Industrial Dynamics in China and India
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Industrial Dynamics in China and India
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Other titles from IDE-JETRO Moriki Ohara INTERFIRM RELATIONS UNDER LATE INDUSTRIALIZATION IN CHINA The Supplier System in the Motorcycle Industry Shigemochi Hirashima, Hisaya Oda, and Yuko Tsujita (editors) INCLUSIVENESS IN INDIA A Strategy for Growth and Equality Koichi Usami (editor) NON-STANDARD EMPLOYMENT UNDER GLOBALIZATION Flexible Work and Social Security in the Newly Industrializing Countries Akifumi Kuchiki and Masatsugu Tsuji (editors) FROM AGGLOMERATION TO INNOVATION Upgrading Industrial Clusters in Emerging Economies Takashi Shiraishi, Tatsufumi Yamagata, and Shahid Yusuf (editors) POVERTY REDUCTION AND BEYOND Development Strategies for Low-Income Countries Hiroko Uchimura (editor) MAKING HEALTH SERVICES MORE ACCESSIBLE IN DEVELOPING COUNTRIES Hiroshi Sato and Mayumi Murayama (editors) GLOBALISATION, EMPLOYMENT AND MOBILITY The South Asian Experience Mariko Watanabe (editor) RECOVERING FINANCIAL SYSTEMS China and Asian Transition Economies Daisuke Hiratsuka (editor) EAST ASIA’S DE FACTO ECONOMIC INTEGRATION Masahisa Fujita (editor) REGIONAL INTEGRATION IN EAST ASIA From the Viewpoint of Spatial Economics Hisayuki Mitsuo (editor) NEW DEVELOPMENTS OF THE EXCHANGE RATE REGIMES IN DEVELOPING COUNTRIES Tadayoshi Terao and Kenji Otsuka (editors) DEVELOPMENT OF ENVIRONMENTAL POLICY IN JAPAN AND ASIAN COUNTRIES Akifumi Kuchiki and Masatsugu Tsuji (editors) INDUSTRIAL CLUSTERS IN ASIA Analyses of Their Competition and Cooperation Mayumi Murayama (editor) GENDER AND DEVELOPMENT The Japanese Experience in Comparative Perspective
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Industrial Dynamics in China and India Firms, Clusters, and Different Growth Paths Edited by
Moriki Ohara Associate Professor, Ryukoku University
M. Vijayabaskar Assistant Professor, Madras Institute of Development Studies
Hong Lin Director, Shandong Institute for East-Asia Studies
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© Institute of Developing Economies (IDE), JETRO 2011 All rights reserved. No reproduction, copy or transmission of this publication may be made without written permission. No portion of this publication may be reproduced, copied or transmitted save with written permission or in accordance with the provisions of the Copyright, Designs and Patents Act 1988, or under the terms of any licence permitting limited copying issued by the Copyright Licensing Agency, Saffron House, 6–10 Kirby Street, London EC1N 8TS. Any person who does any unauthorized act in relation to this publication may be liable to criminal prosecution and civil claims for damages. The authors have asserted their rights to be identified as the authors of this work in accordance with the Copyright, Designs and Patents Act 1988. First published 2011 by PALGRAVE MACMILLAN Palgrave Macmillan in the UK is an imprint of Macmillan Publishers Limited, registered in England, company number 785998, of Houndmills, Basingstoke, Hampshire RG21 6XS. Palgrave Macmillan in the US is a division of St Martin’s Press LLC, 175 Fifth Avenue, New York, NY 10010. Palgrave Macmillan is the global academic imprint of the above companies and has companies and representatives throughout the world. Palgrave® and Macmillan® are registered trademarks in the United States, the United Kingdom, Europe and other countries ISBN: 978–0–230–29878–1 This book is printed on paper suitable for recycling and made from fully managed and sustained forest sources. Logging, pulping and manufacturing processes are expected to conform to the environmental regulations of the country of origin. A catalogue record for this book is available from the British Library. Library of Congress Cataloging-in-Publication Data Industrial dynamics in China and India : firms, clusters, and different growth paths / edited by Moriki Ohara, M. Vijayabaskar, Hong Lin. p. cm. Includes index. ISBN 978–0–230–29878–1 (alk. paper) 1. Industries – China. 2. Industries – India. 3. Technological innovations – Economic aspects – China. 4. Technological innovations – Economic aspects – India. 5. Industrial policy – China. 6. Industrial policy – India. I. Ohara, Moriki, 1967– II. Vijayabaskar, M. III. Lin, Hong. HC427.I523 2011 338.0951—dc22
2011012448
10 9 8 7 6 5 4 3 2 1 20 19 18 17 16 15 14 13 12 11 Printed and bound in Great Britain by CPI Antony Rowe, Chippenham and Eastbourne
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Contents List of Tables
vii
List of Figures
ix
List of Abbreviations
xi
Acknowledgements
xv
Notes on Contributors
xvii
Introduction: Different Competition, Different Industrial Dynamics Moriki Ohara
Part I 1
2
4
5
6
Firms and Competition
Competition and Management in the Manufacturing Sector in China and India: A Statistical Overview Moriki Ohara and Hong Lin
19
China and India’s Electrical and Electronics Industries: A Comparison between Market Structures Koichiro Kimura
40
Part II 3
1
Capability Formation: Skills, Technology, and Innovation
Technology Acquisition by Indigenous Firms: The Case of the Chinese and Indian Automobile Industries Tomoo Marukawa Capability-Building via Interfirm Relationship and In-House Employment in China and India: A Comparative Study of the Motorcycle Industry Moriki Ohara
63
80
Skill Formation through Education and Training: A Comparison of China and India Yoko Asuyama
107
The Institutional Milieu of Skill Formation: A Comparative Study of Two Textile Regions in India and China M. Vijayabaskar and J. Jeyaranjan
135
v
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vi
Contents
Part III The Role of the State and the Global Production Network 7 Two Tales of Agro-Industrial Transformation: State Capacity in China’s and India’s Textile Industries Mark P. Dallas 8 Local Finance and Governments in the Economic Development of China and India: Distribution and Economic Efficiency Kai Kajitani
157
180
9 The Electric Vehicle Industry in China and India: The Role of Governments for Industry Development Martin Lockström, Thomas Callarman, and Liu Lei
203
10 The Role of Local Government in Software and ITES Offshoring in Dalian, China Hiromi Hinata
226
11 The Role of Standards in Technology-Driven Commodity Chains: The Information and Communication Technology Services Industry in Dalian, China, and Bangalore, India Balaji Parthasarathy and Bharath M. Palavalli Index
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237
259
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Tables I.1
Relative contrast of competition, management, and environments in modernized sectors
7
I.2
Hierarchic nature of the labor market in China and India: average monthly wage rate in various industrial clusters
13
1.1
Concentration of market share and the number of firms producing various products
24
1.2 Size comparison of Chinese and Indian manufacturers
28
2.1 Electrical and electronics industries
44
2.2
Market share in China, 1993–2005
46
2.3 Market share in India, 1992/93–2006/07
48
2.4
Firm size in China, 1991–1998
51
2.5 Production volume in India, 1979–1996
54
2.6 Firm size in India, 1992/93–2000/01
55
3.1 Domestic-brand cars in China’s automobile industry
66
3.2
67
Top car manufacturers in China
3.3 Production volume of major automobile manufacturers in India
69
3.4 Chery’s automobile production and exports
71
3.5 Geely’s automobile production and exports
72
3.6 Tata Motors’ automobile production and exports
77
4.1
Motorcycle manufacturers in China and India, 2006–2007
82
4.2
Outsourcing structures of Asian motorcycle makers
86
4.3
Multisourcing and dependency rate
89
4.4
Risk sharing
90
5.1 Distribution of employed persons by level of education, 2005
110
5.2
Skill flows from general and vocational education in China, 2005
112
5.3
Skill flows from general and vocational education in India, 2005–2006
113
5.4 Vocational training scheme of China, 2005
114
5.5 Vocational training scheme of India, around 2005
115
vii
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viii
List of Tables
5.6 Compound annual growth rate of formal employment
126
6.1 Shares in exports of cotton, textiles and clothing
139
8.1
Interregional risk-sharing in China
8.2 Economic data of major states in India
187 188
9.1 Chinese OEMs involved in EV development
205
9.2 China emission standards
206
9.3
The electric vehicle projects of the “863” program in the 11th Five-Year Plan
209
9.4
Details of the support provided by local governments under the “Ten Cities, One Thousand Cars” policy
210
9.5 Indian OEMs involved in EV development
214
9.6 Indian emission standards
215
9.7 Comparison of EV development in India and China
217
10.1
Top three Indian and Chinese software and ITES export companies
228
11.1
IDC’s global delivery index – Asia Pacific, 2007–2008
238
11.2
Leading ICT service producing locations in China, 2002–2008
240
11.3
National and local significance of Dalian’s ICT services industry
241
11.4
Leading ICT services exporting locations in China, 2002–2008
242
11.5
Share of exports in leading ICT service producing locations in China, 2002–2008
243
11.6
ICT service firms in Dalian and their characteristics, 2000–2008
248
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Figures I.1
Structure and size of domestic market and competitors – China, 2000, and India, 2005
8
1.1
Ratio of the manufacturing sector in total employment
21
1.2
Productivity gap between agricultural and nonagricultural industries
22
1.3
Turnover ratio, manufacturing sector in China and India
1.4 Changes in the capital–labor ratio in Asian economies
29 30
1.5
Employment structure by firm size: manufacturing sector
32
1.6
Average KL ratio of different-sized firms: manufacturing sector
32
1.7
Different KL ratios within and between subsectors of the manufacturing industry
33
1.8
Technological gap between firms of different sizes, automobile industry
34
1.9 Correlation between firm size and engineer ratio 2.1
Industrial structures: China, 1980–2005, and India, 1980/01–2005/06
35 43
3.1 Production volume of major automobile producing countries
63
3.2 Structure of India’s automobile production in 2008
68
4.1
Share of the top three motorcycle manufacturers in selected Asian economies
5.1 Student enrollment by education level in China
83 119
5.2
Educational expenditure allocation of India by level of education
120
7.1
Major raw-fiber producers, 1999–2000
158
7.2
Share of total manufacturing costs of similar count cotton yarn, 1997–1998
163
7.3
Average monthly cotton prices: China, India and global, September 1999–April 2007
165
ix
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x
List of Figures
7.4
Cotton profits and synthetic fiber consumption as percentage of total cloth, China 1970–1991
8.1 Ratio of development expenditure in India 8.2
Structure of central and local government expenditure in China, 2006
170 190 191
8.3 Structure of developmental expenditure in states of India
191
8.4 Structure of government expenditure in China
192
8.5
Reserved revenue of local governments by selling landuse rights
194
8.6
Price distinction in the land market of China
195
8.7
Dynamic inefficiency in several countries
198
8.8 Dynamic inefficiency in each region, China 9.1 9.2 10.1
199
Three-times-three R&D mechanism of EV development in the “863” program
208
The “Ten Cities, One Thousand Cars” implementation plan for new energy vehicles in 2012
212
Software and ITES revenues and export ratio in China and India
227
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Abbreviations AITT ASI ATS BEV BPO BS CAGR CCI CCP CCTV CEO CISIS CKD CMM CMMi CMT CNG CR CRT CSIA CSG CSS CTS CTV CVT DCCC DGE&T DIET DLSP DMT DPEP DSIA E&T ESI ETDZ EV FAW FCEV
All India Trade Test (India) annual survey of industries Apprenticeship Training Scheme (India) battery electric vehicle business process outsourcing Bharat Stage (Indian emission standard) compounded annual growth rate Cotton Corporation of India Chinese Communist Party China Central Television chief executive officer China International Software and Information Service Fair complete knocked-down Capability Maturity Model Capability Maturity Model Integration cutting-making-trimming (factory) compressed natural gas concentration ratio cathode-ray tube China Software Industry Association China Southern Power Grid Centrally Sponsored Scheme (India) Craftsmen Training Scheme (India) color television continuously variable transmission Dalian City Computer Center Directorate General of Employment & Training (India) District Institute of Education and Training Dalian Software Park Co., Ltd. dimethyltryptamine District Primary Education Program Dalian Software Industry Association education and training Employee State Insurance (China) Economic and Technology Development Zones (China) electric vehicle First Automobile Works (China) fuel cell electric vehicle
xi
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xii
List of Abbreviations
FDI FERA 5YP GB GB/T GDI GDP GVIO HDTZ HEV ICT IDC IDE IED IIIT IIM IISc IIT ILO INR IP ISI ISO IT ITC ITES ITIs ITPB JETRO JIS JLPT JSIA LFPR LPG MEG METI MEXT MFA MHRD MII MIIT
foreign direct investment Foreign Exchange Regulation Act (India) five-year plan Guojia Biaozhun (national standard, China) recommended (tuijian) Guojia Biaozhun (China) global delivery index gross domestic product gross value of industrial output High-Technology Development Zone (China) hybrid electric vehicle information and communication technology International Data Corporation Institute of Developing Economies industrial enterprise data (China) International Institute of Information Technology (India) Indian Institute of Management Indian Institute of Science Indian Institute of Technology International Labour Organisation Indian Rupee (I USD = 45 INR in 2010) intellectual property import substitution-led industrialization International Organization for Standardization (International Standards Organization) information technology (private) industrial training center (India) information technology enabled services (public) industrial training institutes (India) International Tech Park Bangalore Japan External Trade Organization Japanese Industrial Standards Japanese-Language Proficiency Test Japan Information Technology Services Industry Association labor force participation ratio liquefied petroleum gas monoethylene glycol Ministry of Economy, Trade and Industry (Japan) Ministry of Education, Culture, Sports, Science and Technology (Japan) Multi-Fiber Agreement Ministry of Human Resource Development (India) Ministry of Information Industry (China) Ministry of Industry and Information Industry (China)
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List of Abbreviations xiii
MITI MMT MNC MNES MPV MRTPA MSP MSPI NAICS NAS NASSCOM NBS NC NEV NIC NIT NS NSS NSSO NTC OECD OEM OGL OJT OLS PHEV PIPA PM PTA R&D RMB SAIC SAME SDM SDP SEI SEZ SFS SGCC
Ministry of International Trade and Industry (Japan, predecessor of METI) million metric tons (unit) multinational corporation Ministry of Non-conventional Energy Sources (India) multi-purpose vehicles Monopolies and Restrictive Trade Practice Act (India) minimum support price (India) Ministry of Statistics and Programme Implementation (India) North American Industry Classification System national accounts statistics National Association of Software and Services Companies National Bureau of Statistics (China) numerical control new energy vehicle National Industrial Classification (India) National Institute of Technology (India) National Standard (emission standard) (China) National Sample Survey (India) National Sample Survey Organization (India) National Trade Certificate (India) Organization for Economic Co-operation and Development original equipment manufacture open general license on-the-job training ordinary least squares plug-in hybrid electric vehicle Privacy Information Protection Assessment (Japan) particulate matter purified terephthalic acid research and development Chinese Yuan/Renminbi (I USD = 6.8 RMB in 2010) Shanghai Automobile Industry Corporation Shenyang Aerospace Mitsubishi Motors Engine Manufacturing Co., Ltd. National Skill Development Mission (India) state domestic production (India) Software Engineering Institute (USA) special economic zone skill formation system State Grid Corporation of China (China)
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xiv List of Abbreviations
SIMHA SMC SME SNA SOE STP SUV T&C TDCC TEA TELCO TFP TFPR TIF TPM TUFS TVE UNCTAD USD USDA VAT VET WTO
South Indian Hosiery Manufacturers Association (India) supply and marketing cooperative (China) small and medium-sized enterprise System of National Accounts state-owned enterprise Software Technology Park (India) sport utility vehicle textiles and clothing technology driven commodity chain Tirupur Exporters Association (India) Tata Engineering & Locomotive Co., Ltd total factor productivity revenue-based total factor productivity Tirupur Industries Federation (India) total productivity maintenance Technology Up-gradation Fund Scheme (India) township and village enterprise United Nations Conference on Trade and Development US dollar United States Department of Agriculture value-added tax vocational education and training World Trade Organization
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Acknowledgements This book is the result of a three-year-long international research project, Comparative Study on the Industrial Development Process in China and India, initiated by the Institute of Developing Economies, Japan External Trade Organization (IDE-JETRO), which ran from 2007 to 2010. Several Chinese and Indian research institutes of international repute joined the project, including the Indian Institute of Management, Bangalore (IIMB), the International Institute of Information Technology, Bangalore (IIITB), the Madras Institute of Development Studies (MIDS), the Institute for Development Alternatives, Chennai (IDA), the Institute for Studies in Industrial Development (ISID), the Institute of Industrial Economics of the Chinese Academy of Social Sciences (IIE-CASS), the China Academy of Science and Technology Development (CASTD), the China–Europe International Business School (CEIBS), and the Shandong Institute for East-Asia Studies (SIEA). In this field-survey-oriented research project, their participation was invaluable in our quest to comprehend contemporary industrial realities in the two countries. Special thanks should be expressed to participants in the project other than the contributors to this volume: Pankaj Chandra, Xiaoxia Xie, Aya Okada, Yoshie Shimane, Haritha Saranga, Jun He, Qin Wang, Xinxin Kong, Xu Ye, and Satyaki Roy, who provided us with critical knowledge and insights though their papers and discussions during field surveys and workshops. Zhou Yu and Yuko Aoyama also gave us precious comments on our panel presentations at the 2010 Annual Meeting of the Association of American Geographers held in Washington D.C. The contributors to this volume express their sincerest gratitude to the managers, experts, staff, and employees of firms, business associations, R&D institutes, training schools, and governments of various levels who participated in their repeated interviews or made efforts to arrange them. They are also grateful to the researchers/experts for help in formulating their ideas or in obtaining data sets. In particular, special thanks go to Zhenhua Song, Gangyu Sun, K. Salvaraju, G. Venugopal, S. Sakthivel, Sujian Huang, Yi Ding, Barry Naughton, Loren Brandt, S. Sadagopan, Eswaran Subrahmanian, Peilei Fan, K. V. Ramaswamy, R. Nagaraj, Judith Beine, Wang Dawei, Wang Yapeng, Liang Hu, Ken’ichi Matsumura, Masashi Niino, Hideaki Awano, Yoshiharu Ogi, R. Abhilash, Kiyota Okabe, Tadao Kazuno, Tomomi Okazaki, Li Dong, Yanming Chen, Peng Sun, Longzhong Yang, John Absmeier, and Takahiro Sato for their warm support.
xv
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Acknowledgements
We would also like to thank IDE-JETRO for providing financial resources and intellectual support. In particular, special gratitude is due to Toyojiro Maruya, Katsumi Hirano, Masanobu Saito, Kumiko Sakumoto, Masahiro Okada, Ritsuko Takakusagi, Manami Handa, Miho Shimizu, Naoko Endo, and Nana Izumi for their administrative backup, and to Yukihito Sato, the late Ken Imai, Hiroko Uchimura, Hitoshi Ota, Kensuke Kubo, and Mami Yamaguchi for their scholarly input as experts. The hard work of Koichiro Kimura, the assistant project manager, and Yoko Asuyama was indispensable to the successful completion of the project. Efficient assistance from Ibarat Samakova, Yuanna Xu, and Sumei Chen is also appreciated. Last but not least, the editors express deep gratitude to Taiba Batool and Ellie Shillito of Palgrave Macmillan and the team at Newgen Publishing and Data Services for their expertise and patience during the book production process. In closing, we would like to recall the achievements of the late Professor Shoji Ito, a Japanese scholar on Indian political economy, who is especially well-known for his pioneering studies on Indian business families. Professor Ito joined IDE in 1960 and initiated his life-long research on India after spending time in Chennai in 1961. In addition to producing scholarly volumes on India, he also carried out comparative study projects among Asian economies and inspired a generation of scholars in this area. This volume is one of the offshoots of that stream, and is dedicated with pleasure to the memory of his fruitful professional life. The editors
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Contributors Yoko Asuyama is a research fellow at the Institute of Developing Economies, Japan External Trade Organization. She received her Master’s in Public Administration from Cornell University. Her research interests include labor economics, skill formation, and industrialization in Asian economies. Thomas Callarman is Professor of Operations Management and Director of the CEIBS Centre for Automotive Research at the China–Europe International Business School in Shanghai. He previously spent 25 years at Arizona State University in Tempe, where he was Associate Professor of Supply Chain Management and held several administrative positions. His research interests are in supply chain management, especially in supply management and manufacturing. His research is currently focused on the automobile industry in China. Mark P. Dallas is Assistant Professor of Political Science at Union College in New York. After a year and a half of fieldwork in China, he recently completed his dissertation “New Roads to Capitalism: China and Global Value Chains” at the University of California, Berkeley, which is a comparative historical study of China’s textile agro-industries. His current research considers the reorganization of global industries and commodity trading during the 20th century, and differences in levels of integration among late industrializers. Hiromi Hinata is a research fellow in the Overseas Research Department, Japan External Trade Organization. From 2004 to 2009, she worked with local governments in northeast China to promote Japan–China business relationships as the director of JETRO’s Dalian office. She conducts executive seminars on business management in China and consults with small and medium-sized enterprises around Japan. She received her MBA from INSEAD in 2002. Her research interests include Japanese firms’ overseas business management and the Chinese economy. J. Jeyaranjan is Director, Institute of Development Alternatives, Chennai. In addition to teaching at Pondicherry University, he has served as consultant to several multinational organizations and has written articles and edited volumes on agrarian change, labor, and livelihood regimes. He completed a Ph.D. in Economics at the Madras Institute of Development Studies, University of Madras, Chennai. His research interests include labor markets, agrarian relations, and regional development.
xvii
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Notes on Contributors
Kai Kajitani is Associate Professor of Economics at Kobe University. His work has focused mainly on analysis of two topics: the central–local relationship in China and its influence on financial policy, and China’s contribution to “global imbalance” and its influence on domestic financial policy. He earned his Ph.D. in Economics at Kobe University. Koichiro Kimura is a research fellow at the Institute of Developing Economies, Japan External Trade Organization. He was a visiting fellow at the Institute of Industrial Economics, Chinese Academy of Social Sciences, from 2005 to 2007. His fields of interest are international economics, industrial organization, and the Chinese economy. His research topics include the organization growth of Chinese local firms in globalization and the influence of Chinese outward foreign direct investment on the world economy. Liu Lei is a research assistant at the China–Europe International Business School in Shanghai and a Ph.D. student at the European Business School, London. Formerly he served as a supply chain manager at Grundig Business Systems, Germany, and was a supply chain controller at Foxconn Technology Group. His research interests include supply chain management and supplier integration in the Chinese automotive industry. Hong Lin is Director and Senior Research Fellow at Shandong Institute for East-Asia Studies. He has served as a professor and vice-director at the Japanese Studies Centre, Shandong University, and was a visiting scholar at the Beijing Center for Japanese Studies. He earned his Master’s in International Political Science at Shandong University. His research area is political economy and the international relations of East Asian countries. Martin Lockström is a research associate and Director of the BMWSMI Centre for Purchasing and Supply Management at China–Europe International Business School (CEIBS) in Shanghai. He is also Deputy Director of the CEIBS Centre for Automotive Research and Senior Representative for the Supply Chain Management Institute, China. His research interests focus on global sourcing, outsourcing, and international management. He has published and reviewed for leading academic journals such as the Journal of Operations Management and the Journal of Supply Chain Management. Tomoo Marukawa is Professor of the Chinese Economy at the Institute of Social Science, University of Tokyo. Prior to that, Marukawa was a researcher at the Institute of Developing Economies, Japan External Trade Organization, for 14 years. He has also been a visiting scholar at the Institute d’Asie Orientale in France (2005) and the Institute of Industrial Economics, Chinese Academy of Social Sciences (1991–1993). He is the author of several publications on Chinese industrial development and the labor market.
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Notes on Contributors xix
Moriki Ohara is an associate professor in the Department of Economics, Ryukoku University. Previously he was a research fellow at the Institute of Developing Economies, Japan External Trade Organization, and was a visiting scholar at the Center for Chinese Studies, University of California, Berkeley, and the Institute of Industrial Economics, Chinese Academy of Social Sciences. He earned his Ph.D. in Economics from Kyoto University. His research areas include comparison of growth processes and institutions in China and other Asian economies. Bharath M. Palavalli is a research engineer with the Center for Study of Science, Technology and Policy, Bangalore, India. His interest in the spatial impacts of information and communications technologies (ICTs) has led him not only to undertake comparative studies of the ICT industry, but also to use agent-based modeling to understand the complexities of urban growth. Palavalli has a Master’s in Information Technology from the International Institute of Information Technology, Bangalore. Balaji Parthasarathy is ICICI Associate Professor at the International Institute of Information Technology, Bangalore. He is interested in the relationship between technological innovation, economic globalization, and social change. More specifically, his work has examined the impacts of public policies and firm strategies on the organization of production in the information and communications technology (ICT) industry. Another aspect of his work explores how ICTs are being deployed in various domains of activity to transform social relationships in economically underprivileged contexts. M. Vijayabaskar is an assistant professor at the Madras Institute of Development Studies, Chennai. He has also been a visiting fellow at the School of Oriental and African Studies, London, and a research fellow at the International Institute of Information Technology, Bangalore. He completed his Ph.D. in Economics at the Centre for Development Studies, Thiruvananthapuram (Jawaharlal Nehru University, New Delhi). His research interests include regional developmental processes with an emphasis on labor markets, technological change, and policy institutions.
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Introduction: Different Competition, Different Industrial Dynamics Moriki Ohara
1.1 Aim of the study In the first decade since 2000, China and India have entered into a new era of industrial upsurge, which has made their economic landscapes in the early 2010s enormously different from those of the 1990s. Though the two countries have accelerated deep-going liberalization reforms since the early 1990s (Joshi 1998, Naughton 2007, and Acharya 2009), however, the growth paths of the two have varied greatly, not only in terms of their macroeconomic appearances, but also in terms of the micro-level realities. The aim of this book is to present a detailed comparison of the growth trajectories of representative indigenous firms and clusters during the two decades after the 1990s in China and India, and to explore their relative characteristics in the industrial development process. We also seek to comprehend the underlying socioeconomic backgrounds that have engendered such disparate features. Various pieces of the existing literature point out important differences in the modes of economic development in China and India.1 However, most of the literature focuses on the macroeconomy and policy, and very few have ventured to make firm or cluster-level comparisons. 2 In contrast, every chapter of this study directly compares the same industry or a specific aspect of market institutions in the two countries and dissects the detailed differences found in the growth of representative firms and clusters. The sectors analyzed include the manufacturing sector – textiles, automobiles, motorcycles, electric vehicles, and electronics appliances – and the service sector – software development and business process outsourcing (BPO). As expressed by the phrase “other roots, other routes,”3 the two countries exist in totally different milieus of natural environment, history, culture, social structure, political regime, and international economic geography. And as chapters of this book will illustrate, firms and clusters in the two countries also do not follow exactly the same paths, despite the fact that 1
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2
Moriki Ohara
their basic technologies and tools of business are globally common. By scrutinizing the detailed differences observed in the same industries that basically use the same technology and are in the same international environments, we can glimpse more clearly the important causes of the differences and the underlying factors of market societies and capitalism in China and India. The real significance of this comparative study, in our view, is its examination of the different approaches which were adopted by the two super-huge, populous, agrarian countries in their pursuit of economic development and social transformation, which differ from the experiences of forerunning early-developers in East Asia – including Japan, Korea, and Taiwan. In this endeavor, we shall focus on their specific and unique factors and conditions – for example, their potentially large domestic markets, the legacy of a technological base constructed during the socialist economy period, large amounts of public finance, vast indigenous capability in building skills and technology, ubiquity of the latest technologies and best managerial practices via globalized business networks, the weakness of the central state in its penetration into the society for resource mobilization, and the consequent importance of local government in industrialization.
1.2
Comparison perspective
This study focuses on three spheres of industrial upgrading: (1) indigenous firms and the nature of competition, which are discussed mainly in chapters in Part I, (2) capability formation of firms, which is the main topic of chapters in Part II, and (3) the role of state and global production networks (GPN), which will be discussed by chapters in Part III. From the viewpoint of the growth of firms, (1) is the environment, (2) concerns their internal driving forces, and (3) is concerned with the external driving forces that prompt their growth. 1.2.1
Indigenous firms in competition
We explicitly place our focus on the indigenous firms and clusters. We may assume that indigenous firms, compared to foreign-capitalized firms, have a more earnest desire to utilize local resources and to adapt themselves to the local market. In addition, the two countries have a long history of active construction of indigenous industries, achieved by gaining the wide support of various domestic parties. If such assumptions hold, we can obtain a better understanding of some of the principal characteristics concerning the way they organize their market-economy institutions4 by observing various economic relations formulated between the firms and stakeholders, including entrepreneurs, workers and staff, transaction partners, financial institutions, and government. Furthermore, in many segments of the product
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Introduction 3
markets in the two countries, indigenous firms claim a large share in terms of sales and production, and we may expect that, in the near future, a group of world-class multinational corporations (MNCs) may emerge from them. 1.2.2
Building technological capability
This study has two methodological features. The first is its focus on technological capability formation as the engine of growth of the firm. It is widely acknowledged that the way in which an economic system is constructed influences the nature and manner of building the capability/knowledge of firms and individuals, and the latter also determines the future direction of the former (North 1990). In this line, Chapters in Part II will, based on rich case studies, explore in detail the different manners of organizational technological resource-creation – both via in-house operations and interfirm networks – and explore the creation of human resources via training and education institutions and labor markets. It is widely assumed that latecomers “learn” the ways of advanced firms – in advanced countries – in the early stages of their production and development by “imitation” and reverse engineering, and then – after accumulating enough knowledge and experience – they enter a new stage where they continuously perform “innovations” to gain market competitiveness (Hobday 1995). In the course of this “from imitation to innovation,” firms are expected to acquire and accumulate their own “proprietary” assets that enable them to effect continuous differentiation, which is the result of their long-term firm/transaction-specific investments in technology, human resource skills, and research and development institutions (Amsden 1989; Lall 1992). A feature critical to understanding China and India in the twenty-first century is their relative ease of acquiring and learning about the latest technological and managerial information compared to their antecessors. This stems from a variety of different environmental conditions, including wide-open and ubiquitous access to technologies and the richness of their human resources both in skilled workers and highly-educated experts. After World War II, when Japan started its full-fledged catch-up process by learning from abroad, the only source of advanced technology was the US and other Western countries. Japan was basically the only contender in the non-Western world in the race to catch up, and the method of learning for this purpose was not yet well established. Japanese firms had conducted a massive amount of firm-specific investment and tried to accumulate their own technological assets in-house or inside the specific production networks it organized. However, since the 1990s, the present latecomers have enjoyed far more choices of supply for nearly the same technological sets, including Japan, Korea, and Taiwan. In addition, a massive number of technological consultancies have emerged to support latecomer firms, and packaged, standardized or modularized technology
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and “best management practices” have become extremely widespread. Particularly, the dense involvement of the indigenous firms into the global production chains led by global MNCs offered massive opportunities to abruptly upgrade their manufacturing capability. This caused China to emerge as a global manufacturing powerhouse at an unprecedentedly rapid pace.5 Due to these factors, as soon as new technology becomes available, copycats emerge rapidly to produce the same goods and sell them cheaply – “commoditization” – by massively utilizing the common technological resources outside the firms. Under a situation of technological “modularization” and the widespread use of outsourcing, firms face a severe dilemma of whether to (1) invest firm-specific technological assets in differentiation, which entails a greater risk of inadequate return to complete the depreciation, or (2) massively utilize outsourced – standardized – resources, which is less risky as an investment but does not allow the firm to differentiate itself in the long run. We may assume that the larger the number of homogeneous competitors that emerge in the same product field, the harsher the price-competition becomes – leading to firms that tend to be less profitable and unable to continue risky firm-specific investment. Though highly controversial, the technological reality of China and India is not that pessimistic but it is more dynamic.6 In fact, in the latter half of the first decade of the 2000s, highly innovative global players have emerged from China and India, on the heels of the emergence of successful Korean and Taiwanese innovators in electronics/IT-related hardware and automobiles – such as Samsung, Hyundai, LG, Acer, Mediatec, etc. A symbolic event that stands as evidence of China’s emergence as an innovative power is the fact that Huawei Technologies Co. Ltd., one of the world’s major communication-equipment manufacturers, became the largest applicant for international patents via the Patent Cooperation Treaty (PCT) in 2008.7 Although the number of patent applications is not an exact indicator of real innovative capability, it still presents a convincing case that China and India are now important producers of innovations.8 It should be noted that Huawei can be seen as an exception rather than as representative of the average mainland Chinese firm.9 In fact, on the whole, many research studies seem to be suspicious about China’s innovative capability,10 and some of them regard Indian firms as being more capable than their Chinese counterparts.11 However, the interesting questions are: how many firms in China and India will follow such indigenous front-runners, and – if followers swarm – when and in what size will they emerge? Will leading firms in a wide range of industrial sectors in the two countries become global innovators, as did Japanese firms after World War II? Or, are they likely to remain as mere exceptions in their respective countries? The authors of the chapters of this study bear in mind these questions in their analyses.
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Introduction 5
1.2.3 Catching up, the East Asian experience, and the role of the state The other methodological feature of this study is the frequent reference to East Asian “catching-up” experiences, as observed in China and India. In particular, the “state-led industrialization” or “developmentalistic state” view is adopted by several chapters. It is true that some of the premises of China’s and India’s frameworks, such as the “one-country”-oriented view, the import substitution-oriented view – localization by indigenous firms – and the large-firm-centered view, seem to be out-of-date in this age when emphasis is placed on the expression of entrepreneurship and individual talent at small and medium-sized enterprises (SMEs) or clusters,12 and on the capacity to discover and combine the innovative results that are being produced in every corner of the global production network (GPN).13 However, the states of China and India do not seem to have abandoned that development model yet. These two seem to be some of the few countries that have the potential to achieve “full-set-style” late industrialization driven by leading indigenous firms, which has been achieved in a full-fledged manner by only a few countries – such as Japan and the Soviet Union – following the major advanced Western countries. Plus, they actually seem able to maintain the will to do it. In fact, in China and India – during their economic construction – important industries and large firms have been nurtured and provided with special treatment by the government. While such measures have not functioned as successfully as in the cases of postwar Japan, Taiwan, or Korea – and while the mechanism of these malfunctions have varied between the two countries – nevertheless, the common feature is that the problems arise from a lack of capability on the part of the states – not from a lack of will. That is to say, the politico-economic foundation had not been constructed adequately to enable the central states’ efforts to work efficiently and successfully.14 In fact, it is highly probable that, as a result of the current construction of integrated national infrastructures, the pattern of the past East Asian catching-up might be pursued by China and India in a more full-fledged manner. In this respect, the different nature and role of local governments in China and India, which is the main focus of the chapters in Part III, is a critical issue that is addressed in this book.
1.3 Different industrial dynamisms: the findings of the chapters This section summarizes the findings of the chapters that comprise this book. The industries in our case studies were mainly selected to highlight the competitiveness of indigenous firms. The basic assumption is that the specific type of competitiveness is the result of a unique mix of factors and the institutions that have nurtured the firms and the industrial clusters.15 We selected the textile and motorcycle industries in this line, in which China
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and India have become the world’s largest producers and exporters, led by indigenous firms – although their advantages have been structured differently. In the automobile industry, it is not necessarily the case that firms in the two countries have achieved international competitiveness. However, since the auto industry has been the center of ongoing deliberate efforts to build indigenous capability by governments and indigenous business society, a comparative study on it will provide an excellent opportunity for an investigation to suit our purposes. Electric vehicles are also an interesting case, since through them we can observe – in departure from the assumptions of conventional late-industrializing literature, where it is assumed that developing firms “learn” the matured technology – how indigenous firms and governments try to take the lead with their innovative capability in the latest fluid technological field. A comparison of the electric hardware (manufacturing) sector – where China enjoys prominent competitiveness – and the software and business processing outsourcing (BPO) industry (service sector), where India seems to be more competitive, also provide us with insights into the factors that created such different advantages. 1.3.1
Different competition
Judging from the case studies on various industrial sectors in this book, there seem to be critical differences in the quality of competition in China and India, and this underlies, as a basic thread, all the topics in this book. The basic differences in the competitive environment and firms’ management are: 1. Numerous firms with homogeneity in China vs. great heterogeneity with large gap between the oligopolistic modernized industries and the intensely competitive traditional industries in India. 2. Volume- and low-price-oriented Chinese firms vs. profit-oriented Indian firms – mainly in modernized industries. The latter is a general image obtained from the aggregated data and individual investigations, and is considered to be the outcome of the former. The basic differences are in the competitive environment, settings and natures found in the various aspects in management style – including technological choice, profit rate, focus of competition, production size, and basic forms of organization in representative firms in various industries of the two countries (Table I.1). Some of these basic differences are supported by the statistical overview of various industrial sectors in Chapter 1. Chapter 1, by focusing on manufacturing industries, depicts the pricecompetitive nature of homogenous firms observed in various industries in China, whereas, in India, wide gaps exist between firms both within the same industry and different industries. In modernized (or capital-intensive) industries, firms generally compete in a more oligopolistic and hence nonprice-oriented way, while in traditional industries – mainly labor-intensive
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Introduction 7
Table I.1 Relative contrast of competition, management, and environments in modernized sectors China
India
Competition Number of competitors
Large
Small
Market concentration
Low
High
Low
High
Management features of representative firms Profit rate
Turnover (capital utilization) High
Low
Size of production
Small
Large
Technological capability/Skills Diversity
Homogeneous
Heterogeneous
Acquisition
Rapid Utilization/ outsourced
In-house
Investment
Standardized
Firm/transaction-specific
Dispersed
Integrated
Proximity to GPN
Densely integrated (mainly in manufacturing/East Asia, US, EU)
Less integrated (mainly in service/US, UK)
Resource endowments/ infrastructure (well-fit by)
Manufacturing
Service
Interfirm organization Macro environment
Labor market
Integrated
Segmented
Main market that drive the rapid growth
Overseas/domestic, Urban/rural
Overseas/urban
Government
Growth-oriented
Re-distributive/ balance-oriented
Note: India’s image is confined to that of “modernized” (or more capital/knowledge-intensive) industrial sectors. Indian firms are very heterogeneous when compared to China, and “traditional” sectors, typically textile or food products manufacturing sectors, and non-registered/ informal sectors may share more with Chinese counterparts than with Indian “modernized” firms in the features of competition and management.
light industries, in particular, the textile industry – the degree of pricecompetition is even harsher than in China. More importantly, the chapter reveals the underlying trend that has increased the prominence of the differences in the homogenization of technological capability among different levels of indigenous firms in China, which is the result of the rapid technological catching-up of “subordinates” (new/small/nonpublic firms) to
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0
20
40
Market 60
Competitors in China 80
17500 Top-End 10000
100
120 Foreign Brand (MNCs)
5500 3100
Middle
1750
Indigenous Brand (Superiors)
1000 Indigenous Brand (Miscellaneous/ Subordinates)
550 310 Low-End 175 100 China 2000
India 2005
Figure I.1 Structure and size of domestic market and competitors – China, 2000, and India, 2005 Note: Vertical axis=Per Capita GDP (USD), Horizontal axis=GDP (billion USD) both at current prices. 1. GDP size=the sum of GDP of about 2400 county-level administrative areas in China and about 540 district-level administrative areas in India distributed according to the level of per capita GDP of the areas (vertical axis) in 2000 (for China) and in 2005 (for India). The average per capita GDP of China in 2000, according to the data sets, was 1004 USD, ranging from the highest, Shenzhen Urban District, Guangdong, 16,200 USD, to the lowest, Qusum (Qusong) County, Tibet, 80 USD, and, of India in 2005, was 519 USD, ranging from the highest, Gurgaon District, Haryana, 4566 USD, and the lowest, Sheohar District, Bihar, 95 USD. 2. The top-end market in China is comprised by highly modernized cities like Shenzhen, Pudong of Shanghai, and Guangzhou. Middle market is comprised mainly by central cities of the provinces (such as Wuhan, Chengdu, etc), county centers of affluent areas, and newly urbanized areas in affluent coastal provinces. Low-end market is mainly comprised by the county centers of low-income districts, townships, and rural areas in low income-areas. Source: For China’s urban districts of prefecture-level cities, calculated from National Bureau of Statistics (2001), Zhongguo Chengshi Tongji Nianjian 2001 (China City Statistical Yearbook 2001), and for other county-level administrative areas, from Ministry of Finance, Government of People’s Republic of China (2001), 2000 Nian Quanguo Dishixian Caizheng Tongji Ziliao (Public Finance Statistical Data of Prefecture, Municipal, and County-Levels, Year 2000), Zhongguo Caizheng Chubanshe, and for Indian districts, Website of Planning Commission, Government of India, http://planningcommission.nic.in/plans/stateplan/index.php?state=ssphdbody.htm. Accessed on January 28, 2011.
“superiors” (old/large/state-supported firms) in domestic competition. On the other hand, in India, the firms are more heterogeneous in their capabilities. This seems to be not only the result of the efforts of top firms to accelerate the differentiation, but also the result of the weakness of “subordinates” vis-à-vis their “superiors” in the Indian industrial world. Chapter 2, by delving into the developmental process of the electronics (hardware) industry after the 1980s, supports the idea of different types of
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Introduction 9
competition. In particular, it highlights how the differences in the size and quality of the domestic market have influenced the formation of different firms and competition. If the above assumption is valid, then the next task should be to seek the reasons and factors that brought about such differences; that is, the conditions that allow the Chinese (ex-)“subordinate” firms’ rapid technological catching-up to (ex-)“superiors,” and the conditions that make their Indian counterparts more sluggish. The remaining chapters accomplish this task by using two approaches; examination of (1) the different ways of becoming technologically capable, in the country, cluster, firm, and at the individual level – mainly discussed in the chapters in Part II, and (2) the different natures of the state and GPN, which are mainly discussed in the chapters in Part III. 1.3.2 Methods of capability formation Chapters 3 and 4, using the case studies from the automobile and motorcycle industry, reveal the different inclinations in technological/skill upgrading. Chapter 3 highlights a clear difference in the methods of acquiring new product technology in indigenous automobile manufacturing – by Geely Automobile Holdings Ltd. and Chery Automobile in China and Tata Motors Limited in India – by stating that, while the former tries to acquire new model technology quickly by actively utilizing outside resources, often by bold copying and purchasing of key components, the latter tries to nurture its own proprietary technologies by strengthening its in-house R&D base. This tendency of India in modernized/capital-intensive industries to display a stronger inclination toward “firm/transaction-specific investment” and, by contrast, China’s deliberate avoidance of such investment, are also pointed out in Chapter 4. The chapter also acknowledges the differences and tries to relate these to their different attitudes toward technological capability formation. It explores their in-house resources for nurturing their own workers and their interfirm organization to secure their strategic suppliers. The chapter also points out that different sets of institutions have been formed in firms in the motorcycle industry, that is, the short-termism of management and the dispersed nature of organizations in China, and the stability-oriented management style and integrated nature in India. Chapters 5 and 6 describe the different skills distribution which has been created through different education systems and local labor market institutions over the long run, and how these differences have produced the different industrial performances. Chapter 5 clearly shows that, in China, the primary and secondary levels have been the main target of public education, and this has created rich human resources for the labor-intensive manufacturing sector that matches the basic resource endowment of the country. By contrast, in India, a more higher-education-oriented educational policy has created a more skewed skill distribution, part of which has been the basis for the development of the service sector (in particular of the software and BPO industries).
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Chapter 6 complements the above point by describing the different labor pools and labor market institutions – including firms’ in-house and external training institutions – in the textile clusters in Tamil Nadu in Southern India and Shandong in Eastern China. Interestingly, the textile industry gives us a very different picture from the one obtained in the cases of the automobile/ motorcycle industries. Chinese firms tend to formulate integrated-type inhouse organizations for skill formation, whereas clusters in Tamil Nadu utilize a more dispersed organization and arm’s-length networks. This reflects the large variety inside Indian industry along the spectrum of modernized – or capital/knowledge-intensive – and traditional – labor-intensive – light industries. The variety of the spectrum widened if gaps between formal and informal – “organized” and “unorganized” – sectors are taken into consideration. Chinese firms, on the other hand, are more homogeneous even though they belong to technologically different industries. 1.3.3 The role of government and GPN Chapter 7 clearly contrasts the different backgrounds in capacity and environment of the Chinese and Indian governments during the era of economic transformation from an agrarian society to an increasingly industrial society. The chapter analyzes the tools available to the Chinese government to promote the petrochemical fiber industry while simultaneously mitigating the decline of traditional cotton producers. By contrast, the Indian government found itself in a political environment that necessitated the perception of synthetic fiber as the enemy of cotton producers. Chapter 8 highlights the fundamentally different stances toward growth of the Chinese and Indian local governments – the former being growth-promoting and the latter being redistributive. Then, it explores the background fiscal systems that created such differences. The chapter clarifies the differences through the framework of dynamic inefficiency – whereas Indian local governments tend to be in a situation of underinvestment due to their dependency on subsidies, Chinese local governments, which are more fiscally independent, tend to seek rent, which results in overinvestment. Chapters 9 and 10 elaborate in detail on the roles of the central and local governments in fast-changing sectors. Chapter 9, by analyzing the case of the newly-emerging electric vehicle (EV) industry, demonstrates the aggressiveness and comprehensiveness of the role that the Chinese government plays in comparison with that in India – both at the central and local level – in promoting the industry in the hope that it will become a global leader in this emerging technological sector. Chapter 10, by introducing the municipal government’s promotion policies for the software/BPO industry in Dalian – one of the Chinese catcher-uppers – highlights the deliberate and aggressive roles that Chinese local governments play in the rapid catching-up process, not only in manufacturing sectors, but also in service sectors.
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Introduction 11
Chapter 11 discusses the role of GPN in cluster development. Based on the same observations as in the previous chapter, it clearly depicts the significance of the type of technology of the GPN for the clusters by identifying the different sets of technological processes and skills required for software development in Bangalore and Dalian. It also suggests the fundamental difference in the economic geographical settings of China, which has been closely integrated by networks of Japanese MNCs, and India, which is more closely connected to the US and European GPN. 1.3.4
Manufacturing in China vs. service provision in India
As for the reason for the different industrial comparative advantages in the two countries: India’s competitive position in software/BPO (hence, the service sector) and its inferior position in the manufacturing sector – while the situation is reversed in China – our basic recognition is that the two have been equipped with different sets of capabilities/skills in firms/individuals and been endowed with different institutional factors that have created them in the long run. India has not enjoyed the advantageous human resources and labor market institutions that promote the manufacturing sector as has China. India has experienced less dynamic growth of the domestic – in particular the rural – market, lack of geographical proximity to East Asian production networks, and lack of government initiatives to promote manufacturing firms such as special export-oriented zones, FDI promotion policies, and aggressive infrastructure building investments. Furthermore, the Indian government traditionally has shown a rather antagonistic attitude toward modern large-scale industries, whereas government interests and regulations overlooked the software industry – a fact which is considered to be the critical factor in explaining the development of this sector in India.16
1.4
Sources of the different dynamism
From the above findings and analysis, we confirmed that the different styles of growth of firms and clusters are the outcomes of the different socioeconomic and political settings in each country. Before proceeding to the following chapters, let me conclude this chapter by introducing the larger picture that encompasses the major domestic factors which we have discussed. The basic framework here is based on the ideas proposed by Brandt and Thun (2010) and Mazumdar and Sarkar (2008). Brandt and Thun (2010) proposed a three-layer structure in the Chinese market: top-, middle-, and low-end. According to them, at the early stage of business development in China in the 1990s, there were basic segregations: (1) foreign MNCs with technological sophistication entered the top-end market, (2) indigenous firms (mainly SOEs) with solid technology – mainly transferred from MNCs – and a good domestic reputation occupied the middle-market segment, and (3) newly-emerged indigenous firms – mainly
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smaller non-state-owned firms with a variety of brands and no accumulated technological background – cultivated the low-end segment of the market with their low-priced imitation products. However, as the middle-market segment expanded, the top MNCs began descending to the battlefield in the middle, and solid firms that successfully upgraded their capabilities also climbed from the low-end market to the middle. This has caused a very tough “fight for the middle,” which is now ongoing in present-day China. The above-mentioned status is depicted in Figure I.1. If we use the image in Figure I.1 to illustrate the Indian case, the critical difference in India when compared to China, lies in the smaller heterogeneity in income level among different segments of the domestic market17 and smaller size in each market segment. Greater heterogeneity and absolute market-segment size give Chinese firms more opportunities to compete – vice versa for India. Of particular importance are not the top-end market or the MNCs but rather the middle- and low-end markets and actors, as Mazumdar and Sarkar (2008) assert.18 In addition to the fact that the middle-market segment is smaller and less expansive in India than in China,19 the more critical implication of this study is that the low-end layers of competitors are less dynamic in India than in China.20 The reason for this lower dynamism is the sluggish pace of catching-up in the technological and managerial capabilities of firms located in the low-end category (Chapter 1). One of the critical domestic conditions that may cause this phenomenon is the degree of division in the labor market and the mobility of talent. In India, both within and between the industrial sectors and clusters, there exists a clear hierarchy of the type of capabilities that people possess and the wage levels they enjoy (Table I.2). The quality of labor in the Chinese market – even if the rural labor force is also taken into account – is more homogeneous, with the majority of workers having secondary school education or higher. That is considered to be one of the critical factors that invigorated China as a labor-intensive manufacturing base during the early stages in the 1980s and 1990s. In India, on the other hand, workers are more heterogeneous in educational background – most are “illiterate”21 (Chapter 5). At the same time, in India the smaller movement, of labor mobility from agriculture to non-agriculture – compared to China22 – seems to have prevented Indian manufacturers from choosing more labor-intensive technology. as their Chinese counterparts did. The type of mobility of human resources has also been different. Members of the worker-level workforce – less educated but critical in labor-intensive mass production manufacturing – are less mobile in India but highly so in China. However, members of the staff-level workforce (white-collar workers in administrative, sales, research, engineering, etc), who are generally more highly educated, change jobs no less frequently in India than in China (Chapter 4). Again, segmentation of the Indian labor market – especially in rural areas – seems to be one of the critical socioeconomic factors, which is complementary to the prominent industrial heterogeneity in the country when compared to China.
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Introduction 13 Table I.2 Hierarchic nature of the labor market in China and India: average monthly wage rate in various industrial clusters (2008) (US$) India Skill: expert Edu: high
IT service
China
Bangalore SE
2000
Entry level 500–700 Motorcycle parts
Skill: generic Edu: low
Textile (knitting)
Pune
PG
250
Chongqing
Staff
420
Worker
200
Coimbatore Worker
Dalian SE 800
60–80
Staff
370
Worker 210 Shandong Worker 150–180
Note: SE = system engineer, PG = programmer. Source: Interviews by the author.
Notes 1. Malenbaum (1956), Lal (1995), Huang and Khanna (2003), Nagaraj (2005), Sinha (2005), Desai (2005), Chaudhuri and Ravallion (2007), Bosworth and Collins (2008), Mukherjee and Zhang (2007), Dinello and Wang ed. (2009), Eichengreen et al., ed. (2010), etc. 2. Altenburg et al. (2008), Gregory et al. (2009), and Sato (2010) are exceptions. 3. John King, Fairbank Center for East Asian Research (1989). 4. In this sense, this work is expected to be one of the contributions that expand the cases of “variety of capitalism” discourse by applying it to China and India. See Hall and Soskice (2001) and Aoki et al. (1996). 5. Steinfeld (2004) asserts that, due to this, most Chinese firms have been left incapable in “proprietary” innovation. 6. See Altenburg et al. (2008). 7. In 2009, Huawai descended the rank to the second largest after Panasonic Corporation, and in 2010, ZTE Corporation – another Chinese indigenous communication equipment manufacturer – became the second, with Huawei having declined to fourth. 8. In the country-wise PCT ranking, China now ranks fourth in the world in terms of international patent applications, having surpassed France in 2009 and Korea in 2010. India ranks sixteenth, but it is the second after Israel in the rest of the world excluding Europe, the US and three East Asian countries (Japan, China, and Korea). The World Intellectual Property Organization (WIPO) website at http://www.wipo.int/ipstats/en/statistics/pct/. Accessed on February 28, 2011. 9. In 2010, there were 1,550 firms which submitted more than 11 applications, amounting to 100,280 applications in total via the PCT scheme. Among them, there were 40 Chinese firms (including Hong Kong), which submitted 4,595 patent applications. However, only two firms, Huawei and ZTE, submitted as much as 75% of the total Chinese applications. For comparison, Japan had 23,609 applications submitted by 314 firms, of which 31% were submitted by the top 7 firms.
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10. For example, see Steinfeld (2004) and Altenburg et al. (2008). For a more opportunistic view on China, see Sigurdson (2005) and Yusuf et al. (2007). 11. For example, Huang and Khanna (2003). Chapter 3 in this volume presents one such piece of research. 12. See Piore and Sabel (1984), Schmitz (1995), and Saxenian (2006). 13. See Gereffi (1994), Borrus et al. (2000), and Kenney and Florida (2004). 14. For China, see Segal (2003) and Thun (2006); for India, see Chibber (2003) and Sinha (2005). 15. North (1990) 16. Parthasarathy (2004). 17. The Gini coefficients calculated from the data sets used in Figure I.1 are: for China, 0.48 in 2000 and 0.50 in 2005, and for India, 0.28 in 2000 and 0.31 in 2005. China’s prefecture-level data set, consisting of about 550 samples – we obtained data on 288 “urban districts” and 266 non-“urban districts” from 275 prefecturelevel cities – and hence more comparable to India’s district-level data, also yields 0.46 in 2005 and 0.47 in 2008 – still significantly higher than in India. 18. However, the original assertion made by Mazumdar and Sarkar (2008) differs slightly and some modifications should be added. They claimed that, in India, the middle layer of firms is lacking, but the assertion of this Chapter is that this is not the case. It is not that the middle layer is lacking, but that the middle layers lack the ability to upgrade. Mazumdar and Sarkar claimed that, if we arrange the firms and their employment in order as shown in Figure 1.5 (Chapter 1), India is different from East Asian countries in that accumulation of the middle layer of firms is thin while accumulation at the two extremities – “the large” and “the small” – is thick, resulting in a “missing middle.” However, the relative shape of the layered structure changes with firm size. Mazumdar and Sarkar (2008) used the category “more than 500 persons” as the largest firm size, due probably to the limited comparability of data with Korea and Taiwan, since the census data of those two countries – which are the main source of the comparison – had been presented in that way. However, firms of more than 500 employees are not really the largest in contemporary industrial society. If we set the largest firm size as more than 5,000 or 10,000, the structural shape becomes quite similar in India and other East Asian countries – including China – with the middle being the thickest. 19. As stressed in Ravallion (2009), the degree of Chinese agricultural development in the 1980s could be critically important in explaining the gap. 20. The different levels of rural industrialization in the 1980s and 1990s, in which many “subordinate” firms emerged in China, would be the critical reason for this gap. See Mukherjee and Zhang (2007). 21. Chapter 5 also reveals that the absolute number in the Indian workforce with a higher education exceeds that of China, and this is considered to be the main source of superiority in parts of India’s service sector. 22. In India, 62% out of 24 million (2% of the total population) undertook domestic migration in 1999 from one rural area to another rural area (the main reason being marriage), while in China, 80 million (6% of the total population) undertook domestic migration in 2000 (the main reason being to seek a new job opportunity). Of these, in China, 55% moved interprovince (the equivalent administrative level in India is the state), while in India, only 10% moved across a state line. Source: For India, Institute of Applied Manpower Research (2005), p. 24; for China, Naugton (2007) p. 130.
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Introduction 15
References Acharya, Shankar, 2009, “India’s Growth: Past and Future”, in Dinello and Wang, ed., China, India and Beyond: Development Drivers and Limitations, Cheltenham: Northampton: Edward Elgar. Altenburg, Tilman, Hurbert Schmitz, and Andreas Stamm, 2008, “Breakthrough? China’s and India’s Transition from Production to Innovation”, World Development, 36 (2), pp. 325–344. Amsden, H. Alice, 1989, Asia’s Next Giant: South Korea and Late Industrialization, New York: Oxford University Press. Aoki, Masahiko, Hyung-Ki Kim and Masahiro Okuno-Fujiwara, ed., 1996, The Role of Government in East Asian Economic Development: Comparative Institutional Analysis, Oxford: Clarendon & Oxford University Press. Borrus, Michael, Dietr Ernst and Stephan Haggard, ed., 2000, International Production Networks in Asia: Rivalry or Riches? London: Routledge. Bosworth, Barry and Susan M. Collins, 2008, “Accounting for Growth: Comparing China and India”, Journal of Economic Perspectives, 22 (1), pp. 45–66. Brandt, Loren and Eric Thun, 2010, “The Fight for the Middle: Upgrading, Competition, and Industrial Development in China”, World Development, 38, pp. 1555–1574. Chaudhuri, Shubham and Martin Ravallion, 2007, “Partially Awakened Giants: Uneven Growth in China and India”, in Winter and Yusuf eds., Dancing with Giants: China, India, and the Global Economy, Washington, DC: World Bank Chibber, Vivek, 2003, Locked in Place: State-Building and Late Industrialization in India, Princeton and Oxford: Princeton University Press. Desai, Meghnad, 2005, “India and China: An Essay in Comparative Political Economy”, in Wanda Tseng and David Cowen, eds., India’s and China’s Recent Experience with Reform and Growth, New York: Palgrave Macmillan. Dinello, Natalia and Wang Shaoguang, ed., 2009, China, India and Beyond: Development Drivers and Limitations, Cheltenham: Northampton: Edward Elgar. Eichengreen, Barry, Poonam Gupta and Rajiv Kumar, ed., 2010, Emerging Giants: China and India in the World Economy, Oxford: Oxford University Press. Gereffi, Gary, 1994, “The Organization of Buyer-Driven Global Commodity Chains: How U.S. Retailers Shape Overseas Production Networks”, in Gary Gereffi and Miguel Korzeniewicz, ed., Commodity Chains and Global Capitalism, Westport, CT: Preager. Gregory, Neil, Stanley Nollen, and Stoyan Tenev, 2009, New Industries from New Places: The Emergence of Software and Hardware Industries in China and India, Palo Alto and Washington: Stanford University Press and the World Bank. Hall, Peter A. and David Soskice, eds., 2001, Varieties of Capitalism: Institutional Foundations of Comparative Advantage, New York: Oxford University Press. Hobday, Michael, 1995, Innovation in East Asia: The Challenge to Japan, Brookfield: Edward Elgar. Huang, Yasheng and Tarun Khanna, 2003, “Can India Over-take China?”, Foreign Policy, 137 (July–August), pp. 74–81. Institute of Applied Manpower Research, ed., 2005, Manpower Profile India Year book 2005, MANAK. John King Fairbank Center for East Asian Research, 1989, “Other Roots, Other Routes: China and India, Past and Present” (Conference Report), Bulletin of the American Academy of Arts and Sciences, 42 (8), pp. 7–29. Joshi, Vijay, 1998, “India’s Economic Reforms: Progress, Problems, Prospects”, Oxford Development Studies, 26 (3), pp. 333–351.
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Kenney, Martin and Richard Florida, eds, 2004, Locating Global Advantage: Industry Dynamics in the International Economy, Stanford: Stanford University Press. Lal, Deepack, 1995, “India and China: Contrasts in Economic Liberalization?”, World Development, 23 (9), pp. 1475–1494. Lall, Sanjaya, 1992, “Technological Capabilities and Industrialization”, World Development, 20 (2), pp. 165–186. Malenbaum, Wilfred, 1956, “India and China: Development Contrasts”, The Journal of Political Economy, February, No. 1, pp. 1–24. Mazumdar, Dipak and Sandip Sarkar, 2008, Globalization, Labor Markets and Inequality in India, Routledge/IDRC. Mukherjee, Anit and Xiaobo Zhang, 2007, “Rural Industrialization in China and India: Role of Policies and Institutions”, World Development, 35 (10), pp. 1621–1634. Nagaraj, R., 2005, “Industrial Growth in China and India: A Preliminary Comparison”, Economic and Political Weekly, May 21, pp. 2163–2171. Naughton, Barry, 2007, The Chinese Economy: Transition and Growth, Cambridge, MA: MIT Press. North, Douglass C., 1990, Institutions, Institutional Change and Economic Performance, Cambridge and New York: Cambridge University Press. Parthasarathy, Balaji, 2004, “India’s Silicon Valley or Silicon Valley’s India? Socially Embedding the Computer Software Industry in Bangalore”, International Journal of Urban and Regional Research, 28 (3), pp. 664–685. Ohara, Moriki, 2006, Interfirm Relations Under Late-Industrialization: The Supplier System of Motorcycle Industry, Chiba: Institute of Developing Economies. Piore, Michael and Charles F. Sabel, 1984, The Second Industrial Divide: Possibilities for Prosperity, New York: Basic Books. Ravallion, Martin, 2009, “Are There Lessons for Africa from China’s Success Against Poverty?”, World Development, 37 (2), pp. 303–313. Sato, Takahiro 2010, “External Openness and Firm Productivity in China and India: Evidence from Business Enterprises Surveys”, in Akira Uegaki and Shinichiro Tabata, eds., The Elusive Balance: Regional Powers and the Search for Sustainable Development, Slavic Research Center: Hokkaido University, pp. 83–93. Saxenian, AnnaLee, 2006, The New Argonauts: Regional Advantage in a Global Economy, Cambridge, MA: Harvard University Press. Segal, Adam, 2003, Digital Dragon: High Technology Enterprises in China, Ithaca and London: Cornell University Press. Schmitz, Hubert, 1995, “Collective Efficiency: Growth Path for Small-Scale Industry”, Journal of Development Studies, 31 (4), pp. 529–66. Sigurdson, Jon (with collaboration of Jiang Jiang, Xinxin Kong et al.), 2005, Technological Superpower China, Cheltenham: Edward Elgar. Sinha, Aseema, 2005, The Regional Roots of Developmental Politics in India: A Divided Leviathan, Bloomington and Indianapolis, IN: Indiana University Press. Steinfeld, Edward S., 2004, “China’s Shallow Integration: Networked Production and the New Challenges for Late Industrialization”, World Development, 32 (1), pp. 1971–1987. Thun, Eric, 2006, Changing Lanes in China: Foreign Direct Investment, Local Governments, and Auto Sector Development, Cambridge: New York: Cambridge University Press. Yusuf, Shahid, Kaoru Nabeshima, and Dwight H. Perkins, 2007, “China and India Reshape Global Industrial Geography”, in Winters and Yusuf ed., Dancing with Giants: China, India, and the Global Economy, Washington, DC: World Bank.
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Part I Firms and Competition
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1 Competition and Management in the Manufacturing Sector in China and India: A Statistical Overview Moriki Ohara and Hong Lin
The per capita GDP of China and India remained almost the same until 1990, when it stood at USD388 for India and USD343 for China. However, the pace of increase subsequently widened significantly, leading to a gap in the average annual growth of the per capita GDPs during the period from 1990 to 2008, when it grew by 13.3% for China and 5.5% for India. As a result, in 2008, per capita GDP in China was USD3,266, three times more than India’s, which was USD1,017. As far as GDP growth is concerned, China seems to follow the path of its East Asian antecessors, Taiwan and Korea, in a 25-year time lag, whereas India does not seem to have entered into such a trajectory of high economic growth. We assume that the main source of the growth gap between China and India stems from the paths of their industrial development, in particular in the manufacturing sector. This chapter presents an overview of the aggregated and firm-level statistical data on the manufacturing sector of these countries in order to highlight the differences, on average, between manufacturers in China and India related to competition and management, that is, (1) in firm management, “volume-oriented” Chinese firms vs. “profit-oriented” Indian firms and (2) in competitive environments, numerous homogenous firms in China vs. heterogeneous firms with large gaps between oligopolistic modernized industries and intensely competitive traditional industries in India. Then, we attempt to relate the gap to the fundamental differences in the conditions of their economic growth after the 1980s, that is, the pace of homogenization of technological capability among manufacturers. The basic assertion of this chapter is that the basis of such differences has been created by the labor-intensive nature and rapid technological “catching-up” by “subordinates” to “superiors” among Chinese manufacturers, and lingering heterogeneity of Indian firms where the gap between capital-intensive and labor-intensive firms, in both the inter- and intra-industrial categories, remains very large.
19
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1.1
Macroeconomic overview of manufacturing development
1.1.1 East Asian pattern: labor-intensive manufacturing as initial driver of upgrading It was the manufacturing sector that drove the rapid economic growth in East Asian economies. Figure 1.1 shows the change in the manufacturing sector’s share in the total labor force (manufacturing labor ratio) in China, India, and several other East Asian economies in addition to China. In the other East Asian economies, the ratio has been nearly identical to the ratio of the manufacturing sector in GDP (manufacturing GDP ratio). In their peak year, manufacturing employees, who amounted to 28% of total employment, produced 37% of the GDP in Japan (1970), 32% produced 36% in Taiwan (1980), and 27% produced 32% in Korea (1985). It should be noted that the years around the peak of the ratio coincide with the rapid economic growth period (of average annual GDP growth around 10%) in the countries; for Japan, this period was from the late 1950s to the early 1970s, and for Korea and Taiwan, from the late 1960s to the early 1990s. This indicates that, in East Asian economies, the expansion of the labor-intensive manufacturing sector initiated the rapid economic growth, with the ratio reaching its peak in the latter half of the rapid growth period. Then, after the disappearance of the abundant labor pool, the upsurge in the wage rate brought about the rise of the capital-intensive (and further subsequent knowledge-intensive) sector as the next leading sector, which slowed the growth rate and, at the same time, decreased the income gap among workers as a whole.1 1.1.2
China’s manufacturing sector vs. India’s service sector
The manufacturing sector in China and the service sector in India are the driving sectors of the growth in these countries, not only quantitatively but also in terms of productivity. Bosworth and Collins (2008) calculated the per capita productivity growth during 1983–1993 (Period I) and 1994–2004 (Period II), and found that (1) for both periods, China’s productivity increase was higher than India’s, (2) for both China and India, higher productivity growth was experienced in Period II than in Period I, and (3) secondary industry was the largest contributor to productivity growth in China, while it was the tertiary industry in India.2 The most prominent cases that highlight the differences in industrial competitiveness are software and BPO services in India and electronics and IT-related hardware manufacturing in China.3 1.1.3 Potential “labor-intensive” nature Contrary to the East Asian economies, the manufacturing labor ratio has not increased significantly in either China or India, which indicates the immense difficulty of absorbing the huge absolute number of agricultural laborers by the manufacturing sector in the two countries.
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Competition and Management in Manufacturing Sector
21
40
2.8 mill 35 30
13.8mill
4.4 mill India
25
China 20
86.2 mill 80.4 mill 95.2 mill
0.6 mill 15
Taiwan Korea Japan
10
39.3 mill 5
46.0 mill 37.7 mill 2005
2000
1995
1991
1987
1983
1978
1973
1970
1965
1960
1955
0
Figure 1.1 Ratio of the manufacturing sector in total employment (%) Note: The figures beside the dots are the numbers in manufacturing employment in millions for each country. The figure for China in 2005 is based on the author’s estimation calculated from China’s official statistics on secondary industry employment size. Source: MPI, JSYB, MSKE, TSDB, CSY, various years.
The interesting difference between China and India is that, while in India, as in the other East Asian economies, the manufacturing labor ratio has been broadly identical to the manufacturing GDP ratio, China’s manufacturing GDP ratio has always far exceeded the manufacturing labor ratio. In the case of China, the manufacturing GDP ratio reached 30% as early as the 1960s. China’s high ratio before the start of economic reform in the late 1970s was a result of the artificial emphasis on the construction of heavy industry in the planned economy era.4 The manufacturing GDP ratio declined shortly after the reform began, reflecting the real comparative advantage of the country, but later it rose to a level equivalent to the peak level of Taiwan and Japan during the 2000s. In 2008, manufacturing employees, who occupied 14% of total employment, produced as much as 34% of the GDP, while agricultural employees, who amounted to 40% of total employment, produced only 10% of the GDP.
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Moriki Ohara and Hong Lin 9 China (secondary) 8 7 6
India (tertiary)
Japan (manufacturing)
5
China (tertiary) India (secondary)
4 3 Japan (tertiary)
2 1 0
1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2008 Figure 1.2 Productivity gap between agricultural and nonagricultural industries (Par employee GDP of manufacturing/secondary and tertiary industries when that of primary industry =1 in each country) Source: JSYB, CSY, ADB Key Indicators 2010 (for India).
This reveals the existence of a large gap in productivity, and hence, in the wage level between the manufacturing and agricultural sectors. Figure 1.2 shows the productivity gap between the agriculture and industrial sectors, which has been higher since the planned economy era and widened greatly after the mid-1980s. This is considered to be due partly to the extremely and continuously low productivity in the agricultural sector and partly to the upsurge of productivity in the industrial sector. The productivity growth in the service (tertiary) sector has been less prominent. This is one of the most critical factors that brings about the lingering highly labor-intensive nature of China. By contrast, in India – where 12% of total employment produced 15% of GDP in the manufacturing sector in 2005 – manufacturing does not seem to be the main driver of economic growth. It is the service sector that constitutes the largest share of Indian GDP, with service workers – who make up 23% of the labor force – producing around 50% of the GDP in 2005. Agrarian workers, who comprise 60% of the labor force, only produced 21% of GDP that year. These figures imply that the East Asian pattern of socioeconomic transformation driven by a labor-intensive manufacturing sector is difficult to
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accomplish in super-populous agrarian countries due to the fact that it is extremely difficult for the manufacturing sector by itself to absorb large numbers of agrarian laborers. In India, no sign of such a transformation can be observed (Islam 2009). The long-term existence of a low-productivity agrarian population and the consequent large wage gap between agriculture and other sectors have provided a continuous source of low-wage workers, and hence, the lingering existence of labor-intensive manufacturing in such countries. The wage gap, which is partly due to the institutional segmentation of the labor market and partly due to the far better productivity of the globalized manufacturing sector – which produced high earnings via massive exports –, seems to be even larger in China than in India.
1.2
Competition and management
The following section will present an overview of the degree of competition and several important aspects regarding management of firms. Table 1.1 shows the number of firms that participate in the competition in various product segments and the share of top firms (the top 3, 5, or 10, depending on the industry). According to this table, in most of the product fields, China has a higher number of firms and the share of the top firms in the market is smaller. In the service sector, the software development service sector also displays the same phenomenon. As discussed in Chapter 10, a higher concentration of market share among the huge top firms can be observed in the Indian software and BPO industry, whereas there is no sign of such a trend in that sector in China. We may assume that, in the dispersed market, firms tend to rush into “price competition,” whereas in the oligopolistic market, they tend to maintain “qualitative competition,” since they have more control of prices and distribute more resources to improvements in the non-price aspects. The more homogeneous the firms are in the same segment, the harsher the pressure that pushes firms into “price competition.” This assumption seems to hold when we contrast and compare the two countries. In the following sections of this chapter, using basic official industry data, we will examine the number of firms (participants in competition) and the degree of homogeneity of technology among firms in China and India. The data used here is, for China, Industrial Enterprise Data (IED)5 which is collected by the National Bureau of Statistics (NBS) of the Government of China, and for India, Annual Survey of Industries (ASI) Data which is managed by the Ministry of Statistics and Programme Implementation (MSPI) of the Government of India.6 There were some changes in the policy for collection and categorization of both IED and ASI Data. IED before 1997 includes the data of “all independent accounting industrial enterprises” and does not
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Table 1.1 Concentration of market share and the number of firms producing various products
Apparel Shoes Cotton fabric Cotton yarn Steel Valves Machine tools
top 10 top 10 top 10 top 10 top 3 top 10 top 5
Storage battery
top 3
Air conditioners
top 3
Refrigerators
top 3
TV sets
top 3
Passengers cars
top 3
Motorcycles
top 3
Software
top 5
Share (%)
No. of firms observed
40.3
466
China
6.8
6130
India
23.7
116
China
3.6
443
India
37.0
772
China
11.0
1320
India
18.0
772
China
12.3
1441
India
50.4
410
China
16.4
1848
India
61.0
93
India
China
15.8
518
India
46.2
183
China
22.6
358
India
78.0
16
China
18.0
239
India
48.2
40
China
26.5
195
India
60.0
12
China
68.0
96
India
55.5
54
China
28.4
179
India
79.0
13
China
70.2
16
India
86.0
8
China
21.0
233
India
56.2
628
China
na
na
Note: Number of firms and share refers only to the ones that were observed by CMY and IMSS Source: CMY (China), IMSS (India).
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include massive numbers of individually- or privately-owned, whereas after 1998, it contains “all state-owned enterprises and non-state enterprises with a certain sales level” in the industrial sector. At present, “a certain level” is 5 million RMB (Chinese Yuan, equivalent to 750,000 USD at the 2010 exchange rate). This means that, as time passes (and as the average size of sales per firm increases), the number of firms covered by the statistics also will increase. IED only covers industrial enterprises, and it does not include service sector enterprises. In 2007, IED covered about 60% of total manufacturing employment in China.7 ASI Data includes firms registered under the Factory Law, hiring more than 20 employees without power tools or more than 10 employees with power tools. IED is company-based data, whereas ASI is factory (unit)-based data. As for the coverage, ASI only covers about 16% of the estimated total manufacturing employment in India.8 This means that, if the estimation of total employment size is correct and if the majority of the units that employ more than 20 workers (or 10 workers with power tools) are actually covered by ASI, the Indian manufacturing sector is composed of an overwhelmingly large number of micro-firms/individual business units, at about 80% of the total, and a far smaller number of modernized firms that are covered by ASI. If this holds, the image of Indian industry that this chapter presents is confined to that of the fairly modernized manufacturing sector. Though the original ASI covers the service sectors as well, for purposes of comparison with IED, this section only analyzes the manufacturing sector. The “manufacturing sector” here can be divided into eight sub-industries – food products, textile products, paper/woods/leather-related products, chemical products (including petrochemicals), non-metal/construction material products, metal (including non-ferrous) products, machinery products, electronics and precision machinery products, and transportation equipment products.9 1.2.1 Number of firms and entry into competition The basic factors that caused the aforementioned differences in the nature of competition between the two countries are the absolute size of firms – including the number of employees – and changes in their numbers. Generally speaking, we can say that new entries into the competition were more frequent in the modernized manufacturing sector in China than in India. However, looking at the likelihood of creation of totally new firms, we cannot find any clear difference between the two countries. In fact, India experienced a massive amount of new entries by firms especially during the 1970s and 1980s which was not significantly smaller than that in China. 1.2.1.1 Number of firms and employees The long-term changes in the number of firms and employees in various manufacturing sectors evince the transformation of industrial structure and the changes in comparative advantage and competitive environments.
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According to IED and ASI, the number of modernized manufacturing firms in China is far larger than in India. Firms in the manufacturing sector in China totaled 400,000 in the late 1990s and 300,000 in 2007,10 whereas in India, the figure was 140,000 in 2007. Looking at other 2007 figures, in the textile industry, India had 18,000 firms and China 42,000 firms; in transportation equipment, India had 5,000 and China 15,000; and in the electronics industry India had 7,000 and China 35,000. While the gap at present seems natural since China’s GDP is quadruple the size of India’s, it should be noted that, in 1985, when their GDP size was almost identical, China already had 3.5 times the number of manufacturing firms in India (320,000 in China and 90,000 in India). Though we cannot compare the figures directly due to different methods of coverage in the two countries – particularly because Indian data does not include the huge number of tiny “unregistered” firms, though Chinese data does not either but to a lesser extent – we still can affirm that, as far as the modernized manufacturers are concerned, China always has had a larger number of firms than India, even in the period when China was as impoverished as India.11 The composition of industry also differs greatly. Indian manufacturing is characterized by light industry sectors such as textiles and food products – the two sectors occupy half of total employment. In China, these two light industry sectors composed 30% in the 1980s but decreased to 20% in the 2000s. China has been characterized more by heavy industrial sectors. The machinery sector comprised 20% of manufacturing employment until the 1990s, and after the 2000s, the share of electronics employment increased, reaching 17% in 2007. In India, the share of electronics employment is quite small since it only employs 500,000 persons, whereas China employs 12 million persons in the industry. 1.2.1.2 Change in the numbers: new entry and adjustment The increase in the number of firms can be considered as representing “new entries” into the industry. From this, we can confirm that both India and China had active new entries, and we cannot clearly determine in which country new entries were more active. After 1998, the statistical figures of firms and employees in China swelled greatly; however, as stated above, this is considered to be due mainly to the effect of increased statistical coverage caused by the growth of formerly smaller firms, not purely by the emergence of new firms. We can observe the economic fluctuations caused by the trends in firms’ entry as well. In India, the number of firms continuously increased during the period from the 1970s to the mid-1990s, but in the mid-1980s, there was an absolute decrease in total employment. This decrease in employment was mainly due to the restructuring of the light industry sector, especially textiles and food products, and employment continued to increase in other sectors. This means that, in the manufacturing sector, firms had significant
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levels of freedom to start a business before the launch of the liberalization policy.12 However, from 1998 to 2003, they experienced a decline in both the number of firms and employment in all the subsectors. This period is called the “jobless growth”13 period. In the case of China, we also can observe serious reorganization of the manufacturing sector, which happened during the early 1990s. While the total employment size declined, but the total number of firms remained steady. The sectors that experienced an absolute decline then were textiles, food products, and machinery. The most severely hit were the publicly–owned sectors. The other new sectors were not hit so severely even during this time. 1.2.2 Management: firm size, profitability, and efficiency in investment Below, indicators that give a general idea of firms’ management are introduced. On the whole, we can observe a contrast between “heavy usage of labor-intensive technology” and “low-profit, high-turnover” orientations in China’s management, and “high-profit, low-turnover” orientations in India’s modern manufacturing sector. Such differences were prominent in the 1980s and 1990s; however, the gap seems to have narrowed recently. 1.2.2.1 Firm size Table 1.2 shows the relative average size of per firm employment and sales value14 (calculated in US dollars). According to the table, in 1985, the average Chinese firm employed 1.6 to 4 times more employees, but their sales value was smaller than their Indian counterparts in many subsectors. Chinese firms on average increased their size remarkably during the 1990s and 2000s. In 2003, though Chinese firms employed 3 to 6 times more employees than Indian firms, they only earned 1.6 to 5 times the sales. This means that the basic orientation of management at Chinese manufacturers, “hiring larger number of employees, earning smaller value,” and the technological nature of their labor intensiveness remained the same until recently. 1.2.2.2 Profitability and turnover ratio Another trait of Chinese firms is “low-profit, high turnover,” compared to their Indian counterparts. Table 1.2 also shows an apparent lower profit rate in Chinese manufacturing sectors from the 1980s until recently, whereas Indian firms enjoy a fairly high and stable profit rate (though there is a longterm downtrend). According to Figure 1.3, the average turnover ratio of capital (value-added produced divided by fixed assets utilized) in the manufacturing sector has always been higher in China than in India. This suggests that Chinese firms always use capital equipment more efficiently than their Indian counterparts, which is probably due to China’s more intense input of labor to the capital – for example, running the machines longer by inputting multiple
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1.0 0.8
0.8 1.2 0.8 0.6 0.7 0.9 1.1 305 245
76 251 108 211 137 203 241
C
145 86
50 111 45 70 50 63 58
I
2.1 2.8
1.5 2.3 2.4 3.0 2.7 3.2 4.2
(rate)a
No. of emp. (persons)
14.9 16.4
7.1 7.9 10.9 12.7 13.1 14.3 14.4
C
18.1 19.6
10.0 13.7 13.3 12.0 18.7 12.6 21.8
I
Profit rate
4.9 1.9
3.9 3.0 4.6 1.6 4.7 2.8 3.3
(rate)a
Sales
377 325
193 321 240 237 244 310 248
C
Source: For China, CIEY, for India in 1985, NASI, and India in 2003, MSPI.
Notes C = China, I = India. a (Rate) = Value of China/Value of India for both sales and number of employment. b Profit rate in the box for 2003 is substituted by that of 2001 (due to the availability of Indian figures).
Transportation equip. Electronics/precision mach.
Machinery/electrical
Chemicals/petrochemicals Non-metal/const. mat. Metal/steel
Textiles Paper/wood/leather etc.
(rate)a
Sales
1985
103 67
66 98 40 60 38 56 45
I
3.7 4.9
2.9 3.3 5.9 3.9 6.3 5.5 5.5
(rate)a
No. of emp. (persons)
2003
5.7 3.7
3.4 3.2 4.1 3.0 2.9 3.1 3.3
C
14.8 12.1
8.6 8.5 11.1 10.3 15.4 6.3 16.5
I
Profit rate b (’01)
Size comparison of Chinese and Indian manufacturers (per firm (unit) sales and employment – persons, %)
Food products
Table 1.2
Competition and Management in Manufacturing Sector
29
140 120 100 80
India
60
China
40 20
1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1998 2000 2002 2004 2006
0
Figure 1.3 Turnover ratio, manufacturing sector in China and India – value added/ fixed assets, %, current price in local currency Note: For China, we used “net output value” for 1981–1992, and “value-added” for 1994–2006. Source: For China, CIEY, for India up to 1997, NASI, and for 1998–2007, MSPI.
shifts of workers. At the same time, China experienced a prominent upsurge in the ratio starting from the late 1990s. This strongly suggests that China increased the productivity level by further intensifying the usage of capital, either by technological sophistication or by more labor input. Contravening the conventional image of the source of the Chinese economy’s growth, which has been described as “investment-driven growth,” the investment ratio of Chinese manufacturing firms has not been significantly higher than that of India. Including the serious economic stagnation period during the mid-1990s to early 2000s, there has been no significant gap in the average investment ratios of modernized Indian and Chinese manufacturing firms.15 1.2.3 Labor-intensive technology: capital-labor (KL) ratio To examine the technological differences between the manufacturing sectors in China and India, we examine the change in the capital-labor ratio (KL ratio) from the 1980s to the present (Figure 1.4). Though not shown here, the ratios in various subsectors – including textiles, chemicals, metals, automobiles, IT and electronics-related, machinery, and so on – also follow similar paths in each country. Examination of the change in the KL ratio in various manufacturing subsectors in Japan, Taiwan, and Korea reveals that Taiwanese and Korean firms boosted their KL ratio up to the Japanese level with only a few years’ time
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Moriki Ohara and Hong Lin
100
India China Korea Taiwan Japan
10
1961 1964 1967 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 1999 2002 2005 2007
1
Figure 1.4 Changes in the capital–labor ratio in Asian economies (Manufacturing sector, nominal, USD 1,000) Source: For China and India, CIEY, NASI, MSPI, for Japan, Japan Census, for Taiwan, Taiwan Census, for Korea, Korea Census.
lag behind Japan. This represents a typical case of “catching up.” Compared to these economies, the rise of the KL ratio at Chinese and Indian firms has been slow. It is not proper to say that the manufacturing sectors of the two countries have continued catching up with the three aforementioned other East Asian economies, but rather we should say that the two belong to a different world of technological competition than those three East Asian antecessors. In particular, China followed a rather unique path in comparison to India. While Indian firms have raised their KL ratios steadily from the 1980s up to now, in contrast, China reduced their ratios (in nominal US dollars) for 15 years, from the 1980s until the mid-1990s,16 in various subsectors and then increased their ratios rapidly from the mid-1990s to the present day. Both Chinese and Indian manufacturers have upgraded their technological capability on the basis of the fundamental characteristics of their laborabundant economies. However, comparatively speaking, for most of the reform period after the 1980s, the average Chinese firm has chosen more labor-intensive technology than its average Indian counterpart, which we consider reflects their stronger adaptability and flexibility to changes in resource endowments, in particular in human resources.
1.3
Technological homogeneity among firms
This section attempts to examine the technological homogeneity (or heterogeneity) among firms as the critical factor that caused the differences
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between the two countries observed in the previous sections. The basic assumption is that, the more homogeneous the capability of firms in competition is, the harsher the price competition will be among them. As an indicator of technological capability, we use the KL ratio again, and we examine the difference between firms of different sizes. The underlying assumption is that the more smoothly the “subordinate” firms of, at first, inferior capability can catch up by upgrading their capability, with those of superior capability – which means that they become homogeneous – the harsher the competition becomes, as observed in China and vice versa in India. In addition, to exemplify how smooth the upgrading of technological capability by “subordinates” was in China, the degree of retention of engineers – the engineer ratio – will be examined. 1.3.1 Capital-labor ratio Figure 1.5 shows the number of firms according to employment size in the manufacturing sector (total) in China and India in 2005,17 and Figure 1.6 is the average KL ratio of the firms in each category of employment size. What is noteworthy here is that the KL gap between large and small firms is larger in India and smaller in China. This phenomenon is also true for each subsector in the manufacturing industry. Figure 1.7 presents (1) the largest, (2) the average, and (3) the smallest KL ratios from various sizes of firms in the subsectors. In many subsectors, the gap between “the largest” and “the smallest” is bigger in India than China. At the same time, in the most capital-intensive subsector – the petrochemical industry – the average KL ratio is far larger in India than in China, and in the most labor-intensive subsector – apparels – the average KL ratio is far smaller in India than in China. This means that firms are more homogeneous technology-wise in China – and heterogeneous in India – both within the same subsector and between different subsectors. 1.3.2 Homogenization of technological capability: the automobile sector The East Asian experience shows that there is a tendency wherein, as the industry as a whole upgrades its technological level during the course of industrialization, homogeneity among firms increases in terms of their technological capability. Figure 1.8 compares the changing technology gaps between large and smaller firms in the automobile industry in China, India, and the three other East Asian economies, from the 1960s to the 1990s.18 This figure shows that, in the most advanced economy, Japan, the KL level is the most homogeneous. In Korea and Taiwan, the ratio became homogeneous after the 1960s. In China, the KL level was already fairly homogeneous in the 1990s – as in the other East Asian economies. In particular, the gap between large and very small firms – 50 to 99 employees – was even smaller than in the case of Japan. As far as the automobile subsector is concerned,
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India
>100,000
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Figure 1.5 Employment structure by firm size: manufacturing sector (2005) Note: vertical axis: the par firm’s employment size, persons; horizontal axis: the number of employees, million persons. Source: Calculated from Oriana for China and from ASI for India.
China
India
>100,000 50,000–99,999 10,000–49,999 5,000–9,999 1,000–4999 500–999 100–499 50–99
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49> 0
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Figure 1.6 Average KL ratio of different-sized firms: manufacturing sector (2005) Note: vertical axis: the par firm’s employment size, persons; horizontal axis: KL ratio, USD1,000. Source: Same as Figure 1.5.
technological capability has been as homogeneous in China as in other aforementioned East Asian economies, whereas it remains fairly heterogeneous in India. The important point to be noted here is that, in China, the KL (technology) gap between large and small firms had already become smaller and nearly
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Figure 1.7 Different KL ratios within and between subsectors of the manufacturing industry – USD1,000 Note: The figures beside the bars show the gap between the largest and smallest in the country’s industries: the value of the largest/the value of the smallest. Source: For China, Oriana, for India, ASI.
reached the level of the other East Asian economies in the late 1990s, when its total KL ratio started to increase rapidly, as we have seen in Figure 1.4. 1.3.3 Catching up in the retention of engineers To supplement the evidence that verifies the smooth technological catching up of subordinate firms to superior firms in China during the 1990s, the data on changes in the ratio of engineers out of total employment – the “engineer ratio” – in the Chinese automobile industry will be introduced – since this kind of statistical data is only available for the Chinese automobile industry. There was a wide gap in the engineer ratio in various categories of employment size in the mid-1980s (Figure 1.9).19 However, as Figure 1.9 illustrates, the positive correlation between the size of the firm and the “engineer ratio” disappeared until the late 1990s, and it even became negative after 2000. The apparent gap in the “engineer ratio” between Superiors and Subordinates – or large and small – smoothly narrowed during the 1980s and the early 1990s and then mostly disappeared when the total KL ratio began to rise in the mid-1990s.
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0.6
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Figure 1.8 Technological gap between firms of different sizes, automobile industry – expressed as KL ratio Note: See Note 18 in the text. Source: For China in 1985, China 1985 Auto Census, in 2005, Oriana; for India, ASI; for Japan, Japan Census; for Taiwan, Taiwan Census; for Korea, Korea Census.
1.4 Conclusion From statistical data, we have confirmed the existence of different orientations in the development paths and in the management of firms in the modernized manufacturing sectors in China and India. Regarding the average firm’s management style, we observe two attitudes: “volume-oriented” (China) vs. “profit-oriented” (India). Regarding the basic competitive environment, we observe “harsh price competition among numerous homogenous firms” in various industries (China) vs. “less-harsher competition among heterogeneous firms” (India). We may attribute the gap to the different conditions of their economic growth after the 1980s, in particular, to the different directions of technological choice (labor/capital-intensity) and the pace of homogenization of technological capability among manufacturers. The reason why we witnessed harsh price competition with low profitability among numerous firms in China in the 1990s may be attributable to their highly homogeneous nature20, featuring labor-intensive technology. The main reason is the rapid catching-up (homogenization) of “subordinates” to “superiors” while retaining high labor intensity as a whole during the 1990s in China. This inclination toward price competition remained following the upgrade of their technological capability after 2000. By contrast, Indian firms have existed in a competitive environment characterized more by heterogeneity rather than homogeneity in terms of the technological capability of firms, and the number of firms has been relatively limited in capital-intensive sectors, so that competitive pressure has been relatively weak. That is considered to be the reason for their higher, more stable profitability, which probably has enabled them to
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Figure 1.9 Correlation between firm size and engineer ratio Note: vertical axis: engineer ratio, %; horizontal axis: Firm size in number of employees. Source: CAIY various years.
steadily invest in their technological development but has left us with the impression of less dynamism.
Notes 1. This broadly reflects the time when the societies went beyond the “Lewisian Turning Point” enjoying “growth with equity” in East Asia. 2. In Period I, annual per worker productivity increased on average by 6.4% in China and 2.4% in India, out of which secondary and tertiary industry constituted, respectively, 2.4% and 1.1% in China, and 0.5% and 0.7% in India. In Period II, within the overall growth rate of 8.6% in China, secondary industry made up 5.0% and tertiary industry 1.7%, while out of 4.7% in India, secondary was 0.9% and tertiary was 2.1%. 3. Gregory, Nollen, and Tenev (2009) introduce a clear contrast between China’s strength in hardware manufacturing and India’s in software services in the IT industry.
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4. See Naughton (2007). 5. IED was accessed, for aggregated industry data, from CIEY, and, for firm-level samples of 2005, from Oriana of Bureau Van Dijk (which contains approximately 300,000 firms). The original data of Oriana is considered to be the same as IED. 6. Aggregated industry data of ASI was accessed, for figures up to 1997, from NASI, and for 1998–2007, from the website of MSPI. For 2000 and 2005, we utilized the firm-level sample data (approximately 10,000 samples) purchased from MSPI. 7. In 2002, total manufacturing employment was 83 million (CSY 2008) and the amount of employment covered by IED is 45 million (54% of total). 8. Out of 51 million persons engaged in the manufacturing sector as indicated by the census in 2002 (MPI 2005), 8 million (16%) are covered by ASI. 9. Data categorized in NAICS Code 313–339 (for China) and NIC Code15–35 (for India) was reorganized by the author. Data categorized as “miscellaneous” or “others” is excluded. 10. As stated above, the figures cannot be compared directly since their coverage significantly differs between before and after 1997–1998. 11. This means that the average size of the Chinese firms used to be smaller than modernized Indian firms. In fact, up until the 1990s, it was always lamented in China that the fundamental problem of Chinese firms was that they were “small, dispersed, disordered, and technologically inferior (xiao, san, luan, cha).” 12. Rodrik and Subramanian (2005) assert that productivity growth started to rise in the 1980s, before the start of liberalization policies. They say that, at that time, the government’s attitude toward business society was to support incumbents (“pro-business”), rather than to support new entrants (“pro-market”). The productivity growth then was the result of these policies. 13. See Raveendran and Kannan (2009). 14. “Rate” in the table signifies the relative size calculated by dividing the value of China by the value of India. 15. Based on the calculation using IED and ASI, the investment ratio – the increase of fixed capital from year N-1 to year N/value added in year N, nominal – of the manufacturing sector was, from 1985 to 1997, around 22% in China and 30% in India, for 1998–2002, around 12% in China and 11% in India, for 2003–2007, around 25% in China and 22% in India. On the other hand, the macro-level investment ratio in the Chinese economy has always been higher than in India, with the Chinese ratio of capital formation in GDP changing from 32% in 1980 to 45% in 2008, versus India’s at 18% in 1980 and 33% in 2007. This gap may suggest the fact that the high investment ratio in the Chinese overall economy is the result of high investment in infrastructure construction rather than in manufacturing firms. For example, among the three subsectors that comprise the “industry” sector, the investment ratio of the manufacturing sector was in the range of 8% to 16% during 1998 to 2006, while that of the energy/water/gas supply sector was 70% to 90% and that of the extraction of oil/coal/other minerals sector was 14% to 21% during the same period (calculated from CIEY). Various levels of governments are considered to have played significant roles in this high investment ratio in China. 16. The decline in China’s KL ratio expressed in US dollars (nominal) from 1981 to 1994, shown in Figure 4, can partly be explained by exchange rate fluctuations. During the 12 years from 1981 to 1993, the Chinese Yuan (RMB) depreciated 3.4 times against the US dollar – from 1.7 RMB to 5.8 RMB per US dollar. In RMB (nominal), the KL ratio increased 4.3 times between 1981 and 1994, from 4,800
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18.
19. 20.
37
RMB to 20,000 RMB. Obviously, no absolute decline took place in the Chinese KL ratio in the nominal local currency. However, during the same period, the Indian Rupee (INR) also experienced almost the same rate of depreciation, at 3.5 times – from 8.7 INR to 30.6 INR per US dollar – while India still steadily increased its KL ratio in terms of the US dollar during the period. China and India also experienced an almost identical trend in their price indexes for the period – the fixed asset price deflator for China increased 284% between 1981 and 1994, and in India the machinery price index increased 283%. Korea also experienced a depreciation of the won of 1.6 times – from 304 won to 484 won per US dollar – but rapidly increased its KL ratio in terms of the US dollar. Therefore, we cannot attribute China’s sluggish KL ratio from the 1980s to the mid-1990s only to the depreciation of the Chinese currency. According to this figure, the firms whose employment size is 100 to 500 and 1,000 to 5,000 persons are the largest layers that absorb the most labor in both countries. In this sense, there is no big difference in the basic structure of the employment hierarchy between the two – see Mazumdar and Sarkar (2008) and note 15 of the Introduction to this book. The major difference observed from this figure is that, in China, there exist numbers of superlarge firms employing more than 500,000 persons. This difference might be caused by the difference in data collection; Chinese data is enterprise-based whereas Indian data is unit (factory)-based – though superlarge firms also exist in India, such as Tata Motors, and appear in ASI data as a unit. In China’s figures, the layers of the smallest employment size, 50 to 99 persons and “less than 49,” are fairly thin. This is again due to the method of coverage which was explained above, and ASI also suffers the same problem. However, since this paper mainly deals with firms with modernized technologies and management, this point is not a very serious problem. Since the statistics of Korea and Taiwan do not distinguish between the firms whose size is more than 500 persons – meaning that the size category “more than 500” is largest in their statistics –, in order to make a comparison with Korea and Taiwan, we used the value of the firm size “more than 500” as the standard (=1), Figure 1.8(1). For larger firms, we used “more than 5,000” as the standard for Japan, China, and India – because of the data availability – and compared firms of the size 500 to 999 – Figure 1.8(2). This statistic is calculated from data on 600 firms obtained from China’s 1985 Auto Census. Figure in Bloom and Reenen (2010) also point out the highly homogeneous nature in the management practices among Chinese firms compared to their Indian counterparts.
References Bloom, Nicholas and John Van Reenen, 2010, “Why Do Management Practices Differ across Firms and Countries?” Journal of Economic Perspectives, 24 (1), pp. 203–224. Bosworth, Barry and Susan M. Collins, 2008, “Accounting for Growth: Comparing China and India”, Journal of Economic Perspectives, 22 (1), pp. 45–66. Gregory, Neil, Stanley Nollen, and Stoyan Tenev, 2009, New Industries from New Places: The Emergence of Software and Hardware Industries in China and India, Palo Alto and Washington: Stanford University Press and the World Bank. Islam, Rizwanul, 2009, “Has Development and Employment through Labor-Intensive Industrialization Become History?”, in Kaushik Basu and Ravi Kanbur, ed.,
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Arguments for a Better World: Essays in honor of Amartya Sen, II, Society, Institution, and Development, Oxford: Oxford University Press. Mazumdar, Dipak and Sandip Sarkar, 2008, Globalization, Labor Markets and Inequality in India, Routledge/IDRC. Naughton, Barry, 2007, The Chinese Economy: Transition and Growth, Cambridge, MA: MIT Press. Rodrik, Dani and Arvind Subramanian, 2004, “From ‘Hindu Growth’ to Productivity Surge: The Mystery of the Indian Growth Transition”, IMF Working Paper, WP/04/77, http://www.imf.org/external/pubs/ft/wp/2004/wp0477.pdf
Statistics China CAIY: Zhongguo Qiche Jishu Yanjiu Zhongxin and Zhongguo Qiche Gongye Xiehui (China Automotive Technology Institute and Chinese Association of Automotive Industry) ed., China Automotive Industry Yearbook, various years. China 1985 Auto Census: Zhongguo Qiche Gongye Lianhehui Gongye Pucha Lingdaoxiaozu Bangongshi, ed., 1988, Qiche Gongye 1985 nian Gongye Pucha Ziliao Huibian, (Internal Material: Office of Industrial Census Leader’s Group, China Automobile League, ed., Automobile Industry 1985 Industrial Census Materials). CIEY: National Bureau of Statistics of China, China Industrial Economic Yearbook. CMY: All China Market Research Co., Ltd., China Market Yearbook 2001 (Report on 500 Markets), Foreign Language Press, 2001. CSY: National Bureau of Statistics of China, China Statistical Yearbook. Oriana: Bureau Van Dijk, Oriana (Data Base of China’s Industrial Enterprises for 2005).
India STI: Central Statistical Organization, Ministry of Statistics & Programme Implementation, Government of India, Statistical Abstract of India, New Delhi. IMSS: Center for Monitoring Indian Economy Pvt Ltd., Industry Market Size & Shares, CMIE, 2004. NASI, EPW Research Foundation, ed., 1998, National Accounts Statistics of India, Mumbai, EPW Research Foundation. MSPI: Ministry of Statistics & Programme Implementation, http://www.mospi.nic. in/stat_act_t3.htm MPI: Institute of Applied Manpower Research, ed., 2005, Manpower Profile India Yearbook 2005, MANAK.
Japan JSYB: Statistical Research and Training Institute, Ministry of Internal Affairs and Communications, Japan Statistical Year-book. Japan Census: Cabinet Office, Minister of International Trade and Industry, Census of Manufacturers: Report by Enterprises, Tokyo, Printing Bureau, Ministry of Finance.
Korea MSKE: Economic Planning Board, Major Statistics of Korean Economy. KSY: National Statistical Office, Government of Korea, Korea Statistical Yearbook, various years.
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Korea census Economic Planning Board, Republic of Korea, 1970, Report on Mining and Manufacturing Census 1968. Economic Planning Board, Republic of Korea, 1980, Report on Mining and Manufacturing Census, 1978. National Statistical Office, Republic of Korea, 1995, 1993 Report on Industrial Census. National Statistical Office, Republic of Korea, 2001, Report on Mining and Manufacturing Survey. Enterprise.
Taiwan TSDB: Council for Economic Planning and Development, Executive Yuan, Taiwan Statistical Data Book.
Taiwan census Executive Yuan, 2003, The Report on 2001 Industry, Commerce and Service Census, Taiwan-Fuchien Area, the Republic of China: General Report, Taipei. Executive Yuan, 1998, The Report on 1996 Industrial and Commercial Census TaiwanFukien Area, the Republic of China. Executive Yuan, 1993, The Report on 1991 Industrial and Commercial Census TaiwanFukien Area, the Republic of China. Executive Yuan, 1988, The Report on 1986 Industrial and Commercial Census, TaiwanFukien Area, the Republic of China. Executive Yuan, 1978, The Report on 1976 Industrial and Commercial Census, TaiwanFukien District, the Republic of China. Executive Yuan, 1968, General Report on the Third Industrial & Commercial Census of Taiwan, Republic of China.
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2 China and India’s Electrical and Electronics Industries: A Comparison between Market Structures Koichiro Kimura
2.1
Introduction
Growing countries do not necessarily follow the same industrial development process, despite sharing similar starting points. China and India have both been growing remarkably under gradual economic liberalization since the 1980s; however, they show a significant contrast in industrial development processes. As we see later, the role of secondary industry in the Chinese economy is consistently larger than that in India. In particular, a large difference could be found in the electrical and electronics industry. Although the industries in both China and India were regulated as a part of the defense industry before liberalization, they have started to develop with the production of civilian goods. Consequently, in China, the electrical and electronics industry has consistently developed since the 1980s and has become a leading industry, whereas in India, it stagnated in the 1990s after development in the 1980s. The results in both countries reveal another contrast between their information and communication technology (ICT) industries. Within the ICT industries, the hardware industry has developed remarkably in China; on the other hand, software and IT-enabled services have developed very well in India (Popkin and Iyengar 2007). China and India are on different paths of economic growth from the viewpoint of industrial development.1 According to previous studies, we know that the existence of competition among firms is a key factor of the different results in the electrical and electronics industry. In China, the transition from a planned economy to a market economy has been gradual, and economic liberalization is therefore incomplete, with the entry of private firms being low at first (Naughton 1995; Wedeman 2003). Continuous entries led by local governments, however, have increased competition as a consequence – especially in the 1980s – and competition among indigenous Chinese firms has promoted industrial development. Although indigenous firms were technologically backward compared to foreign-affiliated firms, they have shaped 40
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their competitiveness – for example, with quality improvement, product differentiation in tune with Chinese consumers’ preferences, construction of nationwide sales channels and after-sales service networks, and so on – despite fierce competition (Kimura 2006; Marukawa 1996, 2007; Ohara 1998). In India, too, partial liberalization in the 1980s increased competition in the electrical and electronics industry (Joseph 2004). According to Rodrik and Subramanian (2005), although the partial liberalization in the 1980s still favored incumbents, it has definitely contributed to Indian growth.2 However, the license system remained – possibly discouraging the promotion of competition – and the relatively uncompetitive situation did not bring opportunities to build competitive advantage for indigenous Indian firms.3 Although entries into the electrical and electronics industry increased with the liberalization, the industry was still tied by the influence of the previous entry regulations, which favored small-scale firms and kept India in a state of technological backwardness (Esho 1988). Small-scale firms tended to purchase various components rather than manufacture them by themselves. This consequently reduced opportunities to develop the industry including components (interview at the Electronics and Computer Software Export Promotion Council on July 30, 2009). Consequently, the industry has started to develop since the 1980s, but indigenous firms have faced uphill competition with foreign firms and imports. Previous studies focus on the impact of competition in enhancing industrial development, although the features of such competition have not been explicitly studied. At least the market is not at either extreme, that is, monopoly or perfect competition; it could be that the market appears in a variety of forms between both extremes. Therefore, it is necessary to enquire into the properties of competition pursued by firms. In this study, we will identify the property that leads to differentiation of industrial development processes and investigate their determinants. To identify the properties of competition, we compare the market structures of China and India. Market structure is defined as the number of firms in a market and the distribution of the market share of each firm. We compare the characteristics of the market structure and extract each property in China and India. Next, to understand the determinants of the market structure, we investigate barriers to entry and size of markets. One barrier to entry is that costs are borne only by new entrants but not by incumbents. The barrier is formed by, for example, assets owned by incumbents exclusively, licenses for entry, sunk costs, and so on. The market size is related to survivable space for firms when the existence of fixed costs generates a scale economy. We compare the two aspects and explore the formative factors in market structure. Under this framework, we here consider the television (TV) set industry, to analyze particular market structures concretely. Because it has been a
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major sector both in China’s and India’s electrical and electronics industries, it would be an appropriate case study for the industry. For example, TV sets have more than 100% penetration in urban households in China and almost 100% penetration in rural ones, as discussed in Section 2.3. In India, the industry accounts for 60% of the consumer electronics market (iSuppli Corporation 2008). From a comparison of the TV set market, our study leads us to conclude that homogeneity in competition serves as a key factor in industrial development. In China, reform started at the stage in which there were a few major incumbents; therefore, competition among firms with almost similar technological capabilities promotes industrial development. In addition, the rapid market expansion made room for many new entrants. Consequently, they increased their advantages through fierce competition and expanded their market share against foreign firms. On the other hand, the nature of competition in India was heterogeneous. After partial liberalization in the 1980s, the license system remained, and a stable market structure with only a few major indigenous firms has therefore been maintained. In addition, the market did not expand very much, limiting new entries. Consequently, with limited competition, their market shares decreased as foreign firms entered after full liberalization. The next section reviews the development of the electrical and electronics industries in both countries. In Section 2.3, we show the differences in the market structures and discuss the features of competition. In Section 2.4, the heights of the barriers to entry and market expansion are analyzed as determinants of the market structure. Finally, we make concluding remarks.
2.2 Industrial development Despite the rapid growth of China’s and India’s economies, their development patterns are different in terms of industrial structure. In China, economic reform and the open-door policy – which began in 1978 – successfully promoted economic growth. Similarly, in India, partial and full liberalization – which began in the 1980s and the 1990s – also drove economic growth. However, the ratio of secondary industry, including the electrical and electronics industry, to the whole economy in China is continuously much higher than the ratio in India (Figure 2.1). Manufacturing has been a driving force behind growth in China, whereas software and IT-enabled services, which are classified as belonging to tertiary industry, have been a leading sector in India. It is shown that the engines of growth are different between the two countries. In China, the electrical and electronics industry has developed into one of China’s leading industries (Table 2.1(a)). Although it is in nominal terms, growth after the mid-1990s has been rapid, and the industrial scale
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Figure 2.1 Industrial structures: China, 1980–2005, and India, 1980/01–2005/06 Sources: (a) National Bureau of Statistics, Various years, China Statistical Yearbook. (b) For 1980/81 to 2000/01, Ministry of Statistics & Programme Implementation, Various years, Statistical Abstract of India. For 2005/06, Ministry of Statistics and Programme Implementation, 2008, Monthly Abstract of Statistics (October 2007).
has expanded about threefold every five years. Consequently, the ratio of added value between the electrical and electronics industry and the secondary industry increased from 6.85% in 1985 to 12.88% in 2005. Within the secondary industry – which has been leading the Chinese economy – the added value of the electrical and electronics industry has been growing at a faster rate than that of the entire secondary industry, contributing to the rapid economic growth in China. By contrast, the significance of the electrical and electronics industry in the Indian economy has not grown as rapidly compared to China (Table 2.1(b)). Growth between the mid-1980s and the mid-1990s has been rapid; however, the pace slowed in the late 1990s. Consequently, the ratio of added value of the electrical and electronics industry to secondary industry increased to 5.16% in 1980/81 and 6.02% in 2005/06, whereas the ratio declined after peaking to 8.25% in 1995/96. Because the ratio of secondary industry to the economy in India is smaller than China’s ratio in the first place, the significance of the industry is much smaller than in China. At the time in India, the electrical and electronics industry was expected to be a leading industry as in other countries – developed and developing countries in East Asia. However, the focus moved to software and IT-enabled services during the 1990s. It is known that the
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1.91
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n.a. n.a.
1,648.35
1980
2.81
77.78
111.88 4.04
2,767.37
1985
%
Billion INR Billion INR
Unit
5.16
189.62 9.78
1980/81
5.33
310.81 16.58
1984/85
8.01
933.84 74.83
1990/91
2.87
146.21
209.90 4.12
5,093.25
1990
8.25
2116.59 174.64
1995/96
4.11
635.00
603.82 3.91
15,446.12
1995
5.56
3245.19 180.38
2000/01
7.18
1,824.31
1,231.50 4.85
25,394.80
2000
Sources: Ministry of Statistics and Programme Implementation, Various years, National Accounts Statistics.
2005
6.02
5448.70 328.22
2005/06
7.93
5,722.11
3,574.13 4.95
72,186.99
Note: Although “electrical and electronics industry” is used instead of “electrical machinery” in the statistics, the coverage is almost same.
GDP from manufacturing Electrical and electronics industry Ratio
(b) India, 1980/81–2005/06
Sources: National Bureau of Statistics, Various years, China Statistical Yearbook.
Note: “Added value of industry” for 1980 to 1990 is the value for the net value of output.
%
100 Million RMB
Electronics industry
Ratio
100 Million RMB
100 Million RMB %
Electrical industry Ratio
Unit
Added value of industry
(a) China, 1980–2005
Table 2.1 Electrical and electronics industries
Market Structure: Electronics 45
difference between the Chinese and Indian industrial structures emerged after the 1990s.
2.3 2.3.1
Market structure China
To investigate the background to the differences, we identify the properties of competition as a key driver of industrial development by market structure. As we show in this section, a significant difference in the market structure is that many major indigenous firms with homogeneous competitiveness have kept competing in China, whereas only a few major indigenous firms have kept their positions in India. This property is therefore homogeneous in China, but heterogeneous in India. In the Chinese TV set market, many major indigenous firms have continued to compete (Table 2.2).4 We can find major firms, such as Konka Group (Konka), Sichuan Changhong Electric (Changhong), TCL, Skyworth Group (Skyworth), Hisense Group (Hisense), Haier Group (Haier), Xiamen Overseas Chinese Electronic (Xoceco), SVA Electron (SVA), and Panda Electronics Group (Panda).5 Every firm is a famous nationwide manufacturer in China’s electrical and electronics industry, although most of them were established locally at first. By no means were they established, nor did they enter the TV set market, at the same time, and the timings vary among firms. For example, Changhong was established in 1958 and produced radars for military applications. Thereafter, they started to produce B&W TV sets in 1972 and CTV sets in 1985 and have become a leading firm in the TV set industry. By contrast, Skyworth was established in 1988 and started to produce CTV sets in the 1990s. On the other hand, the market share of Panda, which has a long history in China’s electrical and electronics industry and was ranked second in 1993, dropped during the 1990s, and Panda does not currently belong to the top group. As a result, new entrants have had opportunities to enter the market and become major firms after entry. These major indigenous firms have competed among themselves and with foreign-affiliated firms, and their market share has expanded against foreign firms. Indigenous firms have grown in power through competition during the 1990s, as shown in Table 2.2 above. Needless to say, the product lineup and product segment heavily weighted by each firm in the TV set market are different, but it is a fact that indigenous firms have developed the Chinese market with expansion of a nationwide sales network under fierce competition among themselves. Although some major firms have firmly established their positions in the TV set market, they are still under fierce competition. The market concentration increased during the 1990s. The concentration ratio (CR) is the market share held by the largest firm(s). In China, the CR4 – the ratio for the
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Table 2.2 Market share in China, 1993–2005 (%) 1993
1994
1996
1997 1998 1999 2001 2003 2004 2005
13.4
11.0
12.2
15.1
13.7
15.9
12.7
16.5
15.5
15.7
Changhong
4.2
5.0
20.5
25.0
33.7
13.2
16.5
15.5
14.5
13.9
TCL
n.a.
n.a.
6.2
9.5
7.8
11.0
14.1
12.7
13.5
13.1
Skyworth
n.a.
n.a.
n.a.
4.4
2.6
4.5
8.2 10.3
12.3
11.5
Hisense
1.9
n.a.
n.a.
3.1
5.6
8.5
9.9
8.9
10.4
7.9
Haier
n.a.
n.a.
n.a.
n.a.
7.9
7.8
6.8
6.1
6.7
6.2
Sony (Japan)
n.a.
3.5
5.5
n.a.
2.3
3.6
3.3
3.0
3.2
3.5
Sanyo (Japan)
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
1.3
3.2
3.9
3.3
10.7
14.7
13.3
6.7
2.3
n.a.
1.9
1.9
2.0
2.9
Philips (Netherlands)
n.a.
n.a.
n.a.
4.5
2.4
n.a.
3.2
2.4
2.7
2.5
Xoceco
3.3
n.a.
2.7
3.8
2.0
6.5
3.0
3.0
2.9
n.a.
SVA
4.2
3.7
2.7
4.5
2.0
2.8
2.7
3.0
2.7
n.a.
LG Electronics (S. Korea)
n.a.
n.a.
n.a.
n.a.
3.6
n.a.
2.2
3.5
2.3
n.a.
Toshiba (Japan)
2.1
n.a.
4.2
n.a.
2.1
n.a.
3.0
2.7
2.0
n.a.
11.2
11.0
4.6
3.9
5.6
2.9
2.6
n.a.
n.a.
n.a.
Konka
Panasonic (Japan)
Panda
Note: Notice that the share of each year cannot be compared directly, because the source for each year is different. Sources: For 1993 to 2004, Marukawa (2007). For 2005, Sinomonitor International, 2006. 2006 CMMS Zhongguo Pinpai Fazhan Baogao: Jiadian, IT, Shuma [2006 CMMS Chinese Brand Development Report: Home Appliance, IT and Digital Appliance]. Beijing: Sinomonitor International (Chinese).
four largest firms – was 39.5 in 1993 and 54.2 in 2005. However, no indigenous firms became dominant market leaders. During the 2000s, the top four firms had 10% to 15% of the market share between them, and there are therefore possibilities of changes to their rank order with a small change in the business environment. Consequently, competition is characterized as homogeneous in China. Because major indigenous firms have maintained an almost equal competitive relationship as shown in the structure, they have grown together and expanded their market shares against foreign-affiliated firms.
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Market Structure: Electronics 47
Through this competition, they have built their unique capabilities as mentioned in the introduction of this chapter. 2.3.2
India
By contrast, the Indian market structure is not homogeneous like the Chinese one, namely, there exists a disparity between a few major firms and the others. Despite there being a multitude of companies in the TV set market, there are a few major indigenous firms and they steadily kept their market share during the 1990s (Table 2.3(a)). The major firms are Videocon Industries (Videocon), BPL, and Mirc Electronics (Mirc).6 They grew in the 1980s, and their position has not been shaken. Therefore, the market structure had already been formed at the beginning of the 1990s. The market in the 1980s was more competitive, but the market concentration increased during the 1990s. Except for BPL – established in 1963 – Videocon and Mirc were established in 1979 and 1982, respectively, and started producing TV sets in the 1980s. In the Indian market, too, the incumbent – here BPL – did not have dominant power against new entrants after the partial liberalization. However, once they established their positions in the market, they maintained them during the 1990s. In particular, Videocon is a giant firm in India’s industry. They manufacture cathode-ray tubes (CRT) as a key component for their TV sets. The CR4 in the Indian market embodies this aspect. The CR4 was 46.4 in 1993/94 and it increased to 62.1 in 2005/06. The ratios in both countries increased during these periods, indicating that competitiveness has weakened. The ratios of both years in China are, however, lower than those in India, showing greater competitiveness in the Chinese market. Consequently, competition is characterized as heterogeneous in India. From the stable market structure, it is considered that competition in the 1990s was limited among indigenous Indian firms. In fact, major firms did not compete with each other in terms of market share, as in China, and indigenous new entrants that would subsequently become major companies have not appeared. The effect of competition shown in China has not appeared in India. Evidence of the limited effect of competition is shown in the market structure after the late 1990s. After the structure stabilized, new entrants were foreign rather than domestic after the full liberalization of the 1990s (Table 2.3(b)). Entries of foreign-affiliated firms and imports have shaken the structure for major indigenous incumbents. In particular, the market share of BPL dropped considerably. The net profit margin of BPL also fell, because they expanded a lot of business rapidly (Asaka 2007). In the 1990s, South Korean firms, Samsung Electronics (Samsung) and LG Electronics (LG), expanded their shares. The whole South Korean share was 9.4% in 1998/99, increasing however to 32.8% in 2006/07. Korean firms achieved successful outcomes by various business strategies, such as developing models based
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Table 2.3 Market share in India, 1992/93–2006/07 (a) 1992/93–2000/01 (%) 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2000/01 Videocon
17.97
17.5
21.0
25.4
24.9
20.6
20.7
23.6
23.2
BPL
13.07
15.2
20.3
22.4
21.2
18.3
16.9
17.7
14.6
n.a.
n.a.
n.a.
n.a.
n.a.
3.3
7.2
9.6
LG (S. Korea)
n.a.
Mirc
5.38
7.0
10.5
10.5
8.4
9.1
10.0
10.0
9.0
Samsung (S. Korea)
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
6.1
7.0
8.2
Philips (Netherlands)
5.21
6.7
10.9
7.6
9.5
6.6
5.6
5.5
3.3
Hotline Wittis
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
1.1
2.8
2.8
Sharp (Japan)
3.45
4.5
5.6
3.4
3.6
2.8
2.8
3.1
2.7
Dixon
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
2.4
2.6
Panasonic (Japan)
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
1.7
2.0
2.3
Import
0.1
0.1
0.6
1.1
0.3
0.4
0.7
0.3
0.2
Notes: (1) The item includes spares and kits for TV sets. (2) The number of firms for shares before 2000/01 and after 2001/02 are different in the statistics, so the tables are split. (3) Note that some major foreign firms are not listed in the statistics. Sources: Centre for Monitoring Indian Economy, Various years. Industry: Market Size & Shares. Mumbai: Centre for Monitoring Indian Economy.
(b) 2001/02–2006/07 (%) 2001/02
2002/03
2003/04
2004/05
2005/06
LG (S. Korea)
10.8
13.6
16.7
20.5
Videocon
21.7
20.3
21.2
23.2
19.9
8.6
11.9
14.0
12.0
12.5
Mirc
9.5
10.8
9.4
9.5
9.2
Philips (Netherlands)
4.0
4.1
3.5
4.5
4.7
Trend
2.0
1.9
1.9
2.1
3.3
Panasonic (Japan)
1.5
1.1
1.1
1.2
1.3
Indo Count
n.a.
n.a.
n.a.
0.7
1.2
Sharp (Japan)
2.4
1.9
1.3
1.0
0.9
Samsung (S. Korea)
Salora BPL Import
20.4
1.5
1.7
0.9
0.7
0.5
12.8
5.2
4.8
1.5
0.4
0.3
0.4
2.0
4.6
7.8
Sources: Same as those for Table 2.3 (a).
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Market Structure: Electronics 49
on Indian consumer preferences, extensive advertising to strengthen the value of their brand names, and so forth (Bae 2007; Verma 2007). The entry of Korean firms with a lot of experience in international competition had a major impact on the lasting oligopolistic market. In addition, decreasing import duty and competitive pressure by imports also increased, particularly after 2004/05.7 Incumbents faced fiercer competition before they could build their own competitive power.
2.4 2.4.1
Determinants of market structures China
2.4.1.1 Barriers to entry formed historically In this section, we will examine barriers to entry and market expansion in order to investigate the market structure. First, to understand barriers to entry, we explore a brief history of institutional changes in the electrical and electronics industry.8 China and India have been through a process of liberalization, so the market structures have been influenced by the processes of these institutional changes. We show that the barriers to entry have been lower in China compared to India. Before economic reform, the government restricted entry, because China was a planned economy and industry was developed as a defense industry for national security reasons. Therefore, greater emphasis was placed on military goods – such as radars, wireless communication equipment, and so on – over consumer products. In particular, the germ of the electronics industry – which was developed worldwide after World War II – was brought by the government, and early production capacity was formed with support mainly from the former Soviet Union during the First Five-year Plan (1953– 1957). Thereafter, the policy continued and production bases for military goods were established throughout China, including inland areas. However, in the 1970s, the Chinese government began encouraging the production of consumer goods because of the problem of excess production capacity for military goods. As described above, Changhong entered the consumer-goods market at that time. Through transformation of production from military goods to consumer goods, new product lines – particularly TV sets – were developed in the electrical and electronics industry and it appears that these transformed firms have dominated the industry since then. In the 1980s, however, Chinese local governments set up firms one after another and – in addition to firms transformed from defense-industry companies – many new firms entered the TV set market after the economic reform. They set up production lines with technological introduction and support from overseas firms. In the top four firms occupying more than a 10% share as of 2005 – shown in Table 2.2 above – all except Changhong
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were established in the 1980s. The Chinese central government tried to allow a few registered firms to manufacture TV sets; however, firms led by local government introduced many production lines from abroad (Marukawa 1996). Although not all types of firm could enter, nevertheless, all of the above factors led to the development of fierce competition as a result. Although market entry was mainly led by local government rather than by the private sector, conditions for a competitive market were set through such investment.9 In addition, they were homogeneous in technological know-how for manufacturing TV sets. They had equally insufficient experience in assembling TV sets and facilities for internalizing CRT. Therefore, although some firms might have experience of manufacturing certain electrical and electronics parts, they are equally near newcomers as manufacturers of TV sets. In other words, there was no significant technological gap among indigenous firms. Consequently, under the economic liberalization, many local firms imported production lines and received technical transfers from firms in developed countries. Against the backdrop of market expansion in the 1990s as mentioned below, there was competition among local firms and foreign-affiliated firms, and they formed competitive power through fierce competition. In China, although led by local government, many homogeneous firms have “freely” entered; therefore, there is now adequate competition promoting the formation of competitive power. 2.4.1.2 Market expansion Market size is also an important determinant of market structure. The urban market in China expanded especially in the 1990s; consequently, according to China Statistical Yearbook, the penetration rate of CTV sets has increased from 59.0% in 1990 to 116.6% in 2000. As the urban market matured, the rural market also started to expand in the late 1990s – from 16.9% in 1995 to 84.1% in 2005. The huge market reduced the influence of incumbents in China allowing many new entrants to enter and expand their production capacity. Competition among them consequently decreased the prices of TV sets. Moreover, the decline in prices stimulated further market expansion, that is, there was interaction between competition and market expansion. Concerning market size, the size of Chinese local firms is also large (Table 2.4). In China, the production volume of TV sets in 1991 was more than 25 million sets and the volume in 1998 was more than 42 million sets. About 100 manufacturers entered the market, and each firm produced 140 thousand sets on average in 1993 and 268 thousand sets on average in 1997. The biggest manufacturer was Changhong; they produced about 1 million sets in 1992 and about 10 million sets in 1998. Although many firms entered the market, there was space for many firms to survive because
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of which B&W TV set
1307.3
11.3
14.2
18.7
116
92
140
2615.7
1993
8.2
Its Share in CTV set (%)
7.9
100.9 10.7
140.4 11.9
195.5
Changhong
1637.1
10.5
16.7
19.8
121
98
147
2913.3
1994
1912.1
13.0
19.5
23.4
118
98
147
3441.7
1995
16.0
305.2
Changhong
Source: Ministry of Electronics Industry, Various years, China Electronics Industry Yearbook.
96.8
Konka Changhong Changhong
Its Production size
Largest firm
n.a.
n.a.
1174.8
B&W TV set
CTV production
1269.8
n.a.
n.a.
n.a.
n.a.
n.a.
2586.6
1992
n.a.
CTV set
n.a.
n.a.
n.a.
of which CVT set
Average size of firms
n.a.
2516.9
Number of firms (Unit)
Total production
1991
Table 2.4 Firm size in China, 1991–1998 (Ten thousand, except for number of firms)
22.9
480.6
Changhong
2094.9
n.a.
21.2
20.7
n.a.
99
140
2892.2
1996
23.2
580
Changhong
2496
n.a.
26.8
26.0
n.a.
93
125
3244
1997
25.7
935
Changhong
3643
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
4276
1998
52
Koichiro Kimura
of the large market, including the foreign market. Even after new entry stopped in the mid-1990s, competition continued (Table 2.2). In addition, some major local firms entered foreign markets to expand their business. Market expansion has prevented market inflexibility and made room for competition, through which local-firm advantages – such as sales networks – can be established. 2.4.2
India
2.4.2.1 Barriers to entry formed historically Next, we see in turn that barriers to entry in India were higher than in China.10 First, during the early stages of India’s electrical and electronics industry in the 1960s, foreign-affiliated firms dominated the Indian market.11 For example, Royal Philips Electronics – from the Netherlands – dominated the TV set market and IBM – from the United States – dominated the computer market. In the latter half of the 1960s and in the 1970s, however, the industry in India also started to develop as a defense industry. In 1966, the Bhabha Committee – commonly known as the Electronics Committee – recommended emphasizing the development of the local public and small-scale sectors. On the other hand, to restrict entry and growth of large-scale firms and foreign-affiliated firms, the Monopolies and Restrictive Trade Practice Act (MRTPA) and Foreign Exchange Regulation Act (FERA) were established in 1969 and in 1973, respectively. For the development of the electrical and electronics industry, the government established the Department of Electronics for administration in 1970, the Electronics Commission for policymaking in 1971, and a mid- and long-term plan for the electronics industry in 1975. Under these policies and institutions, large-scale investments were not freely allowed. In the 1980s, Indira Gandhi and Rajiv Gandhi implemented partial liberalization at last. In the early 1980s, preferential treatment for incumbents and large-scale investments started. In 1981, a components policy was launched, and the Indian government partially de-licensed components manufacturers. Although the licensing system was maintained in the TV set industry and a color TV policy was launched in 1983, restriction of production capacity was liberalized.12 During the late 1980s, in addition to this preference, alliance with foreign-affiliated firms was also partially allowed. Some major indigenous Indian firms aligned with overseas firms, such as Japanese TV set manufacturers. In the 1980s, the TV set industry was not fully liberalized, with consequent unevenness in the growth of local firms under the licensing system and a preference for incumbents and large-scale investment. After the 1990s, Narasimha Rao implemented full-scale liberalization. This started with the new industrial policy in 1991, although the electrical and electronics industry was not included at that time. The white goods
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Market Structure: Electronics 53
industry was de-licensed in 1993, and CTV sets among entertainment electronics were finally de-licensed in 1996. Although entry by indigenous firms was de-licensed in 1996 – as shown in Table 2.3 – the ranking of major indigenous firms has remained stable. For local new entrants, it is considered that the partial liberalization gave incumbents and large-scale firms preferential treatment as a kind of barrier to entry. Moreover, major indigenous firms, such as Videocon and BPL, have tended to integrate components, so it is possible that new entrants have had to integrate to the same degree to gain the competitiveness necessary to enter and grow in the Indian TV market.13 On the other hand, the entry of foreign-affiliated firms and imports shook the structure of major local incumbents. Consequently, it is considered that the effects of competition felt in China have not appeared in India. Moreover, after the entry of foreign-affiliated firms, the shares of local firms dropped. 2.4.2.2 Market expansion Despite the large population of India, the size of the market is only half that of China’s. In addition, product penetration of electrical and electronics goods is not very high in comparison to China. The rate of CTV sets both in urban and rural areas was just 17% in 2001/02.14 According to income class, the penetration rates in the rich class – more than 1 million INR, accounting for 0.4% of households – and the middle class – 0.2–1 million INR, accounting for 5.7% – are 99% and 73%, respectively. However, the rates of the aspiring class – 90,000–200,000 INR, accounting for 21.9% – and the deprived class – less than 90,000 INR, accounting for 71.9% – are 40% and 5%, respectively. Households of the lower-income class tend not to own a TV set, although they make up the majority of households in India. This low penetration is also related to the price of CTV in India. The price was twice this in China in 1997, therefore most households could not purchase (Ray 2001). Consequently, in India, space for growth of new entrants – by contrast with the Chinese case – was smaller. Therefore, it is possible that the market size is becoming a restriction for new entrants. In particular, growth of production volume decreased remarkably during the early 1990s compared with the 1980s. It was influenced by significant recession around 1990 in India (Department of Electronics 1992). It is considered that the sluggish growth had a significant influence on the market structure and industrial development. Regarding the market and size of production, indigenous firms also tend to be smaller in comparison with China. In India, the production volume of TV sets in 1990 was 4.8 million sets and 1996 just 8.4 million sets; this volume is much smaller than that of China at that time (Table 2.4 and Table 2.5). In addition, the volume in India includes a large amount of B&W TV set production, compared to production in China. On the size of indigenous firms,
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Table 2.5 Production volume in India, 1979–1996 (Ten thousand) 1979 TV set
1980
1981
1982
1983 1984 1985 1986 1987
31.1
37
43.5
n.a.
n.a.
128
248
300
430
of which CTV
n.a.
n.a.
n.a.
n.a.
n.a.
28
68
85
110
of which B&W TV
n.a.
n.a.
n.a.
n.a.
n.a.
100
180
215
320
1989
1990
1991
1992
1993 1994 1995 1996
520
480
398
423
517
1988 TV set
570
of which CTV
653
775
840
130
120
120
88
83
107
133
185
240
of which B&W TV 440
400
360
310
340
410
520
590
600
Sources: Department of Electronics. Various years. Annual Report. New Delhi.
the biggest manufacturer was Videocon in the Indian market, with about 5 million sets in 2000 (Table 2.6). The volume was, however, just half that of the biggest Chinese manufacturer, Changhong. Nevertheless, the production share of Videocon was bigger than Changhong’s, demonstrating that the top manufacturer had significant presence in the Indian market.
2.5
Conclusion
In this study, we have showed the relationship between the properties of competition and their determinants in China and India. After an overview of the development of the electrical and electronics industries, we first identified the properties of competition in the TV set market. By market structure, competition was homogeneous in China, but heterogeneous in India. Consequently, these properties yielded different results in industrial development and structure. Next, we explored the factors. In China, economic reform started at the stage in which there were not very many major incumbents established in the planning period. Moreover, the market expanded rapidly during the 1990s in particular. Therefore, these factors made room for many new entrants. Their continuous entry enhanced competition and their own competitive advantage increased through fierce competition. On the other hand, India’s TV set industry had already established local firms prior to full liberalization, thereby creating a much higher barrier to entry for new entrants. Moreover, the market did not expand much in comparison to the Chinese case. Under this market structure, the impact of competition on fostering and strengthening local firms was limited. As a result, foreign-affiliated firms entered the market after full liberalization in the 1990s, and their market shares have expanded. The lack of
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3,442.75 84.0
122.9
415.0
1,314.2
5,170.0
1993/94
5,568.2 126.6
156.3
524.9
2,970.2
6,530.0
1994/95
5,709.7 105.7
182.7
641.4
2,378.8
7,750.0
5,499.7 101.8
166.0
598.0
2,574.2
8,600.0
1995/96 1996/97
1998/99 1999/00 2000/01
5,374.6 99.5
185.6
681.9
2,607.0
7,614.9 141.0
296.9
833.2
3,811.6
345.4
886.4
5,058.6
10,504.0 10,952.3 194.5 202.8
385.3
1,039.6
4,763.6
9,240.0 10,260.0 11,330.0 12,000.0
1997/98
Sources: Centre for Monitoring Indian Economy. Various years. Industry: Market Size & Shares. New Delhi: Centre for Monitoring Indian Economy.
2,634.2 61.3
93.5
Mirc
Total for the sample Average
276.3
BPL
4,230.0
1,008.2
Videocon
1992/93
Firm size in India, 1992/93–2000/01 (Thousand production)
Total production
Table 2.6
56
Koichiro Kimura
competition – or heterogeneous competition – did not promote industrial development very much in comparison with the Chinese industry. In conclusion, the development of local firms against foreign-affiliated firms depends on the effect of competition among local firms. Although local firms lacked technological capability in comparison to foreignaffiliated firms, Chinese local firms were able to form their own advantages through competition amongst themselves. Consequently, it was found that homogeneous competition, formed by a low barrier to entry and/or market expansion, would lead to industrial development. We discussed development of the TV set industry mainly in the 1980s and the 1990s above. However, industry in China and India is currently in the midst of major change. First and foremost, the market is making a transition from CRT to flat-panel displays, such as liquid-crystal and plasma. The transition is bringing a new phase of competition. Moreover, in India, the middle-income group grew remarkably in the 2000s. Along with the change in the electrical and electronics industry, the hardware industry is also growing. For example, many global players such as Nokia, Dell, Samsung, Flextronics International, Foxconn Electronics, and so on decided to invest in production bases.15 Consequently, the Indian electrical and electronics industry entered a high-growth phase in the 2000s (Uemura and Iwadare 2007). It is possible that these fundamental movements change the determinants of market structure. Therefore, we have to know what impacts indigenous Chinese and Indian firms have experienced. In particular, it is necessary to clarify whether the recent changes lead to market expansion and industrial development, and whether indigenous Indian firms can seize the opportunities to grow brought by these changes. We must continue to pay attention to the relationship between market structure and its determinants, in order to understand the industrial development process of each country.
Notes I would like to express my gratitude to the anonymous referees, the members of our research project, Mr. John Hanawa, and everyone who cooperated in my research for their helpful suggestions. All remaining errors are my own. 1. The Indian development process is interesting from the viewpoint of not only the Chinese pattern but also the East Asian pattern. Unlike India, the growth of East Asian industrializing countries and areas also tends to depend on hardwarecentered industries. Therefore, a comparison between China and India would shed light on the differences between East Asia and India. 2. Therefore, they describe the partial liberalization in the 1980s as “probusiness” and the full liberalization in the 1990s as “promarket,” and prefer the former period for its economic growth in India. 3. There are also other reasons. The unfavorable investment climate for the whole of manufacturing is also related to the underdeveloped state of the electrical and
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Market Structure: Electronics 57
4.
5.
6. 7. 8.
9.
10.
11. 12.
13. 14.
15.
electronics industry. Ferrari and Dhingra (2009) show problems with electricity, high taxes, corruption, and tax administration. Kojima (2002) and Uchikawa (2006) indicate inadequate infrastructure, particularly electricity shortage. Moreover, relative differences in industrial development are also related to underdevelopment. The possibility of developing India’s components industry is discouraged by rapid tariff cuts and the existence of well-developed industrial agglomerations in East Asia – interview at the Electronic Industries Association of India on July 31, 2009. The Chinese TV market is assumed to be the color TV set market, because color TV (CTV) sets have been prevailing in both urban and rural markets after the 1990s. The Indian TV set market is assumed to be the CTV and black and white TV (B&W TV) set markets, because B&W TVs also still sell well in India, at least in the 1990s. Konka, TCL, Skyworth, Xoceco received investment by overseas Chinese and firms in Hong Kong. However, they were basically investment firms and did not have the technology or know-how to manufacture TV sets; therefore, we treat them here as indigenous firms and a variation of Chinese firms. The brand name of the TV set provided by Mirc is “Onida.” Shiino (2009) indicates that many electronics goods have been imported by Indian traders recently. In addition, whether firms can purchase core components or not also constitutes an entry barrier factor. In China, however, because many local firms could purchase CRT, this factor has not become a barrier (Marukawa 1996). Although we need to review the impact of entries led by local governments on Chinese long-term economic growth, these entries were at least promoting industrial development at this time. As mentioned above, purchase of CRT is important for barriers to entry. Gupta (2006) indicates that “suppliers enjoy high bargaining power.” Videocon and BPL have integrated to manufacture CRT, and it is necessary to evaluate internalization of core components in competitive power. On the development of the Indian electrical and electronics industry, see Esho (1988) and Joseph (2004). Other policies include a policy to promote industrial electronics development in 1983 and a telecommunications policy in 1984. Also, a computer policy and computer software policy were implemented to partially liberalize the industries in 1985 and in 1987, respectively. In addition, the licensing system was also partially liberalized by the integrated policy of 1987. Ray (2001) shows the vertical integration of BPL as their business strategy. Cited from the website of the National Council of Applied Economic Research (http://www.ncaer.org/downloads/PPT/TheGreatIndianMarket.pdf), accessed on October 16, 2008. Yoshimoto et al. (2006) study the recent business development of Japanese firms in the Indian market. There is also growth of indigenous Indian firms – such as Moser Baer India, a storage media and photovoltaic cell manufacturer, NeST Technologies, an electronics manufacturing service, and so on.
References Asaka, Toshimasa, 2007, “Kigyo Keiei Shiten kara no Indo Senryaku [Strategy to India from a Viewpoint of Business Management]”, In Japan Center for Economic Research. Indo Keizai no Genjo to Tenbo: Sono Seichoryoku to Seiyaku Yoin [Current Condition and
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Perspective for the Indian Economy: Its Potential for Growth and Constraining Factors], Tokyo: Japan Center for Economic Research (Japanese). Bae, Hajin, 2007, “LG Denshi, Samsung Denshi [LG Electronics, Samsung Electronics]”, Indo Bijinesu Jitsumu Gaido [The Indian Business Guide], Tokyo: Business Research Institute (Japanese). Department of Electronics, 1992, Annual Report 1991–92, New Delhi: Department of Electronics. Esho, Hideki, 1988, “Denshi Sangyo: 80 Nendai Keizai Jiyuka Sokushinka ni okeru Sinko sangyo [Electronics Industry: Emerging Industry under Promotion of Economic Liberalization in the 1980s]”, In Shoji Ito, ed., Indo no Kogyoka: Kiro ni tatsu hai kosuto keizai [Indian Industrialization: High-Cost Economy Standing at the Crossroads], Chiba: Institute of Developing Economies (Japanese). Ferrari, Aurora and Inderbir Singh Dhingra, 2009, India’s Investment Climate: Voices of Indian Business, Washington, DC: The World Bank. Gupta, Seema, 2006, “Indian Television Industry: A Strategic Analysis”, Vilakshan, XIMB Journal of Management, 3 (2), pp. 195–216. iSuppli Corporation, 2008, Consumer Electronics Industry in India: Poised for Robust Growth, El Segundo: iSuppli Corporation. Joseph, K. J., 2004, “The Electronics Industry”, In Subir Gokarn, Anindya Sen and Rajendra R. Vaidya, eds., The Structure of Indian Industry, New Delhi: Oxford University Press. Kimura, Koichiro, 2006, “Chugoku Keitai Denwa Tanmatsu Sangyo no Hatten: Hanbai Zhushi no Senryaku to Sono Genkai [Development of China’s Mobile Handset Industry: Marketing-oriented Strategy and Its Limitations]”, In Kenichi Imai and Momoko Kawakami, eds., Higashi Ajia no IT Kiki Sangyo: Bungyo, Kyoso, Sumiwke no Dainamikus [The Information Technology Equipment Industry in East Asia], Chiba: Institute of Developing Economies (Japanese). Kojima, Makoto, 2002, “Indo Kogyo Ron [A Study of India’s Industry]”, In Hideki Esho, ed., Gendai Minami Ajia 2, Keizai Jiyuka no Yukue [Contemporary South Asia Vol. 2, Future of Economic Liberalization], Tokyo, University of Tokyo Press (Japanese). Marukawa, Tomoo, 1996, “Shijo Keizai Iko no Purosesu: Chugoku Denshi Sangyo no Jirei kara [The Transition to Market Economy: In the Case of China’s Electronics Industry]”, Ajia Keizai, 37 (6), pp. 2–28 (Japanese). Marukawa, Tomoo, 2007, Gendai Chugoku no Sangyo: Bokko suru Chugoku Kigyo no Tsuyosa to Yowasa [Modern Chinese Industries: Strength and Fragility of Chinese Rising Firms], Tokyo: Chuokoron-Shinsha (Japanese). Naughton, Barry, 1995, Growing Out of the Plan: Chinese Economic Reform, 1978–1993, Cambridge: Cambridge University Press. Ohara, Moriki, 1998, “Chugoku Kaden Sangyo no Yuisei: Eakon Sangyo no Sangyo Soshiki to Haiahru Gruupu no Jirei Kara [Advantage of China’s Home Appliance Industry: From Industrial Organization of Air Conditioner Industry and a Case of Haier Group]”, Ajiken World Trend (36), pp. 38–44 (Japanese). Popkin, James M. and Partha Iyengar, 2007, IT and the East: How China and India Are Altering the Future of Technology and Innovation, Boston, MA: Harvard Business School Press. Ray, Pradeep K., 2001, “BPL Limited: Global Competition and Guerilla Warfare on Local Territory”, In Sumantra, Ghoshal, Gita Piramal and Sudeep Budhiraja, eds., World Class in India: A Casebook of Companies in Transformation, New Delhi: Penguin Books. Rodrik, Dani and Arvind Subramanian, 2005, “From ‘Hindu Growth’ to Productivity Surge: The Mystery of the Indian Growth Transition”, IMF Staff Papers, 52 (2), pp. 193–228.
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Market Structure: Electronics 59 Shiino, Kohei, 2009, Indo Keizai no Kiso Chishiki [Fundamental Knowledge on the Indian Economy], 2nd ed., Tokyo: JETRO (Japanese). Uemura, Tetsushi and Yoshihiko Iwadare, 2007, “Indo no Erekutornonikusu Shijo [The India’s Electronics Market]”, Indo Bijinesu Jitsumu Gaido [The Indian Business Guide], Tokyo: Business Research Institute (Japanese). Verma, Yasho V., 2007, Passion: The Untold Story of LG Electronics India, New Delhi: Biztantra. Wedeman, Andrew H., 2003, From Mao to Market: Rent Seeking, Local Protectionism, and Marketization in China, Cambridge: Cambridge University Press. Yoshimoto, Tetsuo, Junjiro Shintaku, Koichi Nakagawa, Takahiro Fujimoto, Yasuo Sugiyama, Tomofumi Amano, Jun Otahara and Dongsheng Ge, 2006, “Indo Seizogyo no Monozukuri to Nikkei Kigyo no Indo Shinshutsu: Nirin, Yonrin, Kaden no Jirei [Manufacturing in the India’s Manufacturing Industry and Expanding of Japanese firms into India]”, Akamon Management Review, 5 (12), pp. 707–728 (Japanese).
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Part II Capability Formation: Skills, Technology, and Innovation
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3 Technology Acquisition by Indigenous Firms: The Case of the Chinese and Indian Automobile Industries Tomoo Marukawa
3.1
China and India in the world’s automobile market
The economic crisis which has plagued the world since 2008 led to the sharp decline of automobile production in Japan and the United States in 2009. In China, on the other hand, stimulated by fiscal policy to boost domestic demand, automobile production grew by 48% in 2009 compared to the previous year. As a result, China has – for the first time in history – become the largest automobile-producing country in the world (Figure 3.1). China is also the largest automobile market in the world – in terms of the number of vehicles sold. Judging from recent trends, China will be the largest automobile producer and market for years to come. India is also increasing its automobile production rapidly, doubling its production volume from 2003 to 2007. As of 2008, India was the ninth 16,000,000
14,000,000 India 12,000,000 Brazil 10,000,000 Germany 8,000,000 Russia 6,000,000
United States
4,000,000
Japan
2,000,000
China
0 1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Figure 3.1 Production volume of major automobile producing countries Source: World Motor Vehicle Statistics, Japan Automobile Manufactures Association, Inc. 63
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64
Tomoo Marukawa
largest automobile producer in the world. India’s automobile production stagnated somewhat in 2008, but it recovered in 2009, recording 12.9% growth over the previous year. Compared with the other major automobile-producing nations, however, China and India lack powerful domestic automobile manufacturers. A large part of the growth of automobile production in China and India is attributable to the growth of foreign-invested enterprises. In the case of passenger cars, 70% of the production volume in China in 2009 and 88% of that in India in 2008 was produced by foreign-invested enterprises. At the same time, however, the progress of some indigenous automobile manufacturers in China and India is drawing the attention of automobile industry specialists around the world. In China, Chery Automobile Co., Ltd. (Chery) – which began producing automobiles in 2000 – rapidly raised its position to fourth largest passenger-car manufacturer in China in 2007. Zhejing Geely Holding Group Co., Ltd. (Geely), another indigenous automobile manufacturer, came to an agreement with Ford Motor Company in December 2009 on the acquisition of Volvo Car Corporation – a Swedish luxury car manufacturer. India’s Tata Motors astonished the world with its launch of a very cost-effective “one lakh (100,000) Rupees car” in 2009. Among the indigenous automobile manufacturers in China and India, we have selected China’s Chery and Geely and India’s Tata Motors as representative cases of technology acquisition by indigenous firms. The reason these three companies were selected is because they are independent from multinational automakers. Most of the competitive carmakers in the Chinese and Indian automobile markets are joint ventures created by European, American, Japanese, and Korean automakers and domestic automobile manufacturers. Chery, Geely, and Tata Motors, however, are competing with multinational automakers by relying on their own resources. How these indigenous automakers have acquired the technological capability to compete with powerful multinational automakers is the question we would like to address in this chapter. The chapter is structured as follows. Section 3.2 will analyze the present status of indigenous automakers in China and India. Section 3.3 reviews the development process of Chery, Geely, and Tata Motors and analyzes how they acquired the product and process technology necessary to compete with multinational automakers. Section 3.4 deals with exports and foreign direct investment by these automakers, and the conclusion follows in Section 3.5.
3.2 3.2.1
Present status of indigenous automakers China
China’s automobile industry has a long history, dating back to the 1950s. The first automobile plant in China, which was named “First Automobile
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Technology Acquisition by Indigenous Auto Firms 65
Works” – Diyi qiche zhizaochang – was established in 1953. With technological assistance from the Soviet Union, the plant started as a large-scale truck producer with a production capacity of 30,000 units a year, which was soon expanded to 60,000 units a year (Qi 1996). Because of this long tradition, combined with fierce competition among numerous domestic manufacturers, Chinese automobile makers have turned out to be competitive in commercial vehicles, occupying 95% of the domestic market in 2009. However, they remain weak in the passenger car market – where they occupied only 31.3% of the domestic market in 2009 – whereas in the markets for multipurpose vehicles (MPV), sport utility vehicles (SUV) and microvans, they accounted for 61.3%, 42.4%, and 53.0% of domestic sales, respectively. Until the mid-1980s, Chinese passenger-car production remained very underdeveloped, producing only several thousand sedans annually. In 1985, the German automobile manufacturer Volkswagen established a joint venture with a state-owned automaker in Shanghai. The joint venture introduced – for the first time in Chinese history – state-of-the-art production technology for passenger cars. Concurrent with the expansion of car production by Volkswagen’s joint venture and the emergence of other foreigninvested car makers, China’s automobile industry has drastically renovated its technology. Because the Chinese government requires manufacturers to maintain high local content in the cars they produce, foreign-invested car makers have sought a supply of automobile components in China. This has triggered a surge of foreign direct investment by international automobile parts manufacturers, which also contributed to the technological progress of the automobile industry. Especially after China’s entry into the World Trade Organization (WTO) in 2001, there have been a number of new entrants to the Chinese automobile industry, and the production volume of automobiles has increased rapidly, making China the most vibrant and competitive automobile market in the world. Nowadays, all the major players in the world’s automobile industry – including GM, Ford, Toyota, Nissan, Honda, Mazda, Mitsubishi, Hyundai-Kia, Suzuki, Volkswagen, BMW, Daimler, PSA, and Fiat – have more than one factory in China. Because there was a tremendous gap between the technological level of foreign automobile manufacturers and that of China’s indigenous automobile manufacturers, the latter initially were only minor players in the Chinese passenger-car market. Since 2001, however, the share of domesticbrand cars has been rising steadily (Table 3.1). The leaders in the rise of domestic-brand cars are not the old state-owned automobile manufacturers such as First Automobile Works, but new entrants in the industry – such as Chery and Geely. It seems miraculous that such new entrants – which started producing cars in 2000 in the case of Chery, and in 1998 in the case of Geely – were able to reach the positions of fourthand ninth-largest automobile manufacturer in the Chinese car market in
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Tomoo Marukawa
Table 3.1 Domestic-brand cars in China’s automobile industry Year
2001
Number of car brands Of which: domestic brands Share of domestic brands (%)
18
Passenger car 772 production (thousand units) Of which: domestic brands 104 (thousand units) Share of 13.5 domestic brands (%)
2002
19
2003
26
2004
2005
2006
110
115
156
27
34
66
24.5
29.6
42.3
2007
2008
2009
1,230
2,189
2,483
3,118
4,302
4,798
5,047
7,471
212
442
496
741
1,153
1,306
1,308
2,351
17.2
20.2
20.0
23.8
26.8
27.2
25.9
31.5
Sources: Figures for 2001–2003 and 2007–2009 are calculated by the author, using the same method as Zhongguo qiche jishu yanjiu zhongxin (2007). Data is from the China Automobile Information Net.
2007, where more than 30 carmakers – both foreign and domestic – compete for a share of sales (Table 3.2). 3.2.2
India
India has a longer history in automobile production than China. In 1928, General Motors India, Ltd., started assembling completely knocked-down trucks and cars in Bombay. It was followed by Ford Motors Company of India, Ltd., in 1930 (Kathuria 1996, pp. 82–83). The first indigenous automakers – namely Hindustan Motors and Premier Motors – started producing vehicles during the 1940s. Tata Engineering & Locomotive Co., Ltd., – TELCO, later Tata Motors – was registered in 1945, and its automobile division started producing trucks in 1954 in collaboration with Daimler-Benz. Indian automobile production, however, stagnated for a long period because of strict restrictions on entry, import, and production. Production volume of vehicles only reached 113,000 units in 1980. It was only after 1983 – when Maruti Udyog started producing cars with technical assistance
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Technology Acquisition by Indigenous Auto Firms
Table 3.2
67
Top car manufacturers in China (Production volume, unit) 2007
Total
2008 4,797,687
Total
2009
5,037,334
Total
7,471,194
FAW VW
489,176
Shanghai VW
481,730
Shanghai VW
697,249
Shanghai VW
456,085
FAW VW
480,800
FAW VW
670,767
Shanghai GM
447,823
Shanghai GM
403,939
Shanghai GM
663,795
Chery
327,453
FAW Toyota
366,512
Beijing Hyundai
522,457
FAW Toyota
271,037
Dongfeng Nissan
319,455
Dongfeng Nissan
465,581
Dongfeng Nissan
263,012
Chery
281,412
BYD
427,732
Guangzhou Honda
249,417
Guangzhou Honda
279,298
Chery
412,341
Changan Ford
221,117
Beijing Hyundai
258,356
Guangzhou Honda
337,730
Geely
216,774
Geely
220,955
Geely
330,275
Shenlong (Citroen)
213,058
Changan Ford
197,366
Changan Ford
315,830
Note: This table includes only sedan-type passenger cars. FAW is First Automobile Works. Source: China Automobile Information Net.
from Suzuki – that the Indian automobile industry started to modernize its technology and grow rapidly. During the 1990s, restrictions on inward foreign direct investment were largely removed, which triggered the entry of multinational automakers into the Indian market. As seen in Figure 3.1, Indian automobile production volume in 2007 was equivalent to China’s in 2001, but the structure of the industry is not the same (Figure 3.2). Sixty-five percent of production consisted of sedan-type passenger cars, whereas in China in 2001, the ratio was only 30%. Moreover, most of India’s passenger-car market consisted of small cars. Eighty-one percent of cars produced in India belong to either the “A1 (mini) segment” – which consists of cars under 3400 millimeters in length – or the “A2 (compact) segment,” – which consists of cars between 3401 and 4000 millimeters in length. This size corresponds to the “mini-sized” – “weixing” – cars in China, which made up 27% of China’s car-production volume in 2005 and declined to only 6% in 2009. The peculiar structure of India’s passenger-car industry was created because Suzuki – a Japanese manufacturer which specializes in small cars – has led the growth of the Indian car industry since Suzuki’s establishment
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68
Tomoo Marukawa A1(Mini) Cars 3% Mid-sized and Large Commercial Vehicles 11%
Small Commercial Vehicles 10%
Multipurpose Vehicles 4% A2(Compact) Cars 50% Sport Utility Vehicles 10% A6(Luxury) Cars 0% A5(Premium) Cars 0% A4(Executive) Cars 2% A3(Mid-size) Cars 10% Figure 3.2 Structure of India’s automobile production in 2008 Source: Fourin (2009).
of a joint venture in India in 1982. Maruti Udyog – renamed Maruti Suzuki India in 2007, a joint venture by Suzuki and Indian partners – was still the top automobile manufacturer in 2008, turning out 44% of India’s car production and 32% of the country’s automobile production in 2008 (Table 3.3). Following the success of Maruti Udyog, international car manufacturers such as Hyundai-Kia, Honda, and Toyota entered the Indian market. Furthermore, Tata Motors – which formerly produced only trucks and buses – entered the car/station-wagon segment in 1991–1992 (Kathuria 1996, p. 320). As of 2008, Tata Motors was the second-largest automobile manufacturer and the third-largest passenger-car manufacturer in India in terms of production volume (Table 3.3).
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Technology Acquisition by Indigenous Auto Firms 69
Table 3.3 Production volume of major automobile manufacturers in India Year Maruti Udyog (Suzuki)
2006
2007
628,355
755,990
2008 751,784
Tata Motors
554,039
576,084
515,813
Hyundai Motor India
301,305
338,672
486,052
Mahindra & Mahindra
136,194
187,222
182,906
77,985
83,136
71,485
GM India
35,019
60,291
63,619
Honda Siel Cars
55,454
58,106
53,298
Toyota Kirloskar Motor
44,310
52,202
52,990
Ford India
40,677
41,630
28,465
1,958,284
2,253,396
2,312,136
Ashok Leyland
Total Source: Fourin (2009).
3.3 The process of technology acquisition This section reviews the development process of Chery, Geely, and Tata Motors and analyzes how they acquired the product and process technology necessary to compete with multinational automakers. 3.3.1 Chery Chery was established in 1997 by eight engineers who had worked for First Automobile Works. They sought financial support from the Anhui provincial government and Wuhu city – where Chery’s headquarters and plants were located – and therefore Chery became a local state-owned enterprise. As this history reveals, a part of Chery’s technology derives from the founders’ experiences at First Automobile Works, the oldest and largest domestic automobile manufacturer in China. Chery’s process technology also derives from the equipment bought from Ford and Seat. Chery bought a secondhand assembly plant from Seat in Spain and a secondhand engine plant from Ford in England. Chery’s product technology was secured through copying. For example, the first model “Fengyun” was developed on the basis of the chassis of Seat’s “Toledo.” The best selling model of Chery “QQ” derives from a model named “Spark,” released by SAIC-GM-Wuling Auto Co., Ltd. (SGMW) – a joint venture by GM, Shanghai Automobile Industry Corporation (SAIC), and a local state-owned enterprise. “Spark” had formerly been developed by Daewoo in Korea and named “Matiz.” Because “QQ” strongly resembled “Spark” – or Daewoo’s “Matiz” –, GM and GM Daewoo sued Chery for infringing upon their intellectual property rights in 2004 (Gendai Research
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Institute 2009; Oshika et al. 2009). Another Chery model, “Eastar,” is also a copy of the Daewoo car named “Magnus.” Apart from copying, Chery has vigorously introduced product and process technology from various sources. Such sources include the following: (1) Contracts with engineering companies. The external design of Chery’s cars has been contracted out to Italian design houses – such as Pininfarina and Fumia – and some Japanese design houses. The engines which Chery produces in its own engine plant were developed by an Austrian engineering company, AVL. Chery publicized that these engines had been “codeveloped” by Chery and AVL, but it was rather a one-sided purchase of technology by Chery. The installment of machinery and equipment to a new car plant, and their testing and fine-tuning, need to be conducted by many experienced engineers, and – as a newcomer in the automobile industry – Chery lacks such experience. Chery has contracted out this task to a Japanese engineering company. (2) Employment of experienced engineers. Chery has invited Chinese engineers who were working for western automobile manufacturers. Chery also invited an engineer who had retired from Mitsubishi Motors to work as the vice-director of its Production Management Division. The engineer from Mitsubishi Motors designed a car assembly line for Chery. (3) Purchase of key components. In addition to the engines developed by AVL and produced by Chery’s own plant, Chery buys engines from specialized engine manufacturers. The 1.6 liter engines installed in Chery’s cars were purchased from TRITEC, a Brazilian engine manufacturer that was established by BMW and Chrysler. The 2.0- and 2.4liter engines come from Shenyang Aerospace Mitsubishi Motors Engine Manufacturing Co., Ltd. (SAME) – a joint venture by Mitsubishi Motors and a Chinese state-owned enterprise. SAME sells engines coupled with transmissions made by JATCO, a Japanese transmission manufacturer. By purchasing such key components as engines and transmissions, Chery can not only economize on the costs of developing engines and transmissions on its own, but also take advantage of engineering services provided by the suppliers. SAME helps its customers to match the engines with the vehicle. In a similar manner, Delphi, a supplier of engine control units, helps indigenous Chinese automakers to fine-tune the fuel injection systems and the engine (Oshika et al. 2009). Chery has been quick to apply the technology it bought and copied from all over the world. Production of passenger cars started in 2000, only four years after the company’s establishment, and soon production expanded to a large scale. As of 2009, Chery had already released 14 vehicle models – ranging from mini-size cars, mid-class sedans, SUVs, and MPVs. The speed
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Technology Acquisition by Indigenous Auto Firms
Table 3.4
71
Chery’s automobile production and exports
Year
Production
1999
–
2000
2,767
Exports
2001
30,070
2002
50,398
2003
101,141
2004
79,565
2005
185,588
18,000
2006
307,232
50,000
2007
387,880
119,800
2008
350,006
135,013
2009
508,567
Note: This table includes not only sedan-type cars but also SUVs. Source: China Automobile Industry Yearbook, China Automobile Information Net.
of development of new vehicles has been remarkable for a young car manufacturer which was established from scratch only 12 years ago. However, Chery has been too hasty in churning out new models without adequate assimilation of the technology it has acquired. Quality problems in its products have been revealed several times during the course of its development, leading to a drop in its production volume (Table 3.4). After becoming the fourth-largest car manufacturer in China, Chery’s position has subsequently declined among the top car manufacturers (Table 3.2). 3.3.2
Geely
The history of Geely Automobile Co. Ltd. dates back to 1984, when Li Shufu of Taizhou, Zhejiang Province, and his two brothers established a private factory to produce refrigerator components. In Taizhou, there were many refrigerator-component manufacturers at the time, and Li’s factory was one among them. But in 1989, the government started to suppress investments in refrigerator production, and therefore Li gave up the component business and started producing interior decoration goods. In 1994, Li started producing motorcycles. Because of the expansion of demand for motorcycles in rural areas, Li was fairly successful in his business, expanding production volume to 400,000 units in 1999. In 1997, however, Li started preparing for entry into automobile production. Geely’s automobile production began in 1998. Unlike Chery, which was established by engineers who had worked for First Automobile Works,
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72 Tomoo Marukawa
Table 3.5
Geely’s automobile production and exports
Year
Production
1999
3,885
2000
14,530
2001
21,171
2002
47,370
2003
81,284
2004
93,285
Exports
5,000
2005
148,182
6,835
2006
206,958
15,000
2007
216,774
30,000
2008
220,955
41,241
2009
330,275
Source: China Automobile Industry Yearbook, China Automobile Information Net.
no one among the board members of Geely had previous experience in the automobile industry. Geely’s production stagnated for several years after 1998 (Table 3.5) – because the company failed to make cars of sufficient quality. The measures which Geely relied upon to acquire technology were similar to those of Chery: (1) Copying existing models. Geely’s first car utilized a copy of the product platform of “Xiali,” a small passenger-car produced by a state-owned automaker in Tianjin, and originally developed by Japanese Daihatsu. Geely’s recent model “Panda” was developed on the basis of “Aygo,” a passenger-car produced by Toyota’s joint venture in the Czech Republic. (2) Employment of experienced engineers. Geely, like Chery, absorbed many engineers from automobile manufacturers inside and outside of China. For example, the first president of Geely’s Research Laboratory and now the vice-president of Geely Group is the former president of Daewoo Motor’s research lab. (3) Purchase of key components. One Geely car model was installed with engines produced by Tianjin Toyota Engine Co., Ltd., and transmission produced by Tianjin Aisin. Geely’s recent model “Panda” is installed with continuously variable transmissions (CVT) produced by Antonov Plc of the Netherlands (Gendai Research Institute 2009).
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3.3.3 Tata Motors Tata Motors’ acquisition of technology starts with its collaboration with Daimler-Benz for the manufacture of three- to five-ton diesel commercial vehicles, which began in 1954. Daimler-Benz’s engineers resided in Jamshedpur until the end of the collaboration agreement in 1969 (Kathuria 1996, pp. 205–6). Undoubtedly, formal technology transfer from DaimlerBenz was the most important source of technology acquisition by Tata Motors. The transfer proved successful, making Tata Motors the top commercial vehicle manufacturer in India from the 1960s until today. Tata Motors did not rely on the purchase of key components from multinational component manufacturers. On the contrary, Tata Motors produces most of its key components, and even machinery, in-house. Tata Motors created a highly vertically-integrated structure because the company was located in Bihar, a backward state in India where finding reliable suppliers was difficult. Therefore, Tata Motors has facilities to produce engines, gearboxes, rear and front axles, crankshafts, and camshafts, along with a machine-tool factory and die-repairing facilities (Kathuria 1996, pp. 201–2). Unlike Chery and Geely – which started producing cars around 2000 when many multinational component suppliers and engineering companies were ready to provide their products and services to new entrants – Tata Motors began producing vehicles in an environment where no such suppliers and service providers existed. The highly vertically-integrated structure of Tata Motors’ commercial vehicle manufacturing can be compared to the erstwhile structure of First Automobile Works in China, which was established during the 1950s in an environment similar to that of Tata Motors. When Tata Motors entered the passenger-car segment in the 1990s, however, the situation had changed. As the size and technological capability of the world’s automobile component manufacturers grew, the diseconomy of automakers’ integrating component and machine-tool production became obvious. Besides this, the Indian government liberalized inward foreign direct investment. In order to absorb the latest developments in automobile component technology and create a supplier base for passenger car production, Tata Motors established Tata AutoComp Systems, Ltd., (TACO) in 1996. TACO subsequently created 5 subsidiaries and 15 joint ventures, each specializing in particular automobile components. The partners in the joint ventures include international automobile component manufacturers such as Johnson Controls, Faurecia, Yazaki, T. RAD, Knorr Bremse, Ficosa International, SungWoo Hightech, Owens Corning, Chuo Spring, Hendrickson International, Visteon, GS Yuasa, and Nifco. Unlike at Chery and Geely, the development of cars at Tata Motors was undertaken in-house – mainly at the Pune Engineering Design Center – which employs 1,400 engineers. Using its research and development (R&D) center, Tata Motors astonished the world’s automobile industry when it
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announced that it would develop a new “people’s car” named the “Nano” which would cost only 1 lakh (100,000) Rupees (USD2,500). Cheapness, of course, has been the competitive edge of indigenous Chinese car makers in the Chinese market, but the latter has never produced a car that is as cheap as the “Nano.” Moreover, Tata’s method of cutting costs seems to be more reasonable than those of Chinese makers such as Chery and Geely. Chery and Geely resorted to copying other makers’ cars – so that they could economize on development and testing costs – and using cheap, low-grade materials and components. Tata Motors, on the other hand, tries to achieve low-cost production by streamlining the product design. Tata’s engineers have reduced the side view mirrors of the “Nano” to only one on the right side and have reduced the front wipers to only one. The “Nano” is equipped with neither air-conditioning nor car radio. Tata, however, does not sacrifice the spaciousness of the “Nano”’s passenger compartment – which can seat four persons – nor its safety performance, because the “Nano” is intended as a family car. Tata will also try to reduce production costs by producing the “Nano” on a very large scale – one million units a year – in the future. Major suppliers of the “Nano”’s components will erect their plants near Tata’s assembly plant so that they can economize on transportation costs. Tata will ship the knocked-down components of the “Nano” from the main plant to several assembly plants in various parts of India to cut the delivery cost of getting the cars to market.
3.4 Exports and foreign direct investment Selling automobiles in foreign markets can be an opportunity for automobile manufacturers from developing countries to pursue technological improvement. In their home markets, they can take advantage of protectionist policies implemented by their governments’ and consumers’ preference for domestic products, but in foreign markets, they can enjoy neither of these advantages. Only the advantage of the product itself – including its price and quality – counts in foreign markets. Therefore, exports provide an impetus toward technological advancement for automobile manufacturers. Chery, Geely, and Tata Motors are aware of this fact, and they have been eager to sell their cars in foreign markets. Automobile manufacturers may resort to foreign direct investment when they want to sell their products abroad, or when they want to acquire technology, brand, and sales networks through merging existing companies. Considering the above implications of exports and foreign direct investment for technology acquisition by indigenous automobile manufacturers, this section will deal with the foreign economic activities of Chery, Geely, and Tata Motors.
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3.4.1
75
Chery
Chery started to export its cars as early as 2001, in its second year of automobile production. In 2001, Chery exported 10 cars to Syria (Momomoto 2007). Chery became seriously involved in the development of foreign markets in 2003 when the company established an assembly line of complete knocked-down (CKD) kits in Iran, in cooperation with an Iranian company. By assembling cars in Iran, Chery could halve the burden of the 120% import duty imposed by the Iranian government on finished cars. Hence, Iran has become one of the most important foreign markets for Chery. In 2006, Chery began considering exporting its cars to Malaysia by establishing an assembly line in Malaysia in collaboration with Proton. The plan was suspended, however, because an intellectual property-rights dispute emerged between Chery and GM with regard to Chery’s “QQ,” and the dispute led the Malaysian side to refrain from cooperating with Chery. In the same year, Chery established an assembly line in Kaliningrad, Russia, with the cooperation of Avtotor, a Russian automobile assembler. The reason for the establishment of an assembly line in Russia was the same as in the case of Iran – to lessen the import duty burden. Since then, Russia has become the most important export destination for Chery. Chery has tried to enter the American and European car markets through several schemes. In 2007, Chery reached an agreement with Chrysler to provide seven models of cars and pickups designed and produced by Chery for Chrysler using the latter’s brand. However, this plan did not materialize because of Chrysler’s crisis that started in 2008.1 In 2008, Chery established a joint venture with Israel Corporation in Wuhu, China, the purpose of which was to produce and export cars to the American market. The venture’s production of cars, however, has been postponed until 2012.2 In 2007, Chery agreed with Fiat to create a joint venture to produce cars. Chery expected that this joint venture would open up the European market for Chery-brand cars, but the actual establishment of the joint venture has not yet taken place as of this writing. Thus, Chery’s ambition to enter the American and European car markets has not been realized. On the other hand, the company’s efforts to exploit Russian, Ukrainian, and Middle Eastern markets bore fruit, and Chery’s exports grew rapidly from 2006 until 2008 (Table 3.4). In the first half of 2009, however, Chery managed to export only 12,000 cars, of which only four cars went to Russia and Ukraine.3 The reasons for the sudden stagnation of exports were, first, the shrinkage of automobile demand in all of the world’s major markets excluding China, and second, the rise of the import duty on CKD kits in Russia since October 2008.4 Chery, Geely, and other Chinese automobile manufacturers had taken advantage of the low tariffs on CKD kits in Russia and strengthened their cost-competitiveness. However, since the Russian government increased the tariff rate on CKD kits in October 2008, Chinese
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cars have lost their cost advantage in Russia. In November 2009, the total market share of Chery, Geely, and other Chinese cars added together was only 1% of the Russian market. It turned out that the rapid growth of car exports from China to Russia before 2008 was not a result of the enhanced competitiveness of Chinese cars but rather the result of taking advantage of a loophole in the Russian tariff system. 3.4.2
Geely
Geely has been eagerly trying to exploit the foreign market since 2003. In 2004 – the second year after it started exporting cars – Li Shufu, the president of the company, announced that the company’s target was to export two-thirds of its automobile production by 2015. The destinations of Geely’s exports have been quite similar to those of Chery’s. In 2005, 30% of Geely’s car exports went to Syria. In 2007 and 2008, Ukraine and Russia were the most important export markets. Geely exports CKD kits to Ukraine, and a local assembler assembles cars from the kits and sells them in the local market.5 The volume of Geely’s exports has been smaller than that of Chery (Table 3.5). The difference can be explained by the lack of financial support from governmental banks, such as the Export-Import Bank of China, which Chery has enjoyed. Compared with the company’s modest record in the domestic and export markets, the decision by Li Shufu in March 2010 to acquire Volvo Cars from Ford Motors for USD1.8 billion seems to have been a major gamble for Geely, which will leap from being a local manufacturer – with a track record of only producing cheap cars – to owner of an internationally-renowned brand, famed for its large luxury cars. Lacking adequate funds for the acquisition, Geely is said to be receiving investments from local governments in China in order to amass the funds to acquire Volvo Cars.6 President Li said that the main purpose of the acquisition is to obtain the hybrid-car technology which Volvo Cars has been developing for the past ten years.7 Geely has thus followed the path of many other Chinese firms which have tried to acquire technology through cross-border mergers and acquisitions. 3.4.3 Tata Motors Though the growth rate of Tata Motors’ export volume is modest compared to that of Chery and Geely (Table 3.6) – Tata Motors is more experienced and aggressive in international operations than the Chinese automakers. As early as 2003, Tata Motors started to export cars to the European market using the brand and sales channels of MG Rover – a former British carmaker which was later acquired by a Chinese automobile manufacturer. Tata Motors has been aggressively investing in foreign automobile manufacturers since 2004, when it acquired Daewoo Commercial Vehicles Company, the second-largest truck maker in South Korea. In 2005, it acquired Hispano Carrocera, a Spanish bus manufacturer. In 2006, it established a joint
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Table 3.6 Tata Motor’s automobile production and exports Year
Production
Exports
2004
378,479
26,278
2005
427,012
46,020
2006
554,039
53,726
2007
576,084
54,841
2008
515,916
43,075
Source: Fourin (2009).
venture with Thonburi Automotive Assembly Plant Company in Thailand to produce pickup trucks and sell them in Thailand. In 2008, Tata Motors bought Jaguar Land Rover – a British manufacturer of luxury cars and SUVs – from Ford for USD2.3 billion. Tata Motors has started to utilize its assets acquired from foreign automakers for the development of strategic products. In 2009, Tata Motors launched a series of trucks named “World Trucks.” The trucks were developed by Daewoo Commercial Vehicles and Tata Motors European Technical Center, and they will be sold in India and other South Asian countries, South Korea, South Africa, and the Middle East (Fourin 2010). Tata Motors is several steps ahead of Chery and Geely in cross-border mergers and acquisitions and utilization of the R&D capabilities of foreign automakers it has acquired.
3.5
Conclusion
Indigenous automobile manufacturers have occupied important positions both in India and China. From the standpoint of growth in production volume, Chery and Geely – based in China – are growing more rapidly than Tata Motors – based in India. Besides the growth rate of individual manufacturers, the number of new entrants to car manufacturing in China is also impressive. There were 19 indigenous passenger car manufacturers in China, as of 2009, while there were only three in India. The process of technology acquisition has differed significantly at Indian and Chinese automakers. Indigenous Chinese manufacturers tend to rely on external resources, while Tata Motors – during its long history – has built up its in-house ability in R&D and component production. Tata Motors seems to be more experienced in utilizing its R&D resources – as revealed by its launch of the “Nano,” an extremely cheap car developed independently by Tata Motors. Indigenous Chinese car manufacturers, on the other hand, often rely on copying foreign carmakers’ models in order to economize on
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development costs. However, the speed of development of new vehicles is staggering in the case of Chinese automakers. This speed has been achieved by use of external resources, including foreign design and engineering companies. Tata Motors is several steps ahead of indigenous Chinese automakers in cross-border mergers and acquisitions and the utilization of foreign R&D resources it has acquired. The Chinese automakers, however, are very quick to exploit foreign markets, and they are now trying to absorb foreign R&D capabilities through cross-border mergers and acquisitions. If the Chinese automakers are also quick to assimilate the R&D resources they have acquired, it is likely that Chinese automakers will soon surpass Tata Motors in R&D capability. The author is unable to fully discuss the reasons for the differences in the technology acquisition process of Chinese automakers and Indian automakers, but some brief observations can be stated here. First, competition in the car market is fiercer in China than in India. There were 39 car manufacturers in China in 2009, while there were only 13 in India. Indigenous Chinese carmakers need to launch new models frequently just to maintain a presence in the market. To make up for the paucity of their in-house R&D capability, indigenous Chinese carmakers need to rely on external resources and copying. Second, job-hopping is rampant, especially among engineers in China.8 The management hesitates to become involved in long-term development projects when engineers are unreliable, and thus only projects from which quick results can be expected are undertaken. These factors may explain the difference in the technology acquisition process of Chinese and Indian automakers.
Notes 1. 2. 3. 4. 5. 6. 7. 8.
21 shiji jingji baodao, October 22, 2008. 21 shiji jingji baodao, October 21, 2009. Jingji cankao bao, September 2, 2009. 21 shiji jingji baodao, October 22, 2008; Zhongguo qiche bao, December 21, 2009. Jili huibao, No. 49, February 2008. 21 shiji jingji baodao, March 30, 2010. Jingji cankao bao, December 25, 2009. For example, the person in charge of R&D at Geely was the president of the R&D center of another indigenous carmaker only four years previously.
References Fourin, 2009, Indo jidosha buhin sangyo 2010 [Indian Automobile and Component Industry 2010], Nagoya: Fourin (Japanese). Gendai Research Institute, 2009, Chugoku jidosha sangyo no kyosoryoku ni kansuru chosa kenkyu hokokusho [A Report on the Competitiveness of the Chinese Automobile Industry] (Japanese).
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Technology Acquisition by Indigenous Auto Firms 79 Kathuria, Sanjay, 1996, Competing through Technology and Manufacturing: A Study of the Indian Commercial Vehicles Industry, Delhi: Oxford University Press. Momomoto, Kazuhiro, 2007, “Kizui kisha, Kichiri kisha [Chery Auto and Geely Auto]” in Tomofumi Amano and Hiromi Ohki, eds., Chugoku kigyo no kokusaika senryaku [Internationalization Strategy of Chinese Firms], Tokyo: JETRO (Japanese). Oshika, Takashi, Ryuichiro Inoue, Jewheon Oh and Shinya Orihashi, 2009, “Jidosha sangyo [Automotive Industry]” in Junjiro Shintaku and Tomofumi Amano, eds., Monozukuri no kokusai keiei senryaku [International Management Strategy for Manufacturing], Tokyo: Yuhikaku (Japanese). Qi, Guoqiang, ed., 1996, Zhongguo qiche gongye shi [The History of the Chinese Automobile Industry], Beijing: Renmin jiaotong chubanshe (Chinese). Zhongguo qiche jishu yanjiu zhongxin, ed., 2007, Zhongguo qiche gongye nianjian 2007 [Chinese Automotive Industry Yearbook 2007], Beijing: Zhongguo qiche gongye nianjian qikanshe (Chinese). Zhongguo qiche jishu yanjiu zhongxin, ed., 2009, Zhongguo qiche gongye nianjian 2009 [Chinese Automotive Industry Yearbook 2009], Beijing: Zhongguo qiche gongye nianjian qikanshe (Chinese).
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4 Capability-Building via Interfirm Relationship and In-House Employment in China and India: A Comparative Study of the Motorcycle Industry Moriki Ohara
4.1
Introduction
This paper compares the firm-level capability-building systems – both interfirm and in-house – in China and India by closely observing the operations of major indigenous motorcycle manufacturers – makers – and their major components manufacturers – suppliers – in the two countries. The study examines how the skill/knowledge formation of both staff and workers has been conducted within firms, and how interfirm organization of the division of labor supports the upgrading of manufacturing capabilities. In-house and interfirm capability-building mechanisms are mutuallycomplementary and comprise different systems in both countries.1 We will confirm the different nature of the systems – in China, firms are not active in firm/transaction-specific investment to create their own “proprietary” assets, or tend to avoid risk by actively utilizing outsourced standardized resources, compared to modernized Indian firms2 that tend to do more of these kinds of investment – both in-house and interfirm. This chapter, after introducing data and background information on the industry, depicts two different sets of socioeconomic institutions in the motorcycle industry in China and India – (1) interfirm relations and (2) in-house skill formation mechanisms – and will show how they are interrelated in a complementary manner in both countries. The field research to tackle interfirm relations was mainly conducted before 2004, and in-house skill-formation mechanisms were evaluated from the survey conducted between 2006 and 2008, in China and India.
80
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81
Data and firms interviewed
Concerning China, we mainly observed Grand River Group Co., Ltd. – hereafter, Grand River –, China Jialing Industrial Co., Ltd – hereafter, Jialing –, and Chongqing Zongshen Motorcycle Group Co., Ltd., – hereafter, Zongshen –, and their 22 important suppliers – six for Grand River, seven for Jialing, and nine for Zongshen – that have/had particularly close relationships with them. Grand River is a private manufacturer established in 1991 and has enjoyed the highest production in China successively since 2003. Jialing is a large state-owned maker that has initiated the development of the Chinese motorcycle industry as a pioneer since the late 1970s. Zongshen is a young maker that was established and began motorcycle production in the mid-1990s. It is one of the most typical and successful privately-owned makers that grew very rapidly in the late 1990s by purchasing and assembling external standardized parts of existing dominant models. I conducted surveys on Jialing and Zongshen and their suppliers twice, first in 1998– 1999 and then in 2002–2004, and observed the changes during the interim (Ohara 2006). For some reason, many of the suppliers that I surveyed at that time now sell the largest part of their production to Grand River, reducing the portion to Jialing or Zongshen in their production. In the latest survey, conducted in 2007–2008, I reorganized the results into three portions – six for Grand River, seven for Jialing, and nine for Zongshen. In India, Bajaj Auto Ltd. – hereafter, Bajaj – and its ten important suppliers were surveyed. For comparison, Hero Honda Ltd. – a maker capitallyaffiliated with Honda; hereafter, Hero Honda – and other suppliers in close transaction relationships with Hero Honda, TVS, and second-tier suppliers were also surveyed.
4.3 Overview of the motorcycle industry in the two countries Almost 90% of the world’s motorcycles are now produced and consumed in Asia – in terms of production units: 25 million motorcycles – more than half of them – are produced in China, and 8 million – about a quarter of them – were produced in India as of 2007. The two countries occupy critical and unique positions in the world motorcycle industry. It is noteworthy that, in these countries, indigenous makers stand in the leading position in the industry in each country (Table 4.1). In India, the number of motorcycle makers in domestic production is less than ten, and 75% of the market share is still occupied by the top three makers (Figure 4.1). Bajaj is India’s leading and oldest motorcycle maker, and – though
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Table 4.1 Motorcycle manufacturers in China and India, 2006–2007 Main makers China
1 2 3 4
5 6
7 8 9
India
1 2 3 4 5 6 7
Foreign capital Production share (1000 unit)
Grand River Group Co. Ltd (Grand River) Loncin Holdings Ltd. Chongqing Jianshe Motorcycle Co., Ltd. Chongqing Lifan Industry (Group) Co., Ltd. China Jialing Industrial Co. Ltd (Jialing) Chongqing Zongshen Motorcycle Group (Zongzheng) China Qianjiang Group Co., Ltd. Luoyang Northern Ek Thai Ek Chor Chor Motorcycle Co. Ltd. Sundiro Honda Motorcycle Co., Ltd. about 140 other makers (registered) Hero Honda Motors Ltd. Bajaj Auto Ltd (Bajaj) TVS Motor Company Ltd. Honda Motorcycle & Scooters Ltd., Yamaha Motors India Ltd Kinetic Engineering Ltd Enfield India a few makers
Honda 50%
Share (%)
2,825
11.1
1,807 1,593
7.1 6.3
1,571
6.2
1,481
5.8
1,394
5.5
1,351
5.3
932
3.7
888
3.5 45.6
Honda 26%
3,207 2,202 1,352
39.3 27.0 16.6
Honda 100%
883
10.8
Yamaha 100%
300
3.7
74 37
0.9 0.5 1.3
Sources: ZQGNB (2008), SIAM (2008), Honda (2008).
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83
100 90 80 70
India China
60
Taiwan 50
Japan
40 30 20 10
07
04
20
20
00
95
90
20
19
19
85
80
19
75
19
71
19
65
19
60
19
19
19
55
0
Figure 4.1 Share of the top three motorcycle manufacturers in selected Asian economies (in terms of domestic production, %) Sources: ZMGB (1995), ZQGNB, SIAM, and Honda – various years, INTEOS (2001), Shih and Chen (2004).
it was overtaken by Hero Honda in market share from the mid-1990s – Bajaj is still No. 2 and its market share has been increasing steadily in recent years. The picture of the Chinese motorcycle industry is very different from that of India. There are more than 150 officially-registered makers and their market share is fairly dispersed (Table 4.1). No single firm has a large enough market share to influence the rest. Particularly interesting is the fact that, contrary to the other Asian major motorcycle manufacturing economies – Japan, Taiwan, India – where the market share concentrated as the industry entered into the full-fledged development stage, only in China has the concentration ratio declined as the industry entered into it (Figure 4.1). Jialing used to have as large a share as around a quarter until the early 1990s. At that time, 80% of the market was occupied by the ten largest firms, and all of them were state-owned firms. However, as the domestic market expanded at an unprecedented pace in the mid-1990s, many new makers that were very competitive in price – including Zongshen – emerged and many traditional state-owned makers – including Jialing – declined in market share. With the rapid expansion of Grand River the share of top producers became slightly concentrated after 2003. Grand River has now become the largest
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indigenous motorcycle maker in Asia – excluding Japanese makers. It is noteworthy that, only in China is the share of Japanese-affiliated makers very small – the total share of nine Japanese-affiliated makers in China is as small as 10%. There is a large disparity in the motorcycle industry between China and India in terms of the harshness of price competition. In India, a sharp drop in motorcycle prices cannot be observed during the 1990s. But in China, the average price fell as much as 40% during the ten years from the early 1990s, despite the fact that their main products were upgraded from 100 cc to 125 cc during the same period. One of the critical technical reasons for China’s sharp drop in motorcycle prices was that – since the 1990s – numerous makers have redundantly produced “imitations” or “minor-change versions” of a few standardized – dominant – models, which were originally developed by Japanese makers (Ohara 2006). In India, leading makers like Bajaj develop and produce their own models, equipped with their originally-designed engines, and such blatant and harsh price competition among many homogeneous makers experienced in China has not been observed. This situation has not fundamentally changed in the latter half of the first decade of the twenty-first century.
4.4
R&D activities of the motorcycle makers
This section briefly overviews the different statuses of the innovative activities and capabilities of the motorcycle makers; Grand River, Jialing, Zongsheng, and Bajaj. By innovative activities, this paper mainly focuses on their product development activities. Bajaj started scooter production with technological assistance from Piagio in the 1970s. Well protected by the “license raj” of the Indian government, it enjoyed a fairly preferential competitive environment until economic liberalization. However, after a new competitor, Hero Honda – Honda’s affiliate in India – emerged in the 1980s, Bajaj started to prepare for a new era of competition by collaborating with another Japanese manufacturer – Kawasaki – in the field of motorcycle products. After the reorganization of suppliers – which will be explained later – it strengthened its R&D capabilities, especially after the late 1990s. Now, it enjoys the largest number of R&D staff in Asia, 400 – excluding Japanese makers, which is larger than Grand River’s 260, Jialing’s 250, and Zongshen’s 300. The outcome of R&D activities is also prominent: a new engine system with the “digital twin spark” engine for more efficient fuel usage in 2005, and other new engines with small displacement under 150 cc. Bajaj is now recognized by Honda and Yamaha as a strong competitor not only in cost and sales, but also in technological frontiers in small-scale engines that are suitable for the Indian market.
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85
Many Chinese manufacturers also collaborate technologically with the dominant Japanese manufacturers. Jialing has had technological assistance from Honda since the early 1980s and is established, with Honda, as a jointly-capitalized motorcycle manufacturer. Grand River also has a strong technological collaboration with Suzuki and has established a jointlycapitalized R&D center with them. It also launched a new large-scale motorcycle factory with Suzuki in another part of China. However, in contrast to their Indian counterparts, they are not deemed as technologically-strong competitors – in terms of R&D – by Honda and Yamaha. For example, Grand River is rather modest in its expansion of R&D capability. It has two R&D centers – one is for the Suzuki brand and the other is for its own brand. The focus of its own R&D center is adaption to local markets – especially in rural and small-scale city areas – and it is thus not interested in technologically-original engines or other cutting-edge new frontiers. Jialing and Zongshen are more aggressive in adopting new technology into their products, and the two show apparent interest in larger engines – 400 cc and 600 cc, or racers. They have already started collaborating with European manufacturers and distributors and are trying to expand their exports. However, the outcome of such efforts is not yet apparent. The exports of the two – especially that of Zongshen – are still mainly at the low-end world market – such as Africa or other low-income countries – and the product is the C100 – an old and very standardized model of Honda’s, originally developed in the late 1950s by Honda. The size of R&D activities is not large, either in terms of expenditure or personnel, compared to Bajaj.3
4.5 Interfirm relations between makers and suppliers in the three countries This section compares the mode of production networking or interfirm relations in terms of how participating firms are trying to build manufacturing capabilities between final motorcycle manufacturers – hereafter, makers – and the important first-tier network firms that supply important parts to the makers – hereafter, suppliers4 – in China and India. For comparison, we set two ideal types of networking method, and compare the realities of different firms with these two ideal types to distinguish their organizational characteristics, similarities, and differences. An “integrated type” is an organization with division of labor where the core maker sets a common target for suppliers, exerting active leadership over them in managing incentive mechanisms and monitoring to enhance the capabilities of the network as a whole. The risk of tackling innovative activities – especially for new product development – is also carefully
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evaluated by the core maker and distributed within the network. A “dispersed-type” is a typical market-oriented organization where the leadership of the core maker is weak – with less sharing of common goals and information/knowledge – and suppliers seek their own upgrading of capabilities. The risk of innovative challenges is also solely borne by participating firms. The critical points for classifying the two ideal types are the following four:5 1) “maker’s outsourcing structure” – how the maker divides in-house and outsourced parts, 2) “multisourcing” and “dependency” – how the maker creates competition among rival suppliers that supply identical parts to the maker, 3) “risk sharing,” and 4) “supplier development activities” – how the maker deals with suppliers directly in transactions. Point 3) shows how the risk arising in developing new products is shared between them, and point 4) shows what kind of activities makers are initiating to upgrade suppliers’ capability. 4.5.1 Maker’s outsourcing structure Table 4.2 shows the makers’ outsourcing structure – the situation around 2007–2008 for China and 2004–2005 for India – and the trend of change at that time. The changing direction of China in the table is judged by comparing the first survey in the late 1990s, the second survey in 2003– 2004 – for details on China, see Ohara 2006 – and the third survey in 2007–2008. 4.5.1.1
Degree of dependency on outsourced parts and suppliers
The outsourcing ratios6 of Jialing and Zongshen are lower than those of Japanese makers. Jialing – as a typical large-scale state-owned enterprise from the planned economy era – has a tendency to produce important parts in-house.
Table 4.2 Outsourcing structures of Asian motorcycle makers No. of suppliers
Affiliated suppliers (cap relations)
Change
No.
Foreign Collab.
Grand River
380
↓
5
0
Jialing
350
↓
5
1 (cab)
Zongshen
500
↓ 700 (90s)
Several
0
India
Bajaj
210
1400 (97)
0
0
Japan
Honda
200
>30
Yamaha
200
Several
China
Sources: Interview by the author, Annual Report of Bajaj Auto Co. (various years).
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It is noteworthy that Bajaj has a fairly high outsourcing ratio, and this is the result of Bajaj’s drastic transformation in purchasing policy under the “vendor rationalization policy.” Bajaj used to produce in-house as much as 50% of necessary parts and purchase the rest from as many as 1400 suppliers in the mid-1990s. The outsourcing policy at that time was such that it produced as much as possible by itself, purchased critical parts from foreignaffiliated suppliers or imported them from abroad, and used many suppliers to make unimportant parts. However, from the late 1990s, it began to outsource many in-house processes for parts,7 and reorganized the “flat layer”type supplier organization into a more “multilayer” or “hierarchic” type, by selecting capable first-tier suppliers and arranging many others as secondand third-tier suppliers under them.8 The primary aim of this reorganization was to enhance the capability of developing new models (Bajaj 2002). By doing this, Bajaj can focus more resources on new-model development activities, with more parts-development activities outsourced to first-tier suppliers. Through such arrangements, Bajaj put emphasis on initiating activities to upgrade the technological capabilities of suppliers. The outsourcing structures of Grand River and Jialing are almost the same as those of their Japanese counterparts. Zongshen has a fairly strong in-house policy at present. However, it had an outsourcing ratio as high as 90% until the end of 1990s. As stated above, the high outsourcing ratio was the result of its technological characteristics when it started business in the 1990s. It started business being heavily dependent on the “de facto standardized” parts purchased from a large number of local suppliers in Chongqing. However, it should be noted that, as requirements for quality and new product development increased mainly from 2000, Zongshen has increased the kinds of parts manufactured/processed in-house. In particular, after completing the “Zongshen Industrial Zone” project where it established important parts production bases in 2005, it has significantly increased the in-house ratio to as high as 30%. However, a common characteristic of the three Chinese makers is that they use more suppliers than their Japanese and Indian counterparts. The most recent number of 1st-tier suppliers used by Grand River is 384, by Jialing, 300, and by Zongshen, 500, in 2007–2008 – fairly larger number if compared to 210 by Bajaj in 2007, and around 200 by Honda and Yamaha in 2006 – and they used to transact with an even larger number of suppliers in the late 1990s.9 This is the result of the “multisourcing” policy of Chinese manufacturers, as will be discussed soon. 4.5.1.2 Affiliated suppliers: intention to build their own technological bases Though the three Chinese makers also have a few affiliated suppliers, most of them are nothing to do with foreign companies. The one exception is a carburetor supplier established between Jialing and Japanese Mikuni, which also has a strong expertise in the field. However, according to my
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interviews, Jialing has had little intervention in the management of the company except for imposing a profit target, and for the company, Jialing is no longer important in terms of volume of transactions. Instead, its most important customer is now Grand River and it recently established a factory near Grand River to assist with its new product development. The intention of Chinese makers to establish affiliated suppliers does not seem to be the result of a strategic decision to have important suppliers assisting their product development. For example, Grand River has five affiliated suppliers in CVT for scooters, cushions, suspensions, seats, aircleaning parts, and electroplating processes. All of them are for the purpose of cutting costs by substituting imported parts or parts with domestically unstable supply in terms of quantity and quality, and most of them do not have sufficiently strong competitiveness compared to outside expert suppliers.10 There does not seem to be any intention among Chinese makers to depend on powerful international players for several critical parts, particularly with a view to strengthening their development capability. In this point, Indian Bajaj is seemingly more similar to its Chinese counterparts, with almost no suppliers capitally-affiliated with it. However, as will be analyzed later, Bajaj tends to have close and closed relationships with key suppliers, and – though capitally not connected – it has several very critical parts suppliers: indigenous, with closed relationships in such areas as cushions, suspensions, clutches, engine parts, and plastic cowlings. Bajaj seems to be trying to be technologically independent from powerful foreign – in the case of motorcycles, Japanese – suppliers. In terms of strong will to have its own supplier base for further capability both in terms of product development and manufacturing, Bajaj is more similar to Japanese makers, not to Chinese counterparts. 4.5.2
Multisourcing and dependency rate
The “dependency rate” in Table 4.3 is the average ratio of sales to main transaction partners – four makers in two countries – out of all sales of main products11 of the suppliers surveyed. The average dependency of Bajaj’s suppliers – on Bajaj – is the highest, 70%, and that of Chinese suppliers is the lowest. Concerning the direction of change in the dependency ratio, the figure is showing a declining trend in China, whereas it is increasing in India. The “number of transaction partners” in Table 4.3 is the number of makers with which the supplier is simultaneously in a transaction relationship. This figure is small in India and high in China, too. In sum, the transaction relationship is closed in India and open in China. As for the situation of multisourcing, Bajaj utilizes a single-source policy in most cases. This is noteworthy if we remember the maker’s recent very rapid expansion in production volume. In my interview with them, Bajaj said that they use a single-source policy with suppliers for 80% of parts. From the maker’s perspective, under a single-source transaction, the maker can more
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Table 4.3 Multisourcing and dependency rate Dependency ratio
China
India
n
(%)
trend
Grand River
6
24
↑
Jialing
6
15
Zongshen
9
22
No. of transaction
Multisourcing of identical parts
trend
single
two
>3
8.5
↑
0
5
1
↓
15.4
↑
0
3
3
↓
20.4
↓
0
4
5
Bajaj
7
71
↓
2.3
4
3
0
(all)
8
75
↓
2.1
5
3
0
Source: Interview by the author.
easily conduct technical evaluation and monitoring of each supplier,12 and from the supplier’s point of view, the supplier can make a commitment – a transaction-specific investment – with greater confidence. However, since the supplier can enjoy a monopolistic position in transactions for parts, for the maker, there is the risk of a moral hazard problem occurring with the supplier. In contrast, we observed no cases of single-source-based transactions in China. The top management of Zongshen explained to me that “if we concentrate our transactions on one supplier, it is often the case that we cannot control them. That is why we use two suppliers for every single part.” Jialing also answered in the same way. However, according to suppliers, two makers often purchase an identical part from more than three suppliers. This is probably because the two-source policy of the top management has not completely filtered down to the coalface staff in charge of purchasing, for some reason.13 However, we can also observe the trend where makers are concentrating transactions on a smaller number of suppliers in comparison to the late 1990s, and there is now a higher ratio of two-source transactions. 4.5.3 Risk sharing14 Table 4.4 shows the way of sharing the development costs of new products – motorcycle parts. For the sake of convenience of observation, we mainly discuss the sharing of die/mold costs that occupy a significant part of development costs. In this table, “fully paid by the maker” means that the maker insures the depreciation of all die/mold costs. “Fully paid by the supplier” means that the maker does not insure depreciation.15 In this case, if the product does not sell well, the loss will be borne fully by the supplier. So, all the development risk is borne by the supplier. “Sharing” means that, by
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Table 4.4 Risk sharing Dev’t cost (die/mold)
n
Fully paid Fully paid by maker Sharing by supplier
Risk of dev’t failure
Unpayment
China Grand River
6
1
3
2
medium non
Jialing
India
6
0
2
4
high
sometimes
Zongshen 9
0
3
3
high
sometimes
Bajaj
7
2
1
4
low
non
(all)
8
3
1
4
low
non
Source: Interview by the author.
providing advanced payment or ensuring payment of part of the mold/die costs, they are sharing the risk. My previous research result shows that Japanese motorcycle makers have institutionalized the mechanism of maker’s risk absorption, under which suppliers are expected to make greater commitment to product development, which is the same as in automobile industry (Asanuma and Kikutani 1997; Ohara 2006). Such a system can be managed only in a situation where makers and suppliers share information/knowledge on the technology that suppliers use, and the maker can make a proper evaluation of the concrete costs of development based on the shared information. On the other hand, Chinese makers force suppliers to shoulder most of the risk. When development fails – meaning that the product does not sell well in the market – the suppliers take all the risk. The failure rate of development is high in China. In particular, in the late 1990s, many suppliers answered that the rate of success – meaning the possibility that the supplier can depreciate the development costs – was around 20%. Despite the high failure rate, during that period, since there were so many suppliers seeking business opportunities, makers did not have difficulty in finding transaction partners. In practice, suppliers also had measures in place to reduce their risk. Since their products were imitation or minor-change versions of dominant models, suppliers could find other makers who would buy them. In addition, suppliers transferred their risks to their own – second-tier – suppliers in the same way. In the 1990s, nonpayment behavior was very widespread over the business. When makers do not pay their first-tier suppliers, those suppliers do not pay their second-tier suppliers. Under such circumstances, both makers and suppliers were reluctant to make “transaction-specific” investments, and their products became more and more “homogeneous” at the parts level. Makers and suppliers
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were reluctant and actually unable to share technological information/ knowledge between them. When defective parts were “found,” makers simply returned them without analyzing the true causes of the defect – that is, without knowing whether the parts were really defective – and even asked suppliers for compensation. However, it is noteworthy that, in 2003–2004, the second survey in China revealed that more firms were beginning to share development costs compared to the late 1990s. Firms were more deliberate and used more systematic methods to implement development projects, which reduced the rate of development failure as well as the risk to the supplier significantly. It is considered to be the reaction of overall industry after they experienced the dead-end of the profit decline in the late 1990s. Grand River is famous for its most deliberate attitude of not transferring risks to suppliers by deceiving them. Concerning India – according to Table 4.4 – Bajaj’s suppliers also bear die/ mold costs, like the Chinese firms. The difference from China is that the failure rate of development is very low and nonpayment behaviors were not observed in Bajaj’s case. In reality, it would be safe to say that the development costs were virtually borne by Bajaj, but the method of sharing was not as well institutionalized as in Japan. 4.5.4 Nurturing suppliers Makers may practice supplier nurturing – “supplier development” – activities, in which the maker takes various kinds of measures vis-à-vis suppliers to promote their capability growth in ways that the maker expects (Krause 1997). Supplier-nurturing activities include direct measures to enhance transaction-specific and indirect capabilities to develop infrastructural – multipurpose – capabilities, including technological/financial assistance, personnel exchange, information sharing, stabilization of transactions – for example, concentration of orders on specific suppliers, etc. As mentioned above, under the “vendor rationalization policy,” Bajaj began to concentrate transactions on a smaller number of first-tier suppliers that have development capabilities. Since then, Bajaj has practiced several activities to nurture them. All the suppliers surveyed for this study participate in TPM – Total Productivity Maintenance – activities that Bajaj initiated around 2000. A typical case of Bajaj’s supplier-nurturing activities observed by the study is muffler supplier i-7 (See Appendix). Before the policy change, Bajaj used to purchase parts related to the exhaust system from about a hundred suppliers. However, from the end of the 1990s, Bajaj designated five of them as unit-parts – that is, first-tier – suppliers, and supplier i-7 came to manage the integration of many second-tier suppliers. Along with the change, i-7 accepted financial support at the initial phase and technical support from Bajaj, including personnel exchanges. Bajaj also initiates technological training of second-tier suppliers using i-7 as an example.
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An interesting point found in the survey about Bajaj’s suppliers is that all the six metal-processing suppliers surveyed emphasized their efforts in raising their own closely-related second-tier suppliers, and they say some of the second-tier suppliers only transact with them. It is their endeavor to become a superior first-tier supplier with stable quality and delivery. The effort to raise second-tier suppliers was not heavily emphasized in the survey in China. This may suggest that in India, suppliers become technologically weaker further down the hierarchy, compared to China. Concerning the three Chinese makers, not many concrete cases of supplier development were observed during the survey, particularly in the late 1990s. Until the 1980s, Jialing had even provided support for the fixed cooperative suppliers – mostly state-/collectively-owned – including technological training opportunities, via Honda, and financial support. Jialing tried to nurture capable suppliers that could manufacture parts based on the design drawings developed by Honda for the purpose of substituting the imported parts – designated by Honda – in a planned manner. However, in the 1990s, as many, mainly privately-owned suppliers emerged with this type of capability, Jialing had little need to raise such suppliers for themselves. In the first half of the 1990s, such cooperative relationships between Jialing and former cooperative suppliers disappeared. Grand River, on the other hand, was more active than Jialing in the 1990s. Grand River’s basic attitude to supplier development was “to wait patiently until they become competent.” The strength of Grand River – according to the president of the company – is that it directly applies what they learnt from Japanese manufacturers, especially Suzuki and Honda,16 and it does not pursue rapid expansion but tries its best to maintain quality level. That was considered as the main reason why the company was not one of the largest during the 1990s. Zongshen started to manage a “quality assurance system” with its important suppliers with whom they established the “Zongshen Group.”17 Under this scheme, Zongshen collaborated with suppliers on standardized operations, and engineers of Zongshen routinely circulated among suppliers and monitored whether or not they were operating properly as designated in the standard. However, in the second survey in 2004, such circulation had been interrupted, except for c-13. The reason for the interruption was that, since the capability raised by such a system is an infrastructural – multipurpose – capability such as production management, and since suppliers supply similar parts to Zongshen’s many rivals, Zongshen found it does not need to pay for them. In 2004, however, Zongshen started a few new collective schemes in cooperation with important suppliers, including a market – dealer – visiting project and discussion with material suppliers. Such collective coordination to enhance technological capability is noteworthy though – at the time of the survey – they conducted such
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activities as ad hoc projects, not “routine” activities institutionalized in ordinary operations. 4.5.5 Summary: modes of interfirm capability formation In sum, during 2003–2005 and 2007–2008, Bajaj formed a cooperative production network with important suppliers, which is closer to the typical “integrated type” than their Chinese counterparts. They shared risks and practiced active supplier-nurturing activities and strengthened their integrity during these several years. By contrast, the production networks of Chinese makers are the “dispersed” type, particularly in the late 1990s. Their relationship has been more open and unstable, and the sharing of risks has not been practiced. Particularly in the 1990s, this tendency was prominent under the circumstances of very frequent failures of development and blatant risk-transferring and nonpayment. However, after 2000, the relationship has been transforming into the “integrated type” – as shown by our observations, such as makers’ higher concentration of orders on a smaller number of suppliers, less prominent risk-transferring, and the beginnings of more systematic supplier nurturing activities.
4.6
Comparison of in-house skill-formation mechanisms
This section examines the ways of building capability inside firms in China and India, focusing on the skill development of staff and workers at motorcycle-parts manufacturers. The data of this section are collected mainly from interviews conducted in 2007 and 2008. 4.6.1 Profile of operations First, the basic differences in the operation of parts suppliers between China and India are overviewed in this section. This is due to the assumption that internal skill-formation processes and mechanisms are considered to be closely related to the basic characteristics of their direction of management. The average “gross margin rate”18 of 11 Chinese suppliers was 7.3%, whereas the average “profit after tax” was 14.5% for the five Indian suppliers from whom we received answers. It is generally said that, in order to secure a positive final profit – after tax – for manufacturing firms, the “gross margin rate” should be more than 10–12%. In fact, most of the Chinese suppliers that we interviewed said that their final profit was nearly 0%. The lower profit of Chinese motorcycle manufacturers – and the higher profit of Indian manufacturers – can be examined using larger publicized statistics in similar industrial categories.19
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The average size of the parts suppliers that I investigated by (a) employment size was 1,585 employees per firm for China (24 firms) and 640 employees per firm for India (13 firms), and the average size investigated by (b) revenue size was 56.5 million USD for 11 Chinese firms and 56 million USD for their seven Indian counterparts. Interestingly, the revenue size is almost the same, whereas Chinese firms apparently employ more staff and workers. A similar image can also be seen from the data of a larger sample number.20 This is partly the outcome of the gap in profit between the two. However, the price – cost – of production and the production size – in units – also seem to be a decisive factor in this phenomenon. The cost cannot be comparable between the firms of two countries since their products are not all the same. But for the production size of some similar companies, there is a difference. The largest Chinese engine parts die-casting – aluminum – manufacturers produce as many as 7 to 12 million units per year, the largest gear manufacturer produces 10 million sets of transmission gear units, and piston suppliers produce 9.5 million units, whereas the production level of their Indian counterparts is somewhere in the range of 2 to 3 million units for crank cases or transmission gear units. The number of production units of Indian first-tier suppliers does not usually exceed 1 million, but many Chinese counterparts surveyed produce more than 1 million. We can speculate that Chinese firms are using a larger number of workers to make a larger number of units, and that the price of one unit is far lower than in India. And from the case of final production – of motorcycles – in the market, Chinese firms produce a far larger volume for one lot – kind of parts – than Indian firms. And it is also easily presumed that workers are engaging in more specialized work than their Indian counterparts in their in-house division of labor – where a far larger number of workers are making fewer kinds of products. 4.6.2
Wage rate and liquidity
The average monthly wage rate for staff and engineers is 420 USD in six firms, and that of workers is 208 USD in seven firms in India. In China, the wage rate of staff/engineers is 370 USD (20 firms) and that of workers is 213 USD (20 firms). The wage rate of worker-level employees is almost the same between China and India, but at the staff/engineer level, the wage rate is higher in India than that in China. There is a difference in the liquidity of labor between the two. In Indian firms, the average attrition rate at the staff level – managers, engineers, and core technicians – is 13.2%, for six firms, and that at the general operator level is 5% (seven firms). The latter figure is calculated from data including contracted workers. In China, the average attrition rate at the staff level is as low as 1.4% (for 20 firms) and that at the operator level is 11.1% (for 20 firms). In India, staff-level workers have more incentives or opportunities to move
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firms than worker-level employees. On the other hand, Chinese operators have more incentives to change firms than staff. It should be noted that most of the Chinese firms answered that more than five years ago, the attrition rate was far higher than at present – 20–30% a year. Along with the fact that staff-level laborers earn higher wages and have higher liquidity, presumably in India staff-level labor is scarcer than worker-level labor. In China, on the other hand, worker-level labor is scarcer vis-a-vis staff than in India. This interpretation sounds odd from the viewpoint of the conventional image of both countries, where it is believed that abundant rural workers have been the source of Chinese competitiveness and where there are a large number of elite people produced in India’s education system, famous for its historical emphasis on higher education. However, thinking about the supply side for the respective types of labor, it may make sense. It may be the result of the fact that in India, where highly educated people tend to enter the IT service sector that absorbs many of the graduates of engineering colleges, staff in the traditional manufacturing sector such as the motorcycle industry might be scarce compared to workers. On the other hand, the manufacturing sector in India is not yet as fully developed as China’s, which might restrict the demand for worker-level labor. In China, since there is also a massive amount of other manufacturing factories with job opportunities, workers of motorcycle-parts suppliers can find more opportunities elsewhere than in India. 4.6.3 Career-climbing opportunities from the bottom In Chinese firms, it is not rare to find cases where former line operator-level workers climb up to become management staff. Five firms out of fifteen that were asked the question have factory managers who climbed up from operator level, ten have line chiefs who used to be workers, and most of the unit chiefs used to be workers. In India, two out of four firms have a supervisor – equivalent to China’s unit chief – who climbed up from worker level, and four firms do not have section chiefs – equivalent to China’s line chief – from worker level. In India, unit chiefs – heads of the base unit of the operation – are mostly staff – new graduates from higher education, whereas in China, they are talented persons from among the workers. The highest position that a worker can generally expect is as a “leading hand,” a multiskilled supervisor of workers. A supervisor is deemed to be a staff member. It is true that in China, educational background is very important for climbing the ladder of the personnel system – especially in large firms – and the opportunities for low-level workers to do this are limited. However, compared to the clear divide that is easily observed in India, it seems that Chinese firms, and society, tend to provide more opportunities for base workers to rise in their career. An important reason for this phenomenon is
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that, since many of the firms investigated have a shorter history than those in India,21 and since many of them started from very small firms predominantly consisting of workers with a low educational background in their early years of operation, such people have now become manager-class personnel in some of the companies observed. However, a large company with a long history of operation – Jialing – also had a small number of former workers who climbed up to the position of vice factory manager. This case was not heard of in India. From this, we can conclude that the in-house labor market is strictly divided in India whereas, relatively speaking, China is less divided and more open to talented workers climbing up the ladder if possible. 4.6.4 Incentives – manner of determining wages The way of determining wages reflects the firm’s attitude toward the formation and evaluation of the skills of its personnel. In Indian motorcycle-parts suppliers, regular staff and workers are employed without an employment period condition. Their wages or salaries are in general determined once a year partly by simply adding the inflation rate or another unified rate for upgrading within the firm, and partly by evaluating performance and increase in skills. In India, there is a difference between “skilled” and “unskilled” workers for each job category. This also reflects the fact that Indian firms try to evaluate the skill level, meaning that they reward partly for work results, but also partly for skills. In India, the status of personnel is relatively stable, and the wage level also rises in a stable manner every year. In China, however, for the management of workers, firms tend to heavily rely on piece-rate wages – a strong incentive. Only one firm out of twenty answering this question had completely given up the piece-rate system. However, this does not mean that firms regard the piece-rate system as the best way for them. In fact, ten firms said that they will decrease the portion of total salary paid by piece rate and increase the portion paid by time or fixed salary. At present, most of them use a mixture of the piecerate and fixed-salary system, of which the former comprises as much as 40–100%. The reason that firms are trying to decrease the piece-rate portion is that they perceive the system as being deficient in motivating workers to maintain the quality level. Obviously, the piece-rate system tends to encourage workers to produce more in number, and it is often the case that workers disregard quality for the sake of increasing quantity. This has become an increasingly serious problem for most Chinese firms who have faced continuous pressure from their customers to increase their quality levels. However, some firms returned to the piece-rate system after trying a more fixed-wage system for a period of time. Most of them confessed that,
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without the system it was extremely difficult to maintain worker motivation – and it is often workers that want the resumption of the piece-rate system, since for them it is the most “fair” system. For these firms, one solution to the dilemma is to elaborate the design of the piece-rate system so that each job has a different wage-rate, which is appropriate both by reflecting the actual demand–supply gap of workers and by encouraging workers to upgrade their skills. It is interesting that, in China, we seldom find the words “skilled” and “unskilled” in interviews on the wage system. Since the wage rate is mostly determined using the piece-rate system – and skilled and unskilled workers are paid differently automatically according to their performance – the management side does not have to evaluate the skill levels of respective workers. This systematic lack of evaluation mechanism of respective workers’ skill levels in many Chinese firms may influence their system of training or nurturing their own personnel. However, they may work out fairly welldesigned piece-rate mapping of jobs after seriously researching samples of workers.22 As for staff-level personnel, Chinese firms widely use the yearly contract system for wages. Basically, the annual salary is determined based on the performance of the previous year. Though not as strong as the worker’s piece-rate system, this is a highly incentive-driven system adapted to staff-level personnel in China. 4.6.5
Multiskill formation
Multiskill formation is widely deemed to be an excellent practice in the manufacturing sectors of various countries. Both in China and India, firms are generally aware of the positive aspects of this idea, whereas in India, the idea recently came to be generally accepted on the shop floor. In China, though, it is not really practiced widely for their own reasons. All the Indian firms answered that they are aware of the virtue of multiskill formation of workers and some have deliberately started a planned job rotation system in some of their shops. Most of the small manufacturers with very limited human resources are doing this naturally in the course of keeping up with daily orders. The aim of job rotation for most of the firms interviewed is mainly to back up absent workers – other reasons, such as increasing labor productivity by operating different machines with fewer people, are not seriously considered. Upgrading and widening the range of workers’ skills is, in general, not considered important. Chinese firms are generally more passive in introducing the practice concretely to their shop floors, although they are aware of the need to do this for abrupt job vacancies – due to the high attrition rate in workers.
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However, since the workers are organized basically using the piece-rate system, it is often the case that workers are not willing to change jobs for fear of being unproductive – which causes their wage to decline – during the period when they are learning the new job. Another worry about shifting jobs – on the management side – is that workers are keen to take on new jobs with a higher piece rate, and even less able workers try for such jobs, which can cause problems in the shop. In particular, firms that are running at full capacity are very passive for fear of such losses. Some firms express a clear preference for confining workers’ job range so that they can maximize their skill level – and hence productivity. As for staff-level personnel, both in China and India they conduct rotation in an ad hoc way to nurture future core personnel candidates. This is clearly not for the sake of widening the range of technical skills, but rather for the sake of wider knowledge of the firms’ management and operation. 4.6.6 Training activities The necessity of training activities is well perceived both in China and India but, relatively speaking, the Chinese seem to utilize outside training services more than the Indians, and India seems to rely on in-house training more than China does. Some Chinese parts suppliers send staff- or engineer-level personnel to school – even at university level – and larger firms even send them on MBA courses. This kind of investment in higher-management knowledge may be a specific case for current Chinese firms – especially for private firms founded by men from a low-educational background – but as they grow larger, they are aware of the necessity to participate in school programs designed for contemporary managers. At the worker level, Chinese firms have also come to emphasize the necessity of training. According to managers, there are two main reasons: (1) in order to be up to date with new technology – for example, NC machines –, new standards of quality, or new demand for participating in the development of new products, even workers may have to upgrade their knowledge, and (2) to attract workers to the firm – or to discourage them from leaving – they have to be encouraging or at least generous regarding the workers’ desire to improve their skills. In particular, for workers of low-educational background, they have to have the qualification of having finished school – for example, at a polytechnic or the equivalent. Most firms systematically allow or encourage workers to attend school after work hours or at the weekend. For the past several years – especially after 2004 and 2005 – Chinese firms have drastically changed their attitudes toward worker training, with their increased awareness of the need for a higher standard, which is partly due to the penetration of production management standards
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such as ISO as a widespread reaction to the severer competition since the late 1990s. On the supply side, training has been a massively booming business in China for more than ten years. Not only did the number of schools – polytechnics, junior colleges and universities – increase, but the schools themselves also came to be more keen on collecting money from outside by providing services. In reality, opening training courses and contributing to society is highly valued as a role of schools in China. Compared to the recent situation in China, the personnel of Indian firms seem to have limited opportunities to attend school outside, especially workers. Instead, Indian firms are rather dependent on in-house training activities. The main first-tier suppliers of Bajaj are very keen on practicing TPM – total productive maintenance – activities in cooperation with Bajaj, with most of the firms having specific training facilities inside the firms and practicing team activities. The aggressive attitude of Chinese workers toward training – including school qualifications – might come from the fact that they have more opportunities of earning a higher wage with the qualifications, whereas in the case of India, there might be less incentive for workers because their chance to do so is less. And the lower attrition rate at Chinese firms allows them to dispatch core staff to MBA courses. In India, since the rate is relatively high, such provision of training opportunities for staff might be risky. 4.6.7 Summary of in-house skill formation Like interfirm relations, in-house skill-formation mechanisms are also significantly different between China and India. In China, firms are keen on upgrading the skill level of staff or workers, but – due to the piece-rate nature of their wage system, which functions well in maximizing production size – firms have faced difficulty in widening the scope of their skills. On the other hand, many firms – and at the same time, many workers themselves – regard confining skills to some narrow range to be beneficial. Mainly due to the rising awareness of workers, firms are becoming much more generous in offering training opportunities than before. However, it seems that they are better at utilizing outside training courses than developing their own training standards and programs. The liquidity of labor – or greater opportunities outside the firms, both job- and trainingopportunities – seem critical in forming this status. On the other hand, Indian firms seem to be more aware of the in-house mechanism of training. Their labor relationship is more stable than China’s, and – as the way of evaluating wages shows – firms seem to be more concerned about the level of the workers. However, it is not clear whether this awareness in caring about upgrading in-house skills is mainly the result of the firms’ earnest desire to do so in harsh competition, or whether it is the
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Moriki Ohara
result of workers being more confined in terms of outside opportunities. Rather, staff-level personnel are more flexible and seem to be more conscious of their own skill upgrading.
4.7
Concluding remarks
The capability-building mechanisms of both interfirm and in-house relations share some common characteristics: an organized or “integrated” nature in India and a market-oriented or “dispersed” nature in China. In Indian interfirm relations, suppliers are guided by Bajaj in terms of the future direction of development – such as quality upgrading via TPM activities – and of providing other resources, including manpower and a small amount of finance, which can be described as common assets. In the case of in-house nurturing of skills, Indian firms utilize stable labor relations and evaluate skills in the light of long-term labor relations. In both in-house and interfirm relations, there is a common set of principles in their systems: in China, firms do not stick – in firm/transaction-specific investment – to create their own “proprietary” assets, or tend to avoid risks by actively utilizing outsourced standardized resources, whereas Indian firms tend to do more of this kind of investment, both in-house and with interfirm institutions. One of the socioeconomic backdrops that may explain the creation of such different natures is that – compared with their Chinese counterparts – Indian firms have limited opportunities to find other transaction partners for suppliers and individual workers and – to a lesser extent – for staff-level personnel. In the case of China, though suppliers and workers are trying to figure out ways of surviving in a more “dispersed” manner, there is a different backdrop – both suppliers and workers find themselves with more choices of transactions and courses for upgrading their skills. A prominent characteristic of China is its strong incentive orientation in both interfirm relations and labor relations. The piece-rate system is widespread in their transactions to the degree that many firms and workers are accustomed to this, and it seems that some of them are constructing unique methodologies for solving problems such as quality control and labor incentives, by elaborating the mapping of skill chains that workers follow under the piece-rate mechanism. It is interesting that the development path of Indian firms seems more similar to the Japanese experience, and the Chinese system seems unique when compared to the other two countries. The emergence of the gap in the growth modes among these economies cannot be solely attributed to the sheer difference in their “developmental stages,” since China and India should be counted as similar – rather than distinguishable – in terms of the development stage of the motorcycle industry – at least compared to Japan.
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Cylinder
Engine gear
Cylinder head
Crank case
Crank shaft
c-13
c-14
c-15
c-16
Transmission
c-8
Clutches
Mufflers
c-7
c-12
Handling bars
c-6
c-11
Brake
c-5
Cylinder
Engine parts
c-4
Shock absorbers
Valve, FWM
c-3
c-10
Carburetors
c-2
c-9
Electronics (CDI)
c-1
Product type
ZS
GR (ZS)
GR (ZS)
GR (ZS)
ZS
ZS
ZS
Jialing
Jialing
Jialing
Jialing
Jialing
Jialing
Jialing
GR (Jialing)
GR (Jialing)
400
2000
1500
670
170
560
220
320
450
500
200
400
1040
5500
300
280
1984
1991
1994
1997
1994
1992
1986
1998
1993
1982
1970
1983
1960
1964
1994
1988
Jialing
Jialing
Jialing, Japanese
3 3
3 3
3 3 3 3
3 3 3 3
3
Continued
3
3
3
3
3 3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
Year of Observation Main transaction No. of Year of partner employees establishment Capital relations 1998–1999 2003–2004 2007–2008
Chinese motorcycle parts manufactures observed
Appendix: list of the parts suppliers surveyed
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Engine gear
Electronics (FWM)
Shock absorbers
Crank shaft
Carburetors
Brake system
Crank shaft
Bolt nut
Brake valve
forging parts
c-18
c-19
c-20
c-21
c-22
c-23
c-24
c-25
c-26
c-27
Chinese motorcycle parts manufactures observed
2nd tier
2nd tier
2nd tier
Others
GR
Yamaha
ZS
ZS
ZS
ZS
ZS
120
130
100
530
700
412
300
720
280
380
650
1995
1988
1980
1993
1995
1994
1995
1999
1993
1997
1996
Japan
3 3
3
3
3
3
3
3
3
3
3
3
Year of Observation Main transaction No. of Year of partner employees establishment Capital relations 1998–1999 2003–2004 2007–2008
*GR=Grand River, ZS=Zongshen
Shock Absorbers
c-17
Product type
Appendix: continued
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Heat treatment
Die casting parts
Steel metal stamp
Die and mold
i-14
i-15
i-16
Shock absorbers
i-12
i-13
Battery
i-11
Cowlings
i-8
Die cast parts
Mufflers
i-7
Die cast parts
Cylinder
i-6
i-10
Engine gear
i-5
i-9
Engine gear
Flame, case
i-4
Lamp
i-2
i-3
Ignishon coil
i-1
Product type
2nd tier
Bajaj
3rd tier
2nd tier
TVS
TVS
Hero Honda
Bajaj
Bajaj
Bajaj
Bajaj
Bajaj
Bajaj
Bajaj
Bajaj
Bajaj
Main transaction partner
31
1500
43
8
325
260
2000
3600
2500
300
900
50
72
200
130
500
No. of employees
1998
1986
1998
1993
1974
1970
1986
1985
1988
1974
1973
1985
1984
1999
1961
1971
Year of establishment
Hero Honda
Capital relations
Indian motorcycle parts manufactures observed
3
3
3
3
3
3
3
3
3
2003–2004
3
3
3
3
3
3
3
2007–2008
Year of observation
104
Moriki Ohara
Notes 1. As stated in the introduction of this volume, we assume that the way the economic system is constructed influences the nature and manner of building capability/knowledge, and the latter also determines the future direction of the former (North 1990). 2. The Indian firms examined here are modern manufacturers that are registered as formal “factories” – as stated in the Introduction. 3. Compared to Bajaj’s R&D expenditure – 24 million USD in 2007 –, Jialing spent 8 million and Zongshen 19 million in the same year. Bajaj’s figure is according to its annual report and Jialing and Zongshen from the author’s interviews. 4. In Ohara (2006), I exemplified a clear difference in the patterns of forming inter-firm relations in Japan and China. In Japan, manufacturers have formed “integrated type” interfirm relations, whereas in China, major indigenous makers and suppliers have formed “dispersed-type” relations (Ohara 2006). However, the studies did not advance further to explain the causes of this difference. At the same time, directly comparing firms in Japan – an advanced economy – and in China – a developing country – does not tell us whether this gap was caused mainly by the sheer difference in their developmental stages, or by other factors inherent in their characteristic economic systems or market society. This paper aims to make up for this weakness by comparing China with India – whose stages of economic development are more similar to China’s than Japan’s. 5. This section is based on the analytical framework of Fujimoto (1998). 6. The ratio of purchased-material/parts-cost to manufacturing cost. I acquired this data though my own interviews; however, some of the interviewees may have misunderstood the definition. 7. Suppliers i-3 and i-5 in this study employed staff who spun off from Bajaj during the process. 8. Supplier i-7 became a first-tier supplier of muffler units during the process. 9. Zongshen used to use as much as 700 in the late 1990s. 10. My interview with the president of Grand River. 11. Not all the sales of the supplier. If the supplier is selling various kinds of products, dependency on the maker in sales will be less than it appears in the figure in the table. 12. The maker can secure “traceability” of problematic parts as well. 13. According to suppliers, such cases sometimes happen where the maker’s staff in charge of purchasing pursue personal benefit – are open to bribery – and arbitrarily change the transaction partners. 14. The analytical framework of this section is based on Asanuma and Kikutani (1997). 15. Even when the depreciation of die/mold costs is not ensured by the maker, if the new product sells in large enough volume, the supplier can complete the depreciation by adding it to the selling price. 16. Grand River has had official technological cooperation with Suzuki since the early 1990s and the president was the head engineer of a state-owned motorcycle manufacturer when he was in charge of technical cooperation with Honda in 1991. 17. Seven suppliers surveyed in this study for Zongshen (C-10-16) were members of the “Group.”
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18. Gross margin rate = (total sales – manufacturing cost)/total sales. This includes the sales and management costs and taxes. 19. While Indian auto parts manufacturers earned as much as 7–11% operating profit during 1993 to 2004, Chinese counterparts earned less than 2–6% for the same period of time – ACMR for China and MSPI for India. 20. While the average number of employees in Chinese motorcycle-parts manufacturers was as large as 1.7 to 3 times more than in their Indian counterparts during 1992–2004, the average sales size of the Chinese was 1 to 1.7 times more than for the Indians. For China, 763 firms in 1993 and 1462 firms in 2004 (ACMR), and for India, 488 in 1992 and 590 in 2003 (MSPI). 21. The average year of establishment of 27 firms in China is 1991, whereas average year of establishment of 16 Indian firms is 1982. 22. Some Chinese firms say their quality level improved after increasing the piece-rate portion.
References All China Market Research Company (ACMR), Zhongguo Shichang Nianjian [China Market Yearbook], Beijing: Waiwen Chubanshe, various years (Chinese). Asanuma, Banri and Tatsuya Kikutani, ed., 1997, Nihon no kigyō soshiki kakushin-teki tekiō no mekanizumu: Chōki torihiki kankei no kōzō to kinō [Mechanisms for Innovative Adaptation in Japanese Company Organizations: The Structure and Function of LongTerm Transaction Relationships], Tokyo: Toyo Keizai Inc. (Japanese). Bajaj Auto Ltd., 2002, Annual Report 2001–02, http://www.bajajauto.com/bajaj_ investor_annual_report.asp Fujimoto, Takahiro, 1998, “Sapuraiyā shisutemu no kōzō, kinō, hassei [The Structure, Functions, and Formation of Supplier Systems]”, in Takahiro Fujimoto, Toshihiro Nishiguchi, and Hideshi Itoh, eds., 1998, Rīdingusu: sapuraiyā sisutemu: Atarashii kigyō kankei o tsukuru [Readings on Supplier Systems], Tokyo: Yuhikaku (Japanese). Honda Motor Co. Ltd., various years, Sekai nirinsha gaikyō [World Motorcycle Facts and Figures], Tokyo: Honda Motor Co. Ltd. Industrial Techno-Economic Services P. Ltd. (INTECOS) and Center for Industrial and Economic Research (CIER), 2001, Automobile Industry 2001 and Beyond, New Delhi: INTECOS and CIER. Krause, D. R., 1997, “The Supplier Development: Current Practices and Outcomes”, International Journal of Purchasing and Materials Management, 33 (2), pp. 12–19. Ministry of Statistics and Program Implementation (MSPI), Annual Survey of Industries (Factory Sector), various years, Kolkata: MSPI. North, Douglass C., 1990, Institutions, Institutional Change and Economic Performance, Cambridge and New York: Cambridge University Press. Ohara, Moriki, 2006, Interfirm Relations under Late Industrialization in China: The Supplier System in the Motorcycle Industry, Chiba: Institute of Developing Economies. Shih, Yuh-shyan and Chen Mei-lynn, ed., 2004 Jiche chanye nianjian [2004 Motorcycle Industry Yearbook], Hsinchu: Industrial Economics and Knowledge Center, Industrial Technology Research Institute (Chinese). Society of Indian Automobile Manufactures (SIAM), ed., Profile of the Indian Automobile Industry, New Delhi: SIAM, various years. United Nations, various years, Yearbook of Industrial Statistics, Vol. 2, Commodity Production Data, New York: United Nations.
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Zhongguo Motuoche Gongyeshi Bianweihui (ZMGB), ed., 1995, Zhongguo motuoche gongyeshi [The History of China’s Motorcycle Industry], Beijing: Renmin Youdina Chubanshe (Chinese). Zhongguo Qiche Gongye Nianjian Bianjibu (ZQGNB), ed., Zhongguo qiche gongye nianjian [Yearbook of the China’s Automobile Industry], Beijing: Zhongguo Qiche Jishu Yanjiu Zhongxin, various years (Chinese).
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5 Skill Formation through Education and Training: A Comparison of China and India Yoko Asuyama
5.1
Introduction
Human capital is considered one of the most important sources of economic growth (Lucas 1988; Romer 1986). Many empirical studies found a positive association between the quantity of education and economic growth (Barro 1991; Benhabib and Spiegel 1994). Quality of education also matters (Hanushek and Kimko 2000). Not only average skill level, but also the pattern of skill distribution in the economy affects its industrial comparative advantage (Bombardini et al. 2009; Grossman 2004; Grossman and Maggi 2000). Examining quantity, quality, and distribution of skills and the mechanisms of how these skills are generated in an economy has important implications for understanding the path of economic development in the past and the future. This chapter aims to comprehensively analyze the skill-formation systems – SFSs – of China and India, the two rapidly emerging economic giants. I first compare the quantity, quality, and distribution of skills between the two countries. This comparison reveals that China enjoys more equal skill distribution with a much larger semi-skilled labor force. India has more unequal skill distribution, with a substantial share of illiterate workers – about 40% of the total employed population – and many highly-educated workers (Section 5.2). I then explore possible reasons for the different patterns of skill distribution between the two countries by analyzing the three aspects of the SFSs: education and training – E&T – policies by government, individual incentives for skill acquisition, and firms’ demand for skills (Section 5.3). Section 5.4 concludes. This chapter focuses on skills developed through E&T, especially education, which are provided by institutions outside firms, in particular schools. Although formal or informal on-the-job training – which takes place inside firms – interfirm relations, and industrial communities and networks are also important elements of SFSs (Crouch 2005), examination of these skillgeneration channels is left for future research. For analytical purposes, this 107
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108 Yoko Asuyama
chapter assumes that a person who has received more E&T becomes more skilled, that is, has greater skills – in general than before or than other less educated/trained people. It is also assumed that the quality of E&T that a person has received is positively correlated with the quality of skills he or she acquires. There is no literature comparing the entire SFSs of China and India. There are many studies that have examined a part of the education or training system of China or India – referred to in the next two sections. As for comparative studies, Ahmed et al. (1991) and Acharya et al. (2001) compared the education systems of China and India. However, the former only analyzed basic education – literacy, early childhood, primary education, etc. The latter mainly described the history of education policies – especially of China – and the ideologies behind them. Neither study covered most of the recent changes since the 1990s. In addition, most of the studies on E&T of China and India focus on government policies. I try to depict SFSs in terms of not only government policies, but also individual incentives for acquiring skills and firms’ demand for skills. Examining the entire mechanism of the system enables us to realize that demand-side policies, as well as supply-side E&T policies, are important for effective skill accumulation.
5.2 Comparing stock, flow, and distribution of skills 5.2.1 Stock of skills Table 5.1 reports the distribution of Chinese and Indian employed persons by level of education in 2005. While 39.6% of Indian workers are illiterate, only 7.8% have no schooling in China. The proportion of workers with lower-secondary education – “junior secondary” in China and “middle” in India – is much larger in China – 44.1% – than in India – 15.3%.1 By contrast, the proportion of postgraduate and higher education is larger in India – 1.4% – than in China – 0.2%. Gender differences are more notable in India. An educational divide by employment status also exists in India. The absolute number of illiterate workers in India is about three times as many as in China.2 By contrast, China has a massive worker pool with primary and lower-secondary education – 221.6 million and 334.4 million, respectively – while India has only 115.4 million workers with primary education – including literate workers who have received no formal education – and 70.3 million workers with lower-secondary education. Although the total number of workers with tertiary education is larger in China than in India, the differences are not so huge and India even has more workers with postgraduate and higher education – 6.4 million compared to 1.3 million in China.
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5.2.2 Flow of skills and education and training institutions 5.2.2.1 General and vocational education Tables 5.2 and 5.3 show the skill flows generated from general and vocational education in China and India in 2005.3 First, unlike skill-stock comparison, the number of students enrolled in primary education is larger in India. This is due to the recent educational reform in both countries – mentioned in Section 5.3.1 – and demographic changes such as the decline in the young Chinese population caused by the one-child policy since 1979. Second, the size of vocational education – at upper-secondary level in particular – is much larger in China. In 2005, 42% of students – 14.9 million – at upper-secondary level were enrolled in vocational schools such as regular specialized secondary schools, vocational senior secondary schools, and technical schools. By contrast, in India, only 7% of students at upper-secondary level – 1 million seating capacity in vocational education under the Centrally Sponsored Scheme – CSS, and 1.6 million at various professional, technical, and vocational schools such as teachers’ training schools, technical & industrial and arts & crafts schools, and polytechnics – are in vocational education. The actual enrollment in Indian vocational education under the CSS is likely to be much smaller. The World Bank (2008), reports that the average utilization of vocational education capacity is about 42% (p. 12). At tertiary level, 46% of undergraduates and college students were enrolled in specialized courses in China. In India, there are also many institutions offering technical and professional education, which include centrally-funded institutions and many regional engineering colleges.4 5.2.2.2 Vocational training Tables 5.4 and 5.5 show the major vocational training schemes of China and India and the size of their skill output around 2005.5 In terms of vocational training, China again surpasses India. In China, there are four major training institutions: technical schools, employment-training centers, nonpublic vocational training agencies, and enterprise employee-training centers. In total, these institutions trained 50.3 million people in 2005–2006. There are various types of training programs, such as pre-job training, reemployment training for laid-off and unemployed persons, training for current employees, training for rural laborers and rural migrants, and business start-up training. In India, there are two most important vocational training schemes: the Craftsmen Training Scheme (CTS) and the Apprenticeship Training Scheme (ATS) (Table 5.5). In total, these schemes train fewer than 0.97 million people annually. The main institutions under the CTS are public Industrial Training Institutes (ITIs) and private Industrial Training Centers (ITCs). In
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2.2
4.8
10.9
City
Town
Rural
4.4
11.8
Female
7.8
58.8
0
Male
Total
Distribution (%)
Number of employed persons (million)
Standard years of education
China (2005)
LS
US
T
37.8
22.2
13.7
32.6
26.4
29.2
221.6
6
44.7
47.0
41.0
39.6
47.8
44.1
334.4
9
5.9
16.3
24.2
9.9
14.1
12.1
92.1
12
0.7
7.3
11.5
4.2
4.7
4.5
33.8
14–15
0.1
2.3
6.8
1.8
2.4
2.1
16.2
16–17
0.0
0.0
0.7
0.1
0.2
0.2
1.3
–
100.0
100.0
100.0
100.0
100.0
100.0
758.3
Undergraduates and Undergraduates and No Junior Senior college students: college students: full Post schooling Primary secondary secondary specialized courses undergraduate courses graduates Total
P
Table 5.1 Distribution of employed persons by level of education, 2005
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8 70.3
15.3 18.3 9.1 17.6 14.6 16.2 16.9 12.6
0–5 115.4
25.1 27.9 19.4 22.6 25.8 25.4 18.6 27.7
Middle (Upper primary)
LS
US
T
12.9 16.3 5.9 21.4 10.5 14.0 24.9 4.8
10, 12 59.3
4.3 5.5 2.0 12.1 2.1 3.5 15.7 0.3
13–17 19.8
Sources: NBS (2007), NBS (2006) China Statistical Yearbook 2006, NSSO (2006), and Planning Commission (2008).
1.4 1.7 0.9 3.6 0.8 0.9 5.8 0.3
– 6.4
1.4 1.6 0.8 4.2 0.6 0.9 6.1 0.0
– 6.4
Secondary, Diploma/ higher certificate Post graduate secondary course Graduate & above
Notes: China: All employed persons in 2005; India: All usually employed persons (ps+ss). P: Primary, LS: Lower secondary, US: Upper secondary, T: Tertiary.
Standard years of education 0 Number of employed persons 182.0 (million) Distribution (%) Total 39.6 Male 28.5 Female 61.8 Urban 18.5 Rural 45.6 Self-employed 39.1 Regular salaried/wage employee 12.0 Casual worker 54.3
India (2004–05)
Not Literate & up literate to Primary
Literate & P
100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
459.7
Total
112 Yoko Asuyama
Table 5.2 Skill flows from general and vocational education in China, 2005 China (2005) T
No. of Total enrollment institutions (million)
Higher education Postgraduates Doctor’s degree Master’s degree Regular undergraduates and colleges Enrolled in full undergraduate courses Enrolled in specialized courses Vocational and technical colleges
1,792 701 2,012 921
US Senior secondary education Regular senior secondary schools Vocational secondary education Regular specialized secondary schools Vocational senior secondary schools Technical schools
27,976 16,092 11,884 3,207 5,822 2,855
39.0 24.1 14.9 6.3 5.8 2.8
LS
62,486 61,885
62.1 61.7
601
0.4
366,213
108.6
366,213
108.6
Junior secondary education Regular junior secondary schools Junior secondary vocational schools
P
Primary education Regular primary schools Schools for juvenile delinquents Special education Pre-school education Adult education
1,792 (766)
16.6 1.0 0.2 0.8 15.6 8.5 7.1
77 1,593 124,402 68,662
0.01 0.4 21.8 12.5
Notes: The number of institutions offering postgraduate programs is not counted. T: Tertiary, US: Upper secondary, LS: Lower secondary, and P: Primary. Source: NBS (2006) China Statistical Yearbook 2006.
2006, ITIs/ITCs were offering training programs for 107 trades – of which 57 are engineering trades and 50 are non-engineering trades. In 2005, 1,896 ITIs and 3,218 private ITCs had a training capacity for 742,330 people.6 The Apprentices Act of 1961 “makes it obligatory on the part of employers both in public and private sector industries to engage trade apprentices according to the ratio of apprentices to workers other than unskilled workers in designated trades prescribed under the Rules” (DGE&T 2007b, p. 2). There were 32,413 establishments with capacity to train 338,252 apprentices; however, the utilization of training capacity was less than 70%. As a result, 219,808 apprentices were trained in 2004.
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Table 5.3 Skill flows from general and vocational education in India, 2005–06 India (2005–06) T
Universities/colleges Research Post-graduate Graduate Diploma/certificate
No. of institutions
Total enrollment (million)
19,845 – – – –
11.0 0.1 1.0 9.8 0.1
US Secondary/senior secondary Below degree level prof./tech./vocational Grade 11–12 (+2) of which Vocational Education Grade 9–10
168,427 8,760 53,643 9,583 106,024
40.0 1.6 13.4 About 1.0 (capacity) 25.0
LS Middle (upper primary)
288,493
52.2
P
772,568
132.0
67,157 n.a.
5.3 n.a.
n.a.
n.a.
Primary Pre-primary Special education Other education
Notes: Universities/colleges include universities, deemed universities, institutions of national importance, and degree colleges. Below-degree-level professional/technical/vocational schools include teachers’ training schools, technical & industrial and arts & crafts schools, and polytechnics. T: Tertiary, US: Upper secondary, LS: Lower secondary, and P: Primary. Sources: MHRD (2008b) and UGC.
One reason that China is able to train a large number of people is the short duration of the training programs. For example, 89.6% of graduates from employment-training centers and 82.8% of graduates from nonpublic vocational training agencies completed their training within six months. In India, the duration of training varies from six months to three years for ITIs/ITCs and from six months to four years for trade apprentices. Although a statistical breakdown by duration of training is not available, India’s 11th Five-Year Plan (5YP) recognizes that China provides more short-term modular training than India does (Planning Commission 2008, vol. 1, p. 87). Another difference in vocational training between China and India can be found in training for the informal sector. China provides a massive amount of training for disadvantaged people in the informal sector – including laidoff workers, unemployed persons, and rural migrants – by emphasizing the employment or reemployment of such people (MLSS 2002; Mori 2007). By contrast, in India, the size of training for the informal sector is much smaller, although the informal sector is said to constitute more than 90% of the Indian workforce (World Bank 2008, pp. 45–53).
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114 Yoko Asuyama
Table 5.4 Vocational training scheme of China, 2005 Composition of graduates (%)
China (2005) Technical schools No. of institutions Trainees (000) Graduates (000) Employment training center No. of institutions Trainees (000) Graduates (000) Nonpublic vocational Training agency No. of institutions Trainees (000) Graduates (000) Enterprise employee training center No. of institutions Trainees (000) Graduates (000) Total above four No. of institutions Trainees (000) Graduates (000)
2,855 2,733 2,701
3,289 8,044 7,972
21,462 9,552 8,932
Duration of training (%)
LPS Laid-off Rural Employees Others LPS
7.5 17.0 17.8 47.2 10.4 9.1
n.a.
Laid-off Rural Employees Others
42.8 32.9 n.a. 15.2
6 months-1 year > 1 year
6.8 3.5
LPS Laid-off
18.0 9.5
< 6 months 6 months-1 year
82.8 11.3
Rural Employees Others
41.7 n.a. 30.8
> 1 year
< 6 months
89.6
5.9
22,000 30,000 n.a. 49,606 50,329 19,605
Notes: LPS: Pupils of the labor preparation system, Laid-off: Laid-off and unemployed workers, Rural: Rural workers, Employees: Enterprises’ employees. Data for non-public vocational training agencies are those for 2006. Sources: NBS and MLSS (2006, 2007) China Labour Statistical Yearbook 2005, 2006, and D. Yan (2008a, p. 166).
Finally, if we calculate the overall size of vocational education – only at upper-secondary level for comparison – and training, the gap between China and India is huge. China provides vocational E&T to 65.2 million people annually – 14.9 million in vocational education at upper-secondary level and 50.3 million in vocational training, which accounts for 8.6% of the entire workforce. India provides vocational E&T to about 3.1 million
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Table 5.5 Vocational training scheme of India, around 2005 Major institutes under Craftsmen Training Scheme (CTS) (Around 2005) Industrial Training Institute and Center (ITI/ITC) Government ITI Private ITC Advanced/Central Training Institute (ATI/CTI) National Vocational Training Institute for Women (NVTI) Regional Vocational Training Institutes for Women (RVTI) Foremen Training Institutes (FTI) The Apex Hi-Tech Institute (AHI) Total (excluding n.a.)
No. of institutes
Seating capacity (000)
5,114 1,896 3,218 9 1
742.3 400.0 342.3 1.1 0.6
10
2.8
2 1 5,137
n.a. n.a. 746.8
Apprenticeship Training Scheme (ATS) (As of March 31st, 2004)
No. of establishments (of which engaging)
Trade apprentices
32,413 (20,990) n.a.
246.1 (168.8) 92.1 (51.0)
68.6
15.4
55.4
17.0
32,413 (20,990)
338.3 (219.8)
65.0
9.9
Graduate, technician & technician (vocational) apprentices Total (excluding n.a.)
Seating capacity % (of which utilization utilized) (000) of seats
% of SC+ST out of total seats utilized
Notes: No. of establishments (of which engaging): Number of establishments having training facilities (of which those engaged in apprenticeship training). For the differences in four types of apprentices, see p. 25 of the World Bank (2008). SC = Scheduled Castes and ST = Scheduled tribes. Sources: ITI, NVTI, RVTI: MLE (2006, 2007) Annual Report 2005–06 and 2006–07. Other data for CTS: DGE&T (2007c). Data for ATS: DGE&T (2007b).
people annually (Planning Commission 2008, Vol. 1, p. 88) which accounts for only 0.7% of the entire workforce. 5.2.3 Quality of skills Compared to China, the quality of education and training in India seems to be rather poor. This may lead to the better quality of skills of Chinese workers who have received the same amount of E&T as their Indian counterparts.
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First, concerning compulsory education – high dropout rates, teacher shortage, and high rates of teacher absence are longstanding problems for India. Even in 2005–2006, 25.7% of Indian students dropped out before completing primary education, 48.8% did so before completing grade 8 – lower-secondary education, and 61.6% did so before completing grade 10, although the dropout rates have been decreasing over time (MHRD 2008b). According to Minami et al. (2008), the dropout rates of Chinese students between 2001 and 2004 are only 0.1% for primary education and 2.6% for lower-secondary education (p. 118). India also suffers from serious teacher shortage in terms of both quantity and quality. In 2005, pupil–teacher ratios at primary, lower-secondary, and upper-secondary level in China were 19, 18, and 19, respectively. They were 46, 34, and 33, respectively, in India – both figures are calculated from the data of ACMR and MHRD (2008b). A more serious problem is that the teacher–school ratio is very low in India. In India in 2005, only 2.8 teachers on average – compared to 15.3 teachers in China – were allocated per one primary school – calculated from ACMR and MHRD (2008b). The number is too small to provide good-quality education. The high absence rates of teachers are also problematic in India. According to unannounced visits to more than 3,700 Indian primary schools in 20 states in 2003, on average 25% of teachers of public schools were absent from school at the time of the visit. In addition, 55% of teachers present at school at that time were not engaging in teaching (Kremer et al. 2005). In China, problems of teacher absence are not reported. Second, with regard to vocational E&T, the literature indicates that both China and India face similar problems, such as a lack of appropriate facilities, equipment, and qualified teachers, employment problems for graduates, and a lack of linkage or a mismatch between vocational E&T and industry. Due to the limited information, it is difficult to judge which country faces more serious problems. However, if we consider employment to be the ultimate goal of vocational E&T, we can claim that vocational training in China seems more successful than that in India. To put it another way, India has weaker linkages between vocational training and employment. If we define the employment rate as the ratio of employment in a certain year to the number of graduates in the same year, the employment rates of Chinese employment-training centers in 2005 and nonpublic vocational training agencies in 2006 were 70.0% and 83.6%, respectively – these figures are computed from the data of NBS and MLSS (2006, 2007). In India, the International Labour Organization (ILO) surveyed the career outcomes of ITI/ITC graduates in three states – Andhra Pradesh, Maharashtra, and Orissa – in 1999 and 2000 (ILO, 2003). If we define the employment rate as the percentage of graduates employed – employment includes wage employment, self-employment or employer, and assisting parents in doing their job or business – the employment rates computed from the data of ILO (2003)
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are relatively low, ranging from 16.2% for ITIs in Orissa to 41.7% for ITCs in Maharashtra. Labor – or employment – exchanges also function better in China than in India.7 First, labor exchange in China covers a much larger population. In 2006, China had 37,450 labor exchanges with 47.4 million registered job-seekers, while India had 947 employment exchanges with 7.3 million registered job-seekers. Second, the number of registered job-seekers and job vacancies are relatively balanced in China – 47.4 million and 49.5 million in 2006, respectively – while the number of job-seekers registered in India’s employment exchanges – 7.3 million – is 116 times as large as the number of job vacancies notified – 0.36 million. Finally, China’s labor exchanges are more successful in terms of job placement. The total placement through China’s labor exchanges was 24.9 million, which accounts for 52.6% of registered job-seekers in 2006. By contrast, only 0.18 million placements – which accounted for 2.4% of total registered job-seekers in 2006 – were realized through India’s employment exchanges. The poor performance of India’s employment exchanges may be partly due to their nature whereby only information from the organized sector – which constitutes less than 10% of the Indian workforce – is collected.8
5.3 Two skill-formation systems shaping different skill-distribution patterns As was shown in the previous section, while China has more equal skill distribution with a much larger semi-skilled labor force – especially at lowersecondary education level – India has unequal skill distribution with a small semi-skilled labor force and a large portion of illiterate and highly-educated people. Why and how have these two different skill-distribution patterns emerged? In this section, I aim to answer this question by examining three aspects of skill-formation systems in China and India: 1) E&T policies by government, 2) individual incentives for skill acquisition, and 3) firms’ demand for skills. 5.3.1 Education and training policies by government 5.3.1.1 Historical path of the policies Around 1950, the literacy rates of China and India were both around 20%. However, by 1964, China had already accomplished a 66% literacy rate, which is almost the same as that of India in 2004 – in 1961, the literacy rate of India was still 34%. The different skill-distribution patterns of China and India had already emerged in the early years of nation building. In sum, China’s current equal and India’s unequal skill-stock distributions reflect both countries’ E&T policies – especially before the economic reform period. However, the changes in E&T policies in both countries during the reform period resulted in the recent expansion of skill flows at
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the vocational and tertiary levels in China and at the primary and lowersecondary levels in India. Brief history of E&T policies in China9 China’s E&T policies prioritized literacy and basic – primary and lowersecondary – education until China started its economic reform and began to promote vocational and tertiary education. Under the planned economy – 1949–1977 – mass literacy and basic education for workers and peasants were emphasized. A variety of schools – such as worker-peasant primary and lower-secondary schools, and spare-time schools that provided education for people attending school after work – were established nationwide (Acharya et al. 2001, p. 244; Hannum 1999, p. 197). From the foundation of the PRC, China’s E&T policies have always emphasized the linkage between education and work, and tried to foster employability skills in order to prevent unemployment.10 Combining education and mass production skills was emphasized. Mao Zedong advocated “work-study – ban gong ban du” and Liu Shaoqi also proposed “two educational systems and two labor systems” that is, full-time and part-time education and full-time and part-time work.11 Based on these “walking on two legs” strategies, many work-study schools were established from the end of 1950s (Zhuag 2001, p. 49). During the Cultural Revolution (CR), 1966–1976, intellectuals were suppressed and many tertiary and vocational education schools were completely shut down or closed for many years. Although the CR destroyed tertiary and vocational education in China, both the “walking on two legs” strategies and the CR seemed successful in expanding basic education nationwide, at least in terms of quantity. This is reflected in the student enrollment figure shown in Figure 5.1. Due to the strategy of combining education and production skills, China was able to start economic reform in 1978 with a relatively egalitarian society, where a large population – including the rural population – was equipped with both basic education and factory production skills. When China started its economic reform in 1978, the Chinese government started to promote tertiary and vocational education, in addition to basic education. In 1985, the Central Committee of the CCP issued a “Decision on the Reform of the Educational Structure,” which is the guiding document of current educational policy in China. Based on this Decision, China started various educational reforms: to universalize nine-year compulsory education; to delegate responsibility for administration and financing of education – including primary and both general and vocational secondary education – to local governments (Liu 2004, p. 35); to encourage the establishment of private schools; to expand the autonomy of schools by introducing the principal responsibility system (D. Yan 2008b, p. 90); to put emphasis on vocational education; and to promote linkage between pre-job training and employment (Liu 2004, p. 89). Upper-secondary vocational education
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(Million students)
RT
119
(Million students)
SV 70,000
USG
160,000
LSG 60,000
P (right axis)
50,000
140,000 120,000 100,000
40,000 80,000 30,000 60,000 20,000
10,000
20,000 0
19 4 19 9 5 19 2 5 19 5 5 19 8 6 19 1 6 19 4 6 19 7 7 19 0 7 19 3 7 19 6 79 19 8 19 2 8 19 5 8 19 8 9 19 1 9 19 4 9 20 7 0 20 0 0 20 3 06
0
40,000
Figure 5.1 Student enrollment by education level in China Notes: RT: Regular tertiary, SV: Secondary vocational, USG: Upper secondary general, LSG: Lower secondary general, and P: Primary. Sources: ACMR, NBS China Statistical Yearbook (various years).
rapidly expanded. In the mid-1990s, the proportion of vocational education to total enrollment in upper-secondary education reached 56.8% (Liu 2004, p. 246). The establishment of nonpublic vocational training agencies also increased. Various components framing the current Chinese vocational E&T system, such as the vocational qualification certification system (1994), Vocational Education Law (1996), and labor preparation system (1999) – were introduced.12 Large-scale training programs for laid-off workers – since the mid-1990s – and rural laborers and migrants – in the 2000s – started in response to the rapid increase in the number of such disadvantaged people (Mori 2007; Yamaguchi 2007). In recent years, China has also been putting more emphasis on tertiary education. In 1999, China expanded the entrance quota of universities and, as a result, the number of students enrolled in higher education – regular institutions of higher education – increased fivefold between 1998 and 2006. Brief history of E&T policies in India13 Unlike China, India first prioritized tertiary and technical education, and only after the mid-1980s did it begin to promote primary- and lowersecondary education. During the Indian independence movement, Mohandas
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Karamchand Gandhi opposed the elitist education under the British colonial government – which promoted tertiary education provided in English to produce Indian officials who supported the colonial government. Gandhi instead advocated the introduction of free compulsory education nationwide and the introduction of handicrafts into school education (Kohara 2004, p. 211). Gandhi’s views on education were reflected in the First Five-Year Plan (5YP), 1951–1956. However, from the Second 5YP, 1956–1961, India started to put more emphasis on tertiary and technical education under the strong leadership of Jawaharlal Nehru, in order to generate the skilled manpower necessary for heavy industrialization. This trend can be clearly seen from Figure 5.2, which shows the changes in the allocation of educational expenditure by level of education. Unlike China, adult education was understated and official literacy campaigns were not conducted until the late 1980s (Acharya et al. 2001, pp. 244–245). It can be seen from the “National Policy on Education 1986,” which was further updated in 1992 that India started to promote basic education seriously by increasing central funding for education. From the mid-1980s to the 1990s, India introduced various programs to expand basic education and improve its quality: Operation Blackboard (1986), establishment of District Institutes of Education and Training (1988), Total Literacy Campaigns (1988), Minimum Levels of Learning (1989), the District Primary Education Program (1994), etc. – for details of the programs, see Nakamura (2006). In 2001, India launched the Sarva Shiksha Abhiyan or the “Education for All” movement – which ultimately aimed to achieve universalization of primary and lower-secondary education, both in terms of enrollment and (%)
60 Elementary education (P and LS)
50
Secondary education (US) University & other higher education
40
Technical education
30 20 10
19 5
1– 19 56 19 (1 56 st –1 Pl an 96 ) 1 (2 19 nd 61 Pl –1 an 96 19 ) 6 66 (3 –1 r d 96 P 9 la (P n) la n H 19 ol 69 id –1 ay ) 97 4 ( 19 4t h 74 Pl –1 an 97 ) 9 (5 19 th 80 Pl –1 an 98 ) 5 ( 19 6t h 85 P –1 la n) 99 0 (7 th Pl an ) 19 91 –1 99 2 19 96 –1 99 7 20 01 –2 00 2 20 06 –2 00 7 20 07 –2 00 8
0
Figure 5.2 Educational expenditure allocation of India by level of education Notes: 2006–07: Revised estimates, 2007–08: Budget estimates. Expenditures of education departments (both central and state) only. Sources: MHRD (1995), CSO (2006), and MHRD (2008a).
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completion by 2010 – with some interim goals. In 2002, the Constitution was amended to make compulsory education a fundamental right for all children in the age group of 6–14 years. Thus, providing compulsory education universally has become a duty of each state, not a nonbinding target – as had been stated in the Constitution until then. The proportion of educational expenditure allocated to primary and lower-secondary education significantly increased from 33% in the Sixth 5YP to 52% in 2007–2008, while that allocated to tertiary and technical education decreased from 22% to 12% and from 11% to 5%, respectively (Figure 5.2). The gross enrollment ratio of primary education also increased substantially from 83.8% in 1990–1991 to 109.4% in 2005–2006, although there still remains a quality problem, as mentioned previously. 5.3.1.2
Incentive structure of key actors
Especially regarding primary and secondary public education, more incentive mechanisms are embedded in the Chinese E&T system for improving the quantity and quality of E&T, compared to the Indian system. First, local government officials in China have incentives to meet the targets for school enrollment because of the carrot-and-stick policy of upper-level government. For example, it is reported that, during the campaign to universalize compulsory education in the 1990s, some upper-level governments forced lower-level governments to achieve the expansion target of compulsory education with the threat of denying all other noneducational achievements without accomplishing the educational target. Failure to meet the educational targets would reduce opportunities for lower-level government officials of financial incentives or promotion (Minami et al. 2008, pp. 133–134). Liu also reported an example of vocational education in Zhejiang, where the provincial government announced that it would give an award to cities satisfying the student recruitment target while warning those that do not meet the target (Liu 2004, p. 125). Second, Chinese teachers have more incentives to improve the quality of education than their Indian counterparts. Since the mid-1980s, lifetime employment is no longer guaranteed for teachers and they have been working based on three- to five-year contracts. The labor contract is renewable, based on teacher performance and ability. Although firing rarely occurs, replacement to another school or a non-teaching position is possible (MEXT 2006, pp. 207–209). In 1986, four ranks for teachers were created – based on their ability, experience, and academic qualifications. These four ranks are linked by salary and promotion of teachers (MEXT 2006, pp. 209–211, 213–216). Therefore, Chinese teachers have incentives to improve their performance – and hence student academic performance – thereby securing their jobs and receiving better promotion and earnings. In fact, a survey covering 16 secondary schools in a large county in Jiangsu Province at the end of 1990s, Ding and Lehrer (2007) found that teachers’ salaries were actually
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determined by four ranks and experience and that they were positively linked to the ratio of students proceeding to higher education. Monitoring teacher performance is possible, since educational authority is decentralized to local communities and to school level in China. In the mid-1980s, the principal responsibility system was introduced. This system reduced the influence of the Chinese Communist Party (CCP) on schools and significantly enhanced the autonomy of school principals – who became able to hire, fire, monitor, and evaluate teachers (Lin 1993, p. 79). By contrast, India seems to lack such monitoring and incentive mechanisms. As PROBE (1999) reports, government schoolteachers are public servants who are guaranteed lifetime employment and their salary and promotion are unrelated to their performance (PROBE 1999, p. 64). In privateaided schools that are funded largely by grants-in-aid, teachers have been “paid directly from the state government treasury at the state teacher salary rates” (Kingdon 2007, footnote 12) since the early 1970s. Regarding government and private-aided secondary schools, “teacher qualifications are fixed, with little or no involvement of school principals in teacher recruitment” (World Bank 2009, p. 87). Appointments, promotions, and transfers of teachers sometimes seem to reflect political or personal favors (Mehrotra 2006; PROBE 1999, p. 65). The situation is similar in the government ITIs (World Bank 2008, p. 31). Compared to China, educational authority is less decentralized in India, and this makes it difficult to monitor the educational performance of schools and teachers. Since the 42nd Amendment to the Constitution in 1976, educational authority has been shared by both central and state governments. In 1992 – by the 73rd Amendment to the Constitution – state governments were required to delegate various authorities in social services, including education – primary, secondary, vocational, adult, and nonformal education and technical training – to local Panchayat Raji institutions (The Constitution (73rd Amendment), Act, 1992).14 However, in reality, authority regarding primary and lower-secondary education is not handed over to the Panchayat level in many states, although in some states – for example, Madhya Pradesh, Kerala, and Himachal Pradesh – local communities are actively involved in school management (Mehrotra 2006, pp. 272–273). With regard to secondary education, much less power seems to be delegated to the substate level (World Bank 2009, p. xi). The decentralization of education and introduction of an incentive mechanism is not easy in India, since teachers and their unions traditionally have great political power in India and have resisted these educational reforms (Kingdon and Muzammil 2009; Mehrotra 2006, pp. 271–272). 5.3.1.3 Financing education and training E&T policies without a financial basis are not feasible. In China, the financing of education – including both general and vocational – has been
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decentralized as well, and mass community-based and diverse fundraising have contributed to mitigating the shortage of educational funds. Under a planned economy, although central government generally had responsibility for financing education, the People’s Commune contributed to the expansion of basic education in rural areas by financing the construction of schools and salaries for community – minban – teachers (Minami et al. 2008, p. 130). In the mid-1980s, responsibility for financing compulsory education was handed over to the governments of county-level in urban area and township level in rural area. While upper-level governments – such as central and provincial ones – set educational targets, lower-level county or township governments have the responsibility of raising educational funds and actually implementing policies to achieve the targets (Ahmed et al. 1991, pp. 117–120; Minami et al. 2008, pp. 130–134).15 The diversification of financial sources also contributed to financing education. Chinese educational reform since the mid-1980s aimed to diversify the funding channels of education by encouraging the establishment of private schools and diversification of educational funding into: educational taxes, tuition and miscellaneous fees, income generated from school factories, donations, etc. As a result, the proportion of educational funding coming from central and local government declined from 84.5% in 1991 to 64.7% in 2006 – computed from the China Statistical Yearbook 1997 and 2008. India has a longer tradition of providing private-school education. However, a large number of government schools and private-aided schools – which together constituted 92.2% of primary, 78.1% of lower-secondary, and 67.6% of upper-secondary schools in FY2005 – have been mainly financed by the central and state government, and by lower-level governments in some part (Ahmed et al. 1991 pp. 142–143; Tilak 2003, pp. 43–44). Since the central and many state governments suffer from fiscal deficits, substantially expanding public expenditure on education is difficult. In fact, many states banned the recruitment of regular teachers due to the fiscal squeeze, and replaced them with para-teachers (Mehrotra 2006, pp. 270–271).16 Since the 1980s, foreign aid has contributed to financial resources for education. Only in recent years has more proactive diversification and mass mobilization of financial resources gradually started. First, in 2004, the 2% education tax, imposed on all central tax, was introduced (Mehrotra 2006, p. 270). Second, as will be mentioned in Section 5.4 – the 11th 5YP, 2007–2011, advocated a public-private partnership (PPP) to increase private investment in Indian vocational education and training. 5.3.2 Individual incentives for skill acquisition Individual incentives for acquiring skills also influence the speed of skill accumulation in the entire economy. In a simple framework, a rational individual calculates the net benefit – that is, benefit minus cost – received
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by investing in E&T. Only if the net benefit is positive will he or she actually invest in E&T. The sizes of wage premiums and employment opportunities affect the benefit of E&T. The amount of tuition, the availability of educational loans, and the level of family income affect the cost incurred through E&T investment. Although these cost factors are important, this section focuses on the benefit of skill acquisition – particularly through education. Several existing studies indicate that the private rates of return to education – RtoEdu – which measure the wage premiums receivable from education, are high in the urban formal sector in both China and India (Asuyama 2008; Azam 2009; Dutta 2005).17 For example, based on the results of Asuyama (2008), wages obtained by those with a universitylevel education were 46.9% higher compared to urban permanent workers with only primary or lower-than-primary education, in China in 2002. In urban India, Dutta (2005)’s results indicate that the wages of regular wage-workers were 82.7% higher, compared to wages obtained by the illiterate or those with less than two years of formal or informal schooling in 1999. On the other hand, the RtoEdu in the informal sector has been very low in urban India. The corresponding wage premium for tertiary education was only 1.8% and statistically insignificant for the Indian casual wage-workers. By contrast, it was high and statistically significant in urban China. The corresponding wage premium for the Chinese temporary workers was 72.4% in 2002. This is calculated from Asuyama (2008) who examined the data that substantially exclude rural-urban migrants. However, S. Yan (2008) also found that the RtoEdu was statistically significant for both migrant workers and residents in Shanghai, although the rates were lower for migrants. Therefore, at least in urban China, even disadvantaged workers or those in the informal sector have incentives to pursue higher education. Unlike China, in urban India, there is almost no incentive for workers in the informal sector to acquire higher education, since the possibility of acquiring a formal-sector job seems lower in India. Many Indian people who received higher education do not necessarily obtain better jobs. For instance, in 2004–2005, the proportions of regular salaried worker or wage employees to the Indian urban labor force equipped with upper-secondary education and university education were only 42.2% and 55.4%, respectively – calculated from NSSO (2006). The remaining proportions of people were either self-employed, casual workers, or unemployed. Some self-employed workers may receive much higher earnings by successfully running their own business. However, as Ghose (2004) and Sundaram (2007) report, the ratio of the working poor is much higher for self-employed and casual workers compared to regular wage employees. The employment statuses of self-employed and casual workers are also less stable.
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5.3.3 Firms’ demand for skill The above problem of more skill wastage of educated or trained people in India seems to be due to not only supply-side problems such as the quality of E&T, but also demand-side problems – that is, demand shortage for those skilled workers indicated by the small-sized formal labor market, which is the only place where investments in education are rewarded. In 2005, the proportions of formal and informal employment were 33.6% and 66.4% in China; 5.8% and 94.2% in India. It should be noted that these figures for China and India are not directly comparable, since the definitions of formal and informal employment are different between the two countries – for a definition of formal and informal employment, see the notes of Table 5.6. I followed the definitions used by the (OECD 2007).18 The Indian statistics are collected by DGE&T and often used to show the large presence of the informal sector in India. Formal employment, in India, is defined as employment in the organized sector – which includes all the establishments in the public sector and nonagricultural private establishments employing 10 or more workers. However, the registration of establishments employing 10–24 employees is on a voluntary basis, and thus the size of organized – that is, formal – employment is likely to be underestimated. In fact, based on the Economic Census data, the proportion of people usually working – including those who are not hired or paid – at establishments with less than 10 people was 62.9% in 1990, 66.9% in 1998, and 74.5% in 2005 (CSO 2008). Although it is difficult to correctly measure the size of formal and informal employment in the two countries, it is appropriate to say that the presence of informal employment is much larger in India than in China. In addition, informal employment is on an increasing trend in the two countries. Table 5.6 reports the compound annual growth rate – CAGR – of formal employment. It reveals that the CAGR of formal employment in China was higher until the mid-1990s but has experienced negative and slow growth since then. In India, formal employment growth was stagnant throughout the 1980s, 1990s, and the early 2000s. The negative or slow growth of Chinese formal employment since the mid-1990s is mainly due to reduction in employment by traditional firms, including state-owned or collective enterprises. Especially in the late 1990s, many of these traditional Chinese firms laid-off a large number of employees due to deterioration in their financial performance. On the other hand, it is worth noting that urban formal employment by emerging firms – such as limited liability or shareholding corporations, and foreign-owned enterprises – has substantially and continuously increased since the mid-1980s. By contrast, in India, the growth rates of formal employment by public and private firms have both been low. Even in the early 2000s, when India achieved higher economic growth – the CAGR of the GDP was 7.0% between 2000 and
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Table 5.6 Compound annual growth rate of formal employment China
India
Total FE Urban TFE Urban EFE Rural FE Total FE FE−public FE−private 80–85* 85–90
7.54 3.82
3.35 2.45
– 29.78
18.40 5.83
1.81 1.40
2.77 1.68
−0.29 0.74
90–95
3.84
0.73
40.37
6.78
0.87
0.73
1.23
95–00
−2.82
−7.80
17.57
−0.07
0.31
−0.16
1.42
00–05
0.88
−5.34
14.63
2.17
−1.10
−1.39
−0.45
Notes: * 81–85 for India. CAGR: Compound annual growth rate. Definitions of formal employment (FE) and informal employment (IFE) are as follows: China: Following the OECD (2007), FE includes urban TFE (traditional FE) by state−owned and collective−owned firms, urban EFE (emerging FE) by cooperative, joint−ownership enterprises, limited liability corporations, shareholding corporations, and foreign−owned enterprises including those funded by residents of Hong Kong, Macao, and Taiwan, and rural FE by township and village enterprises. IFE includes employment in registered private enterprises, self−employment, and individual businesses. Unlike the OECD (2007), I include irregular employment, which seems to contain rural migrants and laid−off workers in FE, in IFE. India: Following the OECD (2007), FE and IFE are equal to the employment in the organized and unorganized sector, respectively. The organized sector includes all the establishments in the public sector and non−agricultural private establishments employing 10 or more workers. (The registration of establishments employing 10–24 employees is on a voluntary basis.) Sources: NBS (2006) China Statistical Yearbook 2006, and IAMR (2006), DGE&T (2007a).
2005 – both public and private formal employment declined. Since the slow growth of formal employment in China was due to the exiting of poor-performance firms and new entrants have continuously created formal jobs, the problem of jobless growth – high economic growth with stagnant growth in formal employment – is less substantial in China than in India. Why has formal employment in the Indian private sector not grown? Answering this question is beyond the scope of this chapter, but there are a large number of studies dealing with this question. Many studies blame the rigid labor-related laws of India. For instance, Besley and Burgess (2004) – found that employment growth in organized manufacturing was lower in states under the more pro-worker Industrial Disputes Act which was originally enacted in 1947. However, there is also some criticism of these studies. Bhattacharjea (2009) – summarized the methodological problems of these studies, although he still hypothesized that the expansion of the unorganized sector may be due to Indian labor regulations that could be encouraging firms to subdivide and outsource their production processes. Uchikawa (2003) – suggested another reason. He explained that Indian organized manufacturing firms adopted capital-intensive technology
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instead of employing more workers. According to him, this strategy was necessary for firms facing import competition or wanting to access the export market during the economic liberation in the 1990s in order to improve quality and reduce waste of materials.
5.4
Concluding remarks
We have seen that China has more equal skill distribution with a much larger semi-skilled labor force – especially those with lower-secondary-level education – while India has unequal skill distribution with a small semiskilled labor force and a large number of both illiterate and highly-educated people. India also seems to be lagging behind China in terms of quality of education – especially at the primary and secondary levels – and vocational training. Comparison of E&T policy between the two countries reveals that China has prioritized literacy and basic – primary and lower-secondary – education since 1949 and made substantial progress in universalizing basic education. By contrast, India traditionally prioritized tertiary education and only after the mid-1980s did India begin to seriously promote the universalization of basic education. Compared to India, China’s E&T policies have always emphasized linkage between education and employment and tried to foster employability skills and mass production skills. More incentive mechanisms are embedded in the Chinese E&T system for key actors such as local governments and teachers to improve the quantity and quality of E&T – compared to the Indian system. The large and diverse funding that China started much earlier than India also contributed to mitigating a shortage of educational funds in China. In addition to these supply-side problems, India has a demand-side problem: stagnant increase in formal employment opportunities – even during high economic growth. In India, wage premiums receivable through education are very high for formal employment but very low for informal employment. Indian investment in education does not necessarily ensure formal employment – which pays a large education premium. This situation hinders Indian people in investing in education. In China, wage premiums for education are high for both formal and informal employment and thus the Chinese people have more incentives to invest in education than their Indian counterparts. The above findings concerning the pattern of skill distribution can gradually change, since both countries – especially India – have recently started to reform their SFSs. India is trying to introduce many skill-formation techniques that have already been utilized in China – for example, expansion of the size of vocational E&T, stronger linkage between E&T and employment, shorter modular training, diversification of finance, and the introduction of monitoring and incentive mechanisms.
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India’s 11th 5YP 2007–2012 proposed that a “National Skill Development Mission” (SDM) be launched with an outlay of Rs 22,800 crore – approximately US$ 4.7 billion. The SDM aims to provide “a pool of trained and skilled workers, sufficient to meet the domestic requirements of a rapidly growing economy” and to boost the training capacity of India’s vocational education and training (VET) from the current 3.1 million to 15 million. The SDM proposes various reforms: strengthening linkages between VET institutions and industry through public-private partnership (PPP); moving away from regulation to performance measurement and rating/ranking of VET institutions; establishing a “National Skill Inventory” and a “National Database for Skill Deficiency Mapping” on a national web portal; attaching a career counseling function to employment exchanges; establishing 50,000 Skill Development Centers; offering short-duration modular training courses; establishing a National Qualification Framework; etc. It also plans to upgrade ITIs – 500 into Centers of Excellence and the remaining 1396 ITIs by PPP, etc. – and 400 polytechnics and establish many new ITIs and polytechnics (Planning Commission 2008, Vol. 1, pp. 87–100). It is planned to expand the intake capacity of vocational education from the current 1 million students in 9,583 schools to 2.5 million students in 20,000 schools by 2011–2012. Demand-driven vocational education programs in partnership with employers and learning of soft skills such as computer literacy and English are also emphasized (Planning Commission 2008 Vol. 2, pp. 20–22). Having achieved substantial improvement in basic education and faced with India’s progress towards a “knowledge economy” in recent years, the 11th 5YP also proposed some reform of tertiary and upper-secondary education to expand skilled manpower. Considering the above reforms in India, skill distribution in India may gradually become less unequal. However, these reforms are mainly supplyside E&T reforms. Demand-side reforms to expand labor demand – which rewards skill supply generated through E&T institutions – are also necessary. They may include reforms in labor-related laws and industrial policy to promote manufacturing and service industries, which demand relatively more semi-skilled and skilled workers. Introducing some incentives for firms to invest in the training of low-skilled employees – for example, the Skills Development Fund of Singapore – may also be effective.19 With regard to China, due to the expansion of entrance quotas for tertiary education in 1999, the amount of highly-educated manpower has been rapidly increasing. This will make China’s skill stock more highly educated. However, China has also been facing a recent demand-side problem – that is, the high unemployment rate of university and college graduates. China is also required to expand employment opportunities for this highly educated young population, although for China, the demand-side problem is less severe than for India.
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Notes 1. China and India have different educational systems and different names for each level of education. For comparison purposes, I classified the educational levels of both countries into primary – P, lower secondary – LS, upper secondary – US, and tertiary – T, by applying UNESCO’s classification. The classification result can be found in Tables 5.1, 5.2, and 5.3. These classifications apply throughout this chapter. 2. The total employment in India is relatively small compared to its population, reflecting the low labor force participation ratio – LFPR – of females. The female LFPR in 2005 was 71.0% in China while it was 34.2% in India (ILO 2007). 3. With regard to general information on the Chinese education system, see UNESCO-IBE (2006a); Minami et al. (2008), pp. 12–14; and Liu (2004), pp. 42–56 in particular. Concerning the Indian education system, see UNESCOIBE (2006b), and the World Bank (2008). 4. Some centrally funded institutions, such as the Indian Institutes of Technology (IITs), Indian Institutes of Science (IISc), National Institutes of Technology (NITs), Indian Institutes of Information Technology (IIITs), and Indian Institutes of Management (IIMs), are known for their advanced research and technical or professional education. 5. Regarding general information on Chinese vocational training schemes, see Cooke (2005); MLSS (2002); Nishioka (2005); and Yamaguchi (2007). For India, see DGE&T (2007c), pp. 1–6; MLE various years; Okada (2008); and World Bank (2008b). 6. The entry qualification for ITIs/ITCs varies from an 8th grade pass to a 10th grade pass, depending on the requirements of different trades (MLE (2007), pp. 211–226). After completion of training, trainees take an All India Trade Test (AITT). Once they pass the AITT, they receive a National Trade Certificate (NTC). 7. Labor exchange data used in this paragraph were drawn from NBS and MLSS (2007); MLE (2008); and DGE&T (2006). 8. The Employment Exchanges (Compulsory Notification of Vacancies) Act, 1959 requires that employers issue a compulsory notification of vacancies to the employment exchanges. However, this act only applies to all establishments in the private sector and all nonagricultural establishments employing 25 or more workers – MLE (2008), p. 199. 9. For the history of E&T policies in China, I mainly referred to Acharya et al. (2001); Hannum (1999); Liu (2004); Minami et al. (2008); D. Yan (2008b); and Zhuag (2001). 10. For example, one of the reasons for the establishment of technical schools around 1950 and the promotion of vocational education after 1978 was to prevent unemployment – Liu (2004), p. 44. Various vocational training programs – such as pre-job training under the labor preparation system and reemployment training for laid-off and unemployed persons – also have a similar purpose. 11. In India, Gandhi also proposed to combine education and work. However, for Gandhi, “work” meant traditional handicrafts – not factory production skills – since he opposed the industrialization that the British Empire or Western civilization pursued (Kohara 2004, p. 211). In addition, most of Gandhi’s views on education and work were not adopted under the heavy industrialization policy started from the Second 5YP, 1956–1961.
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12. The labor preparation system promotes one- to three-year pre-job vocational training or education for new entrants to the labor force, targeting primary and secondary school graduates (MLSS 2002, p. 17). 13. For the history of E&T policies in India, I mainly referred to Kohara (2004); Nakamura (2006); and EFA’s website (EFA). 14. http://india.gov.in/govt/documents/amendment/amend73.htm. Accessed on December 7, 2009. 15. Due to the big financial burden on township governments, the responsibility for financing education was again transferred from the township level to the upper-county level, and the central and provincial governments increased their financial contribution to the rural areas from 2001. 16. Mehrotra (2006), p. 271 expresses concerns regarding unfair treatment – for example, low salary – of para-teachers and the negative influence on students’ learning achievement – although hiring para-teachers does offer various advantages. 17. Here, I regard permanent workers in China and regular wage-workers in India as workers in the formal sector, and temporary workers in China and casual wageworkers in India as workers in the informal sector. 18. The OECD (2007), p. 12 – says that “the informal-sector employment refers to own-account workers and employers and employees in firms with fewer than 5 (or 10) employees including (unpaid) family workers” and domestic workers engaged by households. “According to ILO guidelines, informal jobs can be defined broadly or narrowly depending on national circumstances from ‘noncompliance to national labour legislation, income taxation, social protection, or non-entitlements to certain employment benefits (advance notice, severance pay, paid annual or sick leave etc.)’” 19. The Skills Development Fund (SDF) of Singapore requires employers to contribute 1% of the gross salary of employees to the SDF. However, firms can recoup 80% of their contribution by requesting training grants (Kuruvilla et al. 2002).
References Acharya, Alka, Rama V. Basu and Geetha B. Nambissan, 2001, “The State and Human Development: Health and Education”, in G. P. Deshpande and Alka Acharya, eds., 50 Years of India, China: Crossing a Bridge of Dreams, New Delhi: Tulika. ACMR – All China Marketing Research Co., China Data Online. Ahmed, Manzoor, Cheng Kai Ming, A. K. Jalaluddin, and K. Ramachandran, 1991, Basic Education and National Development: Lessons from China and India, New York: United Nations Children’s Fund (UNICEF). Asuyama, Yoko, 2008, “Changes in the Causes of Earnings Inequality in Urban China from 1988 to 2002”, IDE Discussion Paper, 176. Azam, Mehtabul, 2009, “Changes in Wage Structure in Urban India 1983–2004: A Quantile Regression Decomposition”, IZA Discussion Paper, 3963. Barro, Robert J., 1991, “Economic Growth in a Cross Section of Countries”, Quarterly Journal of Economics, 106–2, 407–43. Benhabib, Jess and Spiegel, Mark M., 1994, “The Role of Human Capital in Economic Development: Evidence from Aggregate Cross-Country Data”, Journal of Monetary Economics, 34–2, 143–74. Besley, Timothy and Robin Burgess, 2004, “Can Labor Regulation Hinder Economic Performance?: Evidence from India”, Quarterly Journal of Economics, 119–21, 91–134.
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Bhattacharjea, Aditya, 2009, “The Effects of Employment Protection Legislation on Indian Manufacturing”, Economic & Political Weekly, XLIV (22), pp. 55–62. Bombardini, Matilde, Giovanni Gallipoli, and German Pupato, 2009, “Skill Dispersion and Trade Flows”, NBER Working Paper, 15097. Cooke, Fang, 2005, “Vocational and Enterprise Training in China: Policy, Practice and Prospect”, Journal of the Asia Pacific Economy, 10 (1), pp. 26–55. Crouch, Colin, 2005, “Skill formation Systems”, in Stephen Ackroyd, Rosemary Batt, Paul Thompson and Pamela S. Tolbert, eds., The Oxford Handbook of Work and Organization, New York: Oxford University Press. CSO – Central Statistical Organization, Ministry of Statistics and Program Implementation, Government of India – 2006, “Selected Socio-Economic Statistics India 2006”. CSO – Central Statistical Organization, Ministry of Statistics and Program Implementation, Government of India – 2008, “Economic Census 2005: All India Report”, New Delhi, CSO. DGE&T – Directorate General of Employment & Training 2006, “Employment Exchange Statistics 2006”, New Delhi. DGE&T – Directorate General of Employment & Training 2007a, “Quarterly Employment Review: January–March 2005”, New Delhi. DGE&T – Directorate General of Employment & Training 2007b, “Trade Apprenticeship Training in India – As on March 31, 2004 – Under Apprenticeship Training Scheme”, New Delhi. DGE&T – Directorate General of Employment & Training 2007c, “Vocational Training Improvement Project of Government of India: Project Implementation Plan”. Ding, Weili and Steven Lehrer, 2007, “Incentives and the Quality of Teachers and Schools”, in Emily Hannum and Albert Park, eds., Education and Reform in China, London: Routledge. Dutta, Puja Vasudeva, 2005, “Accounting for Wage Inequality in India”, PRUS Working Paper, 29. EFA – Education for All India, http://www.educationforallinindia.com/page48.html. Accessed February 25, 2009. Ghose, Ajit K., 2004, “The Employment Challenge in India”, Economic and Political Weekly, November 27, 2004. Grossman, Gene M., 2004, “The Distribution of Talent and the Pattern and Consequences of International Trade”, Journal of Political Economy, 112 (1), pp. 209– 239. Grossman, Gene M. and Giovanni Maggi, 2000, “Diversity and Trade”, The American Economic Review, 90 (5), pp. 1255–1275. Hannum, Emily, 1999, “Political Change and the Urban-Rural Gap in Basic Education in China, 1949–1990”, Comparative Education Review, 43 (2), pp. 193–211. Hanushek, Eric and Dennis D. Kimko, 2000, “Schooling, Labor-Force Quality, and the Growth of Nations”, American Economic Review, 90 (5), pp. 1184–1208. IAMR – Institute of Applied Manpower Research, 2006, Manpower Profile India Yearbook 2005, New Delhi: New Age International. ILO – International Labour Organization, 2003, “Industrial Training Institutes of India: The Efficiency Study Report”, New Delhi: ILO Subregional Office for South Asia. ILO – International Labour Organization, 2007, Key Indicators of the Labour Market – KILM, 5th edition. http://www.ilo.org/public/english/employment/strat/kilm/ index.htm. Accessed February 25, 2009. Kingdon, Geeta Gandhi, 2007, “The Progress of School Education in India”, Oxford Review of Economic Policy, 23 (2), pp. 168–195.
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Kingdon, Geeta and Mohd Muzammil, 2009, “A Political Economy of Education in India: The Case of Uttar Pradesh”, Oxford Development Studies, 37 (2), pp. 123–144. Kohara, Yuki, 2004, “Indo no Kyoiku [Education in India]”, in Tanaka, Keijiro, ed., Hikaku Kyoiku-gaku no Kiso [Basics of Comparative Education Studies], Kyoto: Nakanishiya Shuppan (Japanese). Kremer, Michael, Nazmul Chaudhury, F. Halsey Rogers, Karthik Muralidharan and Jeffrey Hammer, 2005, “Teacher Absence in India: A Snapshot”, Journal of the European Economic Association, 3 (2–3), pp. 658–667. Kuruvilla, Sarosh, Christopher L. Erickson and Alvin Hwang, 2002, “An Assessment of the Singapore Skills Development System: Does it Constitute a Viable Model for Other Developing Countries?”, World Development, 30 (8), pp. 1461–1476. Lin, Jing, 1993, Education in Post-Mao China, Westport: CT, Praeger. Liu, Wenjun, 2004, Chugoku no Shokugyo-kyoiku Kakudai Seisaku: Haikei, Jitsugenkatei, Kiketsu [Expansion of Vocational Education in China: Backgrounds, Policies and Consequences], Tokyo: Toshindo (Japanese). Lucas, Robert, E., 1988, “On the Mechanics of Economic Development”, Journal of Monetary Economics, 22 (1), pp. 3–42. Mehrotra, Santosh, 2006, “Reforming Elementary Education in India: A Menu of Options”, International Journal of Educational Development, 26, pp. 261–277. MEXT – Ministry of Education, Culture, Sports, Science and Technology, 2006, Shogaikoku no Kyoin [Teachers in Six Countries: USA, United Kingdom, France, Germany, China, Republic of Korea], Tokyo: National Printing Bureau (Japanese). MHRD – Ministry of Human Resource Development, 1995, Budgetary Resources for Education – 1951–52 to 1993–94, http://education.nic.in/cd50years/g/6D/7F/Toc.htm. Accessed February 25, 2009. MHRD – Ministry of Human Resource Development, 2008a, “Analysis of Budgeted Expenditure on Education 2005–06 to 2007–08”. MHRD – Ministry of Human Resource Development, 2008b, “Selected Educational Statistics, 2005–06”. Minami, Ryoshin, Fumio Makino and Huan-zhen Luo, 2008, Chugoku no Kyoiku to Keizai-hatten [Education and Economic Development in China], Tokyo: Toyo Keizai Inc (Japanese). MLE – Ministry of Labour & Employment, “Annual Report”, various years. MLSS – Ministry of Labour and Social Security, 2002, “Skill Training in the Informal Sector in China”. Mori, Romio, 2007, “Chugoku ni okeru Syugyo-ido Sokushin Seisaku to Shokugyokunren System no Genjo [Current Situation of Economic Migrant Promotion Policies and Vocational Training System in China]”, in Mitsuhide Shiraki, ed., Kaigai Hito-zukuri Handbook: Chugoku III [Handbook of Human Resource Development Abroad: China III], Chiba: Overseas Vocational Training Association (OVTA) (Japanese). Nakamura, Shuzo, 2006, “Indo no Shoto-kyoiku no Hattenn to Kongo no Kadai [Development of Primary Education in India and the Challenges that Remain]”, Ritsumeikan Kokusai Chiiki Kenkyu, 24, pp. 11–33 (Japanese). NBS – National Bureau of Statistics of China, China Statistical Yearbook, Beijing: China Statistics Press, various years. NBS – National Bureau of Statistics of China, 2007, 2005 National 1% Population Sample Survey, Beijing: China Statistics Press. NBS – National Bureau of Statistics of China – and MLSS – Ministry of Labour and Social Security – China Labour Statistical Yearbook, Beijing: China Statistics Press, various years.
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Nishioka, Yumi, 2005, “Chugoku ni okeru Shokugyo-kunren Seisaku [Vocational Training Policies in China]”, in Japan Institute for Labour Policy and Training (JILPT), ed., Ajia-shokoku ni okeru Shokugo-kunren Seisaku: Jakunen-so wo Chushin ni [Vocational Training Policies in Asian Countries: With a Focus on the Youth] (Japanese). NSSO – National Sample Survey Organization, 2006, “Employment and Unemployment Situation in India 2004–05”. OECD – Organisation for Economic Co-operation and Development, 2007, “Labour Markets in the BRICs – Brazil, the Russian Federation, India and China”. Okada, Aya, 2008, “Indo: Kyusoku-na Keizai-hattenn to Kaiso-ka sareta Rodo-shijo heno TVET no Taio [India: TVET Coping with a Rapid Economic Development and Hierarchical Labor Market]”, in Aya Okada, Shoko Yamada and Kazuhiro Yoshida, eds., Sangyo Skill Development: Global-ka to Tojokoku no Jinzai-ikusei [Industrial Skill Development: Globalization and Human Resource Development in Developing Countries], Tokyo: Nippon-Hyoron-sha (Japanese). Planning Commission, Government of India, 2008, Eleventh Five Year Plan 2007–2012, Volume 1 and 2, New Delhi: Oxford University Press. PROBE – PROBE Team in association with Centre for Development Economics, 1999, Public Report on Basic Education in India, New Delhi: Oxford University Press. Romer, Paul, 1986, “Increasing Returns and Long Run Growth”, Journal of Political Economy, 94 (5), pp. 1002–1036. Sundaram, K., 2007, “Employment and Poverty in India, 2000–2005”, Economic and Political Weekly, July 28. Tilak Jandhyala, B. G., 2003, “Public Expenditure on Education in India: A Review of Trends and Emerging Issues”, in B. G. Tilak Jandhyala, ed., Financing Education in India, New Delhi: National Institute of Educational Planning and Administration. Uchikawa, Shuji, 2003, “Employment in the Manufacturing Organized Sector”, in Shuji Uchikawa, ed., Labour Market and Institution in India: 1990s and Beyond, New Delhi: Manohar. UGC – University Grants Commission, “Annual Report 2005–2006”. UNESCO–IBE – United Nations Educational, Scientific and Cultural Organization, International Bureau of Education, 2006a, “World Data on Education 6th Edition: China, Updated Version, October 2006”. UNESCO–IBE – United Nations Educational, Scientific and Cultural Organization, International Bureau of Education – 2006b, “World Data on Education 6th Edition: India, Revised Version, November 2006”. World Bank, 2008, “Skill Development in India: The Vocational Education and Training System”. World Bank, 2009, “Secondary Education in India: Universalizing Opportunity”. Yamaguchi, Mami, 2007, “Nairiku Chugoku ni okeru Dekasegi Rodosha no Shokugyokunren [Vocational Training of Migrant Workers in Inland China]”, in Mitsuhide Shiraki, ed., Kaigai Hito-zukuri Handbook: Chugoku III [Handbook of Human Resource Development Abroad: China III], Chiba: Overseas Vocational Training Association (OVTA) (Japanese). Yan, Ding, 2008a, “Chugoku: Tagen-ka, Kodo-ka, Shijo-ka he, Gendai Chugoku ni okeru Sangyo Skill Development [China: Towards Diversification, Sophistication, and Marketization: Industrial Skill Development in Modern China]”, in Aya Okada, Shoko Yamada, and Kazuhiro Yoshida, eds., Sangyo Skill Development: Global-ka to Tojokoku no Jinzai-ikusei [Industrial Skill Development: Globalization and Human Resource Development in Developing Countries], Tokyo: Nippon-Hyoron-sha (Japanese).
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Yan, Ding, 2008b, “Gendai Chugoku no Chuto-shokugyo-kyoiku: Shijo-keizai Iko-ki ni okeru Gijutsu-rodosya-gakko no Henyo [Secondary Vocational Education in China: Changes in Skilled Workers Schools under the Transitional Economy]”, Nagoya, V2-Solution (Japanese). Yan, Shanping, 2008, “Shanghai-shi ni okeru Niju-rodo-shijo no Jissho-kenkyu [An Empirical Analysis on the Dual Labor Market in Urban China: The Case of Shanghai]”, Ajia Keizai, 48 (1), pp. 1–24 (Japanese). Zhuag, Ming-shui, 2001, “50 nen no Rekitei [50–year Historical Path]”, in Reiitsu Kojima, and Xin-pey Zheng, eds., Chugoku Kyoiku no Hatten to Mujun [Development and Contradictions of Chinese Education], Tokyo: Ochanomizu Shobo (Japanese).
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6 The Institutional Milieu of Skill Formation: A Comparative Study of Two Textile Regions in India and China M. Vijayabaskar and J. Jeyaranjan
6.1 Introduction: local labor markets in global worlds of production Growth has been increasingly found to occur in regional agglomerations of firms producing interlinked goods and services. Such dynamic agglomerations/clusters in the “developing” countries have gained more visibility recently among policy makers and global capital looking for “effective” locations. The growing recognition of such phenomena – along with a perceived reduction in the role of the nation-state – has led to scholars arguing a case for the rescaling of economic regulation (Peck 2002). Since then, the “regional agglomeration” has emerged as a prime target for intervention, to improve the ability of these agglomerations to compete in global markets. Critical to the dynamism of such clusters is an array of institutions ranging from those that reduce transaction costs, to those that help them dynamically compete – provisioning of credit, technological capabilities and market information. A vital component of this local institutional milieu is a dynamic labor market that fosters skill formation and diffusion across firms. Creating such conditions for skill formation and social upgrading is a key challenge for policy makers in the developing world, as they seek to negotiate the imperatives of production for global markets and move into more value-adding segments of global-value chains. As is well known, a primary route through which processes of globalization influence low-income regions is via the labor market. Arguments for leveling up of labor markets and hence the possibility of better returns for labor in low income countries are countered by the high possibility of “immisering growth” pointing to the range of outcomes that globalization can generate. Actual outcomes – it has been pointed out – essentially depend 135
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on the institutional mediation between global product-market impulses and local labor markets. Many scholars (Ettlinger 1999) argue that it is possible to envisage a positive relationship between a cluster’s competitiveness and worker well-being. Another area of contention concerns the type of labor-market intervention that can sustain the dynamism of these agglomerations. While neoliberal orthodoxy argues for a deregulation of labor markets – enabling firms to take advantage of a flexible workforce and keep costs down – others point to the need to ensure the provision of skills in a dynamic fashion, to ensure that the cluster can take advantage of any upgrading opportunities that it is likely to confront. It is also believed that the provisioning of skills is critical – not only for competitive dynamism, but for improving labor welfare as well. Once the clusters move into more value-adding segments, there will be a greater demand for skilled workers so as to produce more skill-intensive or technology-intensive products. The greater demand for skilled labor will, in turn, lead to better wages for workers. This argument is further strengthened by growing evidence of the skill-bias inherent in recent technological change (Pavenik 2000). Further, the ability of labor to improve its conditions of work – even when there is product-market dynamism – is critically dependent upon a set of local institutions that ensure a fair distribution of the higher returns generated by moving up the value chain. The vagaries of the global product-market also tend to aggravate labor market insecurities leading for calls to ensure that workers are insulated from such negative impacts. China and India are two countries that are increasingly seen, albeit to very different degrees, to benefit from the recent processes of globalization of production and outsourcing. Among the various sectors that have grown in both the countries, textiles and clothing is one sector common to both the countries that are and have been the forerunners in the process of global market integration. Though China’s share in the global textile and clothing trade, at over 20% is much higher compared to India’s – about 4% – there is a consensus among academics and policy makers that these two countries will be the biggest gainers of the expiry of the Multi-Fiber Agreement (MFA) in 2005. The growth spurt in the exports of the textile and garments from both these countries after the expiry of the MFA is highly suggestive of this possibility.1 Despite common grounds for optimism – such as a good raw material base in cotton and availability of frontier technologies in spinning and infrastructure – differences in performance have been observed between the two regions. A recent study by van Aark et al., (2008) shows that Chinese productivity levels have increased and are higher than India’s in most industries – including textiles and clothing. Further across most provinces in China – and main states in India – labor productivity has registered much higher increases in China. Obviously, this brings the issue of skill formation, labor welfare and the contributing labor-market institutions to the forefront. Several important questions arise in this context: To
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what extent are labor market institutions geared to take advantage of new market opportunities by ensuring appropriate skill formation? How do labor market institutions mediate between global product-market pressures and local labor outcomes? Are there lessons to be learnt from China in the realm of labor-market regulation to improve skill formation? In this paper, we explore these questions through a comparative study of the nature of these institutions in two dynamic textile producing-regions of India and China – the Tiruppur-Coimbatore region in Tamil Nadu, southern India and the Shandong province in eastern China – embedded as they are in a set of different national-level regulatory institutions. In doing so, we make a case for the following arguments. First, differences in basic educational levels of workers – pre-entry skill formation – between the two regions – an outcome of macro-policy regimes – influence the extent to which workers can be trained subsequently on the job. This difference leads to differential incentives and returns for firms and workers for skill acquisition and forging career paths. Further, in the case of textiles and clothing production in the Tiruppur region, there has been an institutional lock-in into “low-road” labor practices that prevent firms from investing in labor-market upgrading. This lock-in has been aided by larger policy shifts that favor deregulation of labor markets to avoid rigidities that may impair competition in global product markets. Under such conditions, even product market upgrading has been accompanied by poor working conditions and lack of investment in skill formation. Finally, even the limited attempts to introduce clusterlevel and firm-level initiatives for skill upgrading suffer from poor standards and inadequate buy-in from firms.
6.2 Method The study of regional learning and skill formation in China is based on fieldwork carried out in the Shandong province – one of the major centers of textile and garment production in China. Shandong province – a center of cotton cultivation – is home to several fast-growing small towns, whose growth is largely based on a thriving garment and textile industry.2 In 2006, the province was the second-highest producer of raw cotton, but ranked first in terms of output of cotton and cotton-blended cloth, and fourth in output of garments (National Textile Industry Statistics Annual Report 2006). In terms of exports, the province accounts for nearly 12% of exports of yarn, fiber and other textile products – 68.3 million USD–and 5.9% of exports of garment and apparel–64 million USD – from China during 2008–2009.3 Though most exports are directed towards Japan and South Korea, firms do export to the US and EU markets as well. Our fieldwork consisted of a series of detailed semi-structured interviews with top level officials of about 15 textile and garment factories and detailed interviews with local government officials – including those involved in industrial and infrastructural development in the region. We also importantly studied a set of training
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institutions involved in the textile industry – ranging from colleges offering degrees in various branches of textile sector to vocational training institutions catering to the textile sector among others. Information from India is based on several rounds of fieldwork in what is arguably the most dynamic textile- and garment-producing region in the country – the Tiruppur and Coimbatore districts in the state of Tamil Nadu. Tamil Nadu is a region long known for the development of its textile industry and, at present, accounts for one-third of India’s textile output, 45% of yarn production, 70% of yarn exports and more than 50% of cotton knitwear exports.4 Fieldwork in this region also consisted of detailed interviews with workers in addition to interviews with officials in different kinds of firms. Issues regarding changes in the labor markets could be captured better in this case. Our discussion in this paper is, however, confined to firms specializing in spinning and cotton knitwear production – from knitting mills to final-finishing – also called cutting-making-trimming (CMT) – factories. Importantly, our interviews with the workers helped us to validate the information provided by the employers and vice-versa in Tiruppur, whereas that was not possible in Shandong. We were also able to cover a range of firms from big direct exporters to smaller subcontractors and job workers. In Shandong, we were able to access only the bigger, vertically-integrated firms. Though it is true that firms in China tend to be large and vertically integrated, there are also several smaller firms linked to the global market in myriad ways.5 We do not have information on the labor-market characteristics of workers in such firms. There are also likely to be regional variations in the dynamics of production and labor markets. However, even a comparison of the situation, using uneven information from the two regions – as the paper shows – does yield insights for appropriate interventions in the labor market. Further, it is important to take on board the fact that the success of the Chinese textile and clothing industry is the outcome of large-scale production. In addition to material gathered from fieldwork, we make use of secondary literature wherever available and required. In discussing the labor markets of a region or a cluster, it is important to understand the policy and institutional developments that have influenced the growth and structure of the textile industry in a particular country/ region. This can be seen as an interactive process between local/national institutional developments and global institutions – fashion trends, buyer characteristics, etc. In the next section, we provide an overview of the Indian and Chinese textile and garment industry.
6.3 The Indian and Chinese textiles and garment industry: structure, performance and sources of learning The textiles and clothing – T&C hereafter – industry is one of the major contributors to Indian GDP, in addition to being the largest employer after the
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agricultural sector. It accounts for “1.9 percent of gross domestic product (GDP), 11.5 percent of the manufacturing value added in 2004–2005” and “16.5 percent of total export earnings”.6 Direct employment generated in the industry – outside cotton cultivation – was estimated to be about 12.4 million in 2000–2001, in addition to large amounts of indirect employment. In China, the share of the T&C sector has declined over time from about 17.7% of gross value of industrial output (GVIO) in 1980, to about 6.5% in 2005 (Brandt et al. 2008, p. 588). The sector employed about 9.8 million in 2005 and accounted for over 15% of the total exports in the same year. Thus, in comparison with India, while the sector’s contribution to the manufacturing sector is lower, in terms of export earnings, it plays an equally important role in both the countries. However, as Table 6.1 illustrates, there are differences in the relative export performance of the two countries in the T&C sector. While in terms of exports of cotton, China’s share has declined in the global market to 0.1% in 2005 from 1.4% in 1980; India’s share has increased to 12.2%, starting with a similar share. On the other hand, China’ shares in both textiles and clothing exports have increased enormously during the period, whereas India’s has increased only marginally. What can possibly explain such differences in performance? Analysts of the transformation of the south-east Asian economies into exporters of manufactured goods have pointed to the critical role played by skill formation (Ashton et al. 1999). They argue a case for “developmental skill formation” where the states – to varying degrees – directed the provisioning of a matching supply of skilled labor in response to the changing needs of the growing productive sectors. Apart from investments in broadbased primary and secondary education, they also highlight the mechanisms through which the state created appropriate institutional incentives Table 6.1 Shares in exports of cotton, textiles and clothing Year
1980–1984
2007
Share of world cotton production (%) India China Share of world cotton exports (%) India China
9.6 25.7 1.4 1.4
19.7 29.7 12.2 0.1
Year
2000
2005
World textile exports (%)
1990 India
2.1
3.8
3.9
China
6.9
10.3
20.2
World clothing exports (%) India China
2.3
3.1
3.0
8.9
18.2
26.9
Source: Adopted from Bedi and Cororaton 2008, tables 2.4, 2.10 and 2.11.
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for firms to invest in specific sector-level learning and skill formation. In the case of Singapore, for instance, the government paid a lot of attention to onthe-job training (OJT), supported by the respective employers (pp. 23–24). On the other hand, there are also instances – as in the case of Malaysia and Thailand – where the government continued to create conditions to compete on the basis of low wage costs by suppressing collective bargaining and keeping wage costs low (ibid.). Such “low road” policy moves prevent the development of pressures to build other competencies that not only sustain competitiveness but also help economies achieve better returns from participation in global trade. Given such strong empirical bases for the importance of skill-formation systems to a globalizing region, it is important to look into the processes that enable – or prevent – the formation of the requisite skills to move from competing merely on the basis of low wage costs to competing through added value and improved skills. As a prelude to our analyses of the processes unfolding in the Indian T&C sector, we delineate, in the next subsection, some of the key features of the sector and the changes that have occurred. As has been described in several studies, the Indian T&C industry has been the site of several state interventions, leading to the formation of a production structure that is unique in several ways. The strategy of importsubstitution-based industrialization – with the emphasis on growth of heavy industry – has exerted a strong influence on prospects for the garment industry. Since heavy industries are capital-intensive, the huge labor surpluses in India forced the state to assign a few light-goods industries – including the garment sector – the role of a labor absorber. Further, since a strong traditional artisan garment sector already existed, it was felt that it needed protection from competition by more “efficient,” modern capital. Consequently, sectors like the garment sector were reserved for firms that fall under the “small scale” sector – with various incentives for such firms. Firms with a capital investment limit of less than 10 million INR were categorized as “small”7 and any firm with greater investment needed to commit to export more than 75% of its output. Small firms therefore found it difficult to upgrade their technology, as this would invite a movement beyond the capital ceiling fixed for the small-scale sector. As a result, the Indian garment sector is dominated by clusters of smaller firms – compared to other exporting low-income nations (Chatterjee and Mohan 1993, M 116). Such policy moves to protect small-scale producers in different segments of the apparel value chain has led to the rise of a large-scale spinning sector, a highly fragmented and small-scale weaving and knitting sector, and again a fragmented clothing sector (Bedi and Cororaton 2008, Tables 4.7, 4.8 and 4.10). Studies argue that the resultant fragmentation process prevents firms from realizing scale economies and consequent efficiency. Further, it is also believed that this predominance of small firms prevented investment in
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processing techniques – compared with other exporting countries (Kathuria et al. 2000). To illustrate, in the weaving segment, India’s average ratio of shuttleless- to shuttle-looms is only 3%, whereas the global average is 16%–indicating the prevailing technology gap. Despite such limitations, Ramaswamy and Gereffi (1998) point out that India has improved its market share in 9 out of its 17 main product categories (p.129) and, further, that there has been an increase in the unit values realized. This appears to have been possible due to the advantages derived from such a decentralized and networked production structure, which enable firms to compete in lowvolume segments with greater fashion content – compared to, say, China or Bangladesh where the minimum efficient scale of operation is much higher. In fact, Kathuria et al. (2000), quoting Khanna (1993), point out that, while Indian firms subcontract 74% of their output, no other country subcontracts more than 36% of their output. Thus, while government policies have constrained garment producers from competing on the basis of scale economies, they have fostered a structure – albeit indirectly – that facilitates production for a more flexible product market. Some of the effects of reservation have been undermined since 2000, with a series of policy reforms aimed to improve the competitiveness of the industry. In 2000, the National Textile Policy dereserved the garment industry – paving the way for large-scale expansion in capacity, and importantly modernization of backward segments. Reforms also included “(1) the removal of restrictions in loom capacity, (2) the use of automatic looms, and (3) the elimination of regulations that allowed only small-scale firms to produce garments and hosiery.”8 Incentives and concessions were also offered to exporters for the creation of export zones and technology parks, concessions for purchase of land, cheaper credit and permission for entry into FDI. Another important policy intervention – aimed at technology upgrade – was through the Technology Upgradation Fund Scheme (TUFS) that offered loans to producers to upgrade their technology on very subsidized terms. The removal of reservation for the small-scale sector has opened up possibilities of movement into large-scale production. Aided by a good domestic production base in cotton fiber and lack of import restrictions to upgrade process techniques, Indian garment producers have begun to enter mass markets as well – though, as Kannan points out, export shares of specific garment segments have declined and only a few have gained since 2000 (Kannan 2010). Importantly, however, until very recently none of these interventions had been directed towards skill upgradation or any other intervention in the labor market. Accompanying these changes in the policy framework has been a steady increase in the export of garments. While textiles and clothing exports grew from 5.2 billion USD in 1990 to 21.5 billion in 2007, the share in merchandise exports rose from 0.3% in 1960/61 to 29.1% of total exports in 1990 and declined to around 15% in 2007 (Chatterji and Mohan 1993;
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Kannan 2010, p. 17). However, India’s share in global exports has been relatively slow – having moved from 1.5% in the 1970s to 2.6% by 1994 (Ramaswamy and Gereffi 1998) and now to 4.3% in 2007. India’s market segments continue to “mainly fall in cotton, semi-fashion, middle price segment with main product category being T-shirts, men’s shirts, ladies’ blouses, ladies’ dresses and skirts” (Tait 2001, p. 44). Tiruppur’s product markets too fall under this category and there is evidence of investments in process upgrading and also improvements in unit values realized over time – as well as a simultaneous movement in lower-value mass-produced products. China’s T&C sector is dominated by large firms, with joint ventures accounting for a larger share of the export market. Over a period of time, there has been backward integration of firms into processes like spinning, dyeing and also forward integration, like design and branding. Joint ventures facilitated learning through training of workers in parent countries – particularly in the quality area. Such product- and process-upgrading is evident in textile and clothing factories in Shandong as well. We also observed that several factories undertook in-house R&D and also interacted with machinery producers and suppliers for better utilization and incremental innovations. Thus, despite successes in the global textile and clothing trade, India’s performance in relation to China is much less spectacular – despite having substantial presence in the various segments of the apparel value chain, including cotton cultivation. While this can be partly attributed to the industrial structure, an important component of China’s success has been its labor productivity. Though hourly wage compensation is higher in China than India and other competing countries, labor productivity is much higher (United States International Trade Commission (2004)). The Global Competitiveness Report 1999 points out that wage rates adjusted for productivity, despite low nominal rates, are among the highest in India. While India ranks extremely low at 51 out of 59 countries in labor productivity, China ranks fifth. Though these indicators are only representative of the entire workforce and may not hold true for the garment sector, it is quite likely that some of the differences would favor China – even within the garment sector. In fact, though the data on wage rates would indicate that Indian wage rates are not too different from other low-income economies, it is found that the costper-standard-minute in India is higher than that of Indonesia, Thailand and China (Majumdar 1996). While investment in modern technology is definitely a factor, literature shows the importance of skill formation and organizational innovations in this regard (Ashton et al. 1999). A decade ago, the average Chinese firm provided about 70 hours of training per year to its workers and managers compared to only 10 hours in India (Chandra et. al. 1998 cited in Tewari 2004). Studies also point to a lack of adequate skills at the managerial and intermediate levels. What explains this difference?
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It has been pointed out that globalization fosters skill-biased technological change and thereby provides incentives for skills training. Studies also show that – despite increases in pre-entry training – there has been considerable in-firm investment globally in training (Gersbach and Schmutzler 2006). The importance of on-the-job learning – in the context of growing skill bias on the one hand and the growing recognition of tacit learning on the other – warrants this training. Further, it is said that increased skill bias creates incentives for individual workers to invest in training (ibid.). Prior to studying the processes of skill formation and diffusion, in the following section we provide a comparative profile of the labor market in the two regions – so as to understand the factors conditioning the processes of skill formation.
6.4
Labor markets in Shandong and Tiruppur9
Given the fact that a considerable section of the Indian garment industry is confined to the “unorganized” or “informal” sector, conditions under which workers labor is hardly subject to the legal realm. Given the predominance of “informal” sector activity, formal interventions are less likely to be enforced – compared to other economies. In China, on the other hand, the dominance of large firms implies that labor can be subject to greater regulation. Though the decline of state-owned enterprises and the rise of joint ventures and other private ventures, have led to a gradual deregulation of labor markets, the regimes of labor control and skill formation are likely to be different. 6.4.1 Access to labor, segmentation and conditions of work The global product markets have influenced the labor market in Tiruppur in two ways. One, the growing demand for labor has been met through incorporation of both women and migrant labor into the workforce. Initially drawn from neighboring villages and towns, over time migrant labor – from different parts of the state and from other regions of the country – has been employed. In the earlier phases of the industry’s growth, the presence of women was marginal, especially when compared to other important centers of knitwear production during that period. Since then, women workers have catered greatly to demand arising both from increases in the total number of existing jobs as well as new jobs created since export orientation. Checking stitched garments for faults – a new job associated with quality requirements of the export market – is undertaken solely by women. In Shandong, women account for more than 80% of the workforce in most of the factories that we visited. A large share of the workers comes from within Shandong province – primarily from nearby villages or towns. A small proportion is from more interior villages and they tend to be housed in quarters provided by the firm. There are also differences in the nature
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of gender-based segmentation in the two clusters. In Shandong, we find that – since most workers are female workers – there is hardly any gender segmentation in the nature of jobs undertaken. It is true that there are more male workers in the spinning department and far fewer in the stitching departments. The segmentation happens only as we move higher up the job ladder, with fewer women represented at managerial levels. However, even among supervisors – line or team leaders – there are many women holding such positions. In Tiruppur, there are hardly any women employees in the higher levels. The volatility in export-product markets and seasonality in demand has led to the rise of two segments within the migrant labor force. One section of the workers consists of permanent migrants. They come as entire families, with each member taking up various kinds of jobs in the industry. The other set of migrant laborers – which accounts for at least 20–30% of the migrant population – is constituted of more temporary migrants. They come to Tiruppur during the peak season and go back to their native villages or towns only to return the next year. Coupled with the informal nature of small-scale production, there has been a rising “impermanence” of the workforce as a result. Such incidence of “impermanence” is much less in the Shandong T&C sector. Workers work for longer periods in these firms – with mobility more internal than external. This is in marked contrast to the workforce in Tiruppur. Secondary literature on China and India – and our fieldwork in Tiruppur – show that export factories are marked by high levels of work intensity – including lengthy workdays. Respondents in Shandong report only six days of work in a week and a maximum of 1.5 shifts in a day. However, studies show that workers are forced to work overtime, stretching to as much as 12–14 hours or overnight, to cater to the delivery schedules of the buyers – even as the buyers force suppliers to comply with their codes of conduct. As a result, supplier firms tend to fudge time sheets to comply with the codes of conduct imposed by the buyers. Such work intensity is observed in Tiruppur as well. In fact, it appears to be even more intense, given the nature of segments that firms in Tiruppur specialize in. Driven by fashion trends, buyers increasingly place orders closer and closer to the season – giving the suppliers less time to complete the orders and ship them. This forces supplier firms to employ larger numbers of workers for shorter periods to complete the orders. Use of just-in-time recruitment through labor contractors and by employing workers for three shifts a day is therefore more frequent. Casualization of the workforce is therefore a phenomenon common to both the regions – though there are variations in the nature of state intervention between the two regions. In Shandong, privatization of the state owned enterprises (SOEs) and allowing entry of foreign capital into garment production has caused a gradual casualization of the workforce. At present – except for a few SOEs – all firms recruit labor on a casual basis. However, the
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state introduced a nationwide policy in 2008 that mandates all firms to provide five types of social-security benefit in China – such as accident and health insurance and unemployment insurance. This follows the earlier formulation of “China Social Compliance 9000 for Textile & Apparel Industry” in 2005–a national standard for labor welfare – which mandated rules on working-hours, wages and safety by the China National Textile & Apparel Council (El Sayed et al. 2006). In Tiruppur – except for about 40 top export firms, probably employing a core workforce of about 25–30,000 workers – the rest of the blue-collared workers are all casual workers without social security entitlements. Such big direct exporters can “afford” to have a “permanent” labor force by virtue of their ability to offer continuous employment throughout the year. Being “permanent” entitles the workers in these units to Provident Fund and Employee State Insurance (ESI) benefits for healthcare – and, above all, a security of employment denied to most workers in the industry. Flexible employment practices do aid capital in Tiruppur to competitively cater to a highly seasonal and flexible product market. Of late, there have been moves by the export firms to comply with the buyers’ codes of conduct and this has pushed them into employing a permanent workforce – with all the attendant social-security benefits – in at least some of their factories. Also, there is a restraint on them to outsource operations. This move has been undertaken completely under pressure from the buyers – with no active efforts undertaken by the state. Even auditing of working conditions is done by independent private firms. Such enforcement of codes of conduct are also reported in Shandong – particularly with regard to overtime work. The implications of this new mode of labor-market regulation, however, need further examination. 6.4.2
Processes of skill formation and non-formation
Skill formation – through formal education, apprenticeship training and on-the-job training – is increasingly seen as an important aspect of building up competitive capabilities in the global economy. As Peck points out, “skill formation and its accompanying system of social regulation seems to be one of the decisive factors in determining whether economies take the high road or the low road” (Peck 1992, p. 328). How local institutions influence this process is very critical to firms’ access to the skills necessary to not only compete but – importantly – to move up the value chain. The key feature of skill formation in Shandong is the higher levels of formal educational qualifications, compared to the workforce in Tiruppur. This is primarily due to the drive towards universal education by the Chinese state. Enrollment rates in senior secondary schools have increased from about 26% in the 1980s to over 60% at present. Participation in higher-education increased from a little over 3% in 1990 to 22% in 2006. Enrollment rates in India compare very poorly with these figures – though the state of
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Tamil Nadu has one of the highest rates in the country.10 Importantly, in China at present, the formal schooling system has also gradually reoriented from focusing exclusively on academic training to a combination of academic and vocational training. Xiao and Tsang – in their study of human capital development in the fast-growing Shenzhen economic zone – provide a succinct picture of the formal schooling system in the region: Currently, the education structure consists of nine-year compulsory education (five/six years of primary education and three/four years of lower-secondary education), a three-year upper-secondary education with academic and vocational/technical tracks, two/three-year junior colleges, four-year universities, and adult-education at various levels. Vocational training begins at the upper-secondary school. “Upper- secondary vocational/technical education is provided in three types of schools: secondary vocational schools run by education bureaucracies, skilledworkers’ schools run by the Ministry of Labor, and secondary specialized schools run by various line ministries.” They also point out that the vocational content in schooling has not only increased over time from the mid-1980s, but has also proved to be an attractive option for students. For instance, “In 1995, out of 16.5 million students in upper-secondary education in China, 57% were in vocational/technical education.” Outside these early-learning systems are the adult-education programmes – both inside the workplace and in formal institutions. While they point out there are no proper estimates of the numbers being trained by firms in their workplaces, they point out that there are “2.57 million participants in adult education at the higher-education level, 56.94 million at the secondary level and 7.78 million at the primary level.” (Xiao and Tsang 1999, pp. 74–75). Most firms report the employment of many workers who have attended junior college. Students are eligible to go to junior college only after uppersecondary education – after completing 12 years of education. Definitely, the educational levels of the workers in Chinese garment factories are much higher, given the prevalence of universal compulsory education from a minimum of 9 years. Importantly – through a survey of workers in the province – they conclude that this enables workers to upgrade their skills later in their work lives. This compulsory education, they point out, has served the firms in the province to access a workforce capable of enhancing their skills – either through workplace training or more formal adult-educational programmes. By contrast, most workers in Tiruppur are poorly qualified – though 90% of them have attended school for at least a year, 60% of them have not gone beyond the primary stage. Women and long-distance migrant workers – who account for a growing share of Tiruppur’s workforce – constitute a greater section of the lesser-educated segment. This lack of formal education appears
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to be a major deterrent to acquiring job- or firm-specific skills through training in the workplace. In Shandong, respondents from local government and in the colleges and technical-training institutions do concede that, in the past, there was a much bigger disjuncture between the content and forms of training provided in these institutions and the demands of the industry. However, in recent years – with the growing realization of this gap – there have been sustained efforts to reduce this supply-demand mismatch. This has led to revision of the syllabus to cater to the changing requirements. Importantly, there is constant interaction between the industry and these institutions through their adult education programmes. Firms send employees to these institutions for short-term programmes, ranging from a few days or weeks up to even a year. Also, graduates from these institutions are called upon to take classes for the employees inside the factories. Such interaction is yet to find its way into the garment and textile factories in Tiruppur – although there have been a few exceptions of late. The NIFTTEA floated by the Tiruppur Exporters Association (TEA) has sought to offer courses that are more directly linked to the needs of the industry. Offering courses in merchandising and quality control, garment-making technology and textile processing, the institute also requires that students have hands-on training in the garment factories of the cluster. For the three-year course, for instance – offered to students who have completed 12th standard – students are expected to work in the factories after one pm on all working days, during their final year in the institute. Since the exporters association started the institute, many firms do allow for such hands-on experience. The placement officer says that about 20% of the students do not even seek placement in these factories but try to set up firms of their own. Of course, it needs to be stated that such moves are possible only among students who also come from families already with a business background. Many, in fact, are from families who already run garment factories or related ancillary units. To this extent, such formalized training also allows for inculcation of skills required for entrepreneurship – though not as broadly-based as it ought to be. In addition, the government – through its Ministry of Rural Development and in collaboration with TEA – has set up a training center to train rural youth looking for jobs requiring basic entry-level skills like sewing. The extent to which those trained have been able to get jobs, however, needs to be studied. Recently, another industry association – the South Indian Hosiery Manufacturers Association (SIMHA) – has set up an institute to train entrants in textile technology, and another association – the Tirupur Industries Federation (TIF) – has set up a fashion design center, as exporters realize the shortage of trained designers in the cluster. These associational activities are clearly the hallmark of a dynamic cluster, with well functioning interfirm networks and associations. At the same time, it also reflects the lack of adequate state intervention in the realm of skill formation in Tiruppur. Further, the absence of clear standards and benchmarks for such
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private initiatives has undermined the quality of training and its suitability for enterprises. In Shandong, we find a more active role assumed by the local and provincial governments in the training field. There is also more basic research being undertaken in the textile departments of colleges – which may not directly feed the immediate requirements of the industry. There is also collaborative work undertaken by faculty in some of these departments – with foreign firms and R&D divisions – to develop new fibers. Some of them publish in leading global textile journals and some have even filed for patents for new processes and products. One respondent said that their department is currently undertaking cutting-edge research on seaweed-based fabric development. Blending of natural and synthetic fibers, mixing of different kinds of natural fibers to produce varied fabric, is done by faculty – in collaboration with large textile firms in the region. Some of them have their own internal R&D divisions, as well, that seek to develop incremental innovations to improve quality of processes and also the time and effort taken for completion of orders. Such focus on building up R&D capabilities is not evident in the Tiruppur cluster. It also appears that in-plant training is another important source of productivity improvements in Chinese textile factories. Apart from periodic training – given to existing workers to upgrade their skills – all factories provide anywhere between three to six months of training for new recruits. Sewing-machine operators, for example, are taught to sew on at least two types of machine. Such basic training also enables firms to move workers from one production line – requiring one kind of stitching – to another line that uses a different kind of sewing machine. Combined with the emphasis on compulsory schooling, the workforce in China tends to be better placed to adapt to changing skill requirements. It also appears that they are better placed to take advantage of the increasing importance of cognitive skills – as opposed to craft-based skills – due to the higher levels of basic education. In Tiruppur, on the other hand, due to the high interfirm mobility of labor, there is little incentive for the firms to offer in-plant training. All but a few factories report an attrition rate of over 50% within a year. One leading export firm, in fact, reports an attrition rate of 90% in a year – for workers at entry level. For an individual firm, it therefore becomes extremely difficult to benefit from the training that it provides. As a result, the entire skillacquisition process is an informal process with interfirm mobility allowing for workers to move from entry-level jobs – such as helpers – to relatively more skilled jobs such as: tailor, fabric cutter, knitting-machine operator, printer or dyer. Even the government-supported skill training initiative is not supported well by the export firms. The head of the institute feels that there is no incentive for firms to sponsor their workers for such training programmes.
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Earlier – when the cluster was characterized by a lesser division of labor and greater levels of vertical integration – workers tended to learn a number of other jobs than the one they specialized in. Thus, a cutting master would also know stitching and packing, whereas a tailor would not only help to cut or pack but even run a knitting machine, when required. The formation of such a “multiskilled” labor force appears to have diminished with the greater division of labor11 and the spatial separation of different functions, such as knitting and stitching. Acquisition of specific skills, however, continues to be an informal process for the industry as a whole. Apart from jobs in dyeing and printing and in fabrication – where workers with formal technical qualifications have been employed in recent years – blue-collared jobs in the knitwear industry need no formal educational qualification. Traditionally, local workers – and, later, migrants – enter the finishing units as child workers and take up unskilled work like folding, trimming and work-helping. Soon, due to their spatial proximity to the tailors, the child workers tend to pick up stitching skills. This process continues for one to two years, after which the child workers move to other firms – either through contractors or directly, claiming experience in stitching and seeking jobs as tailors. Over a period, they become full-fledged machinists. Now, with the growing pressure from buyers and civil society organizations, firms do not recruit child labor anymore. Adolescent men and women join as helpers and within a year try to move to other factories seeking jobs as tailors. This informal process of skill-acquisition enables – to an extent – those with lower educational levels to learn and acquire a degree of vertical mobility. At the same time – as we noted earlier – this process also leads to segmentation across gender and among workers from different economic backgrounds. A formal universal and basic training can undermine such tendencies to an extent. But with the entry of private institutions in the upgrading of skills, the fees charged for training are not affordable to all segments – creating new forms of inequity. Formalization needs to be accompanied by public investment and subsidies that can broad-base the process of skill formation. Further, upgradation of existing workers through continuous training programmes – as observed in the Shandong factories – is completely absent. Only in the last year or two – in response to the growing shortage of skilled operators – have bigger exporters tried to initiate basic training within the factories – for new recruits. By providing them with accommodation, food and a subsistence allowance, they hope to retain them for a longer period. The outcomes of these new initiatives are, however, not clear yet. In the case of the spinning segment – which is part of the formal sector – there has been a gradual dismantling of the Apprenticeship Act in terms of practice. Whereas previously the Act was used to train workers and help them build careers within factories, it is now used by several spinning mills to recruit young girls as apprentices, and pay them the wages due to apprentices which are lower than those paid to regular workers. Furthermore, in
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some of the mills they are paid most of their salaries only at the end of a fixed term of two or three years of work and are not entitled to payment if they choose to quit ahead of the fixed period. At the end of the period, however, workers are not offered a longer-term career in the mill. 6.4.3 Skill formation and labor-market mobility: role of mediating institutions The process of skill acquisition is closely tied to the process of mobility of the workforce. In Shandong, given the vertically-integrated nature of the firm and the in-plant training offered at different times – and the higher formal qualifications of the workers – mobility occurs largely within the firm. There is a clear hierarchy of jobs and prospects for workers to move from one level to the next. Workers at entry level are likely to become line leaders in about three years and group leaders in about five years. Factory manager and Department manager are the next job-level up. In one of the factories studied, out of the 14 managers, 9 have progressed steadily after joining as workers. This process is also facilitated by the relatively lower turnover in these factories – compared to that observed in Tiruppur. However, even within the factories in Shandong there has recently been a greater turnover of workers, due to the multiplying of employment opportunities and the perception of work in textile factories as less prestigious. Managers feel that workers prefer to work in services sectors like retailing, rather than in their factories. The lower turnover in the past has, however, paved the way for this vertical mobility and career prospects. Over 80% of the workers tend to work for more than three years. The attrition rate is much higher in Tiruppur and for most blue-collared workers there are hardly any prospects for intrafirm mobility. Most workers do not work in the same factory for more than a year. Mobility between firms is quite high, which also allows workers to move from unskilled to semi-skilled jobs. This mobility aids the process of skill acquisition, but also acts as a disincentive for firms to impart training and offer career prospects. The move from the semi-skilled to supervisory levels, and further to managerial levels is very remote – though, in the past, when investment limits were low, there were several instances of workers starting units of their own.
6.5 Implications From the above discussion, a few points emerge. The higher levels of schooling among workers in Shandong allows for the possibility of further training to adapt to changing requirements. This highlights the close synergetic links between formal general training and firm-specific on-the-job learning that workers acquire. Movement into higher value-adding segments like
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design – or into processes that ensure a better quality of output – require a set of threshold skills among workers to ensure that such product-market upgrading translates into a broad-based process of skills improvement and enhanced worker welfare. This dimension is completely absent among the workforce in Tiruppur. As a result, the new skill demands are met by an influx of educated workers, thereby accentuating segmentation and labormarket inequities. Further, the casualization of the workforce and high interfirm mobility disincentivise individual firms from investing in training. This has been compensated to a limited extent by the rise of private and some public-private training institutions in the cluster to cater to the needs of the industry. Even then, firms continue to face strong disincentives to fund the training of their workers – given the strong possibility of the leakage of benefits derived from such skills. Further – given the dominance of seasonal and impermanent employment, and the alternating of work in this industry and elsewhere – individual workers also do not have sufficient incentive to invest in training at entry level. What’s more, the absence of clear-cut standards in the quality of training renders such training incapable of moving the workers onto a high-flying trajectory. Public investment in generic and sector-specific training definitely seems to be of a better magnitude in the Shandong region. We also observe that – despite different local level institutions – there are certain global product-market imperatives that exert a strong pressure towards pushing labor towards the “low road.” While national policies – in the case of India – have focussed attention on the hardware of capability building, there has been much less recognition – in this sector – of the role of skills formation in building ability. This appears to be partly due to an institutional lock-in that prevents formal intervention in informal labor markets, and partly due to policy shifts that perceive labor-market intervention as hampering competitiveness in global markets. As the discussion of the use of the Apprenticeship Act in the spinning mills highlights, there has been an undermining of even existing systems of skill formation in the formal sector. Equally, the importance of skill formation is clear – and the role of local institutions in this regard – in a global environment. Importantly, the discussions also hint at a greater need to look into the relationship between national-level policy institutions and the dynamism of regional production systems.
Notes 1. In the quarter after the phasing out of the MFA agreement, imports of Chinese apparel into the US increased by 60% compared to the previous year (El Sayed et al. 2006, p. 17). 2. However, many of these small towns have firms specializing in other sectors too.
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152 M. Vijayabaskar and J. Jeyaranjan 3. Data has been computed from the National and Province-wise statistical yearbooks for the years 2008 and 2009. Detailed references are provided in the References section. 4. Interview with Dr. Selvaraju, South Indian Mills Association (June 10, 2009). 5. The Responsible Supply Chain Association (2007). 6. Bedi and Corotonan (2008, p. 47). The figures are originally calculated from National Accounts Statistics, 2006, Central Statistical Organization, Ministry of Statistics and Programme Implementation, and Foreign Trade Statistics, 2006–07, Directorate General of Commercial Intelligence and Statistics. 7. The investment limit for being designated “small” has been regularly revised upwards and now stands at 10 million INR in plant and machinery. 8. Bedi and Cororaton (2008, p. 48) 9. The discussion on labor markets in Tiruppur draws substantially from Vijayabaskar (2001; 2002; 2005). 10. Asuyama (Chapter 5 of this volume) provides a detailed comparative account of the macro skill-formation systems in China and India. 11. The “deskilling” due to greater division of labor is discussed by Krishnaswamy (1989).
References van Ark, Bart, Abdul Azeez Erumban, Vivian Chen, and Utsav Kumar, 2008, “The Cost Competitiveness of Manufacturing in China and India: An Industry and Regional Perspective”, Indian Council for Research on International Economic Relations Working Paper, 228, New Delhi. Ashton, D., F. Green, D. James and J. Sung, 1999, Education and Training for Development in East Asia: The Political Economy of Skill Formation in East Asian Newly Industrializing Economies, New York: Routledge. Bedi, Jatinder S., and Caesar B. Cororaton, 2008, “Cotton-Textile-Apparel Sectors of India: Situations and Challenges Faced”, International Food Policy Research Institute Discussion Paper No.00801, Washington, DC. Brown, Phillip, Hugh Lauder, David Ashton and Gerbrand Tholen, 2008, Towards a High-Skilled, Low-Waged Workforce? A Review of Global Trends in Education, Employment and the Labor Market, Monograph No.10, Center on Skills, Knowledge and Organisational Performance: Cardiff University and University of Bath. Chandra, Pankaj, Ming. X. Wang, J. Saha, and P. R. Shuka, 1998, “Manufacturing Management in the Primary Textile Industry: Some Assessments from a Plant Level Study in Canada, China and India”, in Pankaj Chandra ed., The Primary Textile Industry in Canada, China and India, Himalaya Publishing House, Mumbai. Chatterjee, S. and R. Mohan, 1993, “India’s Garment Exports”, Economic and Political Weekly, 28 (35), M95–119. El Sayed A. A., R. Kulich, L. Lake and S. Megahed, 2006, The Chinese Apparel Cluster in Guangdong, Harvard: Harvard Business School (Microeconomics of Competitiveness), http://www.isc.hbs.edu/pdf/Student_Projects/Chinese_Apparel_Cluster_2006. pdf. Accessed November 5, 2008. Ettlinger, Nancy, 1999, “Local Trajectories in the Global Economy”, Progress in Humman Geography. Vol. 23: 335–357.
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Institutional Milieu of Skill Formation: Textile 153 Gersbach, Hans and Armin Schmutzler, 2006, The Effects of Globalization on Worker Training, Discussion Paper Series No 2403, Bonn: Institute for the Study of Labor. Kannan, Elumalai, 2010, “Post-Quota Regime and Comparative Advantage in Export of India’s Textiles and Clothing”, Journal of International Economics, 1 (2), pp. 12–28. Kathuria, Sanjay, Will Martin and Anjali Bharadwaj, 2000, “Implications of MFA Abolition for South Asian Countries”, paper presented at the NCAER, World Bank WTO 2000 South Asia Workshop, December 20–21, New Delhi. Khanna, S. R., 1993, “The Challenge of Global Competition in the 1990s: An Agenda for Enhancing the Competitive Position of the Indian Textiles and Clothing Industry”, Mimeo, ICRIER, New Delhi. Krishnaswami, C., 1989, “Dynamics of capitalist labor process: knitting industry in Tamilnadu”, Economic and Political Weekly, July 17, pp. 1353–1359. Majmudar, Madhavi, 1996, “The MFA Phase-Out and the EU Clothing Sourcing: Forecasts to 2005”, Textile Outlook International, March, pp. 31–61. Pavenik, Nina, 2000, “What Explains Skill Upgrading in Less Developed Countries,” National Bureau of Economic Research (NBER) Working Paper, No.7846, Cambridge, MA. Peck, Jamie, 1992, “Labor and Agglomeration: Control and Flexibility in Local Labor Markets”, Economic Geography, 68 (4), pp. 325–347. Peck, Jamie, 2002, “Political Economies of Scale: Fast Policy, Interscalar Relations, and Neoliberal Workfare”, Economic Geography, 78 (3), pp. 331–360. Ramaswamy, K.V. and Gary Gereffi, 1998, “India’s Apparel Sector in the Global Economy – Catching Up or Falling Behind?” Economic and Political Weekly, 33 (3), pp. 122–130. Tait, N., 2001, “Indian Garment Exports: Moving Towards 2005”, Clothesline, April, pp. 43–55. Tewari, Meenu, 2004, “The Challenge of Reform: How India’s Textile and Apparel Industry is Facing the Pressures of Liberalization”, revised version of a policy paper originally prepared for the India Program, Center for International Development, Harvard University, Cambridge MA. United States International Trade Commission, 2004, “Textiles and Clothing: Assessment of the Competitiveness of Certain Foreign Suppliers to the U.S. Market”, Vol. I, Investigation No. 332–448. Vijayabaskar, M., 2001, “Industrial Formation under Conditions of Flexible Accumulation: The Case of a Global Knitwear Node in Southern India”, unpublished Ph.D. Dissertation, Center for Development Studies, New Delhi: Jawaharlal Nehru University. Vijayabaskar, M., 2002, “The Indian Garment Industry”, in Gopal Joshi, ed., Garment Industry in South Asia-Rags or Riches? Competitiveness, Productivity and Job Quality in the Post-MFA Environment, New Delhi: South Asia Multidisciplinary Advisory Team, International Labor Organization (ILO), pp. 39–81. Vijayabaskar, M., 2005, “Labor under Flexible Accumulation: Case of Tiruppur Knitwear Cluster”, in K. Das, ed., 2005, Industrial Clusters: Cases and Perspectives, Aldershot: Ashgate. Xiao, Jin and Mun C. Tsang, 1999, “Human Capital Development in an Emerging Economy: The Experience of Shenzhen, China”, The China Quarterly, 157, pp. 72–114.
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Chinese official statistics Center for Statistics, China National Textile and Apparel Council, 2007, National Textile Industry Statistics: Annual Report 2006, Beijing: China National Textile and Apparel Council. Responsible Supply Chain Association, China National Textile and Apparel Council, 2007, Annual Report on Social Responsibility in the Chinese Textile and Apparel Industry 2006, www.csc9000.org.cn/PDF/Report/2006_en.pdf Statistical Bureau, Shandong Provincial Government, 2009, Statistical Yearbook of Shandong 2008, http://www.stats-sd.gov.cn/tjsj/nj2008/indexch.htm Statistical Bureau, Zhejiang Provincial Government, 2009, Zhejiang Statistical Yearbook, 2008 http://www.zj.stats.gov.cn/zjtj2008/2/indexch.htm Statistical Bureau, Jiangsu Provincial Government, 2009, Statistical Yearbook of Jiangsu, 2008 http://www.jssb.gov.cn/jstj/jsnj/2008/nj12.htm Statistical Bureau, Guangdong Provincial Government, 2009, Guangdong Statistical Yearbook 2009, http://www.gdstats.gov.cn/tjnj/ml_e.htm National Bureau of Statistics, Government of People’s Republic of China, 2009, China Statistical Yearbook 2008, http://www.stats.gov.cn/tjsj/ndsj/2008/indexch.htm
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Part III The Role of the State and the Global Production Network
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7 Two Tales of Agro-Industrial Transformation: State Capacity in China’s and India’s Textile Industries Mark P. Dallas
7.1 Two tales of agro-industrial transformation: state capacity in China’s and India’s textile industries It is widely understand that the textile industry historically has established the link between primary agricultural production and industrialization (Anderson 1992; Farnie and Jeremy 2004). While the industry was central to the early phases of industrialization in Britain and Europe, the same can also be said of late developers. In Japan, textiles were critical to the country’s early industrial development and it was further built up into a globally competitive industry in the interwar period (Lockwood 1965; McNamara 1995; Smitka 1998). In the immediate post-World War Two era, trade frictions between advanced economies first erupted over textiles exports – a harbinger of subsequent trade conflicts (Aggarwal 1985). While Japanese and British colonialism in East Asia planted the seeds of multiple industries, early postwar industrialization in the East Asian NICs – including South Korea, Taiwan, and Hong Kong – has similarly been dominated by textiles (Hsueh et al. 2001; Inoue et al. 1993; McNamara 2002). Interestingly, however – with the exception of the United States – none of these countries possess any significant natural raw-fiber base – most crucially cotton. In Western and East Asian countries alike, cotton was acquired almost entirely through imports – often from colonial possessions. With the invention and spread of man-made fibers in the early 20th century, all of these textile powerhouses developed extensive synthetic-fiber industries – an offshoot of the rising petrochemical industry. In essence, a division of labor existed between the cotton fiber-producing countries of the developing world and the largely fossil-fuel based fiber producers of advanced countries. This division contained a distinct political logic. Lacking a cottonfarming population, the process of establishing a man-made fiber industry in the advanced countries was made politically innocuous. With nearly all
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raw-cotton sourced through imports, there simply was no population of cotton cultivators whose livelihood was threatened by a competing industrial source of raw textile fibers. In the core countries of Western Europe, Japan, South Korea, Taiwan, Hong Kong and, more recently, Thailand and Indonesia – all major producers of synthetic fibers – there has been no political resistance from agricultural cultivators to the establishment of a domestic chemical fiber industry. Because cotton is mainly imported, any impact of the changing composition of fiber consumption by domestic mills was simply externalized to their suppliers – colonial or otherwise. In fact, there are very few examples of major cotton cultivators developing extensive man-made fiber industries (Figure 7.1). The three critical cases are the United States – starting from the early 20th century – and China and India since the late 20th century. Other major raw fiber-producing countries – such as Brazil or Pakistan – have sizeable cotton farming but minor synthetic-fiber industries – at least relative to the importance of their cotton cultivation. In contrast to the U.S., however, China and India can be further singled out because they face a particularly challenging population dilemma. While the U.S. enjoys a relatively sparse population living off abundant arable land,
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Figure 7.1 Major raw-fiber producers, 1999–2000 Source: FEB December 1999; June 2000; December 2001.
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China and India have historically faced severe food-security dilemmas, due to very high population-to-arable land ratios.1 Similarly, both countries – in the postwar period – have made both food and clothing self-sufficiency crucial political and nationalist goals – refusing to rely on imports. This has created a developmental dilemma: plant food grains or major cash crops – such as cotton on limited per capita farmland? Given this dilemma, man-made fibers would appear to be the saving grace. In theory, cotton acreage could be replaced with grain acreage, and synthetic-fiber factories could replace the lost cotton fibers to continue to feed their textile factories. While a sensible strategy, there is a political problem: both countries possess hundreds of millions of agricultural cultivators – a significant portion cotton-growers. Such a transformation has proven to be both politically risky and – in terms of food security – strategically uncertain.
7.2
The dual dilemma, state capacity and policy choice
In spite of their common dilemmas and the promise of man-made fibers in solving them, China and India have adopted widely different policy approaches to the cotton and man-made fiber nexus. This is well reflected over the past 30 years, in the transformation of each country’s textile industry from an overwhelming reliance on cotton, to the building of substantial man-made fiber industries. In the mid-1970s, both countries largely clothed their populations with cotton textiles – accounting for over 80% of total cloth production, the vast majority of which was consumed domestically. Then, from the mid-1970s to the mid-1980s, China rapidly transformed its textile-fiber composition and with it Chinese consumption patterns. For instance – between 1977 and 1984 – the share of pure cotton cloth to total cloth production rapidly declined from 80% to 50%. Although this rose back to 60% after 1984, since the mid-1990s it has remained at 50% – comparable to global averages.2 By contrast, since the passage of India’s 1985 Textile Policy – which initiated important reforms in the industry including greater interfiber flexibility – India’s shift into man-made fibers has been gradual and the country’s production composition still remains heavily tilted towards cotton fibