % Firms training externally
Medium
Large
44.7 31.7 27.0
70.6 53.6 51.4
5.1 3.1 6.3
9.3 4.2 19.9
14.9
28.8
2.3 11.0 1.2* 22.7 9.8 25.1 44.3 12.9
5.1 18.2 2.1 27.1 11.9 25.0 53.0 21.2
External Sources of Training•
Advanced Skills Training Institutes
12.5* 12.5* 12.5*
Skills Development Centers
25.0*
Polytechnics Vocationai!Technical Schools
2.0* 0.0 8.2* 10.2
Institute Kemahiran Mara (IKM)
0.0
4.1*
Industrial Training Institute (ITI)
12.5* 0.0 0.0 0.0 25.0* 25.0* 0.0
0.0 2.0* 20.4 10.2 24.5 28.6 8.2
Youth Training Centers Other Government Institutes Joint Venture Partners Buyers/Material Suppliers Private Training Institutes Overseas Training Conditional on doing external training. *
very small sample sizes (3 or less observations).
Source: 1995 MITP Survey
14
ENTERPRISE TRAJNJNG, TECHNOLOGY AND PRODUCTIVITY
Table 2.5 Workers Trained, Overall and by Firm Size SourceofTraining
NumberofWorkers Trained Overall
Micro•
Small
Medium
Large
Any formal training
195,8 94
35,08 4
13,917
34,5 4 9
112,343
Internal formal training
167,6 14
28,716
12,396
27,286
99,2 14
28,279
6,367
1,52 0
7,262
13,128
External formal training
% workers with formal training
21.7
8.9
10.4
13.2
29.5
% workers with internal training
18.6
7.2
9.2
10.5
26.1
% workers with external training
3.1
1.7
1.1
2.8
3.4
External Training Sources Polytechnics
647
154
24
121
Vocational schools
477
154
0
92
230
Advanced Skills Training Institutes
2,197
1,255
39
198
703
Skill Development Centers
347
7,611
3,844
278
488
3,000
ITIs
833
154
0
232
446
IKMs
275
0
84
113
77
96
0
18
34
43
Other government institutes
1,605
0
160
697
747
Buyers & suppliers
1,792
22
312
548
909
Joint venture partner firms
1,508
0
213
355
938
10,359
782
321
3,972
5,283
872
0
67
405
399
YTCs
Private training institutes Overseas training
Estimates not reliable because of small sample size. Note:
Estimates of numbers trained are weighted using 19881ndustrial Survey weights.
Source: 1995 MITP Survey
five percent of them rely on external training pro
We estimate there figures by using the firm's responses
viders.) The table clearly shows variation in the use
about the numbers of workers trained from each
of different external sources by firms of different
source, and inflating them using size-based weights
size. Training provided by private institutes contin
constructed from the
1988 Industrial Survey. 6
ues to be the single most commonly cited external train ing source.
We caution that these are rough estimates, given changes since 1988 not only in the number of firms
Among the other sources, both small and medium
but also their composition. The estimates for micro
firms are most likely to cite training from buyers
enterprises are likely to be quite imprecise, given
materials suppliers and from other government insti
their small numbers in our sample (153 firms) and
tutes. Large firms are most likely to cite SDCs, other
correspondingly large weights assigned to them.
government institutes, buyers and suppliers, ad
We are much more confident of the estimates for
vanced skills training institutes, and to a growing ex
the small, medium, and large firms where our
tent, ms as well.
sample sizes are larger. We note that this proce dure yields an estimate of the manufacturing workforce of just under one million
Workers Getting Training by Source
which is to be expected since
(900,493), 1988 sample weights
are used. The number of workers trained provides another perspective on the relative importance of the differ
Table 2.5 presents estimates of the number of work
ent in-house and external sources of formal training.
ers receiving formal training by source in the manu-
OVERVIEW OF TRAINING
15
facturing sector, and separately by four firm size
firms or on numbers of workers trained. Both mea
categories.
sures point to the dominant role of private training
First, consider the overall estimates. They suggest
that 196,<XX> workers received fonnal training in 1993, of which 168,000 were trained in-house and just
28,CXX> were trained by external providers. As a share of the total workforce, these represent 21.7 percent for any formal training, 18.6 percent for in-house training, and 3 .1 percent for external training.
institutes, SDCs, and advanced skills training insti tutes which provided training for 10,359 workers, 7,611 workers, and 2,197 workers, respectively. The numbers of workers trained by buyers and materials suppliers and partner firms are as large as the numbers trained by "other government training institutes," and considerably larger than the indi vidual contributions of lTis, IKMs, YTCs, polytech
The overall results are comparable to those based on the proportion of finns that train, but the mix of in house and external training differs widely. While an equal proportion of firms report using in-house and external training sources (13 percent), the. esti mates based on workers trained suggest that fums are giving in-house training to a significantly larger number of employees than they are sending outside for training.
nics, and public vocational and technical institutes. Table 2.5 also presents separate estimates of the num ber of workers trained by fum size. The estimates for micro fums are likely to be unreliable, and will not be emphasized in the following discussion. For the other firm sizes, these worker-based estimates reinforce the points made earlier using utilization rates of finns . For small firms, training provided by private training institutes, buyers and materials sup
The relative importance of each external training source is broadly comparable irrespective of whether estimates are based on utilization rates of
pliers, and SDCs are of roughly equal importance. For medium and large firms private training insti ,
tutes have by far the most significant role in external
Table 2.6 Number of Workers Trained by Industrial Sector Number of Workers Trained Industry
Percent of Workforce
Any
Internal
External
Any
Internal
Formal
Formal
Formal
Formal
Formal
Formal
Training
Training
Training
Training
Training
Training
External
Food
6,331
4,348
1,982
2.9
2.0
0.9
Beverages & tobacco
1,661
1,307
1.0
11,807
11 '180
353 626
0.7 9.9
0.2 0.5 0.1
Textiles
10.4
Apparel
8,549
8,395
153
3.8
3.8
Wood & Furniture
9,773
8,809
964
22.8
20.6
2.2
Paper & Printing
4,139
3,259
880
1.9
0.5
1.5
0.8
3.0
1.2
Chemicals Rubber
4,157
2,705
1,451
2.4 2.3
10,055
7,251
2,803
4.2
7,779
5,871
1,907
8.0
6.0
2.0
Glass & Pottery
10,653
9,358
1,294
33.2
29.2
4.0
Iron & Basic Metals
32,082
25,683
6,399
73.4
58.8
14.6
6,694
6,020
673
3.2
2.9
0.3
Machinery
11 '129
10,193
936
6.8
6.2
0.6
Electric Machinery
Plastics
Fabricated Metals
58,730
52,701
6028
38.8
34.8
4.0
Transportation
5,301
4,319
982
4.7
3.8
0.9
Other industries
7,046
6,207
839
3.5
3.1
0.4
Note: Estimates are weighted using 1988 Industrial Survey weights. Source: 1995 MITP Survey
16
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 2. 7 Workers Getting Formalin-House Training by Skill Group Occupational Group
Number
Total Number
Percentage
Trained
of employees
Trained
Supervisors
17,109
67,713
25.3
Technicians
15,105
47,396
31.9
Skilled Production Workers
76,074
462,855
16.4
Unskilled Production Workers
59,327
443,051
13.4
Note: Estimates weighted using 19881ndustrial Survey weights Source: 1995 MITP Survey
training, though SDCs, buyers and suppliers, part
They suggest that, on average, a higher proportion of
ner firms, and other government institutes are also
technicians (32 percent) and supervisors (25 percent)
responsible for training a sizeable number of work
are trained as compared to production workers (13-16
ers. Particularly striking is the heavy use of SDCs
percent); however, skilled production workers are
by the largest furns which sent about 3,000 workers
more likely to be trained (16 percent) than unskilled
for training in SDCs and 5,283 workers for training
production workers (13 percent).
in private training institutes. Though not reported in Table 2.7, the data indicate that In Table 2.6, we report more aggregated statistics on
production workers are also less likely to get external
the number of workers trained by industrial sector,
training (14 percent) as compared to non-production
as well as their share of the workforce in each indus
workers (28 percent).
try. The latter measure is particularly significant given the recommendation of the Industrial Master Plan
In Table 2.8, we report the numbers trained by ex
(IMP) that employers provide training to 10 percent of their work force (Mill, Review ofthe IMP, 1994)_7
production workers, as well as the proportion getting
ternal source of training for production and non training in each occupation. The figures show that
By this yardstick, it appears that the target of 10 per
private training institutes and SDCs are the most im
cent training has only been achieved in five out of
portant external sources of training for both groups.
the 16 industrial sectors under consideration-iron and
However a higher proportion of non-production
basic metals (73 percent), electric machinery (39 per
workers get training from private training institutes
cent), glass and pottery (33 percent), wood and fur
(52 percent) than from SDCs (18 percent), while pro
niture (23 percent), and textiles (lOpercent). In the
duction workers are more likely to get training at
other industrial sectors, the proportion of the work force
SDCs (31 percent) than at private training institutes
getting training is considerably lower. The indus
(26 percent).
tries with the lowest figures (less than three percent
trained) include food products, beverages and tobacco, paper and printing, and chemicals.
Other key external sources for both groups of work ers are buyers and suppliers-who provide the train ing to meet their product requirements or to use
Which workers are getting training? Table 2.7 pre
their equipment-and advanced skills training insti
sents estimates of the numbers trained in four
tutes. As before, few workers get training at ITis,
broad occupational groups-supervisors, techni
IKMs, youth training centers and vocational schools,
cians, and skilled and unskilled production work
reflecting the primary orientation of these public
ers-as a proportion of the total number of employees
training institutions to pre-employment training in
in the relevant occupation.
basic skills.
OvERVIEW OF TRAINING
17
labor, and whether the firm is unionized. Two-digit
Factors Shaping Training Decisions of Firms
industry dummy variables control for other industry differences.
With this overview of training as background, we
In the discussion that follows, we summarize the ef
now turn to a more formal analysis of the factors that shape firms' decisions to provide their employees
fects of the most important regressors on the likeli
with formal structured training, and whether the de
hood of the employer providing any formal training,
terminants of training differ by skill group and by
by skill group, and by training source. The coeffi
training source. To address these issues, we esti
cients estimated by the probit model (these are re
mate separate probit regression models for any for
ported in Annex Table 2.1) provide insights into the
mal training, training for production workers and
statistical significance of each variable and the direc
non-production workers, and in-house versus ex
tion of its effects on training. However, they cannot
ternal training.
be interpreted as marginal effects because of the non-linear nature of the probit model.
The likelihood of an employer providing each type of training is hypothesized to depend on the relative
To facilitate interpretation, we report instead the
costs and benefits. It equals one if the present value
marginal effects of the probit model evaluated at the
of training exceeds its cost, and equals zero other
sample means of each variable. The marginal ef
wise. The net benefits of training (benefits minus
fects from different probit models are presented to
costs) are not directly observed, but are thought to
gether in Table
be related to a set of observable attributes of the
regressors across the different training measures.
2.9 to facilitate comparisons of
employer. These firm attributes include firm size; worker characteristics such as educational attainment
Firm Size
and skill mix; its level of technology as reflected in
Table 2. 9 confirms that training probability is strongly
its R&D expenditures and its purchases of know
related to firm size. Relative to micro firms (the omit
how; exporting, and foreign capital participation; or
ted size category), small, medium and large firms are
ganizational factors such as the degree of automation,
14, 35 and 53 percent more likely to provide any
use of quality control methods, employment of female
formal training. The importance of firm size, con-
Table 2.8 Workers Trained from External Sources by Occupation Production Workers External Source of Training
Polytechnics Vocational/Technical Schools Advanced Skills Training Institutes Skills Development Centers Institute Kemahiran Mara (IKM) Industrial Training Institute (ITI) Youth Training Centers Other Government Institutes Joint Venture Partners Buyers/Material Suppliers Private Training Institutes Overseas training Note: Source:
Estimates weighted using
1995 MITP Survey
Non-Production Workers
Number
Proportion
Number
Proportion
Trained
Trained
Trained
Trained
2.4 2.1 9.6 31.3 1.2 3.4 0.5 4.1 6.9 10.0 25.7 2.6
219 99 503 2,065 56 228 2 876 294 644 5,810 406
1.9 0.9 4.5 18.4 0.5 2.0 3.6 7.8 2.6 5.7 51.8 3.6
429 379 1,649 5,546 219 605 95 726 1,214 1,767 4,550 466
1988 Industrial Survey weights
18
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
trolling for the other correlates of training (includ-
The effects of firm size on training probability dif-
ing level of technology), may reflect scale econo-
fer by skill group: compared to micro firms, the
mies in training provision, the greater access of large
likelihood of training for skilled workers in large
firms to resources for training, and unobserved em-
firms rises to 61 percent as compared to only 43 per-
player attributes associated with improved manage-
cent for unskilled workers, a trend evident in the
ment and training capabilities.
simple tabulations reported earlier. Larger firms are Table2.9 Marginal Effects on the Likelihood of
Formal Training Estimated from a Probit Model
Independent Variable
Any
In-house
External
Skilled
Formal
Formal
Training
Worker
Worker
Training
Training
Training
Training
0.138 IJI
Small Firm Size (16-100 workers)
(0.067) 0.348�1
Medium Firm Size
(0.065)
(1 01-250 workers)
0.529�
Large Firm Size (over 250 workers)
(0.070)
Mean education
0.024�
of the workforce
(0.007) 0.006 �
Percent of skilled workers
(0.001) 0.140al
Invests in R&D
(0.030) 0.071 a!
Foreign capital participation Exports
Proportion of female
0.026 a! (0.006)
0.002 �
0.005 a!
0.003 a!
0.006 �
(0.0008)
(0.0007)
(0.0008)
(0.0008)
0.135-'!1 (0.026) 0.080 a!
0.095 � (0.023)
0.112 � (0.026)
-0.007
0.019
(0.020)
(0.023)
0.151 a! (0.027) 0.080 �
0.008
0.031
0.001
(0.024)
(0.022)
(0.024)
(0.026)
(0.025)
0.001
0.001 �
0.001 �
0.004
(0.001)
(0.0002)
(0.0003)
(0.003)
0.101 a! (0.023)
0.0431J/
0.128 a!
(0.020)
(0.023)
0.084 a! (0.024)
0.024
0.008
0.013
-0.051
0.005
(0.047)
(0.041)
(0.037)
(0.042)
(0.043)
(0.031) -1133.40
Log (likelihood)
0.025 a! (0.081)
0.430 � (0.071)
-0.004
0.060..£1
Unionization
0.016 a! (0.005)
0.606 � (0.094)
0.224 � (0.060)
0.010
(0.026)
workers
0.028 � (0.006)
0.488 � (0.080)
0.395 � (0.081)
0.085 (0.061)
(0.027)
0.103 a!
Use of quality control methods
0.426 � (0.074)
0.253 � (0.062)
0.168 cJ (0.086)
(0.024)
(0.0003)
automatic machinery
0.261 � (0.063)
0.059 (0.063)
(0.027)
0.001
%Value of
0.129 IJI (0.065)
Unskilled
0.027 (0.026) -1090.86
0.059 � (0.024) -918.23
0.0661Ji
0.020
(0.027)
(0.028)
-970.59
-1102.68
a= Significant at 1% b=
Significant at 5%
c =Significant
Note:
at 10% level
Numbers in parantheses are standard errors. Omitted firm size is micro enterprises with 15 or fewer workers. Age of firm and multi-plant status included but were not statistically significant.
Source: Annex Table 2.1.
OvERVIEW
OF
TRAINING
19
also more likely to use both in-house and external
both skill groups. Thus, unskilled workers enjoy an
training sources than their smaller counterparts.
externality by working in a workplace with a high proportion of skilled workers.
Education and Skill Mix The training effects of education stand out. The
The Firm's Technology
results indicate that employers are more likely to
The results provide strong evidence that skill and
provide formal training for all groups and from all
training requirements are shaped by the firm's tech
sources the more educated are their workers. A
nology. Firms that invest in research and develop
one year increase in the education of the workforce
ment (R&D) are about 10-15 percent more likely to
(the mean in the MITP sample is 8. 7 years of school
train formally than firms without R&D.
ing) is associated with a two to three percent higher probability of training. The significant positive rela
The results, by skill group, suggest that while R&D
tionship is strong evidence that the two kinds of hu
firms are more likely to train both production and
man capital-education and training-are highly
non-production workers than firms not doing R&D,
complementary. Educated workers are better
the likelihood of their training production workers is
learners and thus benefit more than less educated
actually higher.
workers from training. A higher level of work force education also raises the probability that the firm will train in-house relative to sending workers for external training, a result evident from the rela tively larger estimated effects of education for in house training.
Workers typically require little formal instruction, beyond some informal OJT by co-workers, to oper ate mature well-established technologies. When new technologies are being introduced, however, pro duction is no longer routinized. Under these new and challenging circumstances, formal structured
Firms with a more skilled workforce are more likely
training for all workers-both production and non
to train. Skill mix is measured as the percentage
production-becomes critical if unanticipated prob
share of managers, engineers, technicians, supervi
lems are to be detected and fixed, and the
sors, and skilled production workers in the total work
productivity advantage of using new technologies
force of the firm. Controlling for education (and
over mature technologies are to be realized.8
other factors), a one percent increase in the skill mix is associated with roughly half a percent increase in the probability of training.
Doing R&D has different effects on where employ ers train their workers. The marginal effects of do ing R&D on training probability are larger for
The results also indicate that skill mix of the work
in-house programs (13.5 percent) than for training
force is a more important determinant of external
from external sources (9.5 percent).
training than of in-house training. To the extent that skilled worker training tends to be highly technical and specialized, employers may fmd it more eco nomical to send non-production workers to external training providers than to develop these programs
These results-that R&D finns are more likely to train their workers in-house-are consistent with the hy pothesis that the use of advanced technologies is associated with a greater reliance on training in
in-house.
house than on external. 9 In part, this is because
There is also evidence that a more highly skilled
train in new technologies when extant knowledge is
external training providers are not well-equipped to
workforce is associated with a greater probability
so limited; and in part, because in-house experience
of training for both skilled workers and unskilled
working with, and adapting, new technology devel
workers. The skill mix variable is positive for
ops the firm's technological capabilities.
20
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Exports and Foreign Ownership
technology. These results suggest that automation
We hypothesize that finns can acquire relevant and
will require greater efforts on the part of employers
best-practice technology through their links with
to tram non-production workers and to send them
foreign buyers and foreign firms operatirig locally,
for external training.
and are therefore more likely to trairi their employ ees. However, the results suggest that exportirig is
On average, employers that emphasize quality con
not associated with trainirig. The weak result may
trol methods are between four and
be reflecting the high correlation between exports
likely to train than those frrrns without quality con
and other firm attributes, such as foreign capital
13 percent more
trol. This result is significant for training provided to
participation, which are already included in the
all groups of workers and for trairiiri g from both ill
regression.
house and external sources.
Foreign firms are in general about seven to eight
A second result is suggested by comparing the rela
percent more likely to provide trairiirig for their em ployees as compared to local firms. Note that this
tive size of the estimated margirial effects on trairiirig for each skill group and for each training source.
marginal effect persists even after controlling for
These comparisons iridicate that employers using
other factors, many beirig characteristics of multina
quality control methods are more likely to trairi skilled
tionals such as R&D, exports, and firm size.
workers (13 percent) than unskilled workers (eight
Foreign firms are eight percent more likely to tram
opposed to sending them offsite for trairiirig (four
ill-house than local firms, but not when it comes to
percent).
percent), and to tram them ill-house
(10 percent) as
external trairiirig. This may reflect well-developed ill-house trairiirig capabilities, sirice many are large
Use of Female Labor and Unionization
multinationals irivolved iri technology intensive semi
We iriclude two other variables to characterize work
conductor and electronics production and assem
organization in the firm-the use of female labor and
bly. Finally, while foreign firms are no more likely to
unions. Use of large numbers of female workers
train skilled workers than local firms, they are signifi
may reflect forms of organization built around simple
cantly more likely to trairi their unskilled employees.
assembly, manual dexterity, seasonal work, and rela
Automation and Quality Control
support for this hypothesis in Malaysia.
tively low skills. However, there appears to be little The model included two variables-the degree of equipment automation and use of quality control
Controlling for mean education and skill composi
methods-to irivestigate the trairiirig effects of mod
tion, a workforce with a higher proportion of female
em modes of production organization. Automation
workers is not associated with a lower likelihood of
can either lead to the "dumbirig down" of skills, as
training. This is important in the context of tight labor
some have argued, or to iricreased skill requirements
markets in Malaysia for it suggests that iricreased use
to operate and maintairi iricreasirigly sophisticated
of female workers to meet iridustry's labor needs is
equipment. The results suggest that the probability
unlikely to have deleterious effects on firm-level
of formal training is higher the greater is the per
productivity, provided women are similarly educated
centage share of the firm's machinery and equip
and given the same formal trairiing as their male coun
ment that is semi- or fully automatic.
terparts.
Malaysian policymakers have stressed the need for
In theory, unions are thought to reduce the likeli
iridustry to become more automated, both to con
hood of training by negotiating higher levels of
serve on increasingly scarce labor and to deepen
wages and reducirig the ability of employers to lower
OVERVIEW OF TRAINING
wages to finance firm-specific training through a
21
With the exception of SDCs and ClAST, two in
training wage. However, when statistically signifi
stitutions that are either demand-driven or that cater
cant union effects on training are found, they are
to higher-level skills training, the other public
invariably positive and about six to seven percent
training institutions-IDs, IKMs, YTCs, polytech
higher as compared to non-unionized firms. Simi
nics, and vocational and technical schools-play a
lar results have been reported in several industri
very minor role in meeting the in-service training
alized countries (see Lillard and Tan, 1992, Tan et
needs of the manufacturing sector. Their primary
al, 1992).
focus thus far has been on pre-employment train ing in basic and intermediate-level technical skills.
The union effect is strongest in increasing training
Given their limited role in in-service training, it is
from external sources (six percent) and training for
clear is that the private sector will have to take on
skilled workers (seven percent). Unions may have
greater responsibilities for meeting its growing skill
this beneficial effect on training by giving workers
requirements.
an alternative to job turnover. By establishing griev ance and arbitration procedures, unions promote
The Government can, and is, helping facilitate in
greaterjob stability and increase incentives for finns
creased private sector-led training through the Hu
to invest in training.
man Resource Development Fund, through seed-grants to set up private sector-managed SDCs in the different states, and through subsidized credit,
Findings and Policy Implications
training, and technical assistance for the population of small and medium-scale firms that are most likely
Manufacturingfirms in Malaysia under-invest in
not to train or to tely on informal on-the-job training
the training of their employees. This is based on
(these policies are assessed subsequently).
our estimates that about 80 percent of all firms ei ther do no training or rely exclusively on infor
However, the design and implementation of these
mal training from co-workers and supervisors, and
training and related policies are rarely accompanied
that only 21 percent of firms provide formal training.
by adequate monitoring of their take-up, or by pro gram impact analyses, both of which require a sys
This conclusion is bolstered by the responses of
tematic data collection effort.
employers (reported later in Chapter Four) about why they provide little or no training. Most cite
The Government's existing system for training data
the use of mature technology as the principal rea
collection and analysis isfragmented and should be
son for doing little training. While this is not a
strengthened. Data on public training institutions
market failure per se, a sizeable number of other
are typically maintained by each responsible minis
employers, smaller firms in particular, cite other
try but seldom reported, on a systematic basis to
training constraints that are-free ridership from
gether with detailed cost data, to a central coordinating
high labor turnover, lack of knowledge about train
agency for planning and policy analysis.
ing methods, and limited resources for training. Likewise, information on private-sector training in
Finns that train meet their skill needs in-house or
stitutions is only collected on an ad hoc basis. Few
through a variety of external training sources. Of
evaluation studies of training programs-based on
the external training sources, firms rely most
tracer surveys of graduates, comparisons with a con
heavily on private providers-private training in
trol group, and cost-benefit calculations-have been
stitutes, buyers and equipment suppliers, joint
conducted; evaluations comparing different public
venture partners, a n d overseas training
training institutions are even rarer. The National
institutions.
Vocational Training Council (NVTC) was designated
22
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
as the institution to coordinate both public and pri
provide DOS with the necessary resources and in
vate vocational training programs, and the Govern
centives to implement and speedily process the aug
ment should give NVTC the necessary legal standing,
mented surveys on a periodic basis.
resources, and capabilities to play this role more ef fectively.
Several determinants of enterprise training stand out. First, smaller firms are much less likely to train than
Least well developed is in formation on in-service
larger firms suggesting that this groups will require
training. Existing industrial and household surveys
special attention from policymakers. Second, em
fielded by the Department of Statistics (DOS) are
ployers are more likely to train when its workforce
,
potentially potent, but currently under-exploited,
is better educated and more technically skilled since
vehicles for developing these training data bases.
they benefit more from training. As such, firm incen tives to train should increase as education policies to
A great deal of demographic and employer infonna
promote higher school retention rates and more tech
tion is already elicited in these surveys. The addi
nical education are implemented.
tion of a short training module to each survey thus provides nationally representative estimates of train
Investments in new technology, automated equip
ing at the level of the enterprise and at the level of
ment, and quality control are associated with in
the individual. Once institutionalized, these aug
creased training, a fact that reinforces the need for
mented firm- and worker-level surveys will yield
continuous skills upgrading if firms are to adopt
time-series data needed for policymakers to monitor
more technology-intensive production. Finally,
and analyze training trends. The Government
local firms are in general much less likely to train
should set up a committee to design, fund, and coor
relative to foreign firms, reflecting both their weak
dinate analyses using these training modules, and
training capabilities and lack of a training culture.
OVERVIEW OF TRAINING
23
Annex 2.1 The following table reports the parameter estimates of probit models for different training measures, where the dependent variable is one if an employer invests in that source or type of training, and zero otherwise.
While these estimates provide insights into the significance of explanatory variables and the
direction of their impact on the training outcome, they are not readily interpreted because of the non-linear nature of the dependent variable which is constrained to lie between 0 and 1.
However, the marginal
effects of explanatory variables can be calculated and they are reported in the text.
Pro bit Estimates of the Likelihood of Formal Training Independent Variable
Any Formal Training
Small Firm Size
0.362 �/
(16-100 workers)
(0.176)
Medium Firm Size
0.939 �
(101-250 workers)
(0.176)
Large Firm Size
1.446 �
(over 250 workers)
(0.193)
Mean education of
0.064 �
the workforce
(0.019)
Percent skilled
0.0174 �
workers
(0.0023)
Invests in R&D
0.365 � (0.078)
Foreign capital
0.188 �
participation Exports
%Value of automatic machinery Use of quality
Proportion of
Unionization
Log (likelihood) •
Note:
0.801 � (0.192) 1.182 � (0.207) 0.088 � (0.019) 0.0063 � (0.003) 0.395-£1 (0.076) 0.243 �
Unskilled
0.221 (0.232) 0.924 � (0.228) 1.477 � (0.084) 0.062 � (0.021) 0.0194 � (0.003) 0.334 � (0.080)
0.518'"' (0.264) 1.265 � (0.259) 1.748 � (0.271) 0.081� (0.020) 0.0110 � (0.003) 0.344 � (0.079)
-0.029 �
0.064
(0.079)
(0.075)
0.246 (0.177) 0.657 � (0.176) 1.172 � (0.192) 0.076 � (0.019) 0.0167 � (0.002) 0.424 � (0.076) 0.233 �
0.027
-0.012
0.030
0.101
0.002
(0.074)
(0.077)
(0.084)
(0.081)
(0.076)
0.002
0.001
(0.001)
(0.001) 0.309 � (0.071)
0.004 � (0.001) 0.160 �/
0.004 � (0.001) 0.403 �
(0.076)
(0.073)
(0.073)
0.001 (0.001) 0.245 � (0.071)
0.065
0.025
0.048
-0.167
0.016
(0.127)
(0.128)
(0.141)
(0.137)
(0.128)
0.158.l0'
Constant term
0.385 � (0.193)
Skilled
Worker Training Worker Training
(0.073)
(0.070)
female workers
External
(0.072)
0.272 �
control methods
In-house
Formal Training Training
0.082
0.215 �
0.207 �/
0.059
(0.083)
(0.083)
(0.086)
(0.085)
(0.083)
-1.808 �
-2.305 �
-2.331 �
-2.514 �
-2.214 �
(0.326)
(0.336)
(0.374)
(0.387)
(0.329)
-1090.86
-918.23
-970.59
-1102.68
-1133.40
= Significant at 1%
b
= Significant at 5%
c
=Significant at 10% level.
Numbers in parantheses are standard errors. Omitted firm size is micro enterprises with 15 or fewer workers. Age of firm and multi-plant status were also included but were not statistically significant
Source: 1995 MITP Survey
CHAPTER THREE: PRODUCTIVITY
AND
wAGE OUTCOMES
In this chapter, we tum to an empirical analysis of the
rizes the complex engineering relationships be
outcomes of enterprise training-both on firm-level
tween the firm's output and the inputs used to pro
productivity and on the wages of workers. We are
duce that output- plant and equipment, labor,
interested in finding out whether employer investments
intermediate inputs and energy.
in formal training are associated with higher firm-level productivity. Other issues of interest are whether
It can be specified in many ways, but the specifi
there are productivity differences in the training pro
cation that we will use is the Cobb-Douglas pro
vided to different groups of employees, for example,
duction function.1 The firm's output is measured
skilled or unskilled workers, and which source of
as the natural logarithm of value-added, that is
training-in-plant training programs or training pro
gross output less the value of intermediate inputs
vided by external institutions--has the largest im
and energy used, and this is related to the firm's
pact on firm-level productivity.
use of the two major factors of production - capital
We also examine the relationship between training
labor (total employment), both-also expressed in
and monthly wages paid by employers. The issue is
logarithms.
(book value of physical plant and equipment) and
whether the productivity gains from training are shared with workers in the form of higher pay and, if
In this Cobb-Douglas functional form, the coeffi
so, what kinds of training have the largest wage ef
cients of capital and labor represent their relative
fects and which groups of workers benefit most. 1his
contribution to output, and they typically sum to
analysis of the productivity and wage outcomes of train
one, or roughly constant returns to scale. The pro
ing has ramifications for employers, workers and
duction function that we estimate is augmented to
policymakers. Insights into the effects of training on
include different training measures and a set of con
firm-level productivity are important for employers
trol variables.
who must make decisions about whether to train, who to train, and what kinds of training to sponsor.
The training measures range from simple indicator
For workers, these wage gains, if any, represent an
training-to more complex ones, such as training pro
incentive for them to undertake training and a moti
vided to different groups of workers, training by
vation for them to develop long-term job attachment
source (in-house versus external training), and type
to the firm. This is important since high job turnover
of external training providers. These training mea
variables-whether employers provide any formal
reduces employer incentive to invest in workers'
sures allow us to ask whether training investments
skills. The training outcomes are also of interest to
are associated with higher firm-level productivity,
policymakers concerned with issues of economic
controlling for inputs of capital and labor, and for the
performance, resource allocation, design of training
influences of other contemporaneous variables that
policies, and income distribution.
also affect productivity. The latter include the average educational attain ment of the firm's workforce, indicator variables for
Estimating the Productivity Impact of Training
firm characteristics such as whether it exports or in
We analyze the productivity outcomes of employer
licensing agreements), and two-digit industiy dummy
investments in fonnal training within a production func
variables to control for productivity differences
tion framework. The production function summa-
across industries.
vests in technology (measured by R&D or technology
PRODUCTIVITY AND WAGE OUTCOMES
25
Our production function approach takes into account
function. Using the predicted, rather than the actual
the possibility of" selectivity bias" in estimating train
value of the training variable in the production func
ing outcomes. Tills bias may arise if firms have very
tion allows us to get unbiased estimates of the pro
different underlying productivity endowments, and
ductivity effects of training.
the firms that choose to train differ systematically from non-training firms in both their observed and unob served productivity attributes. To the extent that we
Productivity Effects of Training for
cannot fully control for these unmeasured differ
Different Firms
ences, the production function may over or under state (bias) our estimates of the productivity impact of
We begin by presenting estimates of the productiv
training. We use an instrumental variable approach
ity effects of formal training provided by different
to correct for this potential "selectivity bias."
groups of employers. In defining these different groups, we rely on the findings in Chapter Two,
In Chapter Two, we report the results of estimating
namely, that the likelihood of training is greater in
probit models for the firm's decision to train. Here,
larger firms in firms using new technology, in ex
we use those probit results to construct a predicted
porting firms, and in foreign-owned firms. If the
value for the training variable that, by its construc
higher incidence of training in these firms is indica
,
tion, is uncorrelated with the unmeasured produc
tive of the relative profitability of investments in
tivity attributes (the error term) in the production
worker training, we should also expect to find rela-
Table 3.1 Production Function Estimates by Firm Size Independent Variable
Overall
Small
Medium
Large
Log (labor)
0.576• (0.039)
0.583• (0.065)
0.401• (0.201)
0.578• (0.090)
0.267• (0.019)
0.256• (0.026)
0.274• (0.042)
0.304• (0.039)
Invests in technology
-0.104 (0.071)
-0.107 (0.118)
-0.139 (0.115)
0.024 (0.113)
Exports
0.034 (0.069)
0.187b (0.091)
-0.138 (0.124)
-0.387 (0.170)
Age of firm
0.007• (0.002)
0.006b (0.003)
0.002 (0.004)
0.009• (0.003)
Education of workers
0.029 (0.020)
0.025 (0.029)
0.019 (0.034)
0.053 (0.039)
Predicted Training
0.325• (0.080)
0.323• (0.104)
0.297b (0.144)
0.125 (0.151)
Constant
7.614" (0.403)
8.130" (0.505)
8.905" (1.131)
7.179" (0.767)
Log
(capital)
a=
b Note:
=
Significant at 1%.
Significant at 5%.
Numbers in parentheses are standard errors. Industry dummy variables included but their estimates are not reported here.
26
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
tively high productivity outcomes from training
The firm's age is positive, suggesting that the older firms tend on average to be more productive, re
among these groups of firms.
flecting their accumulation of production experience. In interpreting the training results, note that output
The other explanatory variables-the mean educa
or value-added is expressed in natural logarithms.
tional attainment of the workforce, technology, and
This allows us to interpret the coefficient of the train
exports-never attain statistical significance in the pro
ing indicator variable (or its predicted value) as the
duction function estimates though, as seen in Chap
percentage change in output ofbeing a training firm
ter Two, they are very important determinants of the
rather than a non-training firm, controlling for the
firm's decision to train.
productivity effects of other variables. For the MITP sample as a whole, Table 3.1 indicates Productivity Effects by Firm Size
that training has a positive and statistically signifi
Table 3.1 reports the production function estimates
cant impact on firm-level productivity. The esti
for the MITP sample as a whole and separately by
mated training coefficient is 0.325, suggesting that
three firm sizes. Before turning to the training esti
training firms are, on average, about 32 percent more
mates, we note that both labor and capital coefficients
productive than firms that do not train, controlling
are positive and significant, and that their magnitudes
for all other factors that also influence productivity
of approximately two-thirds and one-third, respec
in firms. Training effects of this magnitude are not
tively, are broadly consistent with the shares of la
unusual and, in fact, are broadly similar to those esti
bor and capital in the economy.
mated for other developing countries (see Box 3 .1).
Box 3.1 Enterprise Training and Productivity in Developing Countries
Tan and Batra (1995) used a common production function model to estimate the firm-level produc tivity effects of training in the manufacturing sector of Indonesia, Colombia, Malaysia, and Mexico. In all four countries, they found evidence that enterprise training is associated with higher firm-level productivity. Their findings also indicated that the productivity effects of training, especially training provided skilled workers, are larger in lower-income economies (Colombia and Indonesia) as compared to the higher-income countries in their sample (Malaysia and Mexico), possibly reflecting the relative scarcity of skills in these lower income countries. The implication is that economic development is strongly tied to workforce skills development, and that policies to encourage increased enterprise training will have large productivity gains for the economy. Country (year of survey) Indonesia (1992) Colombia (1992) Malaysia (1994) Mexico (1992)
GNP per capita US$ $ 670 $1,330 $3,140 $3,470
Productivity Effects Any Training 0.711 0.266 0.282 0.444
Productivity Effects Skilled Training 1.430 0.386 0.252 0.204
Source: Tan and Batra, Enterprise Training in Developing Countries, Private Sector Development Department, World Bank, 1995.
PRODUCTIVITY AND WAGE OUTCOMES
Do the productivity effects of training vary by firm
firms, the productivity effects of training are much
size? To address this question, separate production
smaller-12 percent-and these effects are not statis
functions are estimated for three firm size groups
tically significant.
27
small firms (up to 100 employees), medium-size finns (101-250 employees), and large firms (over 250 em
The fact (shown in Chapter Two) that relatively
ployees)-and the results reported in columns two
few smaller firms train despite this evidence of
through four ofTable 3 1
large potential gains in productivity from doing
.
.
so, leads us to conclude that small and medium The estimated training coefficients are 0.32, 0.29 and
firms under-invest in training. Such wide discrep
0.12 in small, medium and large firms. These results
ancies in returns could not persist in a perfectly
indicate that worker training has large productivity
competitive market since firms would train (in
benefits among small and medium-size firms-32 and
crease the supply of trained workers) to equalize
29 percent-productivity increases that are statisti
the returns to training across markets. The fact
cally significant at the five percent level. For large
that they do not suggests that market failures are
Box 3.2 Technology Raises the Productivity of Training in Taiwan, China. Using microdata from the 1986 Taiwan Census of Manufactures, Aw and Tan (1994) investigated the effects of training on firm-level productivity in seven industries. They were interested in whether the productivity effects of training varied with the firm's technology level, as measured by in-house
R&D or purchases of technology.
For each industry, they estimated separate production functions
for firms that invested in technology, termed "high-tech," and for firms that made no such technology investments, or "low-tech," correcting for potential selectivity bias in firms' technology decisions. They found clear evidence that technology had an impact on the productivity outcomes of training. First, within each industry, training provision was associated with a larger impact on firm-level productivity when training was accompanied by firm investments in R&D or purchased technology. Second, looking across industries, the differential impact of training in high-tech and low-tech firms is more pronounced in the technology-intensive industries such as electronics, chemicals, and plastics than in the more traditional industries like textiles and apparel. Thus, both within and across industries, the evidence indicates that the returns to training rises with technological change.
--- -
---- ----�-
P 1
ro d
.
B
0
6
0
4
0
--------
ctivity
Effe
-
---
cts
of
Tra in
in
g
·-
T aiw
a n
1986
2
I' 1 0
u
em H ig h - T e c h
-Lo w -Te ch L-.--------�
2 0
-�--------
---�-
- -
---
----
__j
28
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
present, especially among small and medium firms
Productivity Effects by Technology
(SMis).
The level of technology used in firms may also af fect the productivity outcomes of worker training
This conclusion is bolstered by employer responses
(Lillard and Tan, 1992). The characteristics of new
about why they provide employees with little or no
technologies are often poorly understood, and their
training. The evidence, which will be presented in
productivity advantages over the older technolo
Chapter Four, suggests that several market failures
gies that they replace are seldom manifested without
from lack of information about how to develop and
significant employer investments in learning-by-do
manage their training programs, high job turnover
ing and training. In this environment, the productiv
which makes it difficult for firms to recoup their train
ity gains from worker training can be quite
ing investments, and limited access to fmance for
substantial.
training-are important reasons for why some employ ers invest very little in training. More significantly,
In contrast, older and more established technologies
their responses also suggest that these factors pose
require less training since their specific characteris
particularly severe constraints for mar�y SMis.
tics are well-known; consequently, the productiv-
Table 3.2 Production Function Estimates by Technology Level DoTec=O Log (labor)
Log (capital)
DoTec=1
Age of Firm
Education of workforce
Predicted Training
Constant
R square
0.604"
0.531"
0.624"
0.391"
(0.058)
(0.041)
(0.084)
0.259"
0.294"
0.261"
0.287"
(0.022)
(0.038)
(0.020)
(0.062)
-0.139
-0.218
(0.083)
(0.155)
0.093
-0.132
0.063
-0.084
(0.079)
(0.126)
(0.070)
(0.213)
0.005b
0.009"
0.006"
0.019"
(0.002)
(0.003)
(0.002)
(0.007)
0.028
0.032
0.029
0.004
(0.024)
(0.034)
(0.021)
(0.055)
0.281"
0.282"
0.233"
0.554"
(0.095)
(0.120)
(0.082)
(0.181)
7.954"
7.768"
7.813"
8.798"
(0.421)
(0.643)
(0.375)
(1.035)
0.619
0.635
0.636
0.626
a= Significant at 1%. b = Significant at 5%. Note:
Numbers in parentheses are standard errors. Industry dummy variables included but their estimates are not reported here.
Do Tee= invest in R&D or has technology license. HasTL =has technology licensing agreement(s). Source: 1995 MITP Survey
HasTL=1
(0.047)
Conducts R&D
Exports
HasTL=O
PRODUCTIVITY AND WAGE OUTCOMES
ity gains from training to use older technologies are
29
To summarize, these production function estimates
also likely to be limited. In Chapter Two, we found
show that firms can make potentially large produc
strong evidence that firms were more likely to train
tivity gains of over 55 percent when new technolo
their workers if they were also investing in R&D.
gies acquired through licensing agreements are
These perspectives lead us to formulate the follow
complemented with investments in training. In con
ing tests of the link between the firm's technology
trast, R&D has limited impact either on overall pro
level and the productivity outcomes of training. We
ductivity levels, or on productivity of worker
split the MITP sample into two groups of firms by
training. We interpret this limited impact of R&D
level of technology, and compare the productivity
as reflecting the relatively weak R&D capabilities
effects of training in the high and low technology
of Malaysian firms; MNCs are widely believed to
groups. Such an analysis can also be done for indi
have greater capabilities in conducting R&D but they
vidual industries when data on large samples of
do little in Malaysia.
firms are available (see Box 3.2). Productivity Effects by Export Orientation Two defmitions of teclmology are used. First, we
and Ownership
define an indicator variable, DOTEC, which takes
Two other attributes of firms-export orientation and
on a value of one if the firms invests in R&D or has
foreign ownership-may affect the productivity out
technology licensing agreements with other firms,
comes of training through the mediating role of tech
and zero otherwise. Second, we define an indicator
nology and links with external markets.
variable, HASTL, to distinguish between firms with and without technology licenses.
The level of teclmology in exporting firms may be higher for two reasons: (a) a firm's export-orienta
This second definition recognizes that when in
tion may simply reflect its underlying teclmological
house R&D capabilities are weak, as is true in many
capabilities and international competitiveness; (b) ex
Malaysian firms, licensing agreements can be an im
porting may also raise technological capabilities by
portant means of accessing relatively sophisticated
giving firms access to technologies and know-how
technologies from abroad, even if the firm does no
from abroad and, through interactions with foreign
in-house R&D. The production function estimates
buyers, information about new markets and product
corresponding to these two teclmology measures
specifications as well.
are reported in Table 3.2. When the broad defini tion of technology, DOTEC, is used, the productiv
Foreign firms-defmed here as firms with over 50
ity effects of training-about 28 percent increase in
percent foreign capital participation-are thought to
value-added-are virtually indistinguishable in the
embody relatively high levels of teclmology, know
high teclmology and low technology firm samples.
how, and managerial expertise as compared to do
To see this, note that almost similar training coeffi
mestic firms. Their level of technological capabilities
cients of0.28 are reported in columns one and two.
is not well reflected by indicators such as local R&D spending or technology licenses, since they are able
The second defmition, HASTL, which is based on
to draw on the MNC parent's stock of technology
whether firms have technology licensing agree
and R&D.2 These are not typically located in de
ments, does a better job of discriminating between
veloping countries where there is often a short sup
the high and low teclmology firms, controlling for
ply of experienced R&D scientists and engineers.
their R&D investments. Not only are average pro ductivity levels (reflected in the constant term) much
Table 3.3 reports production function estimates for
higher in firms with teclmology licenses, the pro
groups of firms differing in their export-orientation
ductivity effects of training in these firms are over
and ownership. Columns one and two indicate that
twice as big as those for firms without technology
the productivity effects of training are higher in firms
licenses-55 versus about 23 percent.
30
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 3.3 Production Function Estimates by Export Orientation and Ownership
Exports=O
Exports>O
Foreign=O
Log {labor)
0.678• (0.068)
0.515• (0.046)
0.571• (0.048)
0.578• (0.069)
Log (capital)
0.251• (0.029)
0.266• (0.027)
0.285• (0.022)
0.207• (0.044)
Invest in Technology
0.071 (0.151)
-0.135 (0.075)
-0.096 (0.087)
-0.099 (0.119)
0.041 (0.078)
-0.419 (0.215)
Exports
Foreign=1
Age of Firm
0.004 (0.003)
0.01oa (0.003)
0.007" (0.002)
0.018" (0.006)
Education of workforce
0.036 (0.034)
0.022 (0.023)
0.025 (0.024)
0.099b (0.042)
Predic ted Training
0.270b (0.133)
0.333• (0.095)
0.283• (0.098)
0.327b (0.158)
Constant
7.751• (0.579)
7.784• (0.506)
7.319• (0.487)
7.843• (0.776)
R square
0.583
0.608
0.625
0.673
a= Significant at b
Note:
= Significant at
1%. 5%.
Numbers in parentheses are standard errors. Industry dummy variables included but their estimates are not reported here.
Source:
1995 MITP Survey
that export-about 33 percent-as compared with those that do not-about 27 percent. Columns three and four show a similar result, that the productivity outcomes of training are higher in foreign-owned firms (33 percent) than in domestic firms (28 per cent). It is also noteworthy that overall levels of productivity (as reflected in the constant term) are much higher in the sample of foreign-owned firms (7 .84) than in the domestic firm sample (7 .32).
of domestic firms. As shown in Chapter Two, firms with these characteristics are more likely to invest in the training of their workers. The pro duction function results reported here confirm that the productivity effects of this increased training are significantly higher among firms that export, have technology licensing agreements, and some foreign capital participation.
Taken together, these results and the findings re ported in Table 3.2 provide support for the view that employer investments in technology and train� ing are complementary in that investments in one enhance the productivity of the other. Given cur rent weak local R&D capabilities, the results sug gest that export-orientation, foreign technology licensing and joint-ventures may offer the great est potential for improving the technology levels
Productivity Outcomes by Skill Group and Training Source
Thus far, we have treated all forms of training as if they had the same productivity outcomes. We now consider several potential variations in the produc tivity outcomes of training across different worker groups and sources of training. As before, we con trol for selectivity bias by including the predicted
PRODUCTIVITY AND WAGE OUTCOMES
values of training from pro bit models of training
pervisors, engineers, technicians and skilled produc
for different skill groups and for different training
tion workers; and unskilled production workers.
sources.
For each skill group, we begin by estimating sepa
We also test a specification where training is pre dicted using a tobit model. The tobit specification is a mix of a probit model and a regression model in that it incorporates information both on the prob ability of an event and, conditional on that event taking place, the distribution of a continuous vari
31
rate probit models of whether employers provide in-house or external training, including the group specific measures of skill mix and female workers as the identifying variables. The estimated parameters are then used to calculate predicted training mea sures for each group in the production function.
able. This tobit specification allows us to estimate
A corresponding set of tobit training models is also
the productivity effects of "training intensity," that
estimated to predict training intensity of in-house and
is, the proportion of workers in a specific group
external training. Production function estimates us
getting training, while taking into account the de
ing these alternative probit and tobit training mea
cisions of some firms not to train.
sures are reported in Table 3 .4. Both the probit and
Estimating the separate effects of each type and source of training is complicated by the high correlation that exists between different training measures. The correlation arises in large part because firms that provide training tend to rely on all sources of training while employers that do little training rarely use more than one source. This means that our probit or tobit predicted train ing measures will be correlated, unless identify ing variables can be found to explain why employers might choose one training source over another. Given the paucity of identifying vari ables for each source, we can only address this identification issue in a limited way. For training by skill groups, we rely on variations in the proportion of skilled occupations and un skilled workers to identify what types of training are provided. For training by source, we include the presence of a training center and training staff to identify decisions to provide in-house training, and the use of joint training programs with other firms for external training. The limited number of identifying variables precludes a more disaggre gated analysis of training for each detailed occu pational group or every training source.
tobit measures are consistent in showing that training of skilled workers has a positive and statistically sig nificant impact on firm-level productivity while the training of unskilled workers does not. The training estimates for the latter group never attain statistical significance, and are thus interpreted as having zero impact on productivity. What about training skilled workers? Using the probit measure, the estimated coefficient of0.38 in dicates that provision of skilled worker training is associated, on average, with a 38 percent increase in productivity. A reasonable way of interpreting the tobit measure is to evaluate its coefficient-1.22-at the sample mean of the training variable. The propor tion of skilled workers trained was0.175 or 17.5 per cent. This implies that a 10 percent increase in the proportion of skilled workers trained (i.e. 0.017 5) is associated with a 2 .1 percent increase (1.22 x 0.0175 x 100) in productivity. The differential impact of training by skill group is not surprising once it is recognized that education is the foundation of subsequent learning, and to the extent that skilled workers are more efficient learn ers, they benefit more from training. Employers ap pear to recognize these differences in the learning capabilities of different worker groups. In Chapter
Productivity Effects by Skill Group
Two, the analyses indicated that firms were more
We consider the productivity effects of training for
likely to provide all kinds of training to their skilled
two worker groups: skilled workers, including su-
employees than to their unskilled workers.
32
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
We note that these results are not unique to Malay
ing from all outside sources combined. As before,
sia. Similar patterns of training outcomes, not only
the probability and intensity of in-house and exter
on the productivity but also the wages of skilled and
nal training measures are predicted using probit and
unskilled workers, are found in other developing
tobit
countries such as Mexico, Colombia and Indonesia
tify the employer's choice of each training mode by
(Tan and Batra, 1995). If the experiences of these
the occupational and sex mix of its workforce.
models, respectively. In these models, we iden
countries are any guide, the differential productiv ity impact of training is likely to result in growing
The production function results with the alternative
wage differentials between skilled and unskilled
training measures are reported in Table 3.5, sepa
workers in the absence of training policies to up
rately for local firms (columns one and two) and for
grade unskilled workers to skilled status.
foreign firms (columns three and four). Table 3.5 clearly shows that productivity outcomes by training
Productivity Effects by Training Source
source are quite different depending upon owner
Next, we compare the productivity effects of in
ship status of the firm. 3
house company training programs and external trainTable 3.4 Production Function Estimates with Predicted Training by Worker Groups
Independent Variable Log (labor)
Log (capital)
Invests in Technology
Exports
Age of Firm
Probit
Tobit
Prediction
Prediction
0.5773
0.558•
(0.040)
(0.042)
0.2793
0.266•
(0.019)
(0.019)
-0.102
-0.107
(0.065)
(0.071)
0.010
0.021
(0.064)
(0.069)
0.0063
0.0063
(0.002)
(0.002)
First, consider the productivity effects of internal and external training when training measures are pre dicted by a probit model (columns one and three). For the sample of domestic firms, only externally provided training has a positive and significant im pact on productivity, averaging about 26 percent; no statistically significant impact of in-house training is evident. In the case of foreign firms, the results indicate that both in-house and external training have a positive and significant effect on firm productivity13 percent for in-house training and 33 percent for external. These results are striking-on one hand, they point to the strong in-house training capabilities of foreign firms; on the other hand, they highlight the weak in house training capabilities of local firms and the po
0.035
0.029
(0.023)
(0.022)
0.383b
1.220b
Worker Training
(0.165)
(0.571)
Predicted Unskilled
-0.151
-0.680
Worker Training
(0.248)
(0.723)
7. 5333
7.7323
ence is that external training intensity for foreign
(0.448)
(0.425)
firms is no longer statistically significant.
Education of workforce
Predicted Skilled
Constant
a=
providers can play in meeting their training needs. The qualitative results using the tobit training mea sures are broadly similar in showing the importance of external training sources for local firms and in house training for foreign firms. The only differ
Significant at 5%. Numbers in parentheses are standard
What are the effects of training more intensely, at
errors. Industry dummy variables included but
are statistically significant? For local firms, the
b
Note:
Significant at 1%
tentially important role that external training
=
their estimates are not reported here. Source: 1995 MITP Survey
least for those external sources of training that proportion of workers getting in-house and ex ternal training is 0.094 and 0.026, respectively.
PRODUCTIVITY AND WAGE OUTCOMES
33
Table 3.5 Production Function Estimates: In-house versus External Training
Local Firms
Independent Variable
Probit prediction
prediction
Foreign Firms Probit prediction
Tobit prediction
0.627"
0.589"
0.559"
0.637"
(0.049)
(0.042)
(0.077)
(0.058)
Log (labor)
0.273 a
0.290"
0.201"
0.209"
(0.022)
(0.022)
(0.044)
(0.042)
-0.083
-0.029
-0.120
-0.144
(0.088)
(0.088)
(0.118)
(0.116)
0.101
0.051
-0.442b
-0.331
(0.079)
(0.076)
(0.213)
(0.206)
Log (capital)
Invests in Technology
Tobit
Exports
0.005b
0.005b
0.017"
0.015"
(0.002)
(0.002)
(0.006)
(0.006)
Age of Firm
0.026
0.015
0.089b
0.092b
workforce
(0.023)
(0.025)
(0.042)
(0.042)
Predicted Internal
-0.038
-0.063
Training
(0.050)
(0.169)
Education of
0.400b (0.214)
0.256a
1.751a
0.329b
1.297
(0.096)
(0.691)
(0.151)
(1.021)
Predicted External Training
0.13b (0.068)
Constant
7.555a
7.735a
8.494a
8.364a
(0.512)
(0.437)
(0.847)
(0.747)
a= Significant at 1% Note:
b = Significant at 5% Numbers in parentheses are standard errors. Industry dummy variables included but their estimates are not reported here.
Source: 1995 MITP Survey
Evaluated at these means, the coefficient of 1. 754
eral external sources-poly technics, vocational
on external training suggests that a 10 percent in
training institutes,
crease in the proportion of workers getting external
Skills Training Institutes (e.g. ClAST and GMI),
IKM, ITI, SDCs, Advanced
training (0.0026) will lead to a 0.5 percent increase
buyers and suppliers, other private firms, and over
in productivity. For foreign firms, the correspond
seas (presumably by foreign partners). The pre
ing proportions are 0.191 for in-house training and 0.032 for external training. Using the in-house train ing coefficient of0.40, a 10 percent increase in train ing (0.019) is associated with a produc tivity improvement of about 0. 8 percent. 4
likely to be most important for improving produc
Productivity Effects of Different External
fective for domestic firms as for foreign firms?
vious findings raise the following questions: Which of these external training providers are tivity and, given differences in in-house training capabilities by ownership status, are the same ex ternal training providers likely to be equally ef
Sources of Training The MITP survey elicited information from firms
We begin to address these questions by combin
about the number of employees trained in sev-
ing the different external training providers into
34
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 3.6:
Production Function Estimates: Training from External Sources
Independent Variable
Domestic Firms Tobit
Probit prediction Log {labor )
Log (capital)
Invests in Technology
Exports
Age of Firm
Education of workforce
Predicted Internal Training
prediction 0.588"
0.546"
0.589"
(0.049)
(0.078)
(0.076)
0.269"
0.284"
0.220"
0.208"
(0.022)
(0.022)
(0.043)
(0.043)
-0.077
-0.083
-0.109
-0.095
(0.088)
(0.089)
(0.118)
(0.117)
0.158C
0.002
-0.427c
-0.457b
(0.088)
(0.085)
(0.223)
(0.236)
0.002
0.008"
0.024"
0.015b
(0.003)
(0.003)
(0.007)
(0.006)
0.011
0.005
0.077c
0.105b
(0.026)
(0.029)
(0.046)
(0.051)
-0.031
-0.132
0.147b
0.515b
(0.050)
(0.172)
(0.069)
(0.232)
-12.516b
1.466b
24.396"
(5.376)
(0.602)
(9.129)
-0.339 (0.350) 0.632b
39.099b
(0.258)
(16.767)
Predicted Training in
0.019
11.346
Government Institutes
(0.262)
Constant
a=
b Note:
=
Tobit prediction
0.65 "
Predicted Training in
SDCs & Adv. Train. Ins.
prediction
(0.057)
Private Institutes Predicted Training by
Foreign Firms Probit
(8.341)
-0.741
-31.238
(0.456)
(38.148)
-0.406
-33.619
(0.441)
(17.425)
8.508"
8.158"
7.325"
7.557"
(0.712)
(0.700)
(1.196)
(1.343)
Significant at 1% Significant at 5%
Numbers in parentheses are standard errors. Industry dummy variables included but their estimates are not reported here.
Source: 1995 MITP Survey
three groups5: (1) government-run training in
of external training. The production function re
stitutions, including ITis, IKMs, YTCs, voca
sults with predicted training measures are re
tional and technical institutes, and polytechnics;
ported in Table 3. 6. These results should be
(2) advanced skills training centers and SDCs
treated with caution since we do not have sepa
providing high-level skills training with input from
rate identifying variables for each external train
the private sector; and (3) all other private sec
ing source.
tor training providers, including private training institutes, foreign partners, buyers and sellers,
Table 3. 6 shows that external training providers have
and overseas training sponsored by employers.
very different productivity effects depending upon
We are motivated to aggregate training into
ownership. For local firms, in-house training contin
three broad categories because of the high de
ues to be statistically insignificant. Among external
gree of correlation among the different sources
training sources, the results indicate that only the
PRODUCTIVITY AND WAGE OUTCOMES
35
training provided by SDCs and advanced skills
vanced skills training centers is associated with a
training centers to local firms has a positive and sta
1.2 percent gain in productivity. For foreign firms
tistically significant productivity impact, irrespec
the corresponding productivity gains from increas
,
tive of whether probit or tobit training measures are
ing the intensity of in-house training is one percent,
used. The probit measure indicates that this pro
that from private training institutes and overseas
ductivity impact is large, averaging about 63 per
training is 5. 6 percent.
cent. Tr aining provided by other private providers is actually associated with lower pro
The different patterns of training outcomes in for
ductivity in domestic firms.
eign and domestic firms suggest the following in terpretation. Foreign firms have well developed
For foreign firms, two sources of training are as
in-house training capabilities, and therefore may
sociated with significant productivity gains-in
need to rely less on SDCs and advanced skills
house training, and training from private training
training centers for training their workers. We
institutes-these include local providers as well as
speculate, but cannot confirm, that the relative im
overseas training. However, the latter source of
portance of training from other private providers
training has an implausibly large productivity im
may reflect their ability to send their workers
pact of 146 percent, based on the probit measure.
abroad to the parent company for training. In
In both groups of firms, there are no significant
contrast, domestic firms have relatively weak in
productivity gains from training in government
house training capabilities so that SDCs and ad
institutes.
vanced skills training centers are important
The productivity effects of increased training in
sources of higher-level skills training for them.
tensity are reported in Table 3. 7 for statistically
Firm-Level Wages Outcomes of Training
significant sources of training. For each group of firms, the table reports the sample means of train ing intensity, and the gains in productivity from
We now tum to a second outcome of training-its ef
increasing training intensity by 10 percent.
fects on the monthly wages of employees. Several
For local firms, a 10 percent increase in the propor
tivity gains from training passed on to workers in the
tion of workers getting training in SDCs and ad-
form of higher pay? In which types of firms are the
issues are of interest: to what extent are the produc
Table 3.7: Productivity Effects of Increased Training Intensity Local Firms Training source
Foreign Firms
Fraction
Productivity
Fraction
getting
impact of
getting
impact of
training
10% change
training
10% change
Productivity
In-house training
0.094
not sig.
0.191
1.0
Private training institutes
0.017
not sig.
0.023
5.6
SDCs & Adv. train. ins.
0.003
0.004
not sig.
Government training institutes
0.005
0.005
not sig.
Note:
1.2 not sig.
The productivity impact is calculated for a 10 percent change in mean training intensity; statistically insignificant impacts denoted as "not sig."
Source: Coefficients of tobit training measures taken from Table 3.6, means of training intensity variables calculated from the MITP data.
36
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
wage payoffs to training highest? And, which groups
experience (age), and in firms that invest in new
of workers benefit most from training?
technology. Firms with a workforce that is more highly educated also tend to pay higher wages, while
We are interested in these issues for several rea
those that rely heavily on female workers pay lower
sons. First, how the productivity gains from training
wages.
are shared has implications not only for worker in centives to undertake training, but also for employer
Both training measures indicate a positive and sig
incentives to sponsor and pay for training which may
nificant effect on monthly wages. In column one,
not be able to be recouped because of job turnover.
the training indicator variable has an estimated
Second, to the extent that higher wage payments are
wage effect of 0.04 (four percent); in column two,
feasible only when justified by productivity gains
the estimated wage effect of the predicted train
from training, these wage analyses-by firm charac
ing variable is0.06 (six percent). Even given this
teristics and by worker groups-provide a way of in
range of estimates, what is striking is that the wage
dependently verifying the productivity outcomes of
effects of training are smaller than the productiv
training identified earlier.
ity gains from training of0.32 (32 percent) esti mated in a production function model (see Table
To get estimates of the wage effects of training, we
3.1, column one).
regressed the logarithm of monthly wages on a mea sure of worker training and other control variables.
A comparison of these estimates suggests that roughly
The other explanatory variables are similar to those
one-eighth to one-fifth of the productivity gains from
used in the production function model, and include a
training are passed on to workers in the form of
quadratic measure of firm size (logarithm of employ
higher wages. By implication, the remaining seven
ment), age of the firm indicator variables for whether
eights to four-fifths of the productivity gains accrue
the firm exports or invests in technology, mean
to the employer as the returns to his (share of) in
schooling of the workforce, the proportions of non
vestments in training.
,
production and female workers, and a set of two digit industry dummy variables. We also estimated
This evidence of firm-worker sharing of productiv
separate wage models for four occupational groups
ity gains from training is of some policy interest, given
to determine if the wage effects of training differ for
proposed guidelines on linking wages to productiv
skilled and unskilled workers.
ity growth currently being drafted in Malaysia by a tripartite group representing employers, unions and
Overall Wage Effects of Training
the government. However, we caution that this evi
In Table 3. 8, we report the results of two wage model
dence is cross-sectional, when what is required to
specifications, one where training is measured by an
inform the deliberations of this tripartite groups is
indicator variable (column one), a second where we
evidence on how gains in productivity over time are
include the predicted value of training obtained from
passed through to wages increases. This will re
a pro bit model to account for potential selectivity
quire rigorous time-series analyses of productivity
bias (column two). As noted in previous sections, the
and wage growth, which is beyond the scope of this
wage effects of training may be biased (either up or
report.
down) if the firms that train differ systematically from those that do not.
Do the wage effects of training vary systematically across different groups of firms? The previous pro
Before presenting the training results, we note that
duction function results revealed a pattern of pro
mean pay levels tend to rise with firm size (employ
ductivity gains from training that was higher in firms
ment) up to a point, but decline in the very large
that invested in technology, that exported, or had
firms; they are higher in firms with more production
foreign capital participation. To determine if the wage
PRODUCTIVITY AND WAGE OUTCOMES
Table 3.8 Wage Model Estimates with Training Indicator and Predicted Values
Independent Variable
Training Indicator Predicted Training Specification Specification
Log (labor)
0.0988
0. 0738
cant impact on wages in firms that do not invest in technology, or in domestic firms . These weak wage effects may reflect, in part, the much smaller produc tivity gains from training in these latter groups of
firms . Thus, we conclude that the training-wage re sults by firm characteristics are broadly consistent
(0.027)
(0.029)
Log
-0.0138
-0.0128
with the patterns of productivity gains from training
(labor squared)
(0.003)
(0.003)
found earlier.
Invest in Technology Exports
0.032°
0.031°
(0.018)
(0.019)
Wage Effects of Training by Occupation
-0.023
-0.023
The wage effects of training can also be analyzed
(0.018)
(0.018)
for four occupational groups-supervisors, tech
nicians, skilled production workers, and unskilled
0.0048
0.004a
(0.001)
(0.001)
0.023a
0.0188
(0.004)
(0.005)
0.038b
0.062b
Training
(0.017)
(0.027)
Proportion
-0.034a
-0.046a
tion received in-house or external training, and
Female Workers
(0.013)
(0.014)
then using their corresponding training intensity
Age of Firm
Education of Workforce Any Formal
Proportion of Nonproduction Labor Constant
1.039a
0.943a
(0.060)
(0.079)
production workers. The MITP survey elicited detailed occupation-specific information on wages as well as numbers getting training by source. We exploit this rich detail by estimating separate wage models for each occupation, first using indicator vari ables for whether workers in that specific occupa
measures.
5.779a
5.9538
Table 3.9 Wage Effects ofTraining by Level of
(0.089)
(0.119)
Technology, Exports, and Ownership
a= Significant at 1%
Estimated Training Coefficient
b = Significant at 5% c
Note:
= Significant at 10%
Numbers in parentheses are standard
No investment in technology
errors.
Invest in technology
0.023
0.073b
(0.022)
(0.030)
Industry dummy variables included but Source: 1995 MITP Survey
effects of training also exhibited this pattern of variation, we estimated separate wage models for dif
technology license(s) 0.026
0.106b (0.049)
Does not export
Exports
The training effects for each group of firms are sum
Like the productivity results, they show positive and
0.064a
(0.033)
(0.020) Foreign-owned Firm
0.022
0.070b
(0.022)
(0.028)
a= Significant at 1%
statistically significant wage effects of training in the
b = Significant at 5%
firms that invest in technology, that have technology contrast, there is little evidence (except in non-ex
0.061°
Domestic firm
marized in Table 3.9.
porting firms) that training has a statistically signifi-
technology license(s)
(0.019)
ferent groups of firms defined in an analogous way.
licenses, that export, and that are foreign-owned. In
Has
No
not reported here.
c
Note:
= Significant at 10% level
Numbers in parentheses are standard errors.
Source: 1995 MITP Survey
37
38
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 3.10 Occupation-Specific Wage Effects of Training Training Measures
Supervisors
Technicians
Skilled
Unskilled
Production
Production
Workers
Workers
Training Indicators Internal Training Indicator
External Training Indicator
0.063•
0.014
0.072•
0.029
(0.024)
(0.024)
(0.024)
(0.020)
0.001
-0.019
o.osoc
(0.025)
(0.025)
(0.026)
(0.022)
-0.001
Training lntensi!Y Proportion trained internally
Proportion trained externally
Note:
a=
Significant at 1%
b=
Significant at 5%
c=
Significant at 10%.
0.095•
0.019
0.079•
-0.007
(0.030)
(0.031)
(0.034)
(0.027)
-0.052
0.005
0.110<
0.116
(0.081)
(0.041)
(0.061)
(0.091)
Numbers in parentheses are standard errors.
Source: 1995 MITP Survey
Table 3.10 summarizes the wage effects of training
pace of growth in information technology, increased
for each occupational group. For supervisors and
inflows of capital and technology, and the growing
skilled production workers, the results suggest that
integration of world markets is likely to create strong
in-house training has a positive and significant im
demand for skilled workers far outstripping the sup
pact on wages; external training is not associated
ply capacity of the existing educational and training
with higher pay except for skilled production
institutions. Without appropriate responses from the
workers where it is marginally positive and sig
private and public sector, the outcome is likely to be
nificant. For technicians and unskilled produc
growing income inequality over time between skilled
tion workers, there is no evidence of wage effects
and unskilled groups.
of training f r om either internal or external sources. These conclusions are unchanged irre
This phenomenon of widening wage gap between
spective of whether training is measured by an
skilled and unskilled workers is not unique to Ma
indicator variable or by training intensity-the pro
laysia. It has been observed in industrialized
portion of workers that receive training in each
countries as well, and there is some evidence attrib
occupational group.
uting this growing differential to skill requirements of technological change (Katz and Murphy, 1992;
These results are broadly consistent with the find
DunneandSchmitz, 1995).
ings of positive productivity outcomes of training for skilled workers (defined to include supervisors, tech nicians and skilled production workers) and the ab sence of productivity effects for unskilled workers reported in Table 3.4.
Compensation Policy and Labor Turnover The previous section indicated that some employers
This training-skill complementarity has implications
share part of the realized productivity gains from
for income inequality in Malaysia. The accelerating
training with their workers in the form of higher pay.
PRODUCTIVITY AND WAGE OUTCOMES
For these employers, the higher pay made possible by improved productivity can be an important means
sample size), there is a trend for quit rates to rise
with firm size irrespective of relative wages.
of cementing job attachment without which there
would be little incentive either for the firm to spon sor, or for workers to undertake, training.
Third, there is a negative relationship between quits
� wages.
Training firms (top panel) paying wages
above the mean are able to keep quit rates below 25
Long-term job attachment, especially in the context
percent, while quit rates in firms that pay below av
of the tight labor markets and high rates of labor
erage wages rise to 33 percent and 42 percent for
turnover in Malaysia, is critical if employers are to recoup their investments in workers' job skills. In
Figure 3.1 Quit Rates and Wage Policies: Training and Non-Training Firms
deed, many employers cite concerns about high job turnover as a key deterrent to their provision of worker training. We address this issue by investigat
Training Firms
ing the potential role that compensation policies might play in reducing labor turnover, thus increasing the incentives for employers to train.
60 50
To motivate this discussion, we begin by graphically presenting data on average quit rates in Chart 3 .1. Quit rates are defmed as the ratio of total quits over the past year to the level of employment prevailing at the beginning of the year, expressed as a per
�
40
0
Ul Q) ....
30
....
20
�
·s a
centage. Firms are categorized by their pay levels,
10 0
and defined as being high-wage or low-wage rela tive to the overall mean wage of the MITP sample.
e CJ
They are further disaggregated by firm size to ac
�
(ii E (/)
E
�
Q)
"' ...J
:2
commodate size-related differences in wages and
Q)
::::l
'0
other contemporaneous factors. The top panel of Chart 3.1 shows quit rates in train ing firms according to their pay levels, while the bot
Non-Training Firms
tom panel shows the corresponding quit rates for
non-training firms The chart makes several points:
60
.
50
First, quit rates are generally lower in high-wage fmns than in low-wage fmns for both training and
non-training firms In firms that provide training, quit .
rates are 22 percent per annum when employers pay wages that are above the sample mean, and 34
percent when wage levels are lower than the mean.
�
40
0
Ul Q) ....
�
....
·s a
30 20 10 0
Among non-training fmns, the corresponding quit
e
rates are 19 percent and 25 percent, respectively.
�
Second, larger firms have higher quit rates than
smaller employers. With the exception of micro firms (these firms may be discounted because of their small
CJ
(ii E (/)
E .:! -c Q)
:2
Q)
� "' ...J
39
40
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
medium and large firms, respectively. Among non
elsewhere in the market, in effect by deferring
training firms (bottom panel), quit rates are kept to
current period compensation to the future, these
about 20 percent or less by above average pay, but
latter instruments can have a powerful impact on
rise to 24 percent and 50 percent in medium and
enhancing job retention among workers (Lazear,
large finns that pay below average wages.
1995). For example, there is evidence from Ja
However, quit rates are often higher in training firms
ment in manufacturing firms are shaped to a large
than in non-training firms. This is readily apparent
extent by the use of severance pay schemes (Tan,
from a comparison of similarly sized firms in the top
1989).
pan that the low quit rates and strong job attach
and bottom panels. Higher quit rates in training firms reflect shortages of trained workers in the market,
Modelling Quits and Compensation
and the willingness of other employers to offer
We use a regression model to analyze the effects of
higher pay to hire away these workers (or "poach")
wage and other compensation policies on reducing
from training firms.
labor turnover. In the model, annual quit rates are
To summarize, it appears that firms can use wage policies to reduce quits among employees. Of course, not all employers will pay higher wages to retain workers; the decision will depend upon whether the higher resulting wage bill is offset by cost-sav ings from reduced worker turnover. For employers that invest heavily in worker train ing, the cost-savings from reduced quits can be sub stantial and they will have an incentive to pay higher wages out of the increased productivity from train ing. For other employers doing little or no training, high labor turnover imposes few sunk costs. Conse quently, they will have little incentive to pay com petitive wages to retain their workers.
regressed on a set of explanatory variables, includ ing firm size, industry dummy variables, characteris tics of the workforce, and several measures of compensation. These include the mean monthly wage, the rate of wage growth with seniority, and indicator variables for whether the firm's compensa tion package included a pension plan, a severance pay scheme, or other fringe benefits. 6 In defming the seniority-wage growth measure, we used data on the mean monthly pay of a typical production worker-at the entry point and at 10 years of ser vice with the company-and calculated the wage increase over this period as a fraction of starting pay.7 We estimate quit models for all workers, and for non-production and production workers. 8 If ef
Higher pay is not the only means to reduce quits. In
fective, the coefficients of each compensation
their compensation policies, employers can use a
variable should be negative, implying reductions in
variety of instruments to reduce quits. In addition
quit rates. We also distinguish between training
to higher overall pay, employers can retain work
firms and non-training firms. The motivation is to
ers by offering a variety of fringe benefits such as
investigate whether these compensation policies are
subsidized housing, medical plans, meals, or trans
relatively more effective among training firms-the
portation. They can also tie some parts of compen
employers most able to afford improved compensa
sation to length of se rvice, such as (i) steepening the
tion packages out of higher productivity, and for
rate of wage increase with length of service; (ii)
whom high job turnover is presumably the most
offering a pension in which length of service
costly in terms of sunk training costs.
strongly influences retirement pay; (iii) providing a severance pay scheme linked to length of service.
These quit models control for selectivity bias intro duced by employers' training decisions. This is done
By making compensation grow faster with length
in two steps: first, estimating a probit training model
of service relative to workers' opportunity wages
similar to those reported in Chapter Two, and then
PRODUCTIVITY AND WAGE OUTCOMES
41
Table 3.11: Summary Statistics on Quits and Compensation Policies Variable Means
All workers Firms not Training
training Annual quit rates % Tenure-wage growth Monthly wages Have pension % Have severance pay % Other fringe b enefits % Sample size (firms)
19.8 1.556 644 33.0 43.5 0.5 1,097
Firms
Non-Production Firms not Training
training
7.2 1.556 1229 29.0 38.4 0.5 963
26.7 1.517 699 47.3 56.4 2.2 707
Firms
9.5 1.517 1354 45.0 54.3 1.2 697
Production Firms not Training
training
21.5 1.556 568 31.8 42.5 0.4 1,095
Firms
29.3 1.517 573 45.0 55.3 1.9 700
Source: 1995 MITP Survey
using these estimates to compute a selectivity cor rection variable; second, including this variable in
The Effects of Compensation Policies on Quit Rates
the second-stage quit models estimated separately
Table 3.12 reports the regression estimates of two
for training and non-training firms. We are particu
specifications of the quit model. The first, reported
larly interested in the patterns and relative effects of
in column one, pertains to the pooled sample of all
the different compensation policies in the two groups
firms; the second specification splits firms into two
of firms.
samples by training status, and includes a selectivity correction variable to control for any bias introduced
Table 3.11 provides summary statistics on the key
by separating firms on the basis of a decision vari
variables used in the regression analyses. The vari
able, in this case, training.
able means are reported separately for training and non-training firms, and for three worker groups-all employees, non-production and production workers. The data on quits reflect the point raised in Chart 3 .1, namely, that quit rates are on average higher in train ing firms than in non-training firms; they also show that non-production workers are less likely to quit as compared to production workers. Two points about the compensation variables are noteworthy. First, contrary to our expectations, the measure of wage growth with seniority (which re fers only to production workers) is actually lower in training firms than in non-training firms. Training
firms may be offering higher starting pay in order to
The first model specification provides a convenient summary of the principal correlates of quits in the overall sample when no account is taken of training. It suggests the following broad results-quit rates rise with employer size as compared to micro firms (the omitted group); quit rates tend to fall as overall pay levels rise; and quit rates are lower in firms having a severance pay scheme. The other explanatory vari ables are not significantly related to quits. 9 The second specification, which takes into account
firms' decisions to train, is more illuminating. It sug gests the following results: •
The correlation between firm size and quits dis
attract the most able new recruits, but this may be at
appears when training is considered. This fol
the expense of slower subsequent wage growth with
lows from the fact that larger firms are more likely
years of service. Second, all other compensation
to train (see Chapter Two), and it implies that it is
measures-not only overall wage levels, but also pen
training, rather than firm size per se, that is the
sion plans, severance pay schemes, and other fringe
critical factor in shaping quits. Quit rates from
benefits-are higher among training firms than non
training firms are high because of acute short
training firms.
ages of trained workers in other firms.
42
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 3.12 Compensation Policies and Overall Quit Rates by Training Status Annual Overall Quit Rates Explanatory Variables
Firms All Firms
Not Training
Training Firms
Small firms (16-100 workers)
.0514c
.0249
.0812
Medium firms (101-250 workers)
.0771"
.0211
-.0418
Large firms (over 250 workers)
.1482"
.0469
-.0387
Mean education of workforce
.0003
-.0084
-.0073
Proportion female workers
.0264
.0129
.0553
Foreign-owned firm
.0379b
.0299
-.0009
Wage growth 0-1 0 years tenure
-.0112
-.0046
-.0208C
Monthly wages (x RM1 00 )
-.0081 a
-.0079"
-.0131" -.0078
Have pension plan Have severance pay scheme
.0051
.0009
-.0516"
-.0492"
.0257
.1327
-.0288
n.a.
·.1124C
-.1649"
.2728"
.2551"
Indicator for other fringe benefits Training selectivity correction d Constant term R-squared
0.061
Sample size
0.058
1,804
1,097
•
=
Significant at 1%;
b
=
Significant at 5%;
c
=
Significant at 10%.
d
=
The selectivity variable is the Mills Ratio computed from a probit training model.
-.0512c
.6263" 0.069 707
Industry dummy variables included but not reported in table. Source: 1995 MITP Survey •
•
Higher pay is a deterrent to quits for both training
For the same wage bill, a steeper seniority-wage policy can reduce quits in training firms For train
negative and significant effects of the monthly
ing firms, the increment in pay over 10 years of
wage variable. To the extent that firms have the
service is 1.5 times starting pay (see Table 3.11),
.
higher productivity to do so, both groups of firms
or an increase in pay of about 9.2 percent per
can pay higher wages to reduce quits.
annum. The estimated coefficient of -0.02 suggests
Firms that train are better able to reduce quits through higher pay than non-training firms Their .
coefficients, -0.013 for training firms and -0.008 fornon-trainingfirms, suggestthataRM100increase
in wages is associated with a 1.3 percent decrease in quits for training fmns (from a mean of26.7 to 25.4 percent), and a 0.8 percent fall in quits for non training firms (from 19.8 to 19.0percent). •
•
and non-training firms. This is evident from the
that an increase to2. 5 times starting pay after 10 years, or 12.6 percent increase in pay per annum, will lead to a two percent fall in the quit rate. Table 3.13 reports the regression results separately for production and non-production workers accord ing to whether their employers provide training. The results are broadly similar to the overall regressions, except that the tenure-wage growth is no longer sta
Severance pay schemes can reduce quits by
tistically significant. Some differences between the
about five percent. In both groups of firms, the
two groups emerge.
severance pay coefficients (-0.051 for training and -0.049 for non-training firms) are negative, and
First, while quit rates in both groups are lower
they suggest that employers can reduce quits by
when their employers pay higher overall wages,
about fivepercent by introducing such a scheme.
the effects are most pronounced for production
PRODUCTIVITY AND WAGE OUTCOMES
43
Table 3.13: Compensation Policies and Quit Rates by Occupation and Training Status
Quit Rates of Non-Production Workers Explanatory Variables
Quit Rates of Production Workers
Firms Not
Training
Firms Not
Training
Training
Firms
Training
Firms -.0201
Wage growth with tenure
.0081
-.0020
-.0059
Monthly wages (x RM100)
.0014
-.0025b
-.0098a
-.0133a
-.0149
-.0119
.0067
-.0035
-.0049
Have pension plan Have severance pay
.0062
-.0555a
-.0539C
Other fringe benefits
-.0352
.0908b
.1709
-.0355
Training sel. correction
-.0484
-.0612c
-.1254C
-.1424C
Constant term
-.0314
.3125a
.28623
R-squared Sample size
0.039 963
.5675b
0.077
0.063
0.070
697
1,095
700
a= Significant at 1% b = Significant at 5% c
Note:
= Significant at 10%.
Industry dummy variables, firm size, ownership, and worker characteristics are included
but are
not reported here. Source: 1995 MITP Survey
workers. An increase in monthly pay ofRMlOO is
The productivity benefits of training are particularly
associated with a 0.25 percent reduction in quits
large for SM/s, the group least likely to train, sug
among non-production workers in training firms;
gesting that SM/s under-invest in training. Their
among production workers, this same increase in
use of simple technologies means that skill needs are
pay results in a one percent reduction in quits in
also correspondingly low; they also face several
non-training firms, 1.3 percent in training firms.
market failures-from limited finance for training, high job turnover which makes it difficult to recoup
Second, severance pay schemes are effective in re
training costs, and weak training capabilities-which
ducing quits (about five percent) for production work
deter them from training. To be effective, train
ers; however, such schemes are not effective for
ing policies targeting SMis should not be uni-di
non-production workers.
mensional, focusing on just one constraint or the other. An integrated set of policies is required,
Findings and Policy Implications
The analyses confinn that fonnal training improves finn-level productivity. Firms that train, on average, are about 32 percent more productive than firms that provide no formal training. Productivity effects of
this magnitude are not unusual and, in fact, are broadly
which simultaneously address a multitude of con straints involving fmance, identification of train ing needs, information about training pedagogy, technology upgrading, and adoption of quality control methods.
The productivity effects of training are larger when new technologies acquired through licensing are
similar to the effects estimated for other developing
complemented with training. Compared to technol
countries such as Mexico, Colombia and fudonesia.
ogy licensing, a firm's own R&D has limited effects
This information should be widely disseminated to
either on overall pr oductivity or on the productivity
private sector firms that do not train or provide very
of worker training, suggesting that technological ca
little training because of skepticism about the pro
pabilities are relatively weak among local firms The
ductivity benefits of training.
implication is that licensing may be a more important
.
44
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
source of new technology for most firms, and that
training role in the Seventh Malaysia Plan, not only
the productivity benefits can be quite substantive if
in pre-employment training but also increasingly in
technology transfer is accompanied by training. This
meeting employers' in-service skill needs.
suggests that the Government should place greater training and technology transfer that accompanies
The productivity results suggest ways of improving the delivery of training tofirms. First, they suggest
such agreements, than on encouraging firms to de
that in-service training provided by public training
emphasis on promoting technology licensing, skills
velop their own indigenous technologies through
institutions are not well-tailored to meet employers'
R&D incentives.
skill needs. Ways of making their curricula more
The productivity effects of different sources of train ing vary by local or foreign ownership. The evi
reveal that while SDCs are an important source of training for domestic firms, take-up of SDC training
dence is consistent with local firms having weak
is currently low among SMis. The Government
demand driven should be identified. Second, they
in-house training capabilites as compared to foreign
should implement measures to increase SMI partici
firms. For local firms, no productivity effects from
pation in the design of training programs tailored
in-house training are discernible; however, the train
more to their specific needs. Third, advanced skills
ing they receive from SDCs and advanced skills
training institutes are a second important source of
training institutions are associated with large produc
training for local firms but the supply of their gradu
tivity effects. For foreign firms it is in-house training
ates is still limited. The Government should explore
and training from private sector sources which have
the feasibility of expanding the number of these in
,
large productivity effects.
,
stitutions, and setting up bilateral training centers like GMI, MFI, JMTI with countries such as Britain and
These findings suggest several training strategies
the United States.
targeting local firms: (i) expand their access to ex ternal training institutions capable of delivering train ing in higher-level skills; (ii) expose employers to
Finns pay higher wages out of increased productiv ityfrom training. Overall, training is associated with
best-practice training methods by promoting joint
a six percent increase in wage levels, suggesting
training programs with large firms and MNCs that
that one-eighth to one-fifth of the productivity gains
have world-class training programs; and (iii) provide
from training are shared with workers in the form of
incentives for firms to develop their own in-house
higher pay. The patterns of wage increases mirror
training capabilities, by undertaking training needs
those of the productivity gains from training, being
analyses (TNAs), training trainers, and implementing a
higher in firms that invest in technology, that export,
systematic training plan to upgrade worker skills.
and that are foreign-owned. Similarly, skilled worker
No significant productivity effects were discernible for in-service training provided by public training institutions ms, IKMs, YTCs, and vocational and
workers, and training of supervisors and skilled pro
training is more productive than training for unskilled
.
duction workers is associated with higher pay, but is not for unskilled production workers.
technical institutes tend to focus on pre-employment training, a subject which is not addressed here. None
The implication is that these productivity differen
theless, the absence of any productivity effects of the
tials will lead to growing wage disparities between
in-service training that they provide is striking, and
skilled and unskilled workers in the absence of
it may suggest that the training provided by them is
training policies to upgrade unskilled workers to
not well suited to employers' needs. A careful study
skilled status. Technological change, with its as
of the effectiveness and relevance of training pro
sociated higher skill requirements, will also put
vided by public training institutions should be con
additional upward p ressure on relative pay of
ducted, especially if they are to play an expanded
skilled workers.
PRODUCTIVITY AND WAGE OUTCOMES
Employers can reduce quit rates through appropri
especially among firms that train. The reason is that
ate compensation policies. Employers have at their
training firms are better able to fund more attractive
disposal different instruments to promote long-term
compensation packages out of the higher productiv
job attachment-higher pay, fringe benefits, pay in
ity resulting from training. These findings should be
creases tied to length of service, severance pay and
disseminated to employers, especially to the smaller
retirement schemes. Of these, the analyses indicated
firms unfamiliar with using compensation policy as
that higher pay, steeper seniority-wage profiles, and
part of a personnel strategy to promote training and
severance pay were most effective in reducing quits,
reduce quits of trained employees.
45
CHAPrER FoUR: TRAINING PoLICIEs The previous two chapters provided an overview of the incidence, correlates, and productivity out
Constraints on Training: An Employer Perspective
comes of in-service training. They made two prin cipal points: First, despite evidence showing that
In the design of training policies, it is critical that
training increases productivity, a substantial frac
policymakers know which firms train and which
tion of firms, SMis in particular, provide little or
firms do not, and the reasons why some ftrms in
no structured training to employees. Second, the
vest little in the training of their employees.
evidence shows that local firms have weaker in house training capabilities than foreign firms, and
The following issues are key. Is the low incidence
that most of their productivity gains from training
of formal training, and the striking differences in
come from external training providers such as SDCs
training by firm size, a reflection of the weak train
and institutes providing advanced skills training.
ing and technological capabilities of Malaysian
What little in-service training provided by most gov
firms, small firms in particular, or is it the result of
ernment-run training institutions appears to have
market failure? What market failures are operative?
little impact on productivity.
Are firms constrained by poor access to financing for training, or do they simply lack interest, know-how
In this chapter, we address several issues raised by
or capability to design and implement training pro
these fmdings. Why do so many employers, SMis
grams? How important a constraint is "labor poach
in particular, not train and what constraints do they
ing", the hiring away of employees trained at the
face? If market failures are responsible, what kinds
employer's expense which prevents firms from re
of training policies are effective in addressing these
couping the returns to their sunk investments in
market failures? In addressing these issues, we draw
training?
on the unique perspectives provided by employer responses in the MITP survey, both about why they
Without an adequate understanding of these issues,
provide little or no training, and about their use of
well-intentioned incentives may needlessly benefit
two training schemes-the Double Deduction Incen
firms that already train, while doing little to encour
tive for Training (DDIT) and the Human Resource
age other employers to initiate or increase training.
Development Fund (HRDF). Both policies were designed to encourage firms to play a greater role in meeting their own skill needs, but through very dif ferent means.
Insights into some of these questions are provided by firm respondents in the MITP Survey. They were asked to rank, on a scale of one (not impor tant) to five (very important), the relevance of each
For DDIT, we discuss the incidence of its use
one of seven statements to their decision to provide
across different firm sizes and industries, and rea
little or no training.1 These statements included:
sons for its limited use by firms. For HRDF, we discuss several issues not readily investigated us
•
ing administrative data-non-compliance in regis tering with the HRDC; the extent of training
•
•
sons and policy recommendations.
The finn lacks knowledge about training tech niques and organization
tative insights into whether HRDF has increased training in firms. We conclude with some les
Training is costly because of high labor turn over
claims among firms registered with the HRDC; new schemes introduced by HRDF; and some ten
Training is not affordable because of limited resources
•
The firm uses a mature technology, so learning by-doing is sufficient
TRAINING POLICIES
•
47
Skilled workers are readily hired from other
important constraint, especially if there are no ex
firms
ternal training providers capable of meeting employ
•
Skills provided by schools are adequate
ers' particular skill needs. Finally, resources to
•
We are skeptical about the benefits of training
finance training may not be forthcoming because of imperfect capital markets.
To facilitate comparison of the relative importance of these factors, we coded firm responses to each statement as being "very important" if it was assigned a high score of either four or five, and as "not very important" otherwise. These responses are tabulated in Table 4.1 for the MITP sample as a whole, and separately by four firm sizes.
(56 per
cent) for why firms provide little or no training. In well-functioning markets, this was the response that we expected to find from theory. The productive attributes of mature technologies are well-established and there is typically little scope for improving upon existing production techniques. As such, no additional training is required and work ers quickly become proficient at their jobs through learning-by-doing. Furthermore, employers may not need to train when mature technologies are widely diffused since there is a plentiful supply of skilled workers with experience using the older technolo gies in the external labor market, and they are readily hired from other firms
sizes. About an equal proportion of small, medium and large
firms (36-37 percent) ranked high labor
turnover as an important constraint, as compared to micro firms (29 percent). The differences across firm
size in the importance accorded the other factors are more pronounced-a higher proportion of micro and
For the overall sample, the use of mature technol ogy was the most commonly cited reason
These same three factors were cited by firms of all
.
This interpretation is consistent with the evidence in Chapters Two and Three, namely, that incentives to train are diminished among firms not investing in technology in which the productivity outcomes of training are relatively low. What is significant in Table 4.1 is the importance attributed by a sizable number of firms to three other factors: high labor turnover, lack ofknowledge about
small firms (28-30 percent) ranked lack of knowl edge about training methods as important relative to large firms
(22 percent); they were also more
likely to rank limited resources for training as im portant (25 percent) as compared to large firms
(10
percent). These findings are not peculiar to Malaysia. 2 In a recent study, we compared employer responses to similar questions in two other countries, Indonesia and Colombia. Like Malaysia, manufacturing firms
in the other two countries identified the use of ma ture technology, lack ofknowledge, high labor tum over, and limited resources among the top reasons for little or no training. Firms in both Malaysia and Colombia ranked the use of mature technology and high labor turnover as the most and second most important reasons for limited investments in training. Reflecting its lower relative income level, Indonesia ranked mature tech nology a close second to limited resources, and lack of knowledge about training as number three. In Colombia, limited resources tied with lack of knowledge for third place, while it was ranked fourth in importance in Malaysia. Thus, while markets are generally well functioning in
training methods, and limited resources for train
Malaysia, there is evidence that market failures pose
ing. High labor turnover can inhibit training by pre
important constraints on training for many employers,
venting employers from recouping their investments
especially SMis, and they justify government inter
in workers' skills. Lack of information on how to
vention. What kind of policy intervention is appropri
train or to organize training programs can also be an
ate depends upon the nature of the market failure.
48
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 4.1 Reasons for Little or No Training, Overall and by Firm Size Overall
Micro
Small
Skilled workers readily hired from others
20.2 36.0 26.8 56.3 16.5
25.5 29.4 28.1 42.5 18.3
25.3 35.7 29.7 57.4 19.7
20.8 36.9 27.2 58.3 14.0
10.2 36.8 21.6 55.1 16.6
Skills provided by schools are adequate
14.4
11.1
18.0
14.1
11.1
9.3
7.8
10.2
8.2
10.7
Reason for Not Training Limited resources for training High labor turnover makes training costly Lack knowledge about training Mature technology requires little training
Skeptical about benefits of training
Medium
Large
Source: 1995 MITP Survey
High rates of labor turnover suggest that there are
In the following sections, we use these employer
externalities in training, and to the extent that firms
insights to assess the efficacy of these two training
are unable to internalize the benefits of training be
policies. Even though the scope of DDIT is now re
cause skilled workers are hired away by other finns ,
duced, an assessment of its implementation and lim
there will be under-investment in training. The ap
ited take-up is still important for the lessons it offers
propriate policy response is to institute a payroll levy
policymakers. HRDF now provides the whole in
to provide incentives for all finns to train, or if finns
frastructure of training incentives for employers
do not train, to contribute to the cost of training pro
and a network of public and private training pro
vided by others in the industry.
viders to support their in-service training efforts. Our focus here is on providing insights into the use
When poor infonnation is the constraint, the appro
of existing and new HRDF schemes by private sec
priate policy response is to widely disseminate best
tor firms.
practices in training know-how, as well as infonna tion about the availability and cost of services that external training providers can offer. Finally, when lack of finance for training is the constraint, policymakers can provide incentives by subsidizing the costs of training through the tax system.
Care in the design of training subsi
dies is needed to ensure that they reach only those
Double Deduction Incentive for Training Scheme The objective of DDIT was to encourage firms to train-especially in skill areas related to new prod ucts and processes, and productivity and quality improvements-by permitting employers to deduct double the amount of allowable training expenses
firms that need it.
on their tax returns. 3
Some elements of all three policy responses are
The DDIT scheme could be used in two ways.
reflected in the DDIT and HRDF training
First, employers could send their workers to ap
schemes, though both policies had different ob
proved training institutions, of which there were
jectives and were implemented in different ways.
12 in 1994, including SIRIM, NPC, ClAST, Ger
The DDIT, introduced in 1987, was the principal
man-Malaysia Institute (GMI), SDCs in Penang
training policy unti11993 when HRDF was imple
and Perak, and various public training institutes
mented; thereafter, it was retained for smaller
such as ms and IKMs. Second, employers could
manufacturing firms with less than 50 employ
apply directly to MIDA (the Malaysian Industrial
ees, and HRDF became the principal training
Development Authority) for approval of their
policy instrument for larger firms.
planned training programs. Firms sending their
TRAINING POLICIES
49
workers to approved training institutions were au
1992, over 60 percent of applications were filed
tomatically qualified to claim the double deduction
by MNCs or majority foreign-owned firms; the
incentive directly from theD epartment of I nland
remaining 4 0 percent were principally joint
Revenue. 4
ventures, and a small number of wholly M a laysian-owned firms .
Administrative Records o n DDIT Use I t is widely acknowledged that use of the DDIT incentive has been limited, though the reasons for this are not well-established. D ata onDDIT use through the first route-approved training provid ers-are not available since there was no require ment for firms to notify MIDA of this training.
•
Finally, take-up ofDD IT by small companies has been very low.7 Crude estimates suggest that less than seven percent of all applications to MIDA were from small firms with less than 50 employees; over 40 percent from firms with over 500 employees.
However, administrative records from MIDA are available on applications filed with it in the pe riod between 1987 and 1993. They provide some
DDIT Use Among MITP Firms Table 4.2presents estimates ofDDIT use reported
insights, albeit incomplete, into the take-up of that
in the MITP Survey. These figures are more broad
part of the DDIT scheme:5
based since they include use ofDDIT through both
•
routes-from approved training providers and from Take-up of the DDIT scheme has been quite
MIDA-though they do not distinguish between them.
limited. In the period between 1987 and 1993,
The figures refer toDD IT use in the entire 1987-
MIDA approved a total of 591 in-house train
1993 period when it was still the principal policy
ing programs, involving 3,253 trainees and
instrument for training.
costing a total of just under RM 32.5 million. About 3 5 percent of applications for in-house
•
use. First, the overall use of the scheme has been
or inadequate.
quite low since its inception. Only 8. 3 percent of
TheDDIT scheme expanded its coverage af ter 1991. The number of applications rose from 37 in 1991, to 214 in 1992and, to 392in 1993. This was due in large part to an ex pansion in types of training covered,6 an in crease in the number of approved training pro viders, a simplified application process, and reduced rejection rates for applications.
•
Take-up ofDDIT has been very uneven across subsectors. Firms in the electric and electron ics industry were the primary beneficiaries, accounting for over half of training programs approved and over half of all workers it trained; in contrast, no training programs were approved in the beverage and food in
•
Table 4.2 reveals the following patterns ofDDIT
training were rejected for being incomplete
the firms in our sample (183 firms) usedDDIT be fore 1993. This figure falls to 4. 3 percent when the
data are weighted to reflect the over-sampling of large firms in the MITP sample. Second, take-up ofDDIT among firms has been very uneven. Use by small companies has been very low, averaging three percent for micro firms, and just under 20 percent for large firms. Across industrial sectors, the primary users ofDDIT were electrical machinery, fabricated metals, chemicals, and trans portation equipment; use was low in food, wood and furniture, and textiles. Thus,DDIT use was higher in industries characterized by a higher per centage of firms investing in R&D , having technol ogy licenses, more foreign capital participation, and
dustry.
exports ( see ChapterTwo).
DDIT use has been dominated by the MNCs,
Finally, MNCs and firms with some foreign capi
and few domestic firms have benefited. I n
tal participation were more likely to use it than
50
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 4.2 Participation in DOlT by Industrial Sector MITP firms
Industry
reporting use ofDD IT Overall Sample
little or no training. %of firms by size
the design of the scheme, and its effectiveness in
183
8.32
encouraging firms to train. Arguably, most large and
4 14 74 91
2.61 2.17 7.84 19.83
Micro (<=15 workers) Small ( 16-100 workers) Medium(1 01-250 workers) Large (>250 workers)
14
5.28
5 7 2 16 10 13 12 8 16 8 18 4
39.00* 6.54 1.72* 5.23 7.94 14.44 9.16 6.02 11.19 11.27 16.36 4.65* 15.96 12.82 8.32
Other Food, Beverages, Tobacco Textiles Apparel Wood & Furniture Paper & Printing Chemicals Rubber Plastics Glass & Pottery Iron & Basic Metals Fabricated Metals Machinery Electrical Machinery
34
Transport
10 6
Other Industries
majority foreign-owned firms would train even without the DDIT incentive, given the high-tech subsectors in which they operate and their produc tion for export markets (see Chapter Two). In do mestic-oriented subsectors and in the larger population ofM alaysian-owned firms and SMis,
INDUSTRY Food
*Fewer than 5 observations
1995 MITP Survey
domestic firms. Before 1993, less than six percent of all domestic firms used it as compared to 14 per cent of joint-ventures and wholly foreign-owned
firms
This uneven take-up ofDDIT raises questions about
or industry
FIRM SIZE
Source:
or firms in traditional sectors that typically do
where skill levels and technological capabilities are generally low, the low take-up ofDDIT suggests that
this scheme has generally been ineffective in encour aging training among firms that were not training before. M alaysia's experiences withDDIT are not unique. M any countries have used similar training subsidies or tax write-offs of training expenses to encourage firms to train, including Argentina, Brazil, Chile, Fiji, Pakistan, and the Philippines. The limited evi dence suggests that they often needlessly subsidize well-run firms that already train, while poorly man aged firms either do not respond or respond by es tablishing training designed more to maximize financial gains than to develop needed skills. Evalu ations of these programs in Chile and Brazil indi cate that the main beneficiaries are large firms in the most dynamic sectors of the economy. 8 The fol lowing section provides some insights into why DDIT take-up has been so low.
.
TheseMITP figures, though more broad-based in
Reasons for Not Using DDIT
covering both types ofDDIT use, are nonetheless
TheMITP survey elicited information about why
remarkably similar to patterns revealed by admin istrative data fromMIDA. The strong implica
firms did not use DDIT prior to 1993, from 1 ,504 firms. We classified their responses into fifteen main
tion is that both avenues of DDIT are being
categories-not aware, don't need training, don't
utilized by the same group of employers-namely,
know details, bureaucratic procedures, non-avail
the MNCs, joint-ventures, and larger firms in
ability of appropriate training, don't meet require
skill-intensive sectors-who typically already
ments, no training capabilities, no training, small
train. DDIT approved training institutions are
scale, high cost, no time, confusion with HRDF, la
apparently not relied on more heavily by other
bor turnover, no permission from management, and
groups of small and medium-size local companies
several other minor reasons.
TRAINING POLICIES
Table 4.3 Reasons Given by Firms For Not Using DOlT Reason for Not Using DDIT
#of
%of
Firms
Firms
Not Aware
682
45.4
Don't need training
260
17.3
Don't meet requirements
163
10.8
Don't train
110
7.3
Don't know details
83
Small scale of operations
60
5.5 4.0
No training capabilities
29
1. 9
Others
26
1.7
Source: 1995 MITP Survey
The seven principal reasons cited are listed in Table 4. 3. The remaining reasons are collapsed into an "other" categocy since fewer than one percent of firms reported each of them. The most commonly cited reason (45 percent) was that many employers were not even aware of the DDIT scheme. To this lack of information prob lem should be added another reason cited by firms, namely, that they did not know the details of the DDIT scheme (over five percent). Thus, more than 50 percent of firms did not use the DDIT scheme because they were not aware of it or knew its details only imperfectly, this is despite great effort on the part of the Government to publicize its availability.
51
Table 4.4 breaks out these responses by firm size. They clearly show that lack of information about DDIT was pervasive in all firm sizes, even among the large fums (40percent). Among small-scale firms, a higher proportion did not use DDIT because they did not need it or did not train (25 to 28 percent), as compared to large firms (13 percent). This is consistent with the low skill requirements of SMis associated with their use of relatively mature technology (see Chapter Two). A reason for not using DDIT, unique to large fums and not cited by SMis, is the bureaucratic applica tion procedures for DDIT. These fmdings suggest several lessons and recommendations for policy makers: First, the lack of awareness about DDIT, and its re quirements, has been the principal reason for the limited use of this incentive scheme. While this lack of information was most acute among small fums, it was also the principal reason cited by large firms. The key lesson for policymakers is that any policy or incentive, whether in training or in other areas, is not likely to be effective if targeted beneficiaries are unaware or inadequately familiarized with the program. The Government should thus widely dis seminate information about training incentives and programs, especially to SMis, the group for whom informational constraints are most severe.
Another cluster of reasons for not using DDIT is that employers did not need training (17 percent), were not currently training (seven percent), or lacked training capabilities (two percent). Col lectively, they suggest that over one-quarter of the firms did not train because they did not need it or did not know how.
Second, the DDIT incentive scheme has generally not proved effective in inducing firms to train. It has been used primarily by MNCs, joint-ventures, and larger firms who, arguably, were training al ready. For these firms, the DDIT scheme has meant sizable windfall gains.
Finally, about 11 percent of firms did not use the DDIT scheme because their existing training ef forts did not meet the requirements and standards established by the DDIT scheme, or because DDIT was not attractive because of the small number of trainees involved (four percent).
For the vast majority of small local firms, the DDIT scheme has failed to induce them to begin, or in crease provision of, training. Other more proac tive approaches are needed for SMis. These should be designed to affect a change in their at titudes towards training, and address their weak
52
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 4.4 Reasons for Not Using DDIT by Firm Size Small
Micro Problem
Percentage
Problem
Medium
Percentage
Problem
Large
Percentage
Not aware
50.8%
Not aware
48.3%
Not aware
44.1%
Don't need
20.2%
Don't need
18.5%
Don't need
17.7%
Problem
Percentage
Not aware
40.5%
Don't meet
17.4%
requirements Don't know
8.1%
Don't train
10.1%
Don't meet
1.8%
details
Don't need
12.7%
requirements
Don't train
6.5%
Don't meet
7.1%
Don't train
7.2%
requirements Don't meet
6.5%
Small Scale
5.6%
requirements Small scale
Don't know
5.0%
details
5.7%
Don't know
Don't know
6.2%
details
5.2%
Small scale
Bureaucratic
5.0%
procedures
2.8%
Small scale
3.5%
details Note:
Number of firms: Micro= 124, Small= 466, Medium= 655, Large= 259
Source: 1995 MITP Survey
training and technological capabilities. Examples
50 employees. While MIDA is no longer involved
of proactive SMI training and technical assistance
in approving DDIT applications, it is unlikely
policies include Mexico's CIMO and Chile's
that many eligible small firms are using DDIT
PROFO programs. These are discussed in Chapter
through the approved institutions.
Six. Firms with less than 50 employees should be brought Third, bureaucratic requirements were a major
under the HRDF umbrella and registered. This
constraint on DDIT use. Its low initial take-up,
would simplify administration since the inevitable
and its rapid expansion after 1991 when several
growth and shrinkage of firms above or below the
program modifications were introduced and re
50 worker cutoff would be seamlessly accommo
jection rates reduced, indicates that an onerous
dated by universal coverage of all manufacturing
application process can discourage take-up of in
firms under HRDF.
centives. However, the issue of payroll contributions from Companies may not find the incentive attractive
smaller firms needs to be resolved-one possibility is
because the benefits of doing so are exceeded by
for the government to match their payroll levy con
application costs, including personnel time and
tribution; another is for it to provide a block grant
audit fees to certify training expenditures. S trin
to HRDF from general revenues to cover the costs of
gent application requirements and high rejection
their use of training services.
rates can also reduce interest in the incentive since expected benefits of applying must now be dis counted by a high probability of rejection.
Human Resource Development Fund The HRDF was established with a matching grant
Finally, the Government should eliminate the re
from the Government. 9 The Act created a council
maining DDIT coverage of firms with less than
(HRDC), with representatives from the private sec-
TRAINING POLICIES
53
tor and from responsible government agencies, and
at least 10 percent of the company's workforce
a Secretariat to administer the HRDF schemes.
and 15 percent of junior level employees. In ad dition, HRDC supported efforts of employers to
Unlike DDIT, the HRDF is not a subsidy scheme.
develop training plans through the JURUPLAN
Employers who have contributed a minimum of six
scheme.
months are eligible to claim a portion of allowable training expenditures up to the limit of their total
In 1995 and 1996, the HRDC introduced several
levy (one percent of payroll) for any given year.
additional schemes, many with a focus on the
The HRDC has set rates of reimbursement, varying
needs of small and medium-size companies. The
by type of training and generally being lower for
PERLA Scheme (Training Agreement Scheme) is
larger companies.
designed to lower firms' training cash outlays by enlisting A TP training providers as their agents,
In 1993, the HRDC introduced three basic training
to collect from users only that portion of fees for
schemes that offered firms a great deal of flexibility
which firms are responsible and claim the reim
over their training programs. In the A TP scheme,
bursable balance directly from HRDC. The SBL
employers can freely send employees for approved
Pre-Approved Scheme gives time-tested in-plant
training courses offered by registered training pro
training courses an official pre-approved designa
viders without the prior approval of the HRDC, and
tion, which not only allows training providers to
submit claims on completion of the course.
market this training but also simplifies employer
In the SBL scheme, employers submit plans to HRDC for approval of ad hoc in-plant or external
claims for reimbursement. The HRDC has also targeted SMis with several train
training courses offered by non-registered training
ing schemes. HRDC organizes Training Needs
providers. These plans must include specific objec
Analysis (TNA) workshops and clinics to answer
tives, areas of training, duration, number of train
questions about different schemes; provides assis
ees, instructors, and means of assessment.
tance in the purchase of training aids and setup of training rooms; and most recently, introduced Joint
In the PLT scheme, which is designed for firms with
Training Schemes (ITS) to promote group training
long-term and predictable training needs, employ
of SMis, and on a pilot basis, a Group Training
ers submit detailed annual training plans covering
Scheme (GTS) to encourage employer associations to play a greater role in developing training programs for their members.
Table 4.5 Use of HRDF By MITP Firms, 1994 Schemes
#of
%of
Firms sample
65.9
These most recent HRDF initiatives are not captured in the MITP Survey, which was fielded in 1994 and
1995. The following section focuses on the HRDF
Firms Eligible for HRDF
1450
Firms Registered with HRDF•
1048
72.3
468
44.7
493
47.0
PL T Scheme (annual plan) b
99
9.5
Firms not claiming under HRDF 362
34.5
Table 4.5 tabulates the responses of MITP firms
Of the 1,450 firms eligible, the proportion
regarding the HRDF. It shows the numbers of firms
ATP Scheme (approved programs) b SBL Scheme (ad-hoc programs)
a=
b
registered with the HRDF b
=
Of the 1 048 eligible and registered, number claiming reimbursement.
Source: 1995 MITP Survey
schemes that existed prior to 1995, and we defer dis cussion of recent schemes to a subsequent section.
Use of HRDF Schemes
that were eligible for HRDF, those that said they were registered with the HRDF, those that reported filing claims under the c.iiflerent SBL, ATP and PLT schemes, and those not claiming under any of these schemes.
54
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 4.6 Eligible Firms Not Registered with HRDF by Size and Industry Firm Size and
#of
Industry
eligible
nizing the possibility that both response and coding
Eligible Firms Not Registered with HRDF #
this regulation appears to be significant, even recog
%
Firm Size
errors and the crude definition of eligibility used may be partly responsible for this high figure. Table 4.6 presents crude estimates of the severity of non-compliance by firm size and industrial sector.
461
226
49.0
The estimates are intended to be illustrative because
(101-250 workers)535
140
26.2 36
7.9
Small firms (with 50-100 workers) are more likely
Large (>250workers)
454
145
60
41.4
Tobacco
52
27
51.9
Textiles
74 97
14 25
18.9
food, beverages and tobacco, wood and furniture,
25.8
glass and pottery industries (one-third to one-half of firms), than the electrical machinery, chemicals,
Small (50-100workers) Medium
the MITP sample is not completely representative.
Industry Food Other Food, Beverages,
Apparel Wood & Furniture
208
104
50.0
Paper & Printing
89
22
24.7
Chemicals
62
7
11.3
21
18.6
to be in non-compliance (49 percent) than large
firms (eight percent). Across industries, non-compliance is higher in the
and textile industries where rates of non-compliance rates are lower (10 to 20 percent). As such, it ap
Rubber
113
Plastics
87
23
26.4
pears that non-compliance is concentrated among
Glass & Pottery
80
27
33.8
Iron & Basic Metals
42
9
21.4
small firms and firms operating in the traditional,
Fabricated Metals 71
16
22.5
domestic-oriented industries.
Machinery
39
8
20.5
Electrical Machinery
198
21
10.6
48
10
20.8
probit model to identify the factors associated with
8
17.8
non-compliance. Underlying this analysis is an eco
Transport Other Industries
45
Source: 1995 MITP Survey
To look at this issue in greater depth, we estimate a
nomic model in which firms make cost-benefit cal culations, weighing the probability and cost of being
Wedefine "eligible fume:;" asthoo:::employing50ormore
caught in non-compliance against the benefits of not
workers, broadly following the 1995 Guidelines from
registering with the HRDF.
HRDF, Human Resource Developrrent Couocil.10 On the basis of this rough definition, 402 firms (about 27.7
We hypothesize that the probability of appre
percent) out of the total of 1,450 eligible reported that
hension is lower for smaller firms, who are less
they were not registered with the HRDF.
visible, and for firms that are located in more re mote areas. Benefits of non-compliance are two
Of those that were registered with the HRDF, 45
fold: the firm avoids payment of payroll levies,
percent claimed reimbursements under ATP, 47 per
and the potentially high fixed cost of setting up a
cent under SBL, and less than 10 percent under the
formal training program if one does not already
PLTscheme. However, 34.5 percent of registered
exist.
firms reported that they did not claim reimburse ments under any of the three schemes.
The results of the pro bit analysis are reported in
Non-Compliance with HRDF
First, compared to small :finns, medium size and large
Table 4. 7, and they suggest the following points.
The Human Resource Development Act of 1992
firms are less likely to be in non-compliance, possi
made it mandatory for eligible firms to register with
bly because they believe that the probability of their
the HRDC. The 27 percent non-compliance with
being caught is high, given their higher profile.
TRAINING
Table 4.7 Probit Estimates of Non
PouciES
The HRDC is aware of the non-compliance issue but it has few resources to devote to enforcement.
Compliance with HRDF
55
It
currently has a skeleton team-an administrative of Independent Variable
Estimate
Standard error
Medium size firms (1 01-250 workers)
0.086
-i .323a
0.114
It has established a panel of lawyers but their au
0.254a
0.083
0.759a
0.148
ment of levies by registered firms, not prosecution
-0.767a
0.141
Only internal informal training No training Region: Western
corridor states Trengganu, Kelantan
0.254
0.184
Region: Perlis and Kedah
-0.421 a
0.187
-0.241 a
0.081
Increased production Constant Log likelihood
thority is limited to civil cases regarding non-pay of non-registered firms. Only legal officers can pursue the latter cases, and the HRDC is seeking to fill several of these positions. Until such time
Region: Pahang,
over the last 3 years
underlying population of firms that are eligible but not registered with the HRDC.
-0.532a
Large size firms (>250 workers)
ficer and a clerk-working on developing lists of the
0.420a -684.46
0.153
as the HRDC develops the capability to identify and prosecute non-registered firms, the threat of prosecution will not be credible and the non-com pliance problem will persist.
-684.46
The following steps should be taken to address this a= Statistically significant at 1% level. The omitted re gion is Sabah and Sarawak; the omitted size is small firms with 50-100 workers; the omitted train ing group is firms providing formal training. Source: 1995 MITP Survey
Second, firms that do not train or that rely only on informal training, are significantly more likely to be in non-compliance as compared to those provid ing formal training. This is consistent with the pres ence of high-fixed costs of developing and setting up training programs, and incorporating the new skills into existing production. Third, there are systematic regional variations, with non-compliance being much higher in the eastern states of Pahang, Kelantan and Trengganu, and in East Malaysia as compared to the west coast states. Finally, we attempted to control for the firm's growth experience in the past three years, on the grounds that firms that are not growing are more likely to fail and thus have little incentive to reg
issue. First, the Government should expeditiously provide HRDC with the necessary manpower and legal resources to identify and prosecute firms in non-compliance, and to recover back levies and other penalties. Second, with additional resources in hand, the
HRDC should also mount an information campaign, on television and in newspapers, to encourage eli gible firms to register with HRDC. It should an nounce its intention to vigorously enforce compliance with the HRDF Law and, to ensure that this threat is credible, it should publicize its in creased enforcement capabilities as well as its pros ecutions of selected firms. Finally, this campaign should be accompanied by a time-limited amnesty program for firms to come for ward, register with the HRDC, and pay their back levies without civil or criminal penalties. Similar amnesty programs have been effectively used in the United States.
Claims under HRDF
ister with the HRDF. The estimated results-that
A second issue is that a sizable number (362) of reg
firms with stagnant or declining sales are less
istered firms do not claim reimbursements for train
likely to register-is consistent with this hypothesis.
ing expenditures despite contributions of payroll
56
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
levies to the HRDF. Their claims for training under
line-to June 1995-granted by the HRDC.12 This is
any of the schemes are a crude indicator of how ef
supported by HRDC data showing an increase in
fective HRD F has been in encouraging firms to be
the ratio of funds approved to levy collected, from
gin or increase training.
64.7 percent in 1994 (the time period covered by the MITP survey) to 88.9 percent in 1995.
Tabulations suggest that small firms are less likely to claim as compared to their larger counterparts-
We estimate probit models to get insights into why
50.2 percent for small firms with 50-100 employ
these registered firms did not implement training
ees, 41.3 percent for medium size finns with 101-250
program s and claim reimbu r sements. The depen
employees, and 19.4 percent for large firms with over
dent variable is an indicator variable with a value
250 workers. This is a key issue since firms paying
of one if the firm does not claim, and zero other
into the system, but not claiming reimbursements,
wise.
in effect pay a tax of one percent of payroll without getting any tangible benefits from doing so.
Two models specifications are considered. In the
first model, we include several measures of firm size, Who are these non-claimant firms and why are they
reported training status, an indicator variable for
not training? Table 4.8 reports the distribution of
whether they have a training plan, and industry
registered firms that do not claim according to
dummy variables. In the second specification, we
theirtraining status-no training for workers, only
replace the actual training variables with the fmns'
informal training on-the-job, and training formally.
own responses about why they provided little or no training. Table 4.9 reports the estimated probit re
Table 4.8 Registered Firms Not Claiming from HRDF by Training Status Training Status
Registered
Distribution
firms not claiming
by training status
22
6.1
Firms training informally only
196
54.1
Firms training formally
144
39.8
Firms not training
Source: 1995 MITP Survey
sults for these two models. The results of the first model indicates that the firms least likely to claim from HRD F are small firms, and firms providing no training or only informal train ing. This result was already evident in the simple tabulations. Having a training plan, however, is as
sociated with a greater likelihood of a claim to HRDF, though not necessarily through the PLT (annual training plan) scheme.13 This is not surprising. A training plan is indicative
Interestingly, only about six percent of these non
of an awareness, on thepartoftheemployer, of its
claimants do no training. The majority of firms (54
skill needs, as well as a commitment to a strategy of
percent) are those that only provide informal OJT
systematically training employees to meet these skill
from co-workers and supervisors.11 Thus, about 60
needs either in-house or through services of exter
percent of these firms are not eligible for reimburse
nal training providers.
ments because they either provide no training or are only training informally. The remaining 40 percent report providing formal training yet do not claim reimbursements for these expenditures.
The results of the second model provide insights into why firms contribute but do not claim. The statisti cally significant responses are that employers have limited resources for trainin g, they use mature tech
It is possible that some (unknown) fraction of these
nology with low skill requirements which are
latter firms submitted claims subsequent to the
readily met by school graduates, and skilled work
MITP survey, based upon an extension of the dead-
ers are readily hired from other firms .
TRAINING PoLICIEs
57
Table 4.9 Probit Estimates of Not Claiming from HRDF Independent Variable
Model1
Standard
Model2
Estimates
Errors
Estimates
Standard Errors
Medium firms (101-250 workers)
-0.123
0.107
-0.196
0.105
Large firms (>250 workers)
-0.630 a
0.114
-0.836•
0.110
Limited resources for training
0.242b
0.115
No knowledge about training
0.067
0.099
Mature technology
0.147°
0.084
Get skilled workers from others
0.285b
0.119
Skeptical about training benefits
0.097
0.139
0.283b
0.124
Skills from schools are adequate 0.463•
0.091
Firm does not train
0.511•
0.216
Firm has a training plan
-0.493•
0.089
Firm only trains informally
-0.248b
Constant
-623.06
Log Likelihood a=
0.104 -623.06
Significant at1%
b = Significant at 5% c=
Significant at 10% level Note: The omitted size category is small firms with 51-100 workers; and the omitted training category in model1 is firms that provide formal training. Industry dummy variables included but are not statistically significant.
Source: 1995 MITP Survey
These responses are consistent with the weak
In the JTS scheme, groups of small firms reap
training and technological capabilities of small
scale economies by banding together to engage
and local firms shown in Chapter Two, as well as
training providers who run specific training pro
the financial constraint on funding training iden
grams for them on a joint basis. In addition to
tified in earlier sections of this chapter. They
lower per trainee cost, the ITS provides an added
explain why most of them do little or no formal
incentive for the firm that organizes the joint
training on their own despite the financial incen
training.
tive of the HRDF levy, relying instead on the edu cational system or on trained workers hired from
In the GTS scheme, now being implemented on a
other firms.
pilot basis, 14 employer associations are encour aged to take the initiative in providing training
Recent HRDF Initiatives
to members, with HRDF providing funds to set
The HRDC recognizes the funding and training
up training facilities, and paying the salary of a
difficulties faced by small local firms, and it has
training coordinator for three years. The coordi
introduced several schemes and initiatives to ad
nator conducts a skill needs survey, and organizes
dress these constraints. One set of initiatives seeks
training program for its members.
to assist both large and small firms, in develop ing a training infrastructure-the JURUPLAN for
In this section, we provide insights into these ini
developing a training plan, and a scheme to pur
tiatives using data reported in the MITP survey.
chase training aids and set up training rooms. The
We report the incidence among firms of in-house
second set of initiatives-the Joint Training Scheme
training centers, training plans and how they were
(JTS) and Group Training Scheme (GTS)-is de
developed, and the different types of joint train
signed to encourage group training for smaller
ing programs, focusing in particular on differences
fums.
in these measures by firm size.
58
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 4.10 Training Centers and Training Plans in MITP by Firm Size
Conditional on Having a Training Plan
Training System Firm Size
% firms
% firms
with
% firms with
Training Plan
Training Plan
Training
Training
developed at
developed by
funded by
Centers
Plans
own cost
consultants
JURUPLAN 7.6
% firms
% firms Training Plan
Small
3.1
10.9
83.2
23.7
Medium
9.7
42.4
76.7
33.5
7.1
19.2
69.2
79.3
35.7
8.6
Large
Source: 1995 MITP Survey Table 4.11 Joint Training Programs in MITP by Firm Size
Firm Size
Source of Joint Training Programs Small % Firms with joint training programs
3.9
Medium 9.9
Large 18.9
Conditional on ajoint training program: Through Industry associations
23.4
30.2
37.2
Organized by government institutions
27.7
24.5
30.2
Ad hoc programs with other firms
34.0
49.1
52.3
Through specialized companies
21.3
35.9
40.7
Organized by suppliers
31.9
34.0
17.0
Organized by buyers
14.9
17.0
27.9
Source: 1995 MITP Survey
Table 4.10 reports the distribution of firms with
How were these training plans fmanced? Columns
training centers and training plans by three firm sizes.
three through five report the sources of their fund
Small, medium and large sizes are defined as em
ing to develop training plans, conditional on having
ployers with less than 100 employees, 101-250 em
one. Multiple responses are permitted so that the
ployees, and over 250 employees, respectively.
numbers do not sum to 100.
Column one shows that firm size is an important
Two points emerge. First, there do not appear to be
determinant of whether an employer has a training
major differences by size in how employers develop
center-only three percent of small firms have train
training plans. Second, the figures reveal that most
ing facilities as compared to 19 percent of large firms.
training plans (over 70 percent) are developed by
As such, considerable potential exists for HRDC to
employers at their own cost, followed next by train
extend the training aids scheme to small firms.
ing plans developed with the assistance of consult ants. The proportion of training plans funded by
Column two shows the proportion of firms with a
the JURUPLAN scheme is low, about seven to
training plan. As before, the presence of a training
eightpercent. HRDC should ascertain the reasons
plan is highly correlated with size, though a much
for why employers prefer to fund their own train
higher number of firms of all sizes report having a
ing plans when an alternative source of fmance is
training plan as compared to training facilities. To
available through the JURUPLAN scheme.
the extent that employers can send workers outside for training, it reduces the necessity for them to have
Table 4.11 shows the incidence and types of joint
a training facility in-house.
training reported by employers in the MITP survey.
TRAINING POLICIES
59
Firms were asked whether they had joint
Such ad hoc arrangements arise when firms,
trainingprograms with other firms to provide work
which otherwise compete with each other, see
ers with training, and if so, how these training pro
acollective interest in jointly investing in a com
grams were organized. Finns indicated one or more
mon good, in this case, worker training. The im
of six types of programs organized through:
portance of other types of joint programs varies markedly by firm size.
•
industry or professional associations
•
government or public institutions
For small firms, programs organized by suppliers
•
ad hoc arrangements with other firms
and government agencies are cited most often after
•
specialized training companies
ad hoc arrangements. Unfortunately, the govern
•
programs organized by suppliers
ment and public agencies involved are not identi
•
programs organized by buyers
fied. For medium size firms, suppliers are also important as are specialized training companies. For
The first row of Table 4.11 indicates that joint train
large firms, most commonly cited after ad hoc joint
ing programs are relatively rare in Malaysian indus
programs are specialized training companies and
try. When they occur, these programs are most
employer or professional associations. The latter's
commonly found among large firms (19 percent)
focus on large employers would be reoriented to
rather than among smaller firms (four percent) who,
wards supporting smaller firms under theHRDF's
it may be argued, need them most. Unlike larger
new GTS scheme.
firms, individual small employers are often unable to assemble a large enough group of employees to
Has HRDF Increased Training by Firms?
warrant the fixed costs of hiring an outside provider
It is too early to make judgments about the efficacy
to deliver a t ailored training program. Joint train
ofHRDF in promoting training and skill upgrad
ing programs, such as those envisaged by the
ing. Additional years of accumulated information
JTSscheme, would allow groups of small firms to
(panel data) will be needed to do that. However, a
reap the economies of scale.
crude test is possible using retrospective responses
Given the obvious benefits of such programs, espe
has changed-iocreared, stayed the sarre, ordecreased
cially for smaller firms, it is unclear why more joint
over the past three years, a period spanning the year
from employers about how their level of training
programs are not found among them. Is it due sim
prior to the introduction ofHRDF in 1993, to the
ply to the low skill requirements of small firms,
present (1995). We will do this by comparing the
or are there collective failures-no tradition of col
training experiences of two groups of firms: those
laboration among small firms, or absence of em
registered with theHRDF, and those who were eli
ployer associations to represent the collective
gible but did not register. In principle, the regis
interests of small business-which prevent them from
tered group would have increased incentives to train
working together? This issue should be studied by
so as to recover their payroll levy contributions. In
HRDC to determine if incentives alone are suffi
contrast, the non-registered group would not face
cient to encourage joint training.
these same incentives since they do not contribute toHRDF. We recognize that these two groups of
The remaining columns ofTable 4.10 show how ex
firms are different, not only in terms of their mea
isting joint training programs are organized. When
sured characteristics but also in terms of their unob
firms have one, the single most important type of
served (to us) productivity attributes.
joint training program for all firm sizes is through ad hoc arrangements with other firms-the fractions citing this range from 34 percent for small firms to 52 percent for large firms.
Table 4.12 compares the training experiences of these two groups of firms. Of those registered with the HRDF, about 50 percent said that they had increased
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
60
Table 4.12: Probit Estimates of Increased Training Under HRDF Independent Variable
Combined
Purely
Firms with
Interactions Between Size
Sample of
Domestic
Foreign
Firms
and HRDF Small Firm HRDF
0.160 (0.122)
Medium Firm HRDF
Firms
capital
.141
0.179
(0.151)
(0.215)
0.312"
0.171
0.435•
(0.101)
(0.129)
(0.179)
Large Firm HRDF
0.788"
0.839"
0.753"
(0.102)
(0.147)
(0.175)
Introduced new technology
0.428"
0.499"
0.365"
in last 3 years
(0.076)
(0.103)
(0.114)
Constant
-0.574"
-0.616"
-0.516"
(0.083)
(0.099)
(0.160)
•=
Significant at 1% level
Note:
Industry dummies were included but were not statistically significant.
Source: 1995 MITP Survey
Table 4.13 Changes in Training Levels Over the Past Three Years: Firms Registered with HRDF and Unregistered Firms Registration Status Eligible Registered Firms
Eligible Unregistered Firms
Increased TrainingTraining is the Same
Decreased Training
522
412
12
(49.8)
(39.3)
(1.2)
109 (27.1)
190 (47.3)
21 (5.2)
Note: The percentages do not sum to 100. Close to 10 percent of registered firms and 20 percent of unregistered firms said they did not know. Source: 1995 MITP Survey
training over the last three years , 39 percent firms
creased training over the past three years in regis
said that their training had remained the same, and
tered HRDF firms versus non-registered firms. The
only one percent said that their training had de
effects of HRDF are allowed to vary by firm size
creased. In contrast, of the eligible firms not regis
using a set of interaction terms between firm size
tered with the HRDF, 27 percent said that their
dummies and an indicator variable for being regis
training had increased, 47 percent firms said that
tered with HRDF.
their training had remained unchanged, and five percent said that their training had decreased over
The model includes a set of industry dummy vari
the last three years. Thus, it appears thatHRDFmay have played a role in increasing training provision among registered firms.
ables to control for possible differences in industrycomposition of registered and non-regis tered firms. We include a measure of whether the
firm introduced new technologies over the past three We test this hypothesis formally using a probit
years. The intent was to net out the confounding
model. This model compares the likelihood of in-
effects of increased training due to new technology
TRAINING POLICIES
61
that is independent of HRD F. Finally, separate
sponding increase in demand for training among
models are estimated for pure domestic firms and
such firms.
firms with foreign capital to see if the training ef fects of HRDF varies by foreign ownership. Table 4.13 reports the results of this exercise. They demonstrate that HRDF has had a significant role in increasing training among medium and large firms registered with the HRDF, but not small firms. This result continues to hold for the sample of firms with some foreign capital participation. Among purely domestic firms, HRDF has only been effective in increasing the training of large firms with over 250 employees; the HRDF incentive was not effective in increasing training among small and medium-size local firms. These results were not affected by dif ferences in industrial composition of the two groups, which we control for using industry dummies. However, whether or not firms had introduced new technology in the recent past made a difference. In creases in training and introduction of. new technol ogy over the past three years are significantly correlated, a result consistent with that fmdings in Chapter Two that technological change is accompa nied by higher skill requirements.
Findings and Policy Implications
The DDJI' incentive scheme has generally not proved effective in inducingfirms to train. It has been used primarily by MNCs,joint-ventures,and larger firms who, arguably, were training already. For these firms, the DDIT scheme has meant sizable wind fall gains; for the firms that provided little or no training, the DDIT scheme has failed to induce them to begin, or to increase provision of train ing. Lack of awareness about DDIT, and its re quirements, has been the principal reason for its limited use. A second factor was the heavy re quirements of applying for DDIT, and the corre sponding high rates of rejection, both of which reduced interest in using the incentive. The key lesson for policymakers is that any policy or in centive, whether in training or in other areas, is unlikely to be fully effective if targeted benefi ciaries are unaware of or inadequately familiar ized with the program. Another lesson is that,where feasible, filing requirements should be streamlined to improve take-up of incentives.
The DDJI' incentive is currently restricted to small firms with less than 50 employees; all other firms are covered by HRDF. The Government should eliminate the remaining DDIT coverage entirely
Markets are generally well functioning in Malay
on several grounds. First, it is likely that few
sia, but there is evidence that marketfailures pose
small firms are using the incentive today. Sec
important constraints on trainingfor many employ ers, especially the small and medium-size compa
ond, bringing all firms under the HRDF umbrella greatly simplifies administration, since universal
nies. These include high labor turnover, which
coverage of all firms would searnlessly accommo
prevent employers from recouping investments in
date the growth or shrinkage of firms above or
training; poor information on training methods,
below the 50 employee cutoff. Finally, HRDF is
especipecially how to train or what kinds of training
developing new schemes to support the training
to provide; and inadequate finance for training, es
activities of SMis, and the 50 employee cutoff
pecially among SMis. These market failures justify
would arbitrarily restrict access of small firms to
government intervention. While not a market failure
these programs. The issue of payroll contributions
per se, the use of mature technologies with low skill
for these smaller firms needs to be resolved. The
needs was the principal reason for little or no training
government might consider a waiver of the payroll
both among local firms and SMis. Increased take-up
levy for small firms, and provide HRDF with a block
of incentives to adopt new technology or improve qual
grant from general revenues to cover their use of
ity, such as ITAF schemes, should lead to a corre-
training services.
62
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Non-compliance in HRDF appears to be significant.
deadline granted by HRDC, it is likely that the un
The MITP survey indicates that as many as 27 per
derlying problem remains, especially for smaller
cent of eligible firms with 50 or more employees are
firms. About 60 percent of them provide no train
not registered with, and contributing to, the HRDF.
ing or only unstructured, informal, on-the-job train
I t is concentrated among smaller firms, firms in tra
ing that is not eligible for reimbursement under the
ditional and domestic-oriented industries, firms in
HRDF. Some of their constraints-poor knowledge
the states on the east coast and in East Malaysia, and
about training, not having a training plan, or inad
among firms providing little or no structured train
equate training facilities-are being addressed through
ing. While there may be good reasons to downplay
HRDF'sTNA workshops, theJURUPLANscheme
enforcement in the early gestation period, policymak
to develop training plans, and schemes to fund pur
ers will eventually have to make a strong effort to
chase of training aids. Other factors which limit
address the issue of non-compliance. HRDC cur
demand for training, such as use of mature technol
rently has few personnel or legal officers to devote
ogy, are under the purview of other government
to enforcement. The Government should expedi
agencies, and policies to address them are discussed
tiously provide HRDC with the necessary man
in Chapters Five and Six.
power and legal resources to identify and prosecute HRDC has introduced two new schemes-ITS and
eligible but non-registered firms .
GTS-to encourage group trainingfor smaller em The HRDC should also llWUnt an infonnation cam
ployers, either initiated by groups of small firms
paign, on television and in newspapers, to encour
themselves, or organized by employer associations.
age eligiblefirms to register with HRDC. It should
The MITP survey indicates that such joint training
announce its intention to vigorously enforce com
programs between firms are rare in Malaysia. They
pliance with the HRDF Law and, to ensure that this
are commonly found not among SMis, but among
threat is credible, it should publicize its increased
large firms. When they occur, most are ad hoc ar
enforcement capabilities as well as its prosecutions
rangements. Joint training programs organized by
of selected firms . This campaign should be accom
suppliers and by government agencies are more im
panied by a time-limited amnesty program for firms
portant for small fim1s; joint programs organized
to come forward, register with the HRDC, and pay
by specialized companies are cited by many medium
their back levies without civil or criminal penal
and large fimls; industry associations are also cited,
ties. Similar time-limited amnesty programs have
but primarily by large firms. These industry as
been used effectively in several states in the U.S. to
sociations will have the responsibility, under the
improve compliance.
pilot GTS scheme, for organizing training for SMis. These group-oriented approaches are po
As ofyear-end 1994, over one-third of registered
tentially potent policy instruments for fostering
}inns had not claimed any reimbursementsfor train
training among SMis. Variants of both policies
ing through the HRDF. This figure was especially
have been used, with some success, in a number
pronounced for small and medium size firms about
of developing countries (see Chapter Six) and the
,
half of whom did not claim. While claims have risen
progress of these initiatives in Malaysia should
since them, in large part due to an extension of the
be carefully monitored.
CHAPTER FivE: TEcHNOLOGY, QuALITY
AND
SKILLS
Malaysian policymakers have identified low levels
past three years, and its consequences for changing
of technology and product quality as a bottleneck to
skill needs and employment.
sustained growth and competitiveness. They are actively encouraging firms-through fiscal incentives
This wealth of firm-level data, from such a large
and the activities of technology support institutions:
sample of firms, provides an unprecedented oppor tunity to analyze enterprise decisions to invest in
•
to increase firms ' spending on research and de
technology, to examine the quality control efforts of
velopment,
firms, to identify the effects of introducing new tech
•
to accelerate technology transfer from the MNCs
nology on future skill requirements and productiv
to domestic firms, to invest in automated pro
ity, and to draw out their implications for
duction technologies to economize on scarce
policymakers.
labor, •
•
to modernize small and medium-scale industries
(SMis), to adopt quality control systems and raise prod uct quality to meet exacting international stan dards for exports (MID, IMP Review, 1994).
The 1992 National Survey ofResearch and Devel opment provides some information on industrial train
Technological Characteristics of Firms We begin by using the MITP survey to character ize the technology level of firms in Malaysia, then their efforts to improve quality. Employers can develop their technological capabili ties in several different ways. First, they can de
ing in Malaysia. 1 It indicates that overall the research
velop technology in-house through investments in
and development efforts in Malaysia-about 0.37 per
research and development. Since few local enter
cent of GDP-are lower than projected in the 1990
prises have the requisite scientific, engineering and
Action Plan for Industrial Technology Development
technical capabilities to conduct cutting-edgeR&D,
(APITD), while private sectorR&D spending---0.17
much of this expenditure may reflect relatively mod
percent ofGDP-is higher than projected. However,
est engineering and productR&D activities.
the scale of private sector industrial R&D is Malay sia is relatively modest by international standards
Second, when in-house R&D capabilities are lim
(WorldBank, 19%).2 Much ofR&D is concentrated
ited, technology transfer is an alternative way for
in the electrical and electronics industry and among
local firms to acquire new technology, either through
MNCs, and private R&D spending in Malaysia total
licensing and know-how agreements with other
RM 125.4 million spread over just 97 firms.
firms, or through joint-ventures with foreign firms . Finally, firms can acquire new production technol
In this chapter, we use the MITP survey to provide
ogy embodied in new vintages of capital, through
additional insights on the technology level, quality
investments in automatic machinery, computer-as
control systems, and associated skill needs of enter
sisted production, and testing and quality control
prises. The survey elicited detailed firm-level infor
equipment.
mation on R&D expenditures as a percentage of sales; technology and know-how licensing agree
Table 5.1 begins by providing a broad overview of
ments; investments in automation and quality control
the incidence of these technology indicators by four
equipment, as well as the vintage (age) of machin
firm size categories aiXi by ownership--domestic firms,
ery; quality control methods; IS0-9000 certification;
joint-ventures, and wholly foreign-owned firms.
whether new technology was introduced over the
Three broad sets of indicators are considered:
64
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
•
Research and development -- whether the
most half of this R&D (RM 4.812 million) is concen
firm does R&D, and R&D expenditures as a
trated in the electronics industry.
percentage of sales •
•
Technology transfer -- does the firm have
When these sample estimates are multiplied by the
any technology or know-how licensing agree
population weights, total R&D spending almost
ments, from foreign or domestic sources
doubles--toRM 1,908 million in 1994. Thus, com
Sophistication of machinery and equip
pared to the 1992 R&D survey, the 1994 MITP sur
ment-- percent of equipment that is fully auto
vey finds four times as many firms reporting R&D
matic, whether the firm has quality control or
expendirures, higher per firm R&D spending, and if
testing equipment, and percent of equipment
the weighted estimates are to be believed, almost 15
that is more than 10 years old.
times as much private sector R&D spending as re ported in the 1992 R&D. Some part of this gap is
First, consider the R&D expenditures reported by
undoubtedly due to differences between surveys in
firms in the MITP survey. Out of a sample of2,200
the definition of R&D, and to the two years separat
firms 435 firms or 19.8 percent had positive R&D
ing the surveys. The important point to note is that
expenditures in 1994. Based on reported R&D to
even with this more expansive R&D measure, lev
sales figures, we estimate that these firms spent a
els of private R&D in Malaysian industry are still
total ofRM 1,030 million on research and develop
relatively low in comparison to other Asian NICs
ment, or approximatelyRM 2.4 million per firm. AI-
and industrialized countries.
,
Table 5.1 Technology Characteristics by Firm Size and Ownership Mean Values
Percent of Firms Ownership Type and Firm Size
Do R&D
HaveQC
R&D
Equipment
Automatic
Technology
& Testing
%of
over 10 yrs
equipment
license(s)
Equipment
sales
Have
%
%
Domestic Firms Micro
4.4
1.5
4.4
1.31
39.7
3.1
Small
9.2
2.8
17.1
0.08
34.2
11.6 20.6 27.3
Medium
23.9
5.6
38.4
1.40
25.1
Large
31.4
12.8
50.0
0.38
22.0
Joint-Ventures Small
16.7
10.0
36.7
0.27
28.2
17.4
Medium
23.4
22.5
44.0
0.93
20.9
22.3
Large
38.8
33.8
60.4
1.64
19.3
32.9
100% Foreign Small
15.4
7.7
46.2
0.49
11.4
23.4
Medium
20.7
15.7
47.9
0.43
25.9
Large
26.9
23.1
67.5
2.09
7.2 7.5
Notes:
Micro= less than 16 workers, Small= 16-100 workers,
38.3
Medium= 101-250 workers
Large= over 250 workers. Micro firms not reported for joint-ventures or 100% foreign firms because of small sample sizes. Source: 1995 MITPSurvey
TECHNOLOGY, QUALITY AND SKILLS
65
Table 5.1 shows a striking positive relationship be
Finally, Table 5.1 reveals striking differences in the
tween firm size and the likelihood of R&D. Among
types and vintage of capital equipment by firm size
local firms just over four percent of micro firms re
and ownership. Compared to larger firms, micro,
,
port R&D spending; this figure rises to 24 percent
small and medium size firms are less likely to have
for medium firms and to over30 percent for large
quality control and testing equipment, a smaller frac
finns . A similar size-R&D trend is found amongjoint
tion of their equipment is made up of numerically
ventures and wholly foreign-owned firms. Except
controlled automatic machinery, and a higher frac
for local firms, R&D spending as a ratio of sales gen
tion of their capital equipment is over 10years old.
erally rises with firm size especially among large
Furthermore, for any given finn size, the table shows
firms with foreign capital.
that a progression to more intensive use of testing
A second, intriguing result are the differences by
tages of equipment as the fraction of foreign equity
ownership status. For any givenfirm size, medium
increases in the firm.
equipment, greater automation, and younger vin
and large local firms and joint-ventures are more likely to report R&D spending than wholly foreign
Table 5.2 reports these technology indicators by two
owned firms For example, among large firms with
digit industrial sector. The figures reveal consider
over 1,000employees, over31 and39percent of
able cross-industry variation by foreign equity, by
local firms andjoint-ventures reported R&D spend
capital intensity, and by export orientation. Indus
ing, respectively, as compared to just 27 percent of
tries with high levels of foreign direct investment
wholly foreign-owned finns . Plausibly, the latter firms
(FDI) and joint ventures, such as electrical machin
have few incentives to conduct R&D locally since
ery and chemicals, are more likely to have high pro
.
they can draw on the parent MNC's stock of tech
portions of finns with R&D and technology licenses,
nology and R&D laboratories; these typically are
using quality control and testing equipment in pro
not located in developing economies.
duction. Capital intensive industries with heavy do mestic ownership, such as iron and basic metals and
A similar pattern of technology licenses by firm size
transport equipment, are also relatively technology
and ownership is also apparent. In general, small
intensive. A high proportion of firms in iron and
firms irrespective of their ownership are less likely
basic metals have technology licenses and quality
to report technology licenses than larger firms, re
control equipment, while many finns in the transport
flecting lower levels of technological capabilities in
sector (primarily Proton) report R&D spending. Elec
SMis. Joint ventures are more likely to report tech
trical machinery, along with plastics, rubber and ap
nology licenses than comparably-sized wholly for
parel are also export-oriented industries, and a high
eign firms For example, among small firms, lOpercent
proportion of these firms have quality control and
of joint ventures have technology licenses versus
testing equipment to produce for export markets.
.
eight percent of foreign firms; the differential wid
The remaining industries -- food products, bever
ens among large firms with34 percent of joint ven
ages and tobacco, textiles and apparel, and general
,
tures and 27 percent of foreign firms reporting
machinery -- generally show low overall levels of
technology licenses.
the technology indicators.
This pattern of licensing by ownership status may
Quality Control and Precision in
reflect a conscious strategy by MNCs to recover the
Production
costs of developing new technologies from its joint
To become competitive in world markets, Malaysian
ventures. This incentive to license its technology is
firms will need to produce more and better products
diminished when the enterprise in question is a
that meet international standards for price and qual
wholly-owned subsidiary.
ity. It is not adequate merely to introduce new tech-
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
66
Table 5.2 Technology Characteristics by Industry Percent of Firms Industrial Sector
R&D
Mean Values
Have
HaveQC
R&D
Equipment
Automatic
Technology
& Testing
%of
over10
equipment
equipment
sales
years%
Do
license(s)
%
Food
3.7
1.2
7.9
0.99
19.2
7.0
Beverages & tobacco
1.9
0.3
2.3
0.09
46.3
2.2
Textiles
5.3
0.6
10.2
0.15
12.5
5.9
Apparel
8.1
0.5
11.2
0.51
23.2
4.8
Wood & furniture
4.6
1.4
5.6
0.74
20.3
3.6
Paper & Publishing
4.8
0.7
6.5
0.45
66.9
10.0
Chemicals
30.4
27.0
42.4
1.11
23.1
6.5
Rubber
11.8
5.1
33.0
0.79
29.6
16.0
Plastics Glass & Pottery Iron & Basic Metals Fabricated Metals Machinery
8.3
11.4
14.4
0.08
15.2
16.5
11.1
4.8
17.7
0.30
28.2
7.5
3.8
59.5
66.3
0.02
56.4
5.1
11.6
3.3
19.4
0.90
18.7
5.7
3.7
3.4
18.7
0.80
51.4
6.3
Electrical Machinery
18.9
11.8
76.1
3.23
19.6
27.1
Transport
50.7
2.9
11.9
1.24
82.7
2.2
Other
52.8
2.5
3 .0
0.77
11.3
2.5
Source: 1995 MITP Survey
nologies to reduce production costs. Enterprises will
process control, quality control circles and precision
also need to introduce new fonns of work organiza
testing instruments in production, and only 16 per
tion that emphasize product quality, precision in
cent rely on visual inspection to verify accuracy in
production, consistency of quality, and continuous
production. These figures stand in sharp contrast to
quality improvement. Such organizational features
those for SMis. Less than a quarter of micro and
include the introduction of quality control circles
small firms report using either statistical process con
(QCC), the use of statistical process control (SPC),
trol or quality control circles. Less than one-fifth of
and reliance on quality control and testing equip
them use precision measuring equipment to verify
ment rather than visual inspection to meet the high
accuracy in production; in fact, 64 percent of micro
levels of quality demanded by increasing sophisti
finns and 43 percent of small finns rely exclusively
cated users and consumers.
on visual inspection to verify accuracy. This sharp size differential in quality highlights an area of pri
Table 5.3 reports the incidence, by firm size and
ority for policymakers. There is a clear need for
ownership, of several variables that reflect firms' em
policies to instill quality consciousness among SMis
phasis on product and process quality:
through information dissemination, subsidized QC training, and incentives to use precision measuring
•
whether it relies on statistical process control
•
whether it has quality control circles
•
how it verifies accuracy in production
•
whether it provides training in quality control.
and testing equipment. Second, local finns are less likely than joint ventures and wholly foreign-owned firms to have a quality control system. Between 20 and 25 percent of local
First, firm size is an important determinant of whether
firms use SPC or QCC techniques, and about five
an enterprise has a quality control system in place.
percent provide QC training. The comparable fig
Among large finns , about 50 percent use statistical
ures for joint ventures are 31-46 percent for use of
TECHNOLOGY, QUALITY AND SKILLS
67
Table 5.3 Quality Control and Precision in Production Quality Control System Firm Size and
Statistical Quality
Ownership Type
Process Control
Control Circles
Verifying Accuracy in Production
Quality
Precision
Control
Measuring
Measuring
Training
Equipment
Devices
Simple
Visual Inspection
Firm Size
8.1
4.1
1.6
8.1
23.7
63.8
Small
16.5
25.1
4.7
19.9
31.6
42.8
Medium
30.8
41.7
9.2
34.8
29.9
26.4
Large
49.6
53.5
13.7
52.9
24.5
16.3
Micro
Ownership
20.0
25. 4
5.5
20. 5
30.0
42.9
Joint-Ventures
31.5
46.0
9.9
43.0
28.9
22.3
1 00% Foreign
44.7
47.9
12.3
49.2
25.6
19.4
Domestic
Source: 1995 MITP Survey
these QC techniques and 10 percent of Ns provide
control training variable was constructed from in
QC training. The incidence of QC and QC training
formation provided by employers on the main types
is highest among wholly foreign-owned firms
of training provided to different occupational
.
groups-technicians, supervisors, skilled production While part of this result reflects differences in size
workers and unskilled production workers. A firm
composition by ownership, it is also consistent with
was coded as providing QC training if any one of
the notion that the use of new technology requires
these four occupational groups reported QC training
new fonns of work organization and quality control.
as being the most important training type provided. 3
Are local firms less likely to have quality control systems than joint ventures or foreign firms, once
It very likely understates the incidence of quality
account is taken of size? The answer appears to
control training, since it excludes QC training from
be yes.
external sources and QC training that was a second
Figure 5 .1 graphically shows the incidence of these
provided QC training to one or more occupational
quality control indicators by firm size and foreign
groups. Not surprising, the industries with high pro
ownership. The vertical bars represent the percent
portions of finns providing training in quality con
ary area of training. By this defmition, 160 firms
of local firms, joint ventures (Ns), and wholly for
trol-electrical machinery, plastics and chemicals-were
eign owned firms reporting each QC indicator. The
also the industries where QC methods are common.
four panels clearly show that controlling for firm size, a higher proportion of joint ventures and wholly for
To summarize , the MITP data show that the scope of
eign firms use statistical process control, quality con
private R&D in Malaysia is relatively low by interna
trol circles and precision measuring instruments to
tional standards. Furthermore, there are large dif
verify accuracy in production as compared with do
ferences in technological capabilities-as measured
mestic firms. Across all size categories, a much higher
by R&D, technology licensing, sophistication of ma
proportion of domestic firms rely on visual inspec
chinery, and quality control systems-between local
tion to verify accuracy in production as compared
and foreign-owned firms, and between SMis and
with foreign firms.
large finns. These size and ownership differences in technological capabilities mirror those involving
Finally, the table confinns that the introduction of
training, which is not surprising, given the strong
quality control systems increases the requirement for
linkages between training and technology revealed
training in quality control techniques. This quality
by the analyses in previous chapters.
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
68
Figure 5.1 Quality Control Systems by Firm Size and Ownership
A. Statistical Process Control
B. Quality Control Circles
70 60
50
50
40
40
30
30
20
20
10
10
0 +-"""'"'---+ro E
70
60
60
50
50
40
40
30
30
20
20
10
10
u
.E
12' .!!!
E
D. Visual Inspection Only
70
0 +-'-----t-
QJ
::J
�
Ul
C. Precision Measuring Equipmt.
e
E
ro E
Ul
�------....,
0 ro E Ul
E
::J 15 QJ
E
QJ
1111 Local
If finns with weak technological capabilities are also
E ::J 15 QJ E
ro E Ul
12'
.!!!
0
QJ
12' .!!!
Foreign
First, the overwhelming demand from firms is for
the same ones with weak training capabilities, it im
diffusion services for known technologies rather
plies that policies should be designed to address both
than support to develop wholly new technologies.
sets of finn-level weaknesses and constraints since
For Malaysia, this means focusing support on tech
the target population is the same. A recent study of
nology transfer, licensing agreements, dissemi
technology-support institutions in six countries sug
nation of information, standards and testing, and
gests some broad directions for the design of tech
skills training rather then public R&D or R&D
nology policies to address these firm size and
ince n t i v e s f o r f i r m s .
ownership differences in capabilities (see Box 5 .1).
prioritization o f technology diffusion, rather than
Su p p o r t f o r t h e
TECHNOLOGY, QUALITY AND SKILLS
69
Box 5.1 Use of External Sources of Technical Support by Firms A recent World Bank study looked at six economies--Japan, Korea, China, India, Mexico and Taiwan--to examine the key characteristics of technology support institutions (Tis) and their use by industrial firms (Goldman, 1 995). Tis were broadly defined to include all public and private sources of technology and training support used by firms, including (i) national technology and standards institutes, industry associations, and productivity cen ters; (ii) private sources such as foreign technology licensors and contract laboratories; and (iii) technical assistance from suppliers and buyers.
Over two thousand firms were
interviewed, including both small and large firms and covering six sectors. Several of the principal findings and conclusions are summarized below. The overwhelming demand by firms, both large and small, is for services related to technology diffusion, i.e. the transfer and application of known technology.
Firms most
commonly use basic services related to acquisition of information, standards and test ing, trouble shooting, and technology-related training. And when firms use R&D services of public Tis, they tend to contract for answers to specific technology questions, rather than for development of new technologies. While larger firms tend to use Tis more intensively than smaller firms, use is also shaped by whether firms have in-house laboratories or technical departments. This is especially pronounced among small firms, where those with in-house resources use Tis at nearly twice the rate of other small firms. This highlights the difficulty of reaching and serving small firms, particularly those without internal technological capabilities. Large firms are also three times more likely than the overall sample to have received grants, tax incen tives or soft loans for technology; only assistance directed at technology diffusion--such as help in developing standards, or subsidies for training--seem to be taken up by small as well as by larger firms. A high proportion of firms reported using a public Tl at least once, though long-term customers, followed by suppliers, were the most commonly used external sources of technology.
The survey found that small firms require special Tis dedicated to them;
otherwise, they obtain little or no support. Tis focusing on small firms need to work proactively to expose them to the benefits of change if demand is to be generated for technology improvement and assistance. The Japanese approach--support directed at industry clusters in a region and focusing on technology diffusion--is quite effective in reaching a large number of small firms. The Taiwanese approach--productivity centers which develop generic expertise with applicability to small firms in a wide range of indus tries--is also effective, but reaches a lower fraction of the target population.
development, was provided in Chapter Three
ized support institutions working actively to de
which showed licensing to have greater produc
liver technology support services to hard-to-reach
tivity effects than R&D.
SMis, especially those with limited in-house ca pabilities, to expose them to the benefits of change
Second, larger firms use support services more in
and create demand for technology improvement
tensively, and their take-up of technology incen
and assistance. For Malaysia, this means restruc
tives is more common, than smaller firms. SMis
turing the way public institutions deliver support
have special needs, and these are seldom met by
to firms, SMis in particular-from one that relies
broad-based institutions. They require special-
on firms to take-up incentives, to one in which
70
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
technology support services are delivered
systems and the structured training programs needed
proactively to firms. These policies are discussed
to attain those standards.4 The Brazilian experience
in greater length in Chapter Six.
indicates that adoption ofiS0-9000 certification and total quality management standards (TQM) in pro
150-9000 and Quality Assurance It is increasingly recognized that standards and me
duction has led to productivity and quality gains (see Box 5.2). IS0-9000 certification also provides a strong signal to clients that a firm is prepared to
trology can be an important policy instrument for
attain and maintain high and exacting quality stan
improving and diffusing modem production meth
dards (Frischtak, 1995). As such, it has become the
ods and quality control systems (Dahlman, 1992), and
prerequisite for doing business in many sectors of
upgrading product quality to meet the exacting in
the European Community (EC) and, increasingly,
ternational standards for export markets. One such
is being extended to the East Asian Trade area around
voluntary standard, the IS0-9000 series introduced
Japan.
in 1987 by the International Standards Organization, represents the international consensus on how best
The MITP survey provides insights into the adop
to operate and assess quality management systems.
tion of IS0-9000 standards in Malaysia. There is
The publication of IS0-9000 standards provides
Malaysian firms. The Standards and Industrial Re
growing interest in implementing IS0-9000 among firms with a benchmark of what constitutes best
search Institute of Malaysia (SIRIM), which is re
practice in their specific area, and thus incentives to
sponsible for metrology and standards, is the
put in place both the quality control and assurance
registration body for IS0-9000. It has awarded 700
Box 5.2 Diffusion and Impact of IS0-9000 in Brazil Many observers attribute the recent productivity and quality gains in Brazilian industry to producers' commitment to total quality management (TQM) and adherence to international quality standards of the International Standards Organization (ISO) 9000 series.
The diffusion of IS0-9000 among in
dustrial firms has been rapid--between 1990 and 1994, the number of certified firms increased from 18 to 577, an average annual growth rate of 138 percent. The industries with the greatest number of certified firms are electrical equipment and instruments, chemicals, basic metals and fabricated products, and general machinery.
A number of factors were responsible for the rapid diffusion of TQM and IS0-9000 certification- industrial restructuring during the 1990-92 recession, major trade reforms beginning in 1990, and growing awareness of the increasing importance of quality control to meet client needs, reduce costs, and improve competitiveness viz. a viz. international producers. The Government has played an active diffusion role through the Brazilian Program for Quality and Productivity (PBQP). The PBQP provides (1) analysis of the market environment, (2) assessments of systemic and internal con straints to competitive behavior and the diffusion of TQM (3) establishment of sectoral and global benchmarks in terms of productivity and quality indicators, (4) dissemination of information on TQM and provision of TQM training, and (5) subsidizing adoption of TQM practices.
A recent survey of 93 major Brazilian enterprises indicates that adoption of new managerial methods for quality control, IS0-9000 certification in particular, has had beneficial effects on the firm--55 percent cited increases in productivity, 35 percent improved standardization of processes, 31 per cent increased employee participation in quality control, 25 percent in product quality improvement, and over 20 percent cited increases in client satisfaction (Frischtak, 1995).
TECHNOLOGY, QUALITY AND SKILLS
71
Table 5.4 IS0-9000 Status and Quality Control Systems Systems of Quality Control and Verification of Accuracy
With IS0-9000
Seeking IS0-9000
Certification
Certification
No IS0-9000 plans
Firms
%
Firms
%
Firms
%
229
10.4
731
33.2
1,240
56.4
Statistical Process Control
130
56.8
268
36.7
171
13.8
Quality Control Circles
123
53.7
329
45.0
268
21.6
141
61.6
299
41.0
198
16.0
47
20.5
216
29.6
370
29.9
22
9.6
154
21.1
609
49.1
Total Sample of Firms Quality Control System
Verifying Accuracy in Production Precision Instruments Simple measuring devices Visual Inspection Source: 1995 MITP Survey
foreign and local finns with some level ofiS0-9000
and implemented systems of quality control and
certification, and is reportedly in the process of as
quality assurance. A much higher proportion of
sessing another 600 firms.
IS0-9000 certified firms use QCC and SPC to en sure quality in production and precision instruments
The survey elicited information from firms about
to ensure accuracy in production, followed by finns
whether they had any IS0-9000 series certification,
seeking certification within the next three years.
and if they did not, whether they expected to gain
Firms with no plans for IS0-9000 certification are
IS0-9000 certification within the next three years.
much less likely to report use of QCC or SPC, and
This second question was designed to identify finns
are significantly more likely to rely on visual in
that were preparing for certification, a process that
spection to verify accuracy in production.
can take as long as three years. Firms that did not currently have IS0-9000 certification, or were not
Table 5.5 reports the distribution ofiS0-9000 sta
expecting it within three years, were classified as
tus by firm size and ownership. It indicates that
having no plans for IS0-9000 certification.
while the number of IS0-9000 certified firms is small, interest is growing. Currently, over 30 per
Table 5.4 reports the number of firms with IS0-
cent of large finns are certified, but the proportion
9000 certification, those seeking certification and
of micro, small and medium firms with IS0-9000
those without certification. Out of 2,200 firms in
certification is relatively low-less than one percent
the MITP survey, 229 firms (10.4 percent) had
among micro firms four percent among small firms
IS0-9000 certification; 731 firms (33.2 percent) ex
and eight percent among medium-size firms. The
,
,
pected IS0-9000 certification within the next three
trend in the number of firms expecting certification
years, and 1,240 firms (56.4 percent) did not have
is more optimistic, with 27 percent of small firms
certification and did not have any plans to become
and 48 percent of medium firms expecting IS0-9000
certified. Industries with the highest fraction of firms
certification within the next three years. This trend
with IS0-9000 included the most technology-inten
implies that within three years, over three-quarters
sive industries such as electrical machinery and
of large firms will have IS0-9000 certification.
chemicals as well as the export-oriented industries such as rubber and plastics.
Nonetheless, the total coverage ofiS0-9000 among micro firms will still be below seven percent at the
The bottom panel of Table 5.4 show the distribu
lowest end of the size spectrum. This highlights a
tion of quality control systems by firms' IS0-9000
potentially important area of focus for Malaysian
status. IS0-9000 certifies firms to have documented
policymakers. Another important area of policy fo-
72
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 5.5 150-9000 by Firm Size and Ownership Firm Size and Ownership Type
%Firms With
%Firms Seeking
%Firms With No
IS0-9000
IS0-9000
IS0-9000
Certification
Certification
Plans
Firm Size Micro
0.8
6.5
92.7
Small
4.2
26.9
68.9
8.2
48.2
43.5
31.3
43.6
25.1
Medium Large Ownership Type
5.6
29.6
64.8
Joint-Ventures
14.3
43.9
41.8
100%Foreign
27.8
35.3
36.9
Domestic
Source: 1995 MITP Survey
cus should be local firms. Compared to joint ven tures (14 percent) and foreign-owned firms (28 per cent), only about five percent of local fums currently haveIS0-9000 certification. H owever, this appears to be changing. A growing number of local fmns appear to realize the importance of total quality man agement and quality standards for improving com petitiveness and meeting the increasingly high standards demanded in international markets--thirty percent of them expect to get IS0-9000 certification within the next three years.
IS0-9000. According toSIRIM, the SMI section has provided QIP consultancies to a cumulative to tal of 162SMis by the end of 1995.
SIRIM can play a greater role in disseminating international best practices in production and qual ity control to employers and, through their adop tion of IS0-9000 standards, improve the competitiveness of local firms. The recent corporatization ofSIRIM in 1996, and the reorga nization of the institution that is now in progress, should allow it to respond more flexibly to the dramatic growth in private sector demand forIS09000 certification. 5
QIPs developedjointly bySIRIM and leadingMNCs in specific sub-sectors, are a potentially powerful policy instrument for assisting groups ofSMis to upgrade their quality and to foster increased link ages withMNCs and other larger firms. For many MNCs, a major obstacle to developing supplier rela tions with localSMis is the low and uneven quality of their products(Fong, 1991).SMis may notknow what quality standards are required to become part sup pliers, so that few are willing to invest the necessary resources to upgrade quality practices on the chance ofbecoming a subcontractor. To the extent that QIPs can establish clear, and certifiable, quality standards acceptable to leading firms in a given sub-sector, they provide tangible incentives not only forSMis to improve and upgrade their quality control prac tices, but also forMNCs and other larger employers to accept QIP-certified SMis as part suppliers.
Not all firms,SMis in particular, can afford the high cost and time required (about three years on aver age) to meet IS0-9000 standards.SIRIM can play an expanded role in helpingSMis to improve quality control by building on its existing, but thus far lim ited, consultancies on Quality I mprovement Prac tices (QIP), which are less expensive to attain than
S ub-sectoral QIPs, when developed, are amenable to group provision of assistance toSMis in terms of consultancies, training, finance, as well as technical assistance from leading firms in the industry. SIRIM should pursue this program in collaboration with other goveriUIY;!nt agencies-such as the National Productivity Corporation (NPC), HRDC, and
TECHNOLOGY, QUALITY AND SKILLS
MID's SMI agency-and with leading private sector
73
countries, Australia, and New Zealand. All other countries, primarily those in ASEAN and the
finns.
Middle East, are included in the developing mar ket category.
150-9000 and Export Orientation Table 5. 6 shows the proportion of firms exporting There is considerable anecdotal evidence linking
to different markets by their I S0-9000 status.
quality certification to producers' efforts to penetrate
They suggest two points. First, among firms with
developed markets in the US, the EEC, and Japan
out plans for IS0-9000 certification, a lower pro
(see Frischtak, 1995). In Malaysia, we also observe a
portion export to industrialized markets (20
strong correlation between IS0-9000 certification
percent) as compared to developing country mar
and the export status of firms. About 82 percent of
kets (24 percent). Second, firms with IS0-9000,
IS0-9000 certified firms currently export, while
or in the process of certification, are more likely
export-orientation is 69 percent among firms seek
to export to industrialized country markets-47 and
ing certification within the next three years, and
36 percent, respectively-than to developing coun
just 44 percent among those without certification
try markets, where the corresponding fractions
and not planning to do so in the near future. While
of exporting firms is 36 and 33 percent. The third
it is difficult to establish a causal relationship be
column, which is conditioned on exporting, rein
t ween getting IS0-9000 certification and in
forces these points, namely, that the relative impor
creased exports, these figures suggest that the
tance of exports to industrialized markets increases
firms which already have IS0-9000 certification
with firms' efforts to get IS0-9000 certification.
.•
or those in the process of being certified, are bet Figure 5. 2 shows the proportion of firms exporting
ter able to compete in export markets.
to each market type in each of 16 industries where Exporting is clearly not precluded for firms without
industries are sorted in ascending order (from left to
certification. However, it may be more difficult with
right) by the share of firms with IS0-9000 certifica
out IS0-9000 certification to break into industrial
tion. The percentage share of certified firms in each
ized country markets, where quality requirements
industry is represented by the heights of bars. The
tend to be higher, than it is to export to developing
dark shaded area shows the percent of firms export
countries. To determine ifiS0-9000 certification
ing to industrialized country markets, the light shaded
makes a difference, we distinguished between in
area the corresponding figure for exports to devel
dustrialized country markets and developing
oping country markets.
country markets on the basis of firms reported
primary export market. The industrialized mar
In all industries, a higher proportion of firms ex
kets include the United States, Japan, the EEC
port to developing country markets than to indus trialized markets, as is evident by the light shaded
Table 5.6 IS0-9000 and Export Orientation
% Firms that Export IS0-9000 Status
To
To
Exporting Firms % exporting to
industrialized
developing
industrialized
countries
countries
countries
No certification plans
20.3
23.5
46.6
Seeking IS0-9000 certification
36.0
33.3
51.8
With IS0-9000 certification
46.5
36.0
56.3
Source: 1995 MITP Survey
74
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Figure 5.2
150-9000 and
Exports
90 80 70 60 50 40 30
1
20 1 o 0
-e "'
(l_
(l_
<(
"'
"0
"'
0 u...
Q) � Q) > Q)
aJ
0
E
.2 ciS "0 0
Q;
(l_ "'
[L
�
• industrialized
"'
2 "' :2 .ri "' u...
"' ()
"'
� � Q)
� "' 0::
f-
"'
Q; £ 0
t: 0 (l_ "'
c: �
f-
0 de v elo ping
"' ()
"E= �
"' (.)
"'
2:Q)
�
c:
.c:
:c () "'
"E= Q) (.)
:2
"'
a> 2 en c
_g
Q;
_Q _Q
::J
0::
.c () "'
:2 <.i "'
w
lli!!IIS 0-9 0 0 0
i
__
area being above the dark area. With some excep
with an "umbrella" subcontracting scheme where, in
tions, the general trend is for the export-orientation
return for a commission, a large firm helps Malay
of industries to rise with the share of firms having
subcontractors market their products and provides
IS0-9000 certification in the industry. The exceptions-apparel, textiles, wood and furni ture-are highly export-oriented industries where other factors may play a more important role than formal IS0-9(XX) certification. In textiles and apparel, a very high proportion of
finns give formal training to employees-58 percent
and 37 percent, respectively-as compared to the overall sample average of about 21 percent (see
Chapter Two). These two industries also stand out
them with a wide range of technical, management, training and financial services. Guthrie aggressively entered the export market in 1991 with a furniture finishing plant in Port Klang. We estimated regression models to explain firms' export propensities to industrialized and develop ing country markets by their IS0-9000 status, con trolling for firm size, foreign ownership and industry. Two kinds of models are used. The first is a probit_model, to explain the probabilities that a
firm exports to industrialized markets and to devel
in the proportion of firms that have quality control
oping country markets. The second is an ordered
dustry, in contrast, has a relatively low proportion of
comes-do not export, export to developing country
and testing equipment. The wood and furniture in firms that give formal training (11 percent). Its ex port orientation may reflect its abundant resource base (lumber), or the presence of a marketing agent such as Guthrie Furniture. It is unique in being one of two industries (the other is the food industry)
probit modeLto explain three potential export out markets, and export to industrialized markets-which are ranked in ascending order of difficulty. This model provides a direct test of the hypothesis that exporting to industrialized markets is more diffi cult than exporting to developing country markets.
TECHNOLOGY, QUALITY AND SKILLS
75
Table 5.7 IS0-9000 and Export Propensity by Principal Markets Probit Independent Variables
Export to developing countries
Small
(16-100 workers)
Medium (101-250 workers)
Large (>250 workers)
Joint Ventures
Seeking IS0-9000 Certification
With IS0-9000 certification
Export to industrialized countries
Export to different country groups
0.413a
0.766a
0.589•
(0.148)
(0.279)
(0.143)
0.582a
1.457a
1.251"
(0.147)
(0.275)
(0.142)
0.411a
1.786a
1.609a
(0.162)
(0.282)
(0.155)
0.436 a (0.076)
100 % foreign firms
Ordered Probit
0.183b
0.426a
(0.082)
(0.069)
0.072
0.840a
0.978a
(0.095)
(0.098)
(0.088)
0.109
0.251a
(0.071)
(0.077)
0.264 a (0.064)
0.105
0.283b
0.296a
(0.112)
(0.115)
(0.137)
ll for exports to Developing Countries
0.975a (0.244)
ll for exports to Industrialized Countries
1.999a (0.246)
Log likelihood
-1202.484
-976.543
-1787.01
a= Significant at 1 % b
=
Significant at 5 %
Note:
Numbers in parentheses are standard errors. Industry dummy variables were included in the models but are not reported here.
Source: 1995 MITP Survey
Table 5. 7 reports the results of estimating the two
ond, foreign ownership is not generally a key deter
kinds of models, probits in columns one and two
minant of exports to developing countries (except
and the ordered probit in column three. Several results are suggested by the probit estimates. First, compared to micro firms (the comparison group),
for joint-ventures) but it is a critical factor in ex ports to industrialized markets. In this regard, being a wholly foreign-owned firm is more im
larger firms are, with one exception, more likely
portant than being a joint-venture, not surprising
to export to both industrialized and developing
since many local subsidiaries produce for export
country markets. This is attributable to the strong association between size and a wide variety of mea sures of productivity (see previous chapters). Sec-
to MNC parents. Finally, IS0-9000 is not sig nificant in explaining exports to other develop ing countries.
However, having IS0-9000
76
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 5.8 Introduction of New Technology Since 1992 %afFirms Firm Attributes
%Share Type ofNew Technology"
Any new technology?
All firms
Live Computerization Automation
New Machinery
42.4
24.5
17.7
57.7
Micro firms
13.4
12.1
15.2
66.7
Small firms
31.5
21.5
11.6
65.9
Medium firms
51.2
24.1
19.0
55.8
Large firms
68.9
26.5
23.0
50.5
Firm Size
Ownership Domestic firms
35.5
23.3
15.2
60.9
Joint-ventures
53.5
23.6
21.5
51.3
100 % foreign firms
58.3
20.0
21.1
57.2
a=
Conditional on introducing new technology since 1992.
Source: 1995 MITP Survey
Table 5.9 Effects of New Technology on Skill Needs and Employment Firms Introducing New Technology Since 1992 a
Overall
Micro
Small
Medium
Large
43.3 34.3
46.4
48.1
34.4
31.3
Resulting Employment Change % reporting increases
46.3
35.7
% reporting decreases
35.2
35.7
Resulting Skill Needs Change % reporting increases
78.6
64.3
75.6
78.7
80.7
% reporting decreases
14.6
21.4
18.9
13.9
13.0
a=
conditional on introducing new technology in the past 3 years.
Source: 1995 MITP Survey
certification, or actively seeking it, is important
function shifts for exports to the two different
for exporting to industrialized country markets.
markets. The f-l values are positive, indicating that exporting is more difficult than not exporting.
The ordered probit estimates reported in column
However, the f-l value for industrialized country
three of Table 5. 7 reinforce the principal find
exports is larger than the m for exports to devel
ings of the previous probit models. Conceptu
oping country markets, suggesting that industri
ally, it is the more rigorous model in that it takes
alized country markets are more difficult to
into account all three export outcomes, rather than
penetrate. In such a competitive global market, a
treating the two export markets as being indepen
firm commitment to improve quality control,
dent of each other. Clearly, they are not. The or
adopt TQM methods, and seek IS0-9000 certifi
dered probit model yields two extra parameters,
cation can help Malaysian firms penetrate the mar
f-l, which measure how the export propensity
kets of industrialized countries.
TECHNOLOGY, QUALITY AND SKILLS
77
New Technology and Changing
percent) did not, and the rest (three percent) did
Skill Needs
not respond or did not know. Of those introducing
How will skills and training needs change as firms
machinery (58 percent), followed by computers such
introduce new technologies, and what are the effects
as CAM and CIM (25 percent), and then line auto
on productivity growth? While time-series data are
mation (18 percent).
technology, the most common was new production
needed to address this question, some insights are This table also shows striking differences in the
provided by the MITP survey.
introduction of new technology across firm size
Firms were asked whether they had introduced new
and ownership groups. In general, large firms
technology in the past three years, the nature of the
were more likely to have introduced new technol
technology, and whether its introduction was accom
ogy, especially computerization and line automation,
panied by increased, unchanged, or decreased em
while smaller firms were more likely to have intro
ployment and skill requirements. Unfortunately,
duced new production machinery. In terms of
those not introducing new technology were not
ownership, a higher proportion of firms with for
asked to respond to questions about changes in
eign capital introduced new technologies as com
their employment and skill needs. As such, there
pared to local firms. As before, new production
is no way to determine if employment and skill
machinery was the most common form of technol
needs might have changed for reasons unrelated
ogy introduced in all three ownership categories.
to whether or not the firms introduced new tech
The second ranking type of technology intr o
nology. However, allfirms were independently
duced was computerization in domestic firms and
asked about whether their worker training had
joint-venture firms; however, wholly foreign-owned
increased, stayed the same, or decreased in the past
firms emphasized line automation.
three years. We combine both responses to look at how introduction of new technology has affected skills and training needs, whether its effects differ by firm size, and how it affects productivity.
Employment and Skill Needs Employers were asked whether introduction of new technology had an impact on employment and the skill content of jobs. Table
Table 5.8 provides some summary figures on the proportion of firms introducing new technology over the past three years, and the nature of the new tech
5.9 tabulates their
responses. Of the technology,
925 firms that reported new 428 firms (46 percent) reported that it
led to increases in employment while a smaller
nologies put in place. Out of the 2,200 firms in the
number,
922 firms (42 percent) said that they had introduced new technologies, 1,214 firms (55
technology displaces jobs, the figures suggest that
MITP sample,
324 firms (35 percent), reported a fall in
employment. Thus, contrary to concerns that new
Table 5.10 New Technology and Changes in Training since 1992 Introduced New Technology Training Since 1992 Firm Size
Increased
Same
Decreased
No New Technology Training Since 1992 Increased
Same
Decreased
Overall
50.7
37.6
1.4
21.6
56.6
Micro
33.3
48.5
9.1
7.7
64.6
2.9
Small
35.1
48.3
1.7
17.0
57.8
4.1
Medium
50.7
38.7
0.7
31.4
55.0
3.7
Large
67.4
25.6
1.0
48.5
40.8
2.3
Source: 1995 MITP Survey
3.6
78
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
two-thirds of firms reported either no decrease in
However, it is weakened by not having a benchmark
employment or an actual increase in employment
to compare reported changes in skill needs among
as a consequence of introducing new technology.
firms not introducing new technology. The issue is
What is even more striking are the figures on
skill changes, or for that matter employment
changes in skill content from the introduction of
changes, to introduction of new technology rather
new technology. Fully 79 percent of firms re
than to other contemporaneous factors. These fac
ported that the new technologies led to an increase
tors might include tightening labor markets or
in skill content, while only 15 percent of firms re
changes in work organization. We address this is
whether respondents are able to accurately attribute
ported a decrease in skill needs. These results are
sue in Table 5.1 0, by comparing employers' inde
essentially unchanged when the figures are broken
pendent responses on how their training has changed
down by firm size. However, there is a percep
over the past three years, separately for firms that
tible trend by firm size- among firms introduc
introduced new technology and for those that did
ing new technology, the proportion of firms
not. The employer responses in Table 5.10 make
reporting employment increases and higher skill
three points:
needs rise with firm size. The converse is also reporting declines in employment and skill con
First, introduction ofnew technology is accompa nied by increased training. Among firms that in
tent falls.
troduced new technology over the past three
true, that as firm size increases, the proportion
years, a higher proportion of them also reported This evidence is consistent with analyses in previ
increasing worker training (51 percent), as com
ous chapters that link adoption and assimilation of
pared to the firms that did not introduce new tech
new technologies to skills upgrading and training.
nology (22 percent). Furthermore, firms with new
Table 5.11 Impact of New Technology on Training Firm Size
Marginal Effect
Standard
%Firms Currently
of Introducing
Deviation of
with Formal
New Technology In Past 3 Years
New
T raining or
Technology
Increasing Training
Variable
over Last 3 Years
%Firms with 1 std. dev. Increase in Introduction of New Technology
Probability of Currently Providing Formal Training Small
0.089•
0.448
23
Medium
0.093
b
0.500
51
56
Large
0.039
0.463
71
73
27
Probability of Increasing Training Over Past 3 Years Small
0.104•
0.448
20
25
Medium
0.160•
0.500
41
49
Large
0.082
0.463
62
66
a=Significant at 1% b=Significant at 5%. Note: Column 4 =column 3 +(column 1 x column 2 x 100) Source: Annex 5.1, Tables A5.1 and A5.2.
TECHNOLOGY, QUALITY AND SKILLS
technology were less likely to report no changes in the level of training (38 percent) as compared to those without new technology (57 percent). Second, larger firms are more likely to have in creased training in the recentpast, especially if they also introduced new technology. Compared to smaller firms a higher proportion of large firms re ported increasing training in the past three years ir respective of whether or not they introduced new technology. However, those with new technology were more likely to increase training than those that did not. ,
Finally, introduction of new technology reduces the training gap between small and largefinns. Among firms that did not introduce new technology, a very low fraction of small firms increased training as com pared to large firms-17 versus 48 percent. Among firms that introduced new technology, the corre sponding figures for small and large firms are 35 and 67 percent, respectively. Thus, new technology is associated with a doubling in the probability of-in creased training for small firms (from 17 to 35 per cent) as compared to the smaller increase for their large counterparts (from 48 to 67 percent). To see if these trends are robust, we estimate probit models to analyze the impact of new tech nology introduced in the past on two measures of training. The first-whether the firm increased training since 1992-does not distinguish between formal training and informal OJT. Furthermore, since the survey asks whether training increased, stayed the same, or decreased since 1992, it implicitly assumes that employers were already doing some informal OJT or formal training during this period.6 The second measure-whether the firm currently provides for mal structured training-is less subject to these ca veats. Taken together, the two measures provide a crude decomposition of the potential training effects of new technology introduced in the past: (i) increasing the probability that a firm provides formal training today, and (ii) increasing the lev-
79
els of training for firms already investing in the skills of their workers. The training probit models contain a comprehen sive set of explanatory variables on current attributes of the firm (ownership, industry, and export-orien tation), its workforce including mean education and both skill and sex mix, work organization and quality control, as well as its contemporaneous investments in R&D. These control variables al low us to isolate the training effects of past in vestments in new technology, holding constant the effects of other influences. We estimated separate probit models for each one of three firm sizes-micro and small firms with less than 100 workers, medium firms with 101-250 em ployees, and large firms with over 250 employ ees. This approach allows us to confirm the previous finding that introduction of new tech nology has a greater impact on small firms than on large firms .
The probit results are reported in Annex 5.1. For ease of interpretation, the marginal effects of ex planatory variables are shown in column one. Panel A for current provision of formal training, Panel B for increases in training over time. These probit results confirm the principal trends revealed by simple tabulations of the data. Controlling for other influences, introduction of new technology has positive and statistically significant effects both on the probability that employers currently provide for mal training to their employees, and on the likeli hood that they increased levels of training over the past three years. However, this finding only holds for micro, small and medium-size firms; in large firms, these training effects are not statistically significant possibly because most are already doing a great deal of training. These probit results can be used to simulate what training would be like, if the proportion of firms in troducing new technology is increased by one standard deviation (column two). Column three
80
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 5.12 Impact of New Technology on Productivity by Firm Size
Estimated
Firm Size
Mean (std. dev.)
Parameter from
of new technology
Prod. Function
indicator variable
% Productivity change with 1 std. dev. increase in new technology use
Overall
0.229_QI
0.420
(0.494)
11.3
Small
0.507_QI
0.278
(0.448)
22.7
Medium
0.301
0.512
(0.500)
15.1
Large
0.338
0.689
(0.463)
15.6
a=Significant at 1% b =Significant
at 5%
Note:
Column 3 =column 1 x std. dev of column 2 x 100
Source:
Annex 5.2, Table A5.3.
shows the existing distributions of the two train
Impact on Firm-Level Productivity
ing variables, and column four what the new train
The fmal question we address is whether introduc
ing distributions would be if a higher proportion
tion of new technology in the recent past affects cur
of fmns introduced new technology. To illustrate,
rent levels of productivity. We do this within the
column four is calculated for small firms in Panel
production function framework used in Chapter
A by multiplying columns two and three by 100 to
Three. The model specification adopted here is
get the percentage increase in small firms provid
broadly similar, and needs no additional explana
ing formal training, and adding this increase to
tion (see Annex 5.2).The only difference is the in
the existing percent of small firms already train
clusion of an indicator variable for whether the
ing. These simulations suggest the following out
employer introduced new technology in the past
comes of higher rates of new technology
three years. We want to see whether past invest
introduction:
ments in new technology explain current levels of firm-level productivity, even after controlling for
•
The number offinns that provide formal train
contemporaneous investments in training and R&D.
ing rises. The proportion of firms that train in
Furthermore, we ask whether the productivity ef
creases from 23 to 27 percent for smaller firms,
fects from the past introduction of new technology
from 51 to 56 percent for medium firms, and
varies across firms of different size.
from 71 to 73 percent for large firms •
.
The i mpact on formal training is greater for s maller firms. As a proportion of firms that currently train, the increase for small, medium and large firms is 17.4, 9.8 and 2.8 percent respectively.
•
The number offirms increasing formal train ing or informal OJT rises dramatically. This is most pronounced among small firms--com pared to those that increased training over the past three years, the rate of expansion is 25 percent for small firms, 19.5 percent for medium
firms, and 6.5 percent for large firms.
Column one ofTable 5.12 reports the estimated production function parameters of the new tech nology variable for the overall firm sample, and separately for small, medium and large firms Since .
the dependent variable (value added) is ex pressed in natural logarithms, the parameter of the new technology variable can be directly in terpreted as the percentage change in value added from introducing new technology. Controlling for firm and worker characteristics and contemporaneous investments in worker training and
R&D, two conclusions are suggested by the regres-
TECHNOLOGY, QUALITY AND SKILLS
81
sion results. First, for the overall sample of firms,
ownership. Given the weak R&D capabilities of
the introduction of new technology over the past
most domestic firms, it may be more promising for
three years is associated with a 23 percent increase
firms to acquire technology through licensing agree
in productivity levels. Second, for micro and small
ments and know-how embodied in new equipment
furns, the productivity impact of introducing new
than to develop in-house indigenous technology.
technology is even larger-about 50 percent.
When accompanied by formal training, these exter
nal sources of technology, but not R&D, are associ How would mean levels of productivity in each fum
ated with large productivity gains (see Chapter
size group change if a higher proportion of employ
Three).
ers introduced new technology? Column three in dicates that a one standard deviation increase in the
The policy implication is that greater emphasis
fraction of furns introducing new technology is as
should be placed on facilitating technology and
sociated with much larger productivity improve
know-how diffusion to local firms. This may be
ments among small furns about 23 percent, than the
done through dissemination of information on ap
15 percent average increase in productivity among
propriate technologies, expedited processing of
,
technology licensing applications by MIDA, in
larger furns
.
centives for firms to adopt new technology and This implies that high priority should be given to
purchase new equipment, and greater links be
encouraging SMis to adopt new technology. New
tween local firms and MNCs.
technology which has a direct impact on produc tivity, as well as an indirect productivity effect from
A growing number offinns have implemented qual
training, coming through increased training to
ity control techniques and introduced precision mea
meet the skill requirements of new technology.
suring instruments. This concern with quality is concentrated among foreign-owned and larger firms
Findings and Policy Implications Private sector R&D investments in Malaysia are rela tively low compared to other developing coW1tries. The MITP estimates are broadly consistent with MASTIC's 1992 National Survey of R&D and they confirm that very few SMis engage in R&D activi ties. The number of firms doing R&D rises with size, and between 30 and 39 percent of large firms report some R&D expenditures. Of note is the find ing that wholly foreign-owned furns are less likely to report R&D as compared to local firms or joint-ven tures of similar size. MNCs source their technology from abroad, and it is unclear, given the small local scientific and engineering base, whether financial incentives alone will induce MNCs to locate R&D activities in Malaysia.
ment, as compared to about one-fifth of micro and small firms; most SMis rely on visual inspection to verify accuracy. Not surprisingly, training in quality control is more prevalent in larger firms than in SMis, and in foreign firms than in local firms. Policymak ers should devote greater efforts to raising quality consciousness among SMis and local firms if they are to remain or become internationally competitive. Interest is also growing in implementing IS0-9000 standards, especially amongjoint ventures and local finns. While their numbers are currently low in com parison to MNC subsidiaries, 30percent of local firms and 44 percent of joint ventures report that they ex pect to get IS0-9000 certification within three years. This trend is encouraging since many industrialized country buyers are now requiring exporters to have
Other indicators of technology--licensing agree ments, equipment age, and use of automated equip ment--show similar p atterns
half of them use SPC and precision measuring equip
by firm size and
IS0-9000 certification. Our analyses showed that while exporting to industrialized country markets is more difficult than exporting to developing coun tries, exporting to the fonner is greatly facilitated for
82
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
IS0-9000 firms and to a lesser extent, for firms in
eign capital were more likely to have introduced
the process of getting certification. However, IS0-
new technology, especially computerization and
9000 is apparently not critical for exporting to other
labor saving line automation. When they in
developing countries.
troduced new technology, SMis placed greater
SIRIM can play a critical role in the Government's export promotion strategy by encouraging firms to adopt IS0-9000 standards. Its reorganization, now underway, should allow SIRIM to respond more flexibly to the dramatic growth in private sector demand for IS0-9000 certification. However, IS0-9000 certification may be beyond the finan
emphasis on new machinery which is encour aging since many of them continue to rely on older vintage, less automated machinery.
Introduction of new technology has an ambigu ous impact on employment, but a clear cut im pact on raising skill requirements. Fully 79 percent of firms reported an increase in the skill
cial reach of SMis, and interest in it remains low
content of jobs, while only 15 percent reported a
for the majority of SMis.
fall in skill needs. These reported changes in skill
For SM!s, consultancies in Quality Improvement Practices (Q!Ps), a lower cost alternative to /S09000 certification. SIRIM should work with MNCs and leading companies to develop and ex tend the sectoral coverage ofQIPs for SMis. QIPs establish clear-cut quality standards towards which SMis can work to obtain certification, and which MNCs and other anchor firms can accept as an assurance of quality.
lhe sub-sectoral focus of Q!Ps makes them ame nable to group provision (and funding) of assis tance to SM!s. OnceQIPs are developed, SIRIM can draw upon resources of other government agencies and the private sector to deliver consultancies, training and finance, and technical assistance to interested groups of SMis. The out come is not only more quality upgrading among SMis but also development of greater supplier linkages between SMis and both MNCs and lead
requirements from new technology are reflected in their training activities, both in terms of whether employers currently train, or whether they increased training provision over the past three years. These training impacts of introducing new technology are most pronounced for SMis, increasing the probabilities that they provide training or in creased training over the past three years by nine to ten percent, as compared to just four to eight percent for large firms. On average, technology introduced in the recent past is associated with a 23 percent increase in produc tivity today, even taking into account investments in training and R&D. For micro and small firms, the productivity impact is even larger--about 50 per cent. This fact, coupled with the fmding that new technology increases training more in small firms than in large firms, implies that the Government should give high priority to encouraging SMis to introduce new technology. Several incentives al
ing firms in the industry.
ready exist that target SMis--the Industrial Techni
lhe M!TP survey indicates that about 42 percent of.ftrms have introduced some kind of new tech nology over the past three years. The most com
design and development, quality and productivity
mon technologies new machinery, followed by
grade SMI equipment--but their take-up thus far
computerization and then line automation. Mir roring the patterns of R&D, technology licensing and quality control, larger firms and firms with for-
cal Assistance (ITAF) for consultancies, product improvement, and marketing; and the Soft Loan Scheme for Modernization and Automation to up has been limited. A more proactive approach to promoting SMI use of these incentives should be explored.
TECHNOLOGY, QUALITY AND SKILLS
83
Annex5.1 Introduction of New Technology and Training
This annex reports the probit results of the impact of introduction of new technology over the past three years on two different measures of training. The pro bit parameters are useful for ascertaining the significance and direction of effects of explanatory variables on the outcome of interest, but are difficult to interpret because of the nonlinear nature of the probit model.
For ease of interpretation, we report the marginal effects that
correspond to the estimated probit parameters. Table A5.1 reports the marginal effects of the probit model for formal training, 1 if the firm provides formal training and 0 otherwise. Separate pro bits were estimated for each firm size--micro and small firms with less than 100 workers, medium firms with 101-250 employees, and large firms with over 250 employees. Table A5.1 Probability of Formal Training by Firm Size Marginal Effects of Pro bit Model
Independent Variable
Mean education of the workforce Proportion of skilled workers
Small
(over 250
less workers)
workers)
workers)
0.028�1 (0.008) 0.492 �
0.0861>1 (0.037)
Foreign capital participation
Exports
% Value of automatic machinery
Use of quality control methods
0.158 � (0.056)
0.407 Q/ (0.213) 0.087 f/ (0.050)
0.034
0.019 (0.051)
0.004
-0.001
0.001
(0.027)
(0.057)
(0.069)
0.001 Ql
0.001
0.001
(0.0003)
(0.007)
(0.001)
0.091 Ill
0.106J!'
0.093 fl
0.073
(0.053)
(0.050)
-0.057
-0.009
(0.101)
(0.085)
0.060
0.049
0.026
(0.044)
(0.058)
(0.051)
Introduced New Technology
0.089� (0.029)
Sample size
0.705 � (0.234)
(0.051)
in the past 3 years Log (likelihood)
0.011 (0.014)
0.128
(0.051) Unionization
0.018 (0.014)
(0.034)
(0.030) Proportion of female workers
Large
(101-250
(0.089) Invests in R&D
Medium
(100 or
-534.44 1197
0.093J!' (0.049) -320.61 528
0.039 (0.052) -1102.68 448
a= Significant at 1% b
=Significant at 5%
c
=Significant at 10% level.
Note:
Numbers in parentheses are standard errors. The model also included age of firm, multi-plant status and industry dummy variables. Table A5.2 reports the corresponding marginal effects of introduction of new technology for the probability of increasing training over the past three years.
Source: 1995 M ITP Survey
84
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table A5.2 Probability of Increasing Level of Training Since 1992 Marginal Effects of Probit Model by Firm Size Independent Variable
Small (100 or less workers)
Mean education of
0.038� (0.008)
the workforce Proportion of
0.035
skilled workers Invests in R&D
(0.088) 0.102 � (0.037)
Foreign capital participation
0.032 (0.031)
Exports
Use of quality control methods
Proportion of female workers
Unionization
0.022
0.004
(0.013)
(0.016)
0.535 ):II (0.222) 0.039
0.055
(0.054)
(0.055)
0.108J!
-0.046
(0.049)
(0.056) -0.019 (0.076)
0.001
-0.001
0.001
(0.001)
(0.001)
(0.001)
0.002
0.040
0.045
(0.028)
(0.052)
(0.054)
-0.037'
-0.056
-0.018
(0.049)
(0.098)
(0.095)
0.104�
0.059
0.033
(0.057)
(0.056)
0.160�
Technology in the last 3 years
(0.028)
(0.047)
Log (likelihood)
-528.63
-323.719
Notes:
•
=
b
=
c
=
0.641� (0.268)
(0.056)
0.080-.£'
1197
Sample size
(>250 workers)
-0.091
(0.042) Introduced New
workers)
Large
(0.026)
0.0512
% Value of automatic machinery
Medium (101-250
528
0.082 (0.056) -265.90 448
Significant at 1% Significant at 5% Significant at 10% level.
Numbers in parentheses are standard errors. The model also included age of firm, multi-plant status and industry dummy variables. Source: 1995 MITP Survey
TECHNOLOGY, QUALITY AND SKILLS
85
Annex5.2 Introduction of New Technology and Firm-Level Productivity A Cobb-Douglas production function was estimated to measure the impact of introduction of new technology
over the past three years on productivity.
The dependent variable--value added in logarithms--was re
gressed on the logarithms of capital and labor and a vector of explanatory variables including the new technology indicator variable.
These variables are defined in the text of Chapters Three and Five.
The
production function model was estimated for the pooled sample of firms and the results reported below in Table A5.3. In results not reported here, production functions were also estimated separately by three firm sizes to investigate the possibility that the productivity effects vary by employer size; they are available on request from the authors. Table A5.2 Impact of New Technology on Productivity
Pooled Sample of All Firms Independent Variable
Parameter Estimate
(standard error) Constant
7.283" (0.300)
log (labor)
0.621 a (0.043)
log (capital)
0.289
a
(0.018) Mean Education
0.051"
of the Workforce
(0.0 16)
Proportion of
-0.337a
Female Labor
(0.126)
% Skilled Worker
0. 173C
Training -- current
(0.10 1)
% Unskilled Worker
-0.052
Training -- current
(0.120)
Exports -- current
0.069 (0.061)
Invests in R&D -- current
-0.113 (0.070)
Technology licensing
0.103
agreement -- current
(0.089)
Introduced new technology in the past three years
0.229b (0.098)
a=Significant at 1%, b
=Significant at 5%,
c= Significant at 10%. Note:
Cobb-Douglas production function, dependent variable= log (value added).
CHAPTER SIX: FIRM EFFICIENCY Previous chapters looked first at training and its im
AND
ITS DISTRIBUTION
Another high priority area is improving the techno
pact on firm-level productivity, and then at the tech
logical capabilities of domestic firms, both large and
nology of firms and associated skill requirements. In
small. While the manufacturing sector has demon
this chapter, we bring these two strands of analyses
strated impressive growth both in the production and
together to study their joint effects on technical effi
exports of technologically sophisticated products,
ciency of firms in the Malaysian manufacturing
much of this has been driven by the MNCs. Local
sector.
firms lag behind MNCs in their use of modem equip
Firm-level efficiency-how fur a firm is from best prac
their capabilities to undertake R&D and develop
tice technology-is a key measure of how its competi
indigenous technologies.
ment, in the training provided to workers, and in
tiveness compares to the most efficient firms in the economy, many of which are world-class MNC sub
To address these perceived weaknesses in the do
sidiaries. Our focus is on comparing and explaining
mestic sector, policymakers have introduced a wide
the relative levels of efficiency in firms by size and
range of policies. These include incentives for R&D,
by local and foreign ownership-two dimensions along
building allowances, and tax exemptions; funds to
which pronounced differences in training and tech
promote public sector R&D, venture capital; match
nological capabilities are found-and on drawing out
ing grants for product design, quality improvement
their implications for policymakers.
an d market development under the Industrial Tech
A high priority concern of policymakers is improv
nical Assistance Fund; HRDF to promote upskilling; development of high-tech parks; and measures to
ing the competitiveness of SMis who make up the
foster linkages between SMis and larger firms and
majority of establishments in Malaysian manufactur
between local firms and MNCs (Malaysia, 1994).
ing. In 1989, out of a total of 28,335 manufacturing establishments, SMis accounted for 26,238 or 92.6
Analyses of firms' productive efficiency can pro
percent. However, SMis contributed only 19.6 per
vide insights into both policy concerns. We will es
cent of the manufacturing sector's total value added,
timate frontier production functions to help identify
and 40.2 percent of its employment (MITI, 1994).
the most important technological and workforce fac
Policymakers project SMis will contribute 40 per
tors that are associated with higher firm-level effi
cent of manufacturing value added and 50 percent
ciency. This methodology yields a firm-specific
of employment by the year 2000, a goal which will
index of efficiency which we will use to compare the
require significant upgrading of SMI productivity.
efficiency levels of different groups of firms.
To this end, policies have been initiated to improve
We will use this index to examine the distributions of
SMI access to finance, provide them with incentives
efficiency within each firm size category, and iden
to train workers, give them technical assistance, fa
tify the attributes of highly efficient firms which less
cilitate their links to larger firms and extend to them
efficient firms may emulate to improve their own ef
marketing and export promotion services.1 Hith
ficiency levels. We will estimate separate frontier
,
erto fragmented responsibilities for SMis have also
production functions for firms varying by owner
been recently consolidated into one single agency
ship, to gain insights into the efficiency differences
the Small and Medium Industry Development Cor
between foreign and local firms, and whether the
poration (SMIDEC}-to coordinate support for SMis
efficiency levels of domestic firms are improved by
and to spearhead SMI development.
the presence of foreign firms.
FIRM EFFICIENCY AND DISTRIBUTION
Measuring Technical Efficiency
Equation (2) relates firm-level inefficiency to a set
The methodology we adopt to analyze firm-level
workforce capabilities. Because it is more conve
efficiency is the stochastic frontier production func
nient to think about firm efficiency rather than ineffi
87
of attributes that reflect the firm's technological and
tion. See Annex 6.1. The production frontier is the
ciency, we will reverse signs and discuss these
theoretical maximum output that can be achieved
explanatory variables and their hypothesized effects
using every possible combination of inputs. As such,
on firm-level efficiency:
the frontier can be thought to represent "best prac tice" technology. In practice, many firms operate
Technological Capabilities. Employers can ac
inside that frontier because of inefficiency. For given
quire technological capabilities and attain higher ef
input levels, this level of inefficiency (the existing
ficiency levels in several ways: (i) investments in
output) can be measured relative to the theoretical
in-house R&D or in technology or know-how li
maximum output, so that a value of 1 represents best
censing agreements from others; (ii) contacts with
practice technology and values between 0 and 1
foreign firms, either through exporting relation
measure how far firms' efficiency levels are from
ships with buyers or by setting up joint-ventures
best practice.
with foreign partners; and (iii) production expe rience.
The model is made up of two equations, a frontier production function equation and an equation relat
R&D Investments. In developing countries where
ing firm-level inefficiency to a set of firm attributes.
enterprise capabilities in basic research are often
Similar models have been used in the literature to
limited, indigenous R&D efforts are usually oriented
estimate firm-level efficiency and investigate its cor
towards reverse engineering and modification of
relates. Examples include Pitt and Lee (1981) on
existing product and process technologies. While
weaving firms in Indonesia; Little, Mazumdar and
R&D is associated with higher firm efficiency in in
Page (1987) on five industrial sectors in India; and
dustrialized countries, the evidence for developing
Cortes, Berry and Ishaq (1987) on metal working
economies is mixed.
and food firms in Colombia. Our empirical approach differs from the other studies.2 We use maximum
Know-how licenses. Many firms may not have the
likelihood methods tojointly estimate the stochastic
capabilities to do their own R&D. For these firms,
frontier production function and the model relating
technology and know-how agreements with both
firm-level inefficiency to the explanatory variables.
foreign and innovative domestic firms can be a sub stitute for own R&D investments to develop indig
Model Specification
enous technologies.
Equation (1) is specified as a two-factor Cobb-Dou glas production function. The dependent vari
Exponing. International contacts offer exporting
able is the logarithm of value added, calculated as
firms opportunities for acquiring new technology and
the difference between the firm's value of output
improving their technical capabilities. Foreign buy
and the sum of its expenses on raw materials, en
ers play a critical role in this technology transmis
ergy and electricity. The two factors of produc
sion-by providing firms with crucial information
tion-capital and labor-are expressed in logarithms,
relating to product specifications and, in many cases,
with labor measured by total employment and capi
offering free technical assistance.
tal by the value of net assets. Other explanatory variables include industry indicator dummy vari
Foreign capital panicipation. Foreignjoint-venture
ables to control for industry effects and the firm's
partners can bring new technology not available
rate of capacity utilization, a measure of how fully
domestically. This technology transfer, and the ac
the two inputs are used.
companying management expertise and training to
88
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
use the technology effectively, can lead to signifi cant improvements in firm efficiency.
Determinants of Firm-Level Efficiency In estimating this two-equation model, we assume initially that there is a common production frontier
Age of the Finn. Start-up firms often go through an
for the whole manufacturing sector and that cor
initial period of developing expertise in production,
relates of inefficiency are invariant across firm
management, and marketing. If these learning-by
size and ownership, and control for sectoral differ
doing effects are important, older firms with longer
ences in technology level by using industry
production experience are likely to be more effi
dummy variables.
cient than their younger counterparts. Table 6.1 reports the coefficient estimates of the fron
Workforce Capabilities. A firm's efficiency is
tier production frontier (top panel) and the ineffi
also dependent upon production know-how and
ciency equation (lower panel). The estimated labor
experience embodied in the human capital of its
and capital coefficients are positive and statistically
employees. The productivity effects of human
significant, and they correspond roughly to factor
capital-reflected in the mean education of employ
shares of capital and labor in the economy. To give
ees, the formal training provided to skilled and
the results a more intuitive interpretation, signs of
unskilled workers, and the use of female work
the inefficiency model are reversed so that explana
ers-have been previously studied, but it is useful
tory variables relate to efficiency rather than to inef
to summarize their hypothesized effects on effi
ficiency.
ciency again. Of all the measures of the firm's technological capa Education of employees. Educated workers are not
bilities, only exporting status and firm age are associ
only more productive in performing given tasks, but
ated with statistically higher levels of efficiency. It
they are more adept at critically evaluating new in
appears that there are strong efficiency-enhancing
formation and learning from it. Firms with a more
benefits from operating in export markets, possibly
educated workforce are likely to be more efficient
because of exposure to information about new prod
because of their greater capability to absorb and
ucts and technologies, and interactions with foreign
effectively utilize new technology.
buyers. This export-efficiency relationship also re
Worker Training. Like education, training provides
ducing for export markets. Firm age has a positive
workers with the skills to perform a wide variety of
and significant effect, which is consistent with effi
tasks, to improve quality, and to upgrade job skills as
ciency gains from longer production experience and
flects the presence of highly efficient MNCs pro
new technologies are introduced. Training plays a
learning-by-doing. Holding constant the effects of
key role in adaptation and modification of new tech
exports and age, none of the proxy measures of
nology, without which its superior productivity lev
technology are significantly associated with higher
els over the older technologies that it replaces are
firm efficiency.
seldom realized. There are two ways to interpret these weak tech Use of female workers. Use of large numbers of
nology results. First, and most obvious, they may
female workers may reflect forms of work organiza
reflect the weak technological capabilities of most
tion built around simple assembly, manual dexterity,
local firms to conduct R&D or to effectively use
seasonal work, and low pay. Efficiency levels are
new technologies acquired through licensing and
likely to be low in such organizations where low
know-how agreements, a point that is widely rec
skills and high job turnover inhibit learning and the
ognized by policymakers.
retention of production know-how within the firm.
may be driven by different technology strategies of
Second, the results
FIRM EFFICIENCY AND DISTRIBUTION
Table 6.1 Stochastic Frontier Production Function Estimates Independent Variables
Estimate (standard error)
Frontier Production Function
Constant
6.854 a (0.339)
Log (labor)
0.681 a (0.032)
Log (capital)
0.319
a
(0.021) Efficiency Equation
Constant
-
1 . 296 a
(0.211) Invest in R&D
-0.206 (0.118)
Has technology license(s)
0.089 (0.136)
Foreign ownership
0.002 (0.002)
Exports
0.18P (0.087)
Age of firm
0.011 a (0.002)
Education of workforce
0.091 a (0.020)
Skilled worker training
0.414b (0.211)
Unskilled worker training
-0.105 (0.226)
Proportion of female labor
-0.515 a (0.154) 0.969 a
szs
(0.019) 0.014
g
(0.055) Mean efficiency xz
a:
-2124.096
Significant at 1%
b:
Significant at 5%,
c
Significant at 10%.
Note:
Industry dummy variables included. Numbers in parentheses are standard errors
Source: 1995 MITP Survey
local and foreign firms. As noted in Chapter Five, highly-efficient foreign firms tend to do little R&D in Malaysia, in large part because R&D is conducted elsewhere by their MNC parents. In contrast, local
finns who tend to be less-efficient must get new tech nology from licensing agreements or by relying on their own in-house R&D. The differing technology strategies can introduce a negative correlation be tween R&D and licensing on one hand, and firm level efficiency on the other.
In a subsequent section, we account for the poten tially confounding effects of foreign ownership by estimating separate production frontiers for domes tic firms, joint ventures, and firms with 100 percent foreign ownership. These analyses reveal the pres ence of efficiency gains from technology licensing for domestic firms and from R&D for joint ventures. Consistent with Chapter Three, workforce charac teristics are important determinants of firm-level effi ciency. The mean level of education of employees is positively related to efficiency, indicating that more educated workers are better at learning and re sponding to new information. Only training provided to skilled workers-including supervisors, technicians, and skilled production workers-is significantly cor related with higher efficiency; training of unskilled production workers does not appear to have any impact on firm efficiency. This result parallels ear lier results showing differential productivity and wage effects of training for skilled and unskilled workers. Finally, the intensive use of female workers tends to be associated with lower firm efficiency, possibly because of the low-skill nature of high-volume as sembly operations.
0.74 37.79
Log likelihood
89
Overall, these results have two important implica tions for policymakers. First, when technological capabilities are limited, as is true for many local firms in Malaysia, exports and links with foreign buyers and foreign finns may be a more important source of technology than investments in own in-house R&D to develop indigenous technologies. 3 Second, ir respective of where new technology is acquired, employer efforts to assimilate and effectively use
90
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
new technology require an educated, well-trained
First, consider the broad results suggested by the
workforce. Their investments in training, especially
production frontier estimates for Malaysia and sev
of skilled workers, are associated with gains both in
eral other developing economies as reported in
productivity and in firm-level efficiency.
Table 6.2. The mean efficiency level estimated for all Malaysian firms is 0.7 4 in 1994, a figure that has been adjusted to accommodate for the over-sampling
Distribution of Efficiency by
of large firms in the MITP sample. This estimate is
Firm Size
close to levels estimated for Taiwan in 1986 (0. 76),
The frontier production function approach yields
and is higher than the efficiency levels estimated for
estimates of a firm-specific efficiency index that
Mexico (0.59), Colombia (0.55) and Indonesia (0.39)
ranges from 0 to 1. Firms with an index of 1 operate
in 1992. If the production frontier in all five econo
at the production frontier "best-practice technology"
mies is defined, to a large extent, by the operations
while those firms with a value between 0 and 1, for
of MNCs using international "best-practice" tech
example, 0.5, are producing at 50 percent of best
nologies in each economy, then these figures pro vide a measure of the relative ranking of the overall
practice.
manufacturing efficiency of the five economies. In this section, we use this unit-free index to in
Some support for this interpretation is found in the
vestigate the distributions of efficiencies in firms
broadly similar rankings of economies by efficiency
of d i f ferent sizes, and to address several key
levels and by per capital income. 4
policy issues: how competitive are SMis, what determines how efficient they are, and are there
Second, Table 6. 2 indicates that SMis in Malaysia
attributes of highly efficient firms that can be emu
are on average less efficient than their larger coun
lated by less efficient firms, SMis in particular, to
terparts. Defining micro, small, medium and large
improve their efficiency levels? For purposes of
firms as those with less than 16, 16-100, 101-250,
comparison, we draw upon similar studies con
and over 250 employees, the mean efficiency lev
ducted for Indonesia, Mexico, Colombia, and
els by finnsizeare0.72, 0.74, 0.79 and0.84 for micro,
Taiwan, China (Tan and Batra, 1995). We stress
small, medium and large firms, respectively. This
that these analyses pertain to conditions prevail
result is not unique to Malaysia, but is found in all the
ing at different points in time-1992 for Indonesia,
other economies considered. Sample means, how
Mexico, and Colombia, and 1986 for Taiwan,
ever, can be deceptive. For policymakers, the more
China-and were determined by data availability.
important issue is whether SMis are all uniformly
Table 6.2 Distribution of Efficiency by Firm Size and Economy Colombia
Indonesia
Malaysia
Mexico
Taiwan
(1992)
(1992)
(1994)
(1992)
(1986)
All firms
0.55
0.39
0.74
0.59
0.76
Micro firms
0.53
0.72
0.46
0.74
Small firms
0.54
0.36
0.74
0.58
0.77
Medium firms
0.55
0.35
0.79
0.61
0.81
Large f irms
0.54
0.43
0.84
0.61
0.82
Mean Efficiency ( weighted)
Notes:
M icro= less than16 workers; Small= 16-100 workers, Medium = 101-250 workers; Large= over250 workers.
Source: Tan and Batra (1995), Chapter4
FIRM EFFICIENCY AND DISTRIBUTION
91
inefficient, in which case there is little possibility
Three striking results emerge from a close examina
that SMis can play the vastly expanded role planned
tion of the distribution of efficient firms in Figure 6.1.
for them to the year 2(XX), or whether micro and small
First, in Malaysia as well as in the other economies,
firms exist that are either efficient or with efficiency
there is considerable variance in finn-level efficiency
levels can be raised, and that have potential for grow
in every size category. This suggests that micro and
ing into larger firms.
small enterprises are not inherently inefficient. On average, across economies, at least 35 percent of
Efficiency within Size Groups
firms in these micro and small firm size categories
To address this question, we classify firms in each
are classified as being efficient. Their lower aver
size group as "efficient" and "inefficient" relative to
age efficiency noted earlier is attributable to the fact
the overall mean efficiency estimated for the
that there are fewer efficient firms in these size
economy. Figure 6.1 graphs the percent of effi
groups, and not to uniformly lower efficiency levels
cient firms in each size group for Malaysia and
in all firms.
for each of the other economies. Note that the percent of efficient firms summed across all size
This point is illustrated in Figure 6.2 using the Malay
categories can be more or less than 50 percent
sian case. The figure shows that 41 percent of micro
because firm efficiency is being compared to the
firms have efficiency levels that place them in the
mean, rather than the median. Means and medi
first (bottom) quartile of efficiency in the MITP sample
ans can differ greatly depending upon the shape
and only nine percent in the fourth (top) quartile of
of the efficiency distribution, a fact that we exploit
efficiency. Among large firms, in contrast, the cor
in comparing efficiencies both across size catego
responding figures are reversed with 14 percent
ries and across economies.
anq 42 percent in the first and fourth quartiles, re-
Figure 6.1 Distribution of Efficiency by Economy
Percent of efficient firms
Colombia
1
11Micro
Source: 1995 MITP Survey
Indonesia
•Small
Malaysia
Mexico
oMedium
Taiwan
m3 Large
92
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
spectively. If many SMis are inefficient because
the large-size category, with most micro and small
they invest little in worker skills or technology, as is
enterprises being of below average efficiency. Thus,
the case in Malaysia, these results suggest potential
while Malaysian development policies (including
for upgrading their efficiency levels through train
special tax incentives) to attract large multinationals
ing and technical assistance directed at SMis.
appear to have generated growth, they have done
Second, comparing economies, there is consider
SMis.
relatively little to improve the efficiency of domestic able variation in the proportion of efficient firms in each size category. In Malaysia and Mexico, about
To summarize, these cross-national comparisons
a third of micro and small firms are classified as being
highlight two points. First, they reiterate the need
efficient. In contrast, almost half are in Colombia and
for Malaysian policymakers to place greater empha
Indonesia, and three-fifths in Taiwan. At the other
sis on improving the efficiency ofSMis. This is criti
end of the size scale, the proportion of efficient large
cal if SMis are to play a greater role, in the Seventh
firms is approximately 60 percent in Colombia and
Malaysia Plan and thereafter, in contributing to manu
Indonesia, 70 percent in Malaysia and Mexico, and
facturing value added, employment and exports.
88 percent in Taiwan, China.
Second, the presence of highly efficient SMis sug
These efficiency distributions by size, and their
in upgrading the productivity and competitiveness of
variation across economies, suggest somewhat dif
SMis, provided they are properly designed and
gests that policies which targetSMis can be effective
ferent areas of focus for policymakers in each place.
delivered. Design of these policies should reflect
In Colombia and Indonesia, the proportion of effi
an understanding of the many interrelated constraints
cient firms is relatively low in all size groups, suggest
thatSMis face-in training and technology.
ing problemsendemictoall firms. As such, broad-based policies to improve overall industrial productivity should be the focus in these two economies. In Malaysia as well as in Mexico, there are large size differentials in the share of efficient firms. This fmding suggests that governments should focus on improving productivity at the smaller end of the en
A Profile of Efficient Firms by Size We tum now to a discussion of some correlates of firm-level efficiency to highlight the critical elements in an integrated policy approach to SMI assistance. We compare the attributes of firms with efficiency
terprise scale. The Malaysian Government has al ready recognized the importance of assisting SMis
Figure 6.2 Malaysia-Distribution of Efficiency by Firm Size
to upgrade their competitiveness. Third, the high overall levels of efficiency were at tained very differently in Taiwan, China (sample mean ofO. 76 in 1986) and Malaysia (sample mean of 0.74 in 1994). In Taiwan, there is a high proportion ( 60 percent and above) of efficient firms in all size groups. In addition to higher levels of education and strong external links to buyers and suppliers, small and medium enterprises in Taiwan benefited
micro
from publicly supported R&D and technology ex tension services directed to SMis. In contrast, Malaysia's overall efficiency level is driven by the relatively high proportion of highly efficient firms in
Source: 1995 MITP Survey
FIRM EFFICIENCY AND DISTRIBUTION
levels above the MITP sample mean ("efficient")
•
with those of firms having below average efficiency
•
93
whether the firm conducts R&D in-house; whether the firm has technology or know-how licensing agreements;
("inefficient"). Three broad groups of attributes are considered-technology, workforce skills, and orga
•
whether it exports;
nizational factors.
•
whether it has any foreign capital participation.
These analyses are presented graphically using bar
It was noted earlier that in-house R&D is less impor
charts-efficient firms denoted by dark bars and inef
tant than having technology or know-how licenses
ficient firms by light bars. Each comparison, done
in discriminating between efficient and inefficient
separately by firm size, typically involves asking
firms. Panels A and Bin Figure 6.3lend support to
whether a particular attribute is more or less likely to
this finding. With the exception of micro firms, effi
be found among the efficient firms as compared to
cient firms of all sizes are actually less likely to
the inefficient firms so as to help characterize the
report doing R&D as compared to inefficient
highly efficient firms Furthermore, the importance
firms. In Panel B, this relationship is reversed
.
of that specific attribute to each firm size can be de
and efficient firms in all size categories are more
termined by asking how well it discriminates between
likely to have technology or know-how licenses
efficient and inefficient firms in that size category
than inefficient firms This result is consistent with
versus other firm size categories.
the view that technology transfers through licens
Technology Factors Figure 6.3 shows the char
ogy source t h an o w n R & D w h e n f i r ms'
acteristics of efficient and inefficient firms as mea
technological capabilities are weak (see Tan and
sured broadly by their sources of technology:
Batra, 1995).
.
ing agreements is a more important new technol
Figure 6.3 Technology Attributes of Efficient and Inefficient Firms
A.
Do R&D
B.
Technology Licenses
30
60
25
50
20
40
15
30
10
20
5
10 0
.� E
(ij
E ..
E
"
'6
Q)
E
§
" e>
(ij
E "'
E
.!!!
c. Exports
D.
90 80 70 60 50
§
'6
"
E
" e>
.!!!
Foreign-owned
70 60 50 40
40 30 20
30 20 10
10 0
-�
1ij E "'
Source: 1995 MITP Survey
E
" " E
'6
Q)
e> .!!!
§ E
1ij E ..
E " " E
'6
" e>
.!!!
94
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Figure 6.4 Training Attributes of Efficient and Inefficient Firms A.
B . Technology
Do R&D
Licenses
30
60
25
50
20
40
15
30
10
20 10
0
0
g E
§
�
'ij
c.
Exports
g E
E>
-"!
m
E
l
§ 'ij � E
m
1:" -"!
D. Foreign-owned
90 80 70 60 50
70 60 50 40
40 30 20
30 20 10
10 0
0
§ ·e:
�
§ 'ij �
"
�
§ .E
�
§ 'ij �
m
�
Source: 1995 MITP Survey
Panels C and D indicate that exports and foreign
Panels A and B contrast the degree of formality of
capital participation are important characteristics
two polar strategies-informal training on-the-job
of efficient firms, especially micro, small and me
from supervisors or co-workers, or structured for
dium size firms For these firms contacts with for
mal training within a needs-based training plan. In
e i g n buyers and foreign partners through
general, SMI employers tend to provide only infor
.
,
exporting and FDI are potentially important means
mal on-the-job training as compared to large firms;
for firms to acquire technology and know-how,
however, within each size category efficient firms
and to improve efficiency. However, in the larg
are much less likely to rely exclusively on infor
est firm size category, efficient and inefficient
mal training than inefficient firms.
f irms are not distinguishable on the basis of whether a firm exports.
In contrast, larger firms are more likely to have de veloped a training plan than smaller firms (no micro
Workforce Skills Figure 6.4 compares efficient
firms reported having a training plan), and in each
and inefficient firms along several dimensions of
size category, efficient firms are always more likely
employers' training strategy:
to have a training plan. Thus, there appears to be payoffs to conscious efforts by employers to identify
•
• •
•
whether the firm provides only informal train
their critical skill needs and develop a structured
ing to its employees;
training plan to address these skill shortfalls.
whether it has a developed training plan; the proportion of skilled workers getting formal
Such efforts are supported by the HRDF through
structured training;
regional seminars on training needs analysis (TNAs)
the proportion of unskilled workers getting for
and support for the development costs of training
mal training.
plans under the JURUPLAN scheme. HRDC has
fiRM EFFICIENCY AND DISTRIBUTION
95
Figure 6.5 Quality Control in Efficient and Inefficient Firms A.
Statistical Process Control
B.
Quality Control Circle
60 .-------.
60 .-------�
50
50
40
40
30
30
20
20
10 0
10 +-----+--
micro
small
0
medium
+-"""'---+--
micro
large
small
medium
large
D. ISO 9000
C. Precision Measuring Equipment
35 .-----,
60 ·r------
30
50
25
40
20
30
15
20
10
10
5
0
a+-------�-
micro
small
medium
micro
large
small
medium
large
Source: 1995 MITP Survey
also recently introduced new schemes to promote
local firms
group training for SMis, and these new incentives
formal, structured training programs. Both HRDC
should be coordinated with SMIDEC and other pub
and other agencies with SMI responsibilities should
lic agencies to promote more group or joint training
play a greater role in disseminating this information.
-
from reliance on informal OJT to more
amongSMis.
Organizational Factors Employer decisions Panels C and D show the percent of workers re
about technology and skills development are deter
ceiving formal training in skilled and unskilled occu
mined by, and in tum shape, the organization of pro
pations, respectively. They make two points. First,
duction and work. Organizational modes can vary
not only are efficient firms significantly more likely
markedly by size, and have different efficiency im
to have a training plan than inefficient firms but they
plications for small and large firms
,
also tend to provide formal training to a much higher proportion of their workforce. Second, compared to inefficient firms , efficient firms are always associ
ated with greater intensity of training for both skilled and unskilled workers. Both skilled and unskilled workers play a critical role in the adoption and as similation of new technology, and this last point high lights the importance of not neglecting the training of unskilled workers.
.
Figure 6.5 show four variables which reflect the finn's concern with product and process quality, including: •
whether it relies on statistical process control;
•
whether it has quality control circles;
•
whether it verifies accuracy by using precision measuring instruments;
•
w hether the f i r m has received IS0-9000 certification.
The HRD F provides the framework for promoting
Panels A and B indicate that, with the exception of
change in the training approach of most SMis and
micro firms, efficient firms are slightly more likely
96
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
than less efficient finns to use statistical process con
whether the firm's compensation package in
•
trol (SPC) and quality circles (QC) to monitor quality.
cludes profit-sharing or bonuses.
Panel C highlights the importance of accuracy in production-in all finn size categories, efficient finns
First, consider quit rates in efficient and inefficient
are significantly more likely to verify production ac
firms. Panel A shows that while quit rates increase
curacy using precision measuring instruments rather
with firm size for both groups of firms, they are in
than through visual inspection. Finally, Panel D
variably lower in efficient finns especially in the larg
shows that IS0-9000 certification is associated with
est firm size category. As noted in Chapter Three,
higher efficiency, since it signals the finn's high level
high rates of job turnover can have a detrimental
of quality and commitment to ongoing improvement.
effect on incentives to provide training since quits prevent employers from recouping their investments
In Figure 6. 6, we turn to several measures of
in worker skills. As such, HRM practices-compen
workforce organization or human resource manage
sation policies that reduce quits, facilitate training,
ment (HRM) that affect job retention and employee incentives, and thus ultimately, finn-level efficiency. These include: •
•
•
and provide employees with incentives to use their new skills and share their accumulated knowledge with co-workers-can have a powerful impact on finn
the firm's annual quit rate, a variable defined
efficiency.
previously in chapter three;
Panel B compares the starting monthly pay of the
the starting monthly pay of a typical, newly-hired
typical production worker in efficient and inefficient
production worker;
finns. In all size categories, efficient finns appear to
whether the firm has a severance pay scheme;
pay a mean wage premium ofRM 3040 over starting
Figure 6.6 Quits and Compensation in Efficient and Inefficient Firms A. Quit Rates
B. Starting Monthly Pay (RM)
60 .-------,
380.------
50
360
40
340
30
320
20 10
300
0
280 micro
small
medium
large
micro
small
medium
large
C. Severance Pay System
D. Have Profit-Sharing/Bonus
70 �------� 60 50 40 30 20 10 0
100 �------�
micro
small
Source: 1995 MITP Survey
medium
large
80 60 40 20 0 micro
small
medium
large
FIRM EFFICIENCY AND DISTRIBUTION
97
pay in inefficient firms Except for micro firms the
employees a stake in the higher productivity that
premium persists as the typical production worker gains
results. Such compensation policies are already in
experience. In graphs not shown here, the premium
use among larger employers and MNCs, and their
either remains the same or gets larger by the tenth
experiences with these HRM practices should be
year on thejob, to the RM 100-140 range in small and
widely disseminated to SMis and local finns with poor
.
medium size finns
.
,
This high-wage policy allows em
personnel practices.
ployers to attract and retain higher quality produc tion workers; it is sustainable because of their higher
Technology and Training in the Last Three Years
overall productivity, including the large productivity
Finally, we relate current efficiency levels to past
gains from training reported on ealier.
investments in technology and training. Figure 6. 7 shows the percentage of efficient and inefficient
Finally, Panels C and D show two components of
firms that:
compensation that are thought to have incentive ef fects for workers. Severance provides workers with
introduced new technology (including comput
•
a lump-sum tied to years of seniority at the time of
erization, line automation, and new production
separation from the firm. To the extent that it re
machinery) in the past three years;
wards long seniority, it can enhance job attachment
increased provision of training over the last
•
and encourage skill acquisition. Panel C shows that severance pay schemes are more common in effi
three years; neither invested in new technology nor in
•
cient firms . Especially in the small and medium size category.
creased training; both introduced new technology and increased
•
training.
A similar pattern is found in Panel D, with efficient
firms being more likely than inefficient ones to have
Panels A and B in Figure 6. 7 reveal a strong rela
profit-sharing and bonuses to reward effort and give
tionship between size and the introduction of new
Figure 6.7 Technology and Training in Past 3 Years A. New 80 70 60 50 40 30 20 10 0
Technology
Last 3 Yrs
.-------,
B. Increase Training Last 3 Yrs 70 60 50 40 30 20 10
-1------t-micro
0 medium
small
large
.-----�
-�--�----+micro
C . Neither Tech Nor Training 90 80 70 60
.-----�
D . Both 60
small
New
medium
Tech
&
large
Training
.-------�
50 40
50 40 30 20
30 20 10
10 0
0 mic ro
sma II
medium
Source: 1995 MITP Survey
large
-�-----mic o
sma II
medium
large
98
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
technology or increased training provision over the
These fmdings, together with those from previous
past three years. Within each size category, effi
chapters, suggest the following two implications for
cient firms were more likely to have done so than
the design of SMI policies.
inefficient firms. Panels C and D, which combine responses from both questions, are mirror images of
First, they indicate that mostSMis face multiple con
each other. Firms that neither invested in new tech
straints, and the way that these constraints interact
nology nor increased training are primarily micro
implies that no single policy alone-focusing just on
and small finns , while those that did both are found
training or just on technology-is likely to be effec
mainly among larger firms In each size category,
tive. To be effective, policyrnakers must deliver an
efficient firms were less likely to have done neither,
integrated package of incentive and services spe
.
and more likely to have done both, as compared to inefficient firms.
cifically designed for SMis covering consulting, training, technology upgrading, finance, quality con trol, and personnel management. Responsibility for
These trends are consistent with the results reported
delivering services toSMis is currently spread over
in Chapter Five that introduction of new technology
multiple agencies, with little coordination or informa
has consequences for rising skill requirements, in
tion sharing among them despite their targeting, or
creased training, and higher productivity.
often even serving, the same firms.
Summary The results indicate that highly efficient firms, both large and small, have specific technological, work force, and organizational characteristics that can in principle be emulated by less efficient firms. •
They do not necessarily invest in R&D, but in stead tend to acquire technology through licens ing and know-how agreements, others through foreign capital participation and exports.
•
They have structured training programs that reach a greater number of their employees, both skilled and unskilled.
•
They have modes of work organization that em phasize quality control, including statistical pro cess control, quality control circles, and use of
•
and employer resistance to change are important constraints for SMis, responsible public or private sector agencies must work proactively withSMis to expose them to the benefits of change, and create demand for support services. The current policy approach-providingSMis with incentives and leav ing the responsibility for take-up with them-ignores these informational and cultural impediments to change, and the result has been low take-up of most incentives targeting SMis. A rethinking of the whole approach to SMI support is required, and one part of a proactive strategy should be an initial diagnostic of constraints facing SMis, so that a tailored program of assistance can be developed and delivered. Mexico's CIMO program is an example of a proactive strategy of delivering integrated training and technical assistance to SMis
precision measuring equipment.
that has proved to be cost-effective. See Box 6.1.
They have HRM practices that provide incen
A first step in this direction has been taken with the
tives for job retention, skill acquisition and greater worker effort. •
Second, to the extent that poor access to information
creation of theSmall and Medium Scale Develop ment Corporation (SMIDEC) within MITl to coordi nate planning and delivery ofSMI services by other
And they are more likely to have introduced
government agencies. SMIDEC should undertake
both new technologies and increased training
a careful review of existingSMI incentives to deter
in the recent past.
mine why their take-up is so low, and how existing
FIRM EFFICIENCY AND DISTRIBUTION
99
incentives and services can be delivered more ef
all the attributes of 100% foreign finns? We do this
fectively. Such a review should study the potential
by assigning local finns and Ns the mean values of
for increased coordination of both training and tech
attributes (from the efficiency model) of the 100%
nology support services from implementing agen
foreign firms and then scaling the efficiency levels
ciessuch asHRDF,SIRIM,NPC, MOSIEandMITI.
of local firms and Ns to that of the numeraire group.
,
It should also consider the feasibility of implement ing a mechanism for active promotion and delivery
Table 6. 3 reports the estimated parameters of the
of integrated services to hard-to-reach SMis, one
production frontier and efficiency model. The re
that will require devolution of service delivery to
sults of the efficiency models for each ownership
the state or local areas, and the creation or expan
group are of particular interest, and they make four
sion of existing regional institutions. This would be
principal points. First,regarding technology invest
consistent with Mill's recent adoption of the indus
ments,they clearly indicate that R&D and efficiency
trial cluster approach to development.
are significantly related among Ns, but not local or 100% foreign firms. Technology licensing, how
Ownership, Efficiency Differences and FDI Spillovers
ever,is weakly associated with improved efficiency for domestic firms. Second,exporting-an informal source of foreign technology and know-how-is im
Domestic and foreign firms have different profiles of the attributes associated with efficiency. Chapter Five showed that domestic firms were less likely to do R&D, have technology licenses, provide worker training, emphasize quality control and have IS09000 certification, and export than either joint -ven tures or wholly foreign-owned firms Since all are .
attributes associated with highly efficient firms,it raises two questio�how fur do local firms lag behind,firms with foreign capital participation in their efficiency and what can be done to improve their efficiency
portant for efficiency only among Ns,but again not among local firms or 100% foreign firms. Third,the intensive use of female workers is associated with lower efficiency in local finns and Ns,presumably because of the low-skill nature of their assembly op erations, but not in 100% foreign fmns. Finally, a more educated work force and the provision of for
mal training have statistically significant and positive effects on efficiency levels of N s and 100 % for eign firms,but not local firms. This last result mirrors the production function results on training in Chap
levels?
ter Three.
Efficiency Differences
How efficient would local firms be if they were
We examine differences between local finns,joint
more like foreign firms? As noted earlier in Chap
ventures (JVs), and wholly foreign-owned firms
ter Five,domestic finns lag behind MNCs in R&D
( 100% foreign) by estimating separate frontier pro
investments and technology licensing, in worker
duction functions for each of the three ownership
training, and in export orientation. Adjusting for
categories. First, we are interested in whether the
differences in mean efficiency attributes of these
correlates of efficiency are the same in each owner
three groups of firms, we fmd that foreign firms are
ship category. In the preceding analyses, estimated
more efficient than domestic firms and, among this
parameters of the efficiency model were constrained
former group,firms with 100 percent foreign owner
to be the same for all firms, irrespective of owner
ship are the most efficient.
ship. Second, we want to compare overall efficiency
levels of domestic firms, joint-ventures,and wholly
levels of the three groups, controlling for mean
foreign-ownedfirms are0.74,0.76 and0 .81 ,respec
group differences in these efficiency attributes. This
tively. These estimates suggest that even if do
5
The mean efficiency
allows us to ask the counter-factual question: how
mestic fmns had the same attributes as the wholly
efficient would local firms or Ns be if they adopted
foreign-owned firms-in tenns of export status, R&D,
100
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Box 6.1 Mexico's Pro-active Approach to SMI Support The Mexican Secretariat of Labor has developed a pro-active approach to SMI support-the CIMO program-that has proved to be effective in reaching and assisting SMis upgrade worker skills, improve quality, and raise productivity. CIMO, initiated in 1988 as a pilot project to provide subsidized training to SMis, quickly evolved when it became apparent that lack of training was only one of many inter-related factors which contribute to low productivity among SMis. By 1994, it had expanded the scope of its coverage and was providing an integrated package of training and industrial extension services to over 23 thousand SMis per annum and training to 150 thousand of their employees. Since 1988, CIMO has assisted a cumulative total of over 70 thousand SMis and trained a quarter million workers. Private sector interest has also grown, and over 300 business associations now participate in CIMO, up from 72 in 1988. The CIMO program is operated by 49 CIMO units in most major urban to be close to their target population. All states and the Federal District of Mexico have at least one CIMO unit, each staffed by 3-4 promoters, and most units are housed in business associations which contribute office and support infrastructure. These CIMO promoters organize workshops to disseminate information about training and technical assistance services, identify potential local and regional training suppliers and consulting agents for the program, but most importantly, they actively seek out the SMis to deliver assistance on a cost-sharing basis. They work with interested SMis to conduct an initial diagnostic of the firm, which forms the basis on which training programs and other consulting assistance are recommended and delivered. CIMO is currently expanding SMI support in two directions-assisting groups of SMis (a cluster approach) according to their specific sub-sectoral needs, and providing an integrated package of services including information on technology, new production processes, quality control techniques, and marketing as well as subsidized training. An evaluation study showed that CIMO is a cost-effective way of assisting SMis. The study tracked two groups of SMis over three years, one that participated in CIMO in 1991 or 1992, another a broadly comparable control group of enterprises that were not related to the CIMO program. While CIMO firms tended to have lower performance indicators than the control group prior to participation in the program, by 1993 their levels of labor productivity had either caught up or exceeded those of the control group. Other performance indicators showed similar improvements-increased profitability, sales, capacity utilization rates, and wage and employment growth; and reduced rejection rates for products, labor turnover, and days of absenteeism. The most dramatic impacts of the CIMO interventions were among micro and small size firms and, to a lesser extent, among medium-size firms. Source: STPS, La Capacitacion y Asistencia Tecnica en Ia Micro, Pequena y Mediana Empresa: Evaluacion del programa CIMO, Mexico, 1995.
technology licenses, workforce education, train
firms have more of the measurable attributes not
ing, and reliance on female workers-they would
included in the efficiency model-including qual
still only be 8.6percent (i.e. 1-0.74 I 0.81) less effi
ity control methods, training systems, intensity of
cient than the wholly foreign-owned finns, andjoint
training, and capital equipment-but that are asso
ventures would be 6.1 percent less efficient.
ciated with higher firm efficiency. They may also have unmeasured productivity attributes-includ
The residual difference in efficiency between the
ing superior technological capabilities, technical
three groups of firms are due to several factors. As
know-how, high quality of its personnel, and or
shown in earlier sections, wholly foreign-owned
ganizational forms-not readily captured in our
FIRM EFFICIENCY AND DISTRIBUTION
101
data. To some extent, local firms may acquire
Interfirm Linkages and FDI Spillovers
these intangible kinds of "knowledge and human
Interfirm linkages are ongoing relationshipsbetween
capital" through joint venture arrangements with
finns, with repeated transactions that range from arms
foreign firms, or through increased interactions
length transactions, to contractual buyer-supplier
and linkages with them as suppliers or subcon
relationships, to licensing and franchising, and to joint
tractors. We tum to some of these interfirm link
ventures (Wong, 1991). Such linkages are poten
agesbelow.
tially beneficial to all parties involved. For some
Table 6.3 Stochastic Frontier Production Function Estimates by Ownership Independent Variables
Domestic
6.021 a
Constant
(0.329) Log (labor)
Log (capital)
0.566 a
Joint Ventures
1 00 percent foreign
7.113"
7.304"
(0.491)
(0.950)
0.613•
0.599•
(0.058)
(0.044)
OA27" (0.026)
(0.031)
-0.278
-2.368"
-3.504"
(0.193)
(0.679)
(1.501)
1.429"
-0.272
0.358"
(0.088) 0.339" (0.071)
Efficiency Equation Constant
0.194
Do R&D
Technology License(s)
(0.137)
(0.418)
(0.344)
0.168° (0.089)
0.357 (0.412)
0.387 (0.385)
2.502 a (0.579)
0.316 (0.611)
0.059
Exports
(0.058) Proportion female labor
Mean Education
-0.486a
-2.275a
-0.399
(0.177)
(0.597)
(0.325)
0.026 (0.022)
Provide Formal Training
s2s
0.022
Mean Efficiency Log likelihood
1.379a
0.614b 0.246)
(0.438)
1.393 a (0.082)
(0.353)
(0.039)
2.216a
0.604a (0.090)
0.74
0.76
-1552.01
-412.08
a= Significant at 1% level, b = Significant at 5% level, c=
Significant at 10% level.
Note:
Industry dummy variables included. Numbers in parentheses are standard errors.
Source: 1995 MITP Survey
0.33oa (0.143)
(0.074)
0.030
g
0.558" (0.1 02)
0.759a (0.092) 0.103 (0.141) 0.81 -222.177
102
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
large firms and MNCs, such relationships make it
mies, the exception being HRDC's efforts to intro
possible for them to achieve cost reductions by con
ducejoint and group training schemes targeting SMis
centrating on their core lines of business and sub
(see Chapter Four).
contracting certain production activities to specialized local firms. Where these vertical in
Numerous questions remain about interfirm linkages,
terfirm linkages develop, they can provide small
how they develop, the nature of their benefits, the
subcontractors not only with new markets but also
way in which technology transfer takes place, and
exposure to new forms of production and man
what role public policy can play in enhancing inter
agement organization, and access to technical as
firm linkages. As currently structured, the MITP
sistance and training support to upgrad e their
survey is ill equipped to answer these questions since
technological capabilities. Horizontal linkages
no information was elicited on interfirm linkages.
among groups of smaller firms can also, in principle,
Nonetheless, it can provide limited insights into the
allow them to take advantage of scale economies-in
importance for domestic firms of "spillovers" from
hiring high-calibre group managers, joint training,
the presence of MNCs and joint-ventures. We do
technology upgrading, finance, and exporting-not
this by asking the following questions: Is the effi
available to them as individual firms . The initial evi
ciency level of domestic firms improved by the pres
dence on efforts to promote SMI enterprise net
ence of foreign firms operating in the same
works in some industrialized and developing
subsector? If so, what is the nature of these spillovers
countries is encouraging (see Box 6.2).
and are technology and skill spillovers from foreign firms important?
Policymakers in Malaysia have recognized the po tential importance of interfirm linkages as a means
We extend the stochastic frontier production func
of fostering technology transfer from foreign to do
tion model to test for the presence of efficiency
mestic small and medium-scale enterprises.6 To date,
spillovers to local firms from foreign firms. Three
government policies to promote linkages have been
proxy variables for the magnitude of the foreign
m:xlest.
firm presence are developed:
( 1) the employment
share of foreign firms in total employment of the sub The Subcontracting Exchange Scheme (SCX), a
sector, (2) the foreign firm share of total R&D spend
MITI-operated computerized clearing house to
ing in the sub-sector, and (3) the corresponding share
match SMis with larger firms, has thus far gener
of workers getting formal training. We further dis
ated few solicitations. According to Fang (1991), the
tinguish between the spillovers from joint-ventures
main obstacle to SMI supplier development is the
and from wholly foreign-owned firms. To see if
low and uneven quality of their products, and limited
spillovers are important, we re-estimated the local
technological and skill capabilities. Vendor devel
firms' frontier production function without the indus
opment programs such as Proton reportedly en
try dummies, augmenting it to include the different
countered similar problems-low quality, little
spillover proxy variables. If they are, we should
appreciation for the importance of quality improve
expect the spillover variables to be positively re
ment, and limited use of testing equipment, and im
lated to fum-level efficiency.
precise pricing (Meyanathan,
1994).
However, in
electronics, an increasingly dense network of inter
. Table 6.4 reports the augmented frontier produc
firm linkages have begun to develop, as local capa
tion function estimates for the sample of domestic
bilities have improved and MNCs such as Intel have
firms .
spun off suppliers (Rasiah,
To date, there
ployment share measure-indicates that there are ef
have been no efforts made to promote SMI enter
ficiency spillovers for local firms from the presence
prise networks to take advantage of scale econo-
of bothjoint-ventures and wholly foreign-owned
1994).
The first model specification-the simple em
FIRM EFFICIENCY AND DISTRIBUTION
103
Box 6.2 Promoting SMI Networks in Chile
In 1990, the Chilean SMI promotion agency, SERCOTEC, introduced the PROFO program to foster the creation of networks among SMis and, through promoting links among SMis and with large customers, to upgrade their competitiveness. It also saw this as a strategy for increasing the limited take-up of other services provided by SERCOTEC, and for using these networks as focal points for stimulating industrial development through increased participation by private sector firms and public sector agencies in the locality. PROFOs are developed in three steps. In the first step, SERCOTEC identifies potential groups of SMis (usually between 10 and 30) in a particular locality where the basis for collaboration exists, conducts a diagnosis of individual and group problems, and works with SMis to establish its credibility and to begin addressing their problems. The second stage is to facilitate consolidation by hiring a group manager, whose salary is financed 70 percent by SERCOTEC in the first three years and wholly thereafter bythe SMI group. The group manager has several tasks: (i) increasing take-up subsized training and support services by members through SERCOTEC's Technical Assistance Fund; (ii) coordinating delivery of these services by public and private sector bodies; and (iii) promoting cooperation through visits to each other's factories, workshops and group travel, and developing joint initiatives to address common problems and pursue common objectives. The third and final stage is graduation from SERCOTEC support as PROFOs become self-sustaining. The early results of this PROFO SMI initiative has exceeded SERCOTEC's expectations. Of the 16 PROFOs operating in Chile in 1993, a number had expanded market shares, gaining new access to markets in Chile and abroad, and especially important, developing supplier linkages to large firms. Several groups of metalworking SMis were able to improve their performance to such an extent that they began supplying state mining companies with local inputs that had originally been imported or sourced in other regions. Despite initial concerns, many PROFOs have demonstrated that SMis have the capacity for collective action and, with appropriate support from public sector institutions, for initiating collective efforts on product design, process development, human resource development and training, sales and finance. These early results were sufficiently encouraging that SERCOTEC has introduced a new PROFO program directed at helping SMI groups enter export markets. Source: Humphrey and Schmitz, Principles for Promoting Clusters and Networks of SMEs, report prepared forUNIDO, 1995
firms. Efficiency levels in domestic firms are sig
These results suggest that the presence of foreign
nificantly higher the larger are the employment
capital in the same industry, whether joint-ventures
shares of joint ventures and foreign firms in the in
or wholly-owned foreign MNC subsidiaries, has
dustry. The second model specification-R&D and
beneficial effects on the productive efficiency of
training shares-reveals an interesting pattern of effi
local firms . The efficiency spillovers to local firms
ciency spillovers to local firms varying by whether
appear to come through the R&D activities of joint
FDI is in the form of joint-ventures or wholly for
ventures, and the training efforts of wholly foreign
eign-owned firms. The results indicate, first, that
owned firms. We speculate, but cannot confirm, that
training by wholly foreign-owned firms, but not
these efficiency spillovers operate through subcon
joint-ventures, has a significant positive impact on
tracting relationships between local and foreign firms,
local firms efficiency. The results are reversed for
throughjob turnover of trained personnel from for
R&D, with positive R&D spillovers fromjoint-ven
eign firms, through diffusion of information about
tures but not 100 percent foreign-owned firms
new production techniques and new products gen-
'
.
104
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Table 6.4 Stochastic Frontier Production Functions Estimates with FDI Spillovers Independent Variables
Mode/1.
Mode/2.
FDI Employment
FDI Training & R&D
Share Production Function Constant
6.688a (0.232)
Log (labor)
0.589a (0.043)
Log (capital)
Efficiency Equation Constant
Exports
0.381a
Education of workforce
Proportion of female labor
Own Training
Own R&D
6.645 a (0.081) 0.576 a (0.042) 0.390 a
(0.021)
(0.022)
-0.226a
-0.301a
(0.020)
(0.017)
0.093C (0.048)
Has technology license(s)
Shares
0.054a (0.011)
0.200
0.133
(0.228)
(0.189)
0.010
0.005
(0.070)
(0.054)
-0.381
-0.200
(0.687)
(0.831)
0.031
0.066
(0.033)
(0.123)
-0.167
-0.105
(0.115)
(0.067)
Measures of FDI S�illovers Employment share of joint ventures
0.234b (0.117)
Employment share of 1 00% foreign firms
0.334b (0.167)
Training share of joint ventures
n.a.
n.a.
n.a. 0.167 (0.139)
Training share of 100% foreign firms
n.a.
0.331 a (0.019)
R&D share of joint ventures
n.a.
0.263b (0.048)
R&D share of 100 %foreign firms
n.a.
0.179 (0.293)
g2
s
g
Mean Efficiency Log likelihood
1.413a (0.059) 0.001
0.022
(0.002)
(0.010)
0.73 -1559.97
a= Significant at 1% level, b= Significant at 5% level, c= Significant at 10% level. Note: Numbers in parentheses are standard errors. Source: 1995 MITP Survey
1.471a (0.067)
0.74 -1551.14
FIRM EFFICIENCY AND DISTRIBUTION
105
erated by R&D conducted by joint ventures and,
Highly-efficientfirms, both large and small, have
to a limited extent, wholly foreign-owned firms,
several identifiable attributes: (i) they do not neces
and possibly through other demonstration effects.
sarily invest in R&D, rather acquiring know-how
These efficiency effects are over and above the
and technology through licensing agreements,
direct benefits that FDI are thought to provide
through joint-ventures, and through exports; (ii) they
the local economy-investment capital and foreign
sponsor structured training programs for their em
technology, employment creation, foreign ex
ployees, both skilled and unskilled, in in-house pro
change, tax revenues, and higher productivity
grams or through external training providers; (iii)
and wages.
their work organizations emphasize quality control,
Policymakers will need to have a better understand
circles, and use of precision measuring equipment;
including statistical process control, quality control ing of these linkages-both the vertical links between
(iv) they have human resource practices that pro
local firms andMNCs on which we have reported,
vide incentives for job retention and skill acquisi
and horizontal links among groups ofSMis on which
tion; and (v) they are more likely to have introduced
less is known-to design effective policies to foster
new technologies and increased training in the re
increased interfirm linkages and promote industrial
cent past. Employers should benchmark themselves
development. To this end, a second round of the
against these attributes and, where feasible, emulate
MITP survey will be fielded to elicit additional infor
them so as to improve their productivity levels. These
mation about the nature of firm linkages, the flows of
"best-practices" may not be familiar to many firms
technology, knowhow, training, and technical assis
and policymakers, state development authorities, and
tance that takes place between firms, and the effec
industry associations should widely disseminate this
tiveness of different policies in overcoming
information to the private sector, SMis in particular.
constraints to the development of these interfirm net works.
,
The design of SMI policies should have several fea tures. First, because SMis face multiple constraints,
Findings and Policy Implications
focusing assistance just on training or just on tech nology is likely to be effective. To be effective,
The empirical evidence indicates that while SM!s
policies should deliver an integrated package of in
as a group are generally less efficient than larger
centives and services designed including consult
firms, there is considerable variability in the effi
ing and technical assistance, training, technology
ciency of individual SM!s in Malaysia. This find
upgrading, finance, quality control, and management.
ing is important for policymakers: if SMis are all
Responsibilities for delivering services to SMis are
uniformly inefficient, there would be little that
currently spread over multiple agencies, and there
policymakers can do to upgrade their levels of
should be greater coordination and information shar
efficiency. Nonetheless, the efficiency gap be
ing among them. Second, because poor information
tween the majority ofSMis and larger firms is quite
and employer resistance to change are important
pronounced in Malaysia (as in Mexico) unlike
constraints for SMis, responsible public or private
Taiwan, China. The high overall efficiency level
sector agencies must work proactively with SMis to
ofMalaysia's manufacturing firms is primarily the
expose them to the benefits of change, and create
result of a high proportion of highly efficient firms
demand for support services.. Malaysia's current
in the large-size category, principallyMNCs, with
policy approach-providingSMis with various incen
most micro and small firms being of below aver
tives and leaving the responsibility for take-up with
age efficiency. A primary focus of policy should
them-ignores these cultural and informational impedi
therefore be on improving productivity at the
ments to change, with the end result that take-up of
smaller end of the enterprise scale.
most incentives targetingSMis has been low.
106
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
A rethinking
of the whole approach to SMI support is required. The first priority ofSMIDEC should be to conduct a careful review of all existing SMI in
The evidence reveals that the efficiency levels of domesticfirms are improved by the presence offor eignfirms. These efficiency spillovers to local firms
centives, and identify why incentives work or do
appear to come from R&D activities of joint-ven
not, and why. Part of this review should consider
tures, and the training efforts of wholly foreign
the feasibility and desirability of alternative ap
owned firms. They suggest that supplier linkages
proaches to SMI support, one being an incremental
between firms and job turnover of trained workers
improvement in the coordination of services deliv
may be important routes through which these
ered by other agencies, the other being a more pro
spillovers operate. Future rounds of the MITP sur
active system of outreach, promotion, diagnoses, and
vey should elicit information about these linkages
delivery of tailored services to SMis. Examples of
the flows between firms of technology, know-how,
proactive SMI policies exist in both industrialized
training, finance, and assistance in such matters as
and developing countries, including Mexico's CIMO
production, quality control, and marketing-to pro
program of training and technical assistance toSMis,
vide policymakers with insights on how to facilitate
and Chile's PROFO program to foster enterprise
technology transfer to local firms building on exist
networks amongSMis, and study tours to glean les
ing incentives (such as ITAF) and vendor develop
sons appropriate to Malaysia should be undertaken
ment and "umb rella" schemes to promote
as part of this review.
subcontracting and development ofSMI clusters.
,
FIRM EFFICIENCY AND DISTRIBUTION
107
ANNEX6.1 Stochastic Frontier Production Functions Following Aigner, Lovell and Schmidt (1977), the stochastic frontier production function is expressed as:
Y;
=
exp(x;[3 +vi - u) (1)
where subscript
i indexes the firm, yiis the maximum output obtainable from a vector of inputs, xi, and j3 is
an unknown parameter vector to be estimated. The V; s are random errors which are assumed to be independently distributed of the one-sided error term U; where U; <0. The non-positive one-sided error term U; reflects the fact that each firm's output must lie on or below its stochastic frontier,
f( X;; f3 + v; ) .
To investigate the presence of systematic influences on firm-level inefficiency, we incorporate firm characteristics into the model by expressing U;as: U;
=zl>+W; (2)
where inefficiency is assumed to be a linear function of a systematic component z i, and a random component
W;.
The systematic component includes a vector of firm attributes Z;, e.g. the firm's
technology and workforce capabilities, which are related to efficiency by the parameters, 8. The random variable
W;
follows the same truncated normal distribution as the one-sided error term, U;, where the point
of truncation is
, -z .
Equations (1) and
l
8
such that w. >
l-
, -z. l
8.
(2) are estimated jointly using maximum likelihood techniques to obtain consistent
estimates of the parameters of the production frontier (equation 1) and the inefficiency effects (equation 2). From these results, an index of firm-specific efficiency can be calculated as
TE;
=
exp(-u ) = exp(-z /5 i
-
w
)
which ranges between 0 and 1. The joint estimation of these two
equations is necessary to obtain consistent estimates of technical efficiency. Some studies, using a twostage procedure, have simply regressed the efficiency estimates on Z;. This yields inconsistent parameter estimates of equation
(2) because ordinary least-squares treats W;
as being normally distributed in the
second-stage regression when it should follow the same distribution as ui.
CHAPTER SEVEN:
CoNCLUSIONS
Human resource development will underpin
REcoMMENDATIONS
AND
sights, from the employer perspective, of what fac
Malaysia's strategic vision of attaining industrialized
tors constrain their training, and the efficacy of
country status by the year 2020. For policymakers,
alternative incentive schemes to promote in-service
the HRD challenges are how best to increase the
training
supply of skilled workers to meet current acute la
.
bor shortages as well as projected growth in skills
Summary of Main Findings
demand; upgrade skills and technical competencies of the workforce to facilitate technological and orga nizational change by enterprises to compete in in ternational markets; and address the associated problems of sharply rising relative pay for skilled workers and high labor turnover, both of which threaten Malaysia's wage competitiveness and abil ity to continue attracting foreign direct investment. For policymakers, it is evident that growth in skills demand over the past decade has outstripped the supply capacity of public sector training institutions, and that the private sector will have to play an in creasingly greater role in training and meeting its own skill needs. This report is concerned with in-service training and its role in raising finn-level productivity and promot ing technological change in Malaysian industry. As part of this study, a broad-based survey of2,200 manu facturing enterprises was fielded in 1995 to obtain hitherto unavailable information on the incidence of in-service training, provided in-house and by dif
Chapters Two through Six used a variety of ana lytic methods to investigate several key topics, in cluding the incidence, determinants, and productivity and wage outcomes of training; train ing constraints faced by firms and policies to ad dress them; the links between technology, quality control, and skill needs; and the technical efficiency of firms by size and ownership. Analyses of these topics yielded a large number of findings, which confirm, reinforce and complement each other. Taken together, they suggest the following broad con clusions:
Firms under-invest in training. Manufacturing firms in Malaysia under-invest in the training of their employees. This is based on our estimates that about 80 percent of all firms either do no training or rely exclusively on informal training from co-work ers and supervisors, and that only 21 percent of firms provide formal training.
ferent public and private training providers.
This conclusion is supported by employer responses
Analyses using this survey yielded new insights into
cite mature technology, which has low skill require
about why they provide little or no training. Most employer's use of training from different sources,
ments, as the principal reason for doing little train
variations in the productivity and wage outcomes
ing. While this is not a market failure per se, a sizable
of training of different types of training provided
number of other employers, smaller firms in particu
different groups of workers, and how these rela
lar, cite other training constraints that are-free rider
tionships are influenced by employer investments
ship from high labor turnover, lack of knowledge
in technology and organizational change. It also
about training methods, and limited resources for
revealed marked differences in the training and
training
technological capabilities of firms varying by size and ownership, with most local firms and SMis oper
.
Employers play a key role in skills develop
ating at significantly lower technical efficiency lev
ment. The MITP survey revealed that many em
els as compared to joint ventures and MNC
ployers can, and do, meet their skill needs through
subsidiaries. The survey also provided unique in-
formal, structured programs of in-service training.
CONCLUSIONS AND RECOMMENDATIONS 109
In fact, notwithstanding the conclusion that firms
skill requirements, and hence creates little de
under-invest in training, employers provide in-ser
mand for training.
vice training to more workers than traditional voca tional and technical institutions. The MITP survey
Training raises firm-level productivity. Firms
showed that employers sponsored formal training
that train, on average, are about 32 percent more pro
courses for about 196,000 workers in 1994. In com
ductive than firms that provide employees with no
parison, all public training institutions combined
formal training. The productivity effects of train
produced a total of 145,000 skilled and semi-skilled
ing are more important, both in terms of the magni
graduates over the five years of the Sixth Malaysia
tude of its impact and in a statistical sense, for
Plan.
in-house formal training than for training from ex
The private sector is the most important source
ers than for unskilled worker training.
ternal sources, and for the training of skilled work
of training. Firms that train meet their skill needs in-house or through a variety of external training
The productivity effects of training are larger when
sources. Of the external sources, firms rely most
new technologies acquired through licensing are
heavily on private sector providers-private training
complemented with employee training. Reflecting
institutes, buyers and equipment suppliers, joint
the weak R&D capabilities of local firms, a firm's
venture partners, and overseas training institutions.
own R&D spending has limited effects either on
With the exception of SDCs and advanced training
overall productivity or on the productivity of worker
institutes (such as ClAST or GMI), both of which
training. Similar results on the productivity effects
are either demand-driven or cater to higher-level
of training and its links with technology adoption
skills training, the other public training institutions
are found in other developing countries such as
ills, IKMs, YTCs, polytechnics, and vocational and
Mexico, Colombia and Indonesia.
technical schools-play a minor role in meeting the in-service training needs of industrial firms. Their
SMis will benefit most from formal training.
primary focus thus far has been on pre-employment
The analyses revealed that formal training has par
training in basic and intermediate-level technical
ticularly large productivity effects for SMis, the
skills.
group least likely to train or only to provide informal
Technology shapes the skill requirements of
dium size firms, the productivity impact is about 32
on-the-job training to employees. For small and me
employers. The MITP survey showed that firms
and 29 percent, respectively, as compared to 12 per
are more likely to train when they are large, employ
cent for large firms.
an educated work force, invest in R&D, possess tech nology or know-how licenses, have foreign capital
It is clear that SMis under-invest in training. This is
participation, use quality control methods, and ex
attributable to their use of simple technologies, which
port to foreign markets. Many of these factors are
means
related to the ways firms acquire technological ca
and to several market failures-from limited finance
that skill needs are also correspondingly low;
pabilities-through own R&D, or through contacts
for training, high job turnover which makes it diffi
with foreign firms and buyers. Employers invest
cult to recoup training costs, and weak training capa
ing in these technological capabilities are more
bilities-which deter them from training.
likely to use highly-educated workers, who are more adept at working with new technologies and
Local and foreign firms have different train
new production methods, and to train them. For
ing needs. The productivity effects of different
firms that provide little or no training to their em
sources of in-service training vary by local or for
ployees, the single most important reason was
eign ownership. For local firms, no productivity
their use of mature technology, which has low
effects from in-house company training are discern-
110
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
ible; however, the training they receive from SDCs
schemes to promote longer-term job attachment
and advanced skills training institutions such as
among employees, and hence training. Of these, the
ClAST or GMI are associated with large productiv
analyses in Chapter Three indicated that higher pay,
ity e ffects. For foreign firms, it is in-house com
steeper seniority-wage profiles, and severance pay
pany training and training from private sector
were most effective in reducing quits, especially
sources that have large productivity effects.
among firms that train. The reason is that firms that train are better able to fund more attractive com
These fmdings suggest that most local firms have
pensation packages out of the higher productivity
weak in-house training capabilities, and they will need
that results from training, as compared to firms that
to rely more on SDCs and other institutions provid
do not.
ing advanced skills training. In both groups offinns, no significant productivity effects were discernible
The DDIT is ineffective in inducing training.
for in-service training provided by public training
It has been used primarily by MNCs,joint-ventures,
institutions such as ITis, IKMs, YTCs, and vocational
and larger firms who, arguably, were training al
and technical institutes. They focus mainly on pre
ready. For these finns , the DDIT scheme has meant
employment training, and it appears that the little in
sizable windfall gains; for the firms that provided
service training they provide is not well suited to
little or no training, the DDIT scheme has failed to
employers' needs.
induce employers to begin, or increase provision of, training.
Firms that train also pay higher wages. Em ployers that provide training pay wages that are 6
Lack of awareness about DDIT, and its requirements,
percent higher on average, suggesting that one
has been the principal reason for its limited use. Over
eighth to one-fifth of the productivity gains from train
half of all firms in the MITP survey reported not
ing are shared with workers in the form of higher
using it because they were unaware of the incen
pay. The patterns of wage increases mirror those of
tive, or knew its details only vaguely. Another fac
the productivity gains from training, being higher in
tor was the heavy bureaucratic requirements of
firms that invest in technology, that export, and that
applying for DDIT, and the corresponding high rates
are foreign-owned. The evidence confinns that train
of re the D DIT covers only small employers with
ing of supervisors and skilled production workers is
less than 50 workers, and few (if any) of these firms
associated with higher pay, but not training for un
are likely to be using the DDIT incentive.
skilled production workers.
HRDF is effective but non-compliance is If these trends are extrapolated, they imply that pro
significant. The HRDF provides firms with dif
ductivity differentials from training will lead to grow
ferent schemes to flexibly organize their training ef
ing wage disparities between skilled and unskilled
forts and upgrade their training systems. The HRDC
workers in the absence of training policies to up
has actively sought to reduce application and report
grade unskilled workers to skilled status. Techno
ing requirements, expedite processing and reim
logical change will also put additional upward
bursements of training claims, disseminate
pressure on relative pay of skilled workers.
information on training through TNA workshops and clinics, and support hard-to-reach SMis through
Compensation policies can deter quits and encourage training. High labor turnover deters employers from training. However, they can reduce
group-based training initiatives. However, non-compliance remains an important is
quit rates through different compensation policies
sue, with as many as 27 percent of eligible firms not
such as higher pay, fringe benefits, pay increases tied
registered with, or contributing to, the HRDF. The
to length of service, severance pay and retirement
problem is concentrated among smaller firms firms ,
CONCLUSIONS AND RECOMMENDATIONS
111
in traditional and domestic-oriented industries, in
trial country buyers now require exporters to
the states on the east coast and in East Malaysia, and
have IS0-9000 certification. The analyses indi
among finns providing little or no structured train
cated that exporting to industrialized country
ing. While there are good reasons to downplay en
markets is greatly facilitated for IS0-9000 firms
forcement in the early gestation period, policy
and to a lesser extent, for firms in the process of
makers will eventually have to make a strong effort
getting certification.
to address the issue of non-compliance.
Local firm s and SMis have weak techno
New technology raises skill and training needs. The MITP survey showed that about 42
logical capabilities. The MITP survey elicited
percent of firms have introduced some kind of
data on a number of technology indicators which
new technology over the past three years. Larger
confirm the main findings of MASTIC's 1992 Na
firms and firms with foreign capital were more
tional Survey of R&D. They show that private sec
likely to have introduced new technology, espe
tor R&D spending in Malaysia is relatively low
cially computerization and labor saving line au
compared to other developing countries. They con
tomation; when they introduced new technology,
firm that the number of firms doing R&D rises with
SMis placed greater emphasis on new machinery
firm size, with 30-39 percent of larger firms report
to replace their older vintage, manual machinery.
ing some R&D spending, while few SMis engage in
R&D activities. Of particular note is the finding that wholly foreign-owned firms are less likely to report R&D activities as compared to local firms or joint-ventures of similar size. The other technology indicators-technology licensing agreements, equip ment age, and extent of automation-show similar patterns by firm size and ownership.
impact on employment, but a clear cut impact on rais ing skill requirements. Fully 79 percent of firms re ported an increase in the skill content ofjobs, while only 15 percent reported a fall in skill needs. These changing skill requirements were reflected in their training activities, both in terms of whether employ ers currently train, or whether they increased train
Quality consciousness is growing among larger .finns. The MITP survey showed that some finns have introduced quality control systems and imple mented QC training programs to become internation ally competitive and export. However, this is concentrated among foreign-owned and larger finns half of them use SPC techniques and precision mea suring equipment, as compared to about one-fifth of smaller firms; most SMis continue to rely on visual inspection to verify accuracy. Not surpris ingly, QC training is more prevalent in larger firms
than in SMis, and in foreign firms than in local firms
Introduction of new technology had an ambiguous
.
Interest is also growing in implementing IS0-9000 quality standards, especially among joint ventures and local firms. While their numbers are currently low, 30 percent of local firms and 44 percent of joint ventures report that they expect to get IS09000 certification within three years. Many indus-
ing provision over the past three years.
New technology is associated with higher productivity. Firms introducing new technol ogy in the past three years had productivity lev els today that were, on average, 23 percent higher even taking into account their current investments in training and R&D. For micro and small firms, the productivity impact was even larger-about 50 percent. This productivity impact comes on top of another outcome of new technology, namely, its effects on increasing training which, in tum, is associated with increased productivity as shown in Chapter Three. The effect of introducing new technology on train ing is most pronounced for SMis, increasing the probabilities that they provide training or in creased training over the past three years by 9-10 percent, as compared to just 4-8 percent for large
112
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
firms. Together, they highlight the potentially
Local firms lag behind foreign firms in tech
large productivity gains from encouraging SMis
nical efficiency. The analyses showed that, on
to adopt new technology.
average, local firms were less efficient than joint ventures and, in turn, joint ventures were less effi
SMis are not inherently inefficient. The tech
cient that MNCs. Some part of these differences is
nical efficiency of SMis is central to the debate about
due to group differences in R&D, technology licens
the role of small scale enterprises in economic de
ing, worker training, and export orientation.
velopment. SMis are unlikely to be an important source of growth and employment generation if
However, even if local firms andjoint ventures were
they turn out to be relatively inefficient, with lim
given all the attributes of MNCs, such as export sta
ited ability to compete, survive and grow into
tus, R&D, technology licenses, workforce educa
larger firms The analyses in Chapter Six revealed
tion and training, the efficiency ranking by
that while they are on average less efficient than
ownership status would still remain. The adjusted
their larger counterparts, a significant number of
mean efficiency levels of local firms, joint-ventures,
.
SMis are actually more productive than many
andMNCs are0.74, 0.76and0.81, respectively, sug
large firms .
gesting that local firms would still be nine percent less efficient than MNCs, and joint ventures would
For policymakers, the latter is the more important
be six percent less efficient than MNCs.
finding. It indicates that SMis are not inherently inefficient as compared to large firms, and that well
Spillovers from foreign to local firms are
designed policies targeting SMis can be effective in
important. The efficiency levels of domestic firms
raising their productivity and efficiency levels.
are higher in industries with a large foreign direct investment (FDI) presence.
These efficiency
Highly efficient firms have identifiable
"spillovers" to local firms appear to come from the
characteristics. Efficient firms, both large and
R&D activities of joint-ventures, and the training ef
small, have several technological, work force, and
forts of wholly foreign-owned firms. These findings
organizational characteristics that can, in principle,
suggest that local firms benefit from FDI through
be emulated by less-efficient SMis.
supplier linkages with joint ventures and MNCs, and
They have better access to new technology through
such firms These findings need to be confirmed by
licensing agreements, joint-ventures with foreign
further study. To the extent that these inter-firm
partners, and export contacts with foreign buy
linkages can be encouraged, they provide a poten
ers and suppliers, and have introduced new tech
tially important source of technology transfer from
nology in the recent past. They have a more educated
MNCs to local firms.
through the job turnover of trained workers from .
workforce, and they sponsor structured training pro grams for employees, both skilled and unskilled.
Policy Recommendations
Their work organization emphasizes quality control, including statistical process control, quality con trol circles, and precision measuring equipment rather than visual inspection, and they have HR management and compensation practices that pro vide incentives for job retention and skill acqui sition. The wide dissemination and adoption of these best practices are likely to have significant productivity-enhancing benefits for SMis.
These empirical findings have implications not only for training institutions and training policy, but also for technology and SMI policies. Our policy recom mendations are grouped under the following five topic areas:
I
Collection and Dissemination of Training Information
CONCLUSIONS AND RECOMMENDATIONS
ll.
113
Expanded Role of Education and Training
veys can be compared, to monitor and analyze
Institutions
private sector training efforts and the efficacy of
ill. More Effective Training Policies
public policies in promoting worker training,
IV. Technology Diffusion and Promotion
technological change, and productivity growth.
V.
Better Coordinated and Proactive SMI Policies
I. Collection and Dissemination of Training Information The Government's existing system for collecting, analyzing, and disseminating information about train ing in Malaysia is fragmented and uncoordinated, and should be strengthened. Data on public training institutions are typically maintained by each responsible ministry but seldom reported, on a systematic basis together with detailed cost data, to a central coordinating agency for plan ning and policy analysis. Likewise, information on private-sector training institutions is only collected on an ad hoc basis. Few evaluation studies of train ing programs-based on tracer surveys of its gradu ates, comparisons with a control group, and cost-benefit calculations-have been conducted to ensure that public resources are being used cost effectively; evaluations comparing different public training institutions are even rarer. The National Vocational Training Council (NVTC) was designated as the institution to coordinate public and private vocational training programs. The Gov
ernment should give NVTC the necessary legal standing, resources, and capabilities to play this role more effectively. Little effort has been made to make training in formation widely available to the final consumer individuals and the private sector. They can only make informed training decisions if they pro vided with periodic, timely publications and analyses on both public and private sector train ing. One constraint is that little data exist on how much and what types of training employers are providing a n d individuals are receiving. The MITP Survey provides a benchmark on in-ser vice training against which future firm-level sur-
Our recommendations to strengthen data collec tion for monitoring worker training, both at the level of the firm and the individual, are as fol lows:
The Government should develop andfield nation ally representative enterprise and household sur veys oftraining on a periodic basis, building on the existing survey capabilities of the Department of Statistics (DOS). A great deal of policy-rel evant information is already collected in the pe riodic industrial and household surveys fielded by DOS, and these are readily augmented with a core module of questions about training. Once institutionalized, these augmented firm- and household-level surveys will yield time-series data needed for policymakers to monitor and ana lyze training trends.
An inter-agency steering committee should be set up to design, fund, and coordinate this survey ef fort with DOS. This committee should identify the priority training or related issues to be addressed in each industrial or household survey, and work with DOS to augment the core modules with questions designed to address these issues. The steering com mittee should also have responsibilities for commis sioning studies using the survey data, and for the publication and wide dissemination of information on training and training trends.
Timely turnaround of survey results is critical. As such, DOS should be corporatized to give it theflexibility and the resources to respond to this new mandate. It should be given the standing to bill appropriate costs to the government agencies for which the augmented finn and household sur veys are being conducted. Several national sta tistical agencies play this role, including Statistics Canada and Mexico's INEGI, and they offer po tentially useful lessons for DOS.
114
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
II. Expanded Role of Education and Training Institutions
stitutes, which focus on pre-employment training. This suggests that the in-service training they pro
In-service training is one, albeit key, part of the
vide are not well-suited to firms needs. In contrast,
process of human resource development. Em
depending upon the firms concerned, it found large
'
ployers' decisions to train, and the productivity
and positive productivity effects of in-service train
and wage outcomes of that training, depend criti
ing provided by SDCs, advanced skills training cen
cally upon the stock of education and technical
ters, and private sector training institutes. Our
skills that individuals bring with them into the la
recommendations, based on these findings
bor market.
lows:
The MITP study clearly showed that pre-employ
An in-depth study of the effectiveness and relevance
,
are as fol
ment education and in-service training are comple
of training provided by public training institutions
ments, not substitutes,for each other. Employers
should be conducted, especially if they are to play
are more likely to train, and provide more training,
an expanded training role in the Seventh Malaysia
when the schooling attainment of its workforce is
Plan. The study should assess the relative efficacy
higher because educated employees are better
of different institutions within each ministry and across
learners and thus benefit more from investments in
ministries, identify weaknesses that should be cor
training. A one year increase in the mean years of
rected and strengths that can be built on, field tracer
schooling attainment leads to a two to three percent
studies of their graduates that are comparable across
increase in the probability that employers will pro
training institutions, and conduct cost-benefit analy
vide workers with formal structured training. If the
ses using these data. The study should also take
average years of schooling rises to 11 years, from
stock of the structure, organization, staffing, and cur
the MITP sample average of8.9 years, this would
ricula of these institutions with an eye to exploring
raise the percent of firms training by four to six per
their potential for playing a greater role in in-ser
cent. In addition to facilitating in-service training,
vice training. The World Bank has helped design
education also has an independent effect on raising
and conduct similar program impact studies of VETs
firm-level productivity and wages.
in other developing countries and can provide the
Existing low raJes of continuation intofit.rther educa
Government with technical assistance.
tion or post-secondary education cannot sustain de
On the basis of such an exercise, the Government
sired rates of post-employment training and
should identify selected public training institutions
retraining. Continuous learning and skills upgrad
as candidates for corporatization.
ing required are for moving into higher technology
corporatized training institutions should be given the
production. The Government has recognized the
flexibility and incentives to design and deliver cus
need to address this issue, and it is embarking on an
tom training courses tailored to the needs of indus
ambitious program to expand secondary and tertiary
try, with input from industry and institutes of higher
education with an emphasis on sciences, engineer
learning, and to compete with other public and pri
ing and technical subjects. Firms' use of different external training providers appear to accurately reflect the relative productivity of the training courses offered by these training pro viders. The MITP study could not find any discern ible productivity effects for the in-service training
These
vate training providers for training resources. Pub lic training institutions in several Latin A merican countries, including Brazil's SENAI, have been suc cessfully corporatized to make them more demand driven, and lessons for Malaysia's training institutions can be gleaned from their experiences.
provided by public training institutions, such as the
SDCs have demonstrated their effectiveness in de
ITis, IKMs, YTCs, and vocational and technical in-
livering demand-driven training to both MNCs and
CONCLUSIONS AND RECOMMENDATIONS
115
domestic firms, especially in Penang where the
application requirements to obtain the incentive, as
PSDC has been in existence since the late 1980s.
well as high rejection rates.
Nonetheless, large firms and MNCs are the most in tensive users of SOC training.
The key lesson for policy makers is that any policy
The Government should ascertain why take-up of SDC training is so low among small and medium size domestic compa nies, and implement measures to increase their par ticipation in the design of training programs tailored more to their specific needs.
should be widely publicized and, for hard-to-reach
Advanced skills training centers such as ClAST, the
public offices and employer associations. Another
ATC in Sepang, and GMI are another important
lesson is that, to the extent feasible,filing require
source of higher-level skills training for domestic
firms and the analyses showed that this training was ,
associated with productivity gains. However, the supply capacity of these institutions is limited rela tive to the revealed demand for their services, a point that the Government has recognized and will address in the Seventh Malaysia Plan. It plans to establish nine new skills training institutes offering advanced courses, some with input :Q.-om MNCs.
or incentive, whether in training or in other areas, is unlikely to befully effective if targeted beneficia ries are unaware or inadequately familiarized with the program. Information about policy initiatives SMI firms, disseminated proactively through local
ments for incentives should be streamlined to im prove take-up. Implementation of policies should be closely monitored to quickly identify and resolve the inevitable problems that firms face in respond ing to, or taking up, new incentives.
The Government should eliminate the remaining coverage of the DDIT incentive for small firms with less than 50 employees. The justification
These include two new ATCs in Johor Bahru and
for doing so is as follows: First, it is likely that
Klang, the JMTI in Penang, and the Japanese Ma
very few small firms are using the incentive today.
laysia Institute in Kulim. In addition to the bilateral
Second, bringing all firms under the HRDF um
training institutes that have been set up with Ger
brella greatly simplifies administration, since uni
many, France, and Japan,
the Government should also explore the feasibility of setting similar bilateral training institutes with Britain and the United States.
versal coverage of all firms would seamlessly accommodate growth or shrinkage of firms above or below the 50 employee cutoff. Finally, HRDF is developing new schemes to support the train
III. More Effective Training Policies The MITP study used employers' responses to the DDIT and HRDF to assess the efficacy of these two training policies in encouraging firms to provide structured training programs to their em ployees.
ing activities of SMis, and the 50 employee cut off would arbitrarily restrict access of small firms to these training programs.
The issue of payroll contributions for these smaller firms needs to be resolved. Two options are avail able for funding this recommendation. First, the gov
The DDIT incentive scheme has generally been inef
ernment may consider a waiver of the payroll levy for
fective. It was used primarily by MNCs,joint ventures,
small firms, and provide a block grant to HRDF from
and larger domestic firms who were training already.
general revenues to cover the costs of their use of
For these firms the DDIT scheme has meant sizable
training services. The drawback is the potential dis
windfall gains and a loss of tax revenues to the Govern
incentive effects for SMis to remain small so as not to
�. Amongfinns doinglittleornotraining, 1he lack of
contribute to the HRDF. An alternative is to require
,
awareness about DD IT was the principal reason for
SMis to register and contribute at a reduced rate,
its limited use. Other factors which reduced interest
perhaps half a percent of payroll, with the govern
in the incentive were the time-consuming and costly
ment matching the SMis contribution. This govern-
116
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
ment contribution could be time-limited, and fall sciousness and training capabilities.
The HRDC slwuld also moum an iriformation cam p aign, on television and in newspapers, to en courage eligible firms to register with HRDC. It
The HRDF, in contrast, has made considerable
force compliance with the HRDF Law and, to en
over time, as SMis begin to develop a training con
should announce its intention to vigorously en progress in creating an enabling environment for
sure that this threat is credible, it should publicize
training. It has done this by providing firms with
its increased enforcement capabilities as well as
alternative schemes for training through in-house train
its prosecutions of selected firms. This campaign
ing programs and external training providers, stream
should be accompanied by a time-limited amnesty
lining reimbursement of training expenditures,
program for firms to come forward, register with
reducing administrative and reporting burdens on em
the HRDC, and pay their back levies without civil
ployers, widely disseminating information about
or criminal penalties. Similar time-limited am
training through TNA workshops and clinics, help
nesty programs have been used very effectively
ing fund the development of training plans and es
in several states in the United States to improve
tablishment of training facilities in firms, and
tax compliance.
introducing new group-based training schemes tar geting SMis. The design and delivery of schemes have been flex ible and imaginative. The HRDF has also created a large and growing market for both public and pri vate sector training providers, which augurs well for increased training supply in the near and medium term. In short, HRDF has developed a market-re sponsive framework for encouraging in-service training. Our recommendations are intended to complement these efforts.
A
sizable number offirms in the MITP survey had
not claimed any reimbursementsfor training through the HRDF as ofyear-end 1994. While claims have risen since then, in large part due to an extension of the deadline granted by HRDC, it is likely that the underlying problem remains, especially among smaller firms who provide no training or only un structured, informal on-the-job training that is not eligible for reimbursement. Some of their constraints include poor knowledge about training, not having a training plan, or inad
Non-compliance in HRDFappears to be significam.
equate training facilities. These are being addressed
The MITP survey indicates that as many as 27 per
by TNA workshops, the JURUPLAN scheme to de
cent of eligible firms with 50 or more employees are
velop training plans, and schemes to fund purchase
not registered with, and contributing to, the HRDF.
of training aids, and HRDC should continue to vig
Non-compliance reduces funds available to the
orously promote these activities. Other factors which
HRDF, and it circumvents the very intent of the
limit demand for training among SMis, such as use of
policy-to induce firms to invest in training and skills
mature technology, are under the purview of other
upgrading, and to reduce free-riding on the training
public agencies. To address these SMI constraints,
of other firms which, in tum, has a chilling effect on
HRDC should closely coordinate its ([/forts with those
overall employer incentives to train. HRDC is aware
planned under SMIDEC, the new SMI agency.
of this problem but currently has few resources to devote to enforcement. It only has a staff officer and
HRDC has introduced the ITS and GTS schemes to
clerk to develop the necessary databases to identify
encourage group training for smaller employers,
firms that are eligible but not registered, and no legal
either initiated by groups of small firms themselves
officers with the power to prosecute non-compliance.
(ITS), or organized by employer associations (GTS).
HRDC has submitted a staffing request which should
The MITP survey indicated that such joint training
be acted on expeditiously by the Government.
programs between firms are rare in Malaysia, and
CONCLUSIONS AND RECOMMENDATIONS
they are most commonly found among large firms
,
not among SMis. HRDC, in collaboration with
117
these dimensions, as compared to large domestic companies and MNCs.
SMIDEC, should conduct a study to identify the impediments to collective action by SM!s to ben
The strong message for policymakers from all the
efitfrom scale economies in training. Some lessons
analyses is that increasing R&D spending alone
may be gleaned from Chile's experience in foster
through incentives-is not the solution. More impor
ing SMI networks for joint activities, or Mexico's
tant than inadequate funding for R&D, the critical
CIMO program for supporting training among clus
issue among most local firms is weak in-house tech
ters ofSMis.
nological capabilities. For most firms (except joint
The MITP survey also showed the principal ways in
on firm-level productivity or efficiency, while tech
which joint training activities are organized. Suppli
nology licensing agreements were associated with
ventures), R&D spending had no significant impact
ers and government agencies play key roles in organiz
large productivity gains, especially when accompa
ing joint training courses for small firms, while
nied by training programs. The R&D in joint ven
specialized training companies are more important for
tures is more productive because of transfer of
medium and large firms. Industry associations are also
technology and know-how, technical assistance, and
cited, but primarily by large firms. Industry and em
training from foreign partners. These findings sug
ployerassociationsshouldassume greaterandmorepro
gest the following recommendations:
active responsibilities for organizing training among its SMI members. The GTS scheme currently being pi
For most localfirms, technologies acquired through
loted by HRDC is one avenue for doing so.
licensing and laww-how agreements are a more im portant source of productivity gains than in-house
Regional offices of the HRDF should be established
R&D efforts to develop indigenous technologies.
closer to the principal regional clusters ofbulustries.
This implies that, at least in the near term, the Gov
The HRDC has submitted a working paper to the
ernment should make technology licensing and the
Government proposing the establishment of regional
wide diffusion of existing technologies to local firms
offices in Penang, Johor, Sabah and Sarawak.
the principal focus of technology policy. Actions
Operationalization of these regional offices should
to facilitate technology transfer and diffusion of
speed up HRDF response to firms training applica
know-how include the wide dissemination of in
tions, facilitate closer interactions with employers
formation on appropriate technologies, expedited
and provision of advisory services, and promote reg
processing of technology licensing applications by
'
istration of, and payment of levies by, employers
MIDA, incentives for firms to adopt new technol
not yet registered with the HRDC. HRDC should
ogy and purchase new equipment, or expanded ac
also consider co-locating its staff in local offices of
cess for SMis to incubators or to joint-use facilities
other agencies with SMI responsibilities, so as to
with testing and precision measurement equipment.
better coordinate delivery of integrated training and other support services toSMis.
The wide gap in the productive efficiency of local firms and SM/s as compared to foreign firms is
IV. Technology Diffusion and Promotion
an
added argument for emphasizing technology diffu
The MITP survey revealed marked differences
sion over R&D spending. The efficiency gap is
across firms in a wide range of technology indica
much less pronounced in Taiwan, China, which has
tors-industrial R&D spending, technology licensing,
actively promoted technology diffusion and skills
quality control systems, use of precision measuring
upgrading to its large population ofSMis. Given the
equipment, vintage and sophistication of machinery.
evidence of large productivity gains from adopting
Local firms and SMis in particular fare poorly on all
new technology and training bySMis, a similar strat-
118
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
egy in Malaysia of promoting diffusion of known
productivity, quality control circles (QCC), and to
technologies to the majority of local firms and SMis
tal quality management (TQM). However, as the
should go a long way towards narrowing this effi
MITP survey shows, quality consciousness among
ciency gap and, through upgrading their technol
SMis is still low, and most SMis have no quality
ogy, raising overall efficiency growth in the
control systems in place. This suggests that NPC
manufacturing sector.
will need to take a more active approach to promote quality and producti vity among SM!s, and to pro
Technology transfer can also occur through links with MNCs and efficient domesticfirms. The MITP study indicated that the technical efficiency of local
finns was improved by the presence of foreign finns , though it was silent on the inter-firm relationships through which these transfers occurred. A careful study should be conducted to better understand the nature of these inter-firm linkages-both vertical in volving an anchor MNC or large domestic firm and its subcontractors or suppliers, and horizontal in volving groups of SMis cooperating for mutual ben efit-and the nature of the flows of technology, technical assistance and skills between firms. Such a study, which is currently planned by the World Bank and EPU as part of a second round of MITP
vide them with technical assistance and training. SIRIM can also play a critical role by encouraging finns to adopt IS0-9000 standards. The analyses in dicated that exporting to industrialized country mar kets was greatly facilitated by having, or working towards, IS0-9000 certification. The recent surge of interest in IS0-9000 has reportedly exceeded SIRIM's capacity to respond in a timely fashion, and many firms are seeking certification through foreign institutions. SIRIM's reorganization, now underway, should allow it to respond more flex ibly to this growth in private sector demand for IS0-9000 certification.
surveys, will identify the extent to which such firm
IS0-9000 certification may be beyond the financial
linkages and networks exist, and where they are
reach of SMis, and interest in it remains low for the
poorly developed, assess whether such networks can
majority of SMis. SIRIM has provided some SMis
be created or fostered by public policy.
with consultancies in Quality Improvement Practices (QIPs), a lower cost alternative to IS0-9000 certifi
Standards and metrology is an imponant policy in strument for diffusing modem production methods and quality control systems tofirms, and upgrading product quality to meet the exacting standards for expo11 markets. The experiences of several devel oping countries, such as Brazil, indicates that adop tion of iS0-9000 and TQM has led to strong quality
cation. It should work with MNCs and leading com
panies to develop and extend the sectoral coverage of Q!Ps for SM!s. QIPs establish clear-cut quality standards towards which SMis can work to obtain certification, and which MNCs and other anchor firms can accept as an assurance of quality. MNCs and other leading firms should find this approach attrac
improvements and productivity gains. The MITP
tive since they would bear few of the costs of identi
study indicated that a similar phenomenon is oc
fying and developing a pool of local suppliers that
curring among Malaysian firms. While their num
meet their quality standards. The Government should
bers are currently low in comparison to MNCs, a
approach the principal foreign employer associa
growing number of local firms and joint ventures
tions in Malaysia to encourage their active participa
expect IS0-9000 certification within three years.
tion in this exercise.
The National Productivity Corporation (NPC) cur
The sub-sectoral focus of Q!Ps makes them ame
rently provides a wide range of services to SMis
nable to group provision andfunding ofquality up
through regional quality centers operated jointly with
grading for SM!s. Once QIPs are developed, SIRIM
SIRIM. It disseminates booklets on the importance
can leverage its limited staff in the SMI section by
of quality, and runs subsidized training courses on
drawing upon rnanpower and financial resources of
CONCLUSIONS AND RECOMMENDATIONS
other government agencies (the QC training of NPC
119
tive approach to assisting SM/s. Such an approach
and HRDF's new JTS and GTS schemes) and the
would actively seek out and deliver to individual
private sector, to expand delivery of associated
SMis or groups of SMis a package of integrated ser
consultancies, technical assistance, training, and
vices-including consultancies, training and technol
funding needed to upgrade SMis to these new QIP
ogy information and incentives, and technical
standards. The outcome is not only more quality
assistance in production, quality control, and mar
upgrading among SMis, but also the development
keting.
of greater supplier linkages between SMis and both MNCs and other leading firms in the industry. V. Better Coordinated and Proactive SMI Policies A consistent theme running throughout the report is that SMis have weak training and technologi cal capabilities, and low levels of productivity
This implies a fundamental restructuring of poli cies toward SMis. A first step in this direction has been taken with the recent creation of the Small and Medium Scale De velopment C o rporation (SMID EC) within MID. Its objective is to consoli date the hitherto fragmented planning and coordi nation of SMI policies that are administered and
and efficiency relative to larger firms and MNCs.
implemented by other government agencies. Our
Most SMis do not train, and those that do rely on
follows:
recommendations for improving SMI support areas
informal OJT. They face a variety of training con straints from high labor turnover, poor information,
SMIDEC should begin by wuiertaking a careful re
and finance. Most SMis use older vintage, manual
view of existing SMI incentives to detennine why
equipment, they rarely have quality control systems,
their take-up is so low. Firm-level information perti
and most they tend to rely on visual inspection rather
nent to such a review has already been collected as
than precision measuring instruments to verify qual
part of the 1994 SMI study. This SMI survey re
ity. Reliance on these outdated technologies and pro
sembles the MITP survey, but it is more compre
duction methods creates little demand for high-level
hensive in its coverage of SMis, their constraints,
skills or training. These weak training and techno
and use of a wide range of policies that target them.
logical capabilities interact to create a vicious cycle
Similarities between the two surveys suggest that
of low levels of investments in human or knowledge
many analytic approaches used in the MITP study
capital, low levels of productivity, and with limited
can be fruitfully applied here.
resources, few incentives to train or adopt new tech nology.
As part of this review, SMIDEC should address the
The strong implication is that simply providing fi
delivered more effectively to SM/s. When new in
nancial incentives-whether for training as in DDIT,
centives are introduced, such as DDIT or the differ
or for technology upgrading as in ITAF-is inad
ent ITAF schemes, the principal responsibility for
issue ofhow existing incentives and services can be
equate. It ignores the reality that funding is seldom
take-up rests with the firms; implementing agencies
the only constraint that impedes SMis from invest
typically focus on reviewing and assessing applica
ing in training or technology. Given their weak ca
tions, or delivering a service, only when firms take
pabilities, most SMis may not even recognize that
the initiative to approach them. Many SMis have a
they have a problem, or if they did, most would not
poor grasp of their limitations, or their training or
know what incentives were available, or how they
technology needs, so that many incentives designed
would apply for, and effectively use, these incen
for them are not taken up. As such, a proactive ap
tives. To the extent that their problems are systemic,
proach needs to be adopted, with active promotion
as our analyses suggest, what is required is aproac-
and delivery of services to hard-to-reach SMis.
120
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
SMIDEC must either ensure that the implementing
Outreach and closer interactions with SM!s will re
agencies adopt a more proactive approach in ser
quire devolution of service delivery to states or lo
vice delivery, or alternatively, it must take on some
cal areas, and new or existing regional institutions
of these outreach functions, and coordinate service
need to be expanded. Many agencies are already in
delivery from other implementing agencies.
the process of doing so. The Malaysian Industrial Tech nology Information Center (MISTIC) has been des
SMIDEC can draw lessonsfrom the experiences of
ignated the one-stop-shop for information about
other countries with proactive approaches to SMI
technology and related incentives. SIRIM and NPC
support. Examples close to home include the indus
jointly operate Regional Quality Centers through
trial extension services provided to SMis in
which they deliver productivity and quality training.
Singapore and Taiwan, China; farther afield,
The HRDC has proposed setting up regional HRDF
Chile's SMI agency has actively promoted the
offices to provide information about training, organize
creation of SMI networks to increase take-up of
TNA workshops and clinics, and interact with firms.
policies, with professional managers to coordinate
SMIDEC should ensure that regional and local offices
members' use of a wide range of training and other
of all agencies provide information not only on their
SMI support services (much like HRDF's GTS
own programs but also those of other agencies, in
scheme); Mexico has set up CIMO offices in all states
effect, turning each office into a first-stop for all other
to proactively reach and deliver integrated training,
services. Integrated provision of these services may
consulting, and marketing support to SMI groups.
also be improved by co-locating staff from different
SMIDEC should visit these countries to glean and
agencies in the same office.
adapt lessons more appropriate to Malaysia's insti tutional context. While the details of each approach
A wide range of SMI incentives and programs
may vary, they all share similar features.
already exist and SMIDEC's challenge is to inte grate the efforts of diffe rent agencies to reach
All interventions in the context of service deliv
the maximum number of SM!s. For example, in
ery should involve a diagnostic or audit of the
expanding its vendor development programs to
SMI's capabilities and constraints, either individu
other groups of SMis and sub-sectors, SMIDEC
ally or as a group. This is to ensure that an inte
can draw not only on SIRIM to develop the rel
grated set of services, both financial a n d
evant QIPs, but also on NPC to deliver quality train
non-financial, can b e designed that are appropri
ing and productivity upgrading, and on HRDF to
ate to that SMI or group of SMis' real, rather than
fund group training activities. An expansion of
own perceived, needs. This diagnostic serves other
QIP certification may also revive interest in its
functions: it has a pedagogic role, in helping SMis
moribund subcontracting exchange (SCX)-which
learn about their strengths and weaknesses; it is in
has few entries and few queries-by providing po
formational, in informing them about the range of
tential foreign buyers and MNC users with the
services available to address their constraints; and
quality assurance that SMI subscribers have QIP
it serves to establish the credibility of the imple
certification. Similarly, because HRDC does not
menting agency and overcome the aversion that
have the staff resources to catalyze and identify
many SMis have to dealing with government
what kinds of joint training courses are needed
agencies. For SMIDEC, the issues to address are
by SMI groups, SMIDEC should ensure that other
which agency should conduct the audit, how to
agencies provide these functions and the audit
minimize duplicative efforts, and design ways to
needed to maximize the training benefits of the
share this information among agencies.
ITS scheme.
NOTES
121
NoTEs Chapter One The linkage between the 1988 MLFS and 1994 MITP surveys was not completed in time to be included in this report, but the panel data will be analysed in future work on the MITP project. 2
Department of Manpower, Government of Malaysia(1991), Survey of Industrial Skill Needs, regional reports, Kuala Lumpur.
Chapter Two The sampling weights from the 1994 industrial survey would have been preferable but they were not available at the time of this study. 2
The proportion of firms investing in technology in chemicals is 45. 13% , iron and basic metals (62.84%), electrical machinery(25.37%), transport equipment(52.61%), plastics(19.12%). The average export shares of these industries are 37.86% in electrical machinery, 41.68% in apparel, 41% for rubber, and 20% for plastics. This evidence is based on empirical studies of wage outcomes from training in three industrialized countries(Lillard and Tan, 1992, Tan et al, 1992), .and the productivity outcomes of training in produc tion function studies of four developing countries including Malaysia(Tan and Batra, 1995).
SIRIM and NPC are the Standards and Industrial Research Institute of Malaysia and National Produc tivity Corporation, respectively. Unfortunately, the data did not permit a more disaggregated break down of training by these two agencies. 6
Estimates of the total number of workers trained are obtained by multiplying the number of reported trainees in each firm by its sampling weight. These weights, representing the number of firms repre sented by each firm in a given industry-firm size category, were calculated from the frequency distributions of firms in the 1988 industrial survey. The resulting training figures under-estimate how much training actually occured in 1994 given the growth in manufacturing since the 1988 survey was undertaken. Changes in the composition of firms since 1988 are another source of imprecision in these estimates.
7
The recommendation to make it mandatory for employers to train 10 percent of their workforce was superceded by the enactment of the Human Resource Development Fund in 1993. Nonetheless, it is of some interest whether this target of 10 percent training has been achieved. John Enos, "Invention and Innovation in the Petroleum Refining Industry", in Kenneth Arrow(edJ, The Rate and Direction of Inventive Activity, Princeton University Press, 1962. See Hong Tan, Human Capital and Technological Change, Ph.D thesis, Yale University, 1980; and Lee Lillard and Hong Tan, "Private Sector Training: Who Gets It, How Much, and Why", in R. Ehrenberg(ed.), Research in Labor Economics, JAI Press, 1993.
122
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
Chapter Three
The constant returns to scale Cobb-Douglas production function was selected for its flexibility and ease of interpretaton. Studies have demonstrated its superiority over other more complex functional fonns, like the trans-log, in the presence of missing data and measurement error problems such as those common to developing country data sets (Tybout, 1992). We note that foreign-owned firms are not homogeneous, and that the country of origin of foreign capital may be associated with differences in their propensity to train or to invest in R&D. While a potentially interesting issue, analyses based on separate production function estimates by country of ownership was precluded by small sample sizes. When a common production function was estimated for all finns, the results indicated that only external training had a positive and significant effect on firm-level productivity; in-house training had no discernible effects on productivity. This counter-intuitive result was driven by the ownership composi tion of finns in the MITP sample, and it led us to estimate separate production functions by ownership status . 4
For local firms the productivity impact of external training is calculated as (0.0026 x 1. 751 x 100); for foreign firms the productivity impact of internal training is (0. 019 x 0. 4 x 100). To identify which external training source had the important impact on productivity, we experimented with alternative grouping schemes such as dividing external sources by public or private training providers, or by whether the institution provided advanced versus basic skills training. In general, they reveal that private training providers are more important than public-run institutions, and that advanced skills training is more important than basic skills training. However, in each case, the result was driven by the productivity effects of training from SDCs and ClASTs. Information was also collected on profit-sharing, but this variable proved to be highly correlated with some of the other components of compensation and was dropped. To be more precise, if starting pay is W(O) and pay after 10 years of service is W(lO), then the wage increase is calculated as [W(lO)- W(O)] /W(O). A more disaggregated analysis by specific occupational groups was precluded by the availability of information on the components of compensation by only two broad groups, non-production workers and production workers. A set of industry dummy variables were included in all regressions but their estimates are not reported here in the interest of brevity. ,
,
5
6
7
9
Chapter Four
2
Respondents were actually asked to rank the relevance of eight statements. One of these, that informal training is sufficient, was deemed to be similar to another statement on the adequacy of learning by doing because of mature technology used. As such, the eighth statement was dropped from consideration. See Tan and Batra (1995), Enterprise Training in Developing Countries, Private Sector Development Department, The World Bank. Employers already deduct training expenditures as a business expense, but the DDIT scheme allows them to deduct an additional amount equal to eligible training expenditures.
NOTES
4
In 1994, there were 12 approved training institutions: the National Productivity Corporation, SIRIM, Mara Institute of Technology,Malaysian Agricultural Research and Development Institute, Forest Research Institute ofMalaysia, Centre for Instruction in Advanced Skill Training, Penang Skill Development Centre, IKM, Industrial Training Institutes, German-Malaysian Institute, Malaysian Timber Industry Board, and Perak Entrepreneur and Skill Development Centre. This discussion draws upon an analysis ofMIDA's administrative data on DDIT reported in the World Bank study (1994), Malaysia-Meeting Labor Needs:More Workers and Better Skills, Chapter
Poor. 6
Originally, training programs had to be directed at either ( 1) development of craft, supervisory and technical skills for the manufacture of new products or processes, or (2) upgrading of craft, supervi sory and technical skills in existing products and processes. In 1991, two broader categories were added: (3) production-related training for productivity improvements, and (4) training for quality improvements in production. This expansion in the scope of eligible training programs resulted in a dramatic increase in the number of production workers getting training.
7
MIDA 's administrative records did not contain employment size information on applicants. This was determined by matchingMIDA's list of DDIT applicants with a master list of all manufacturing
firms in operation in 1992 which contained data on employment size. Only 70 percent of applicants could be matched so that the estimates are necessarily tentative. World Bank, Vocational Education on the Threshold of the 1990s, commissioned study by CINTERFOR andiLO, volumes land II, 1991. 9
The Government contributed R48. 9 million to match projected company levies in the fust year; in each of the following three years, it will add an additional R16.3 million to the HRDF.
10
We note that our definition of "eligibility" is partial. The HRDC defines finns as eligible if they have
50 or more employees that are citizens ofMalaysia, not including foreign workers or workers sup plied by labor contractors. Some finns meeting the employment size criterion were subsequently deregistered when the nationality of their employees was taken into account. I 1
On-the-job training is eligible for HRD F reimbursement provided that the orr is structured, with a clearly defined program objective, training plan, and identifiable trainers. These structured training programs are excluded from our definition of informal orr.
12
Many firms were reportedly unable to meet the original deadlines because of missing receipts and turnover of flnns ' human resource officers; this prompted the HRDC to grant these fums dispensa tion to file claims as late as June 1995 for training expenditures incurred in the third quarter of the previous year.
13
In fact, administrative data from HRDC indicates that use of the PLT scheme-both in tenns of workers trained and training expenditure-is lower than that of the SBL scheme. Even finns with a training plan rely on the SBL scheme because of its flexibility.
14
Five employer associations have been selected to participate in the pilot GTS. They include the Malay Chamber of Commerce and Industry, the Chinese and Indian Chambers of Commerce and Industry in Selangor state, the BurniputraManufacturer's Association, and theMalaysian Iron and Steel Federation.
Chapter Five Malaysian Science and Technology Information Centre (1994), Ministry of Science, Technology and the Environment, Kuala Lumpur.
123
124
2
ENTERPRISE TRAINING, TECHNOLOGY AND PRODUCTIVITY
By way of comparison, overall R&D as a percent of GDP is
1 percent in Singapore, 1. 7 percent in
Taiwan, and 2.1 percent in Korea, while the corresponding private sector contribution to R&D is 0. 6,
0.8 and 1.7 percent, respectively. World Bank, Strengthening Industrial Technology Development for Sustainable Growth 1996, Table 1.3. The eleven training categories included (1) technical (2) managerial (3) machine operation (4) quality control (5) machine maintenance (6) skills upgrading (7) safety and health (8) team work and motivation (9) technology upgrading (10) on the job training , and (11) production systems and procedures. In interviews, SIRIM confirmed that having a structured training program with instruction in quality control techniques is one important criterion for IS0-9000 certification. According to SIRIM, the recent growth of interest in IS0-9000 has been so great that it has exceeded SIRIM 's capacity, and many firms have turned to foreign certification bodies despite their substantially higher fees. 6
A check reveals that, for the most part, firms that are not currently training tend to respond "don't know" or "reduced training", though there are a few cases when firms said they increased training levels but were not currently providing training.
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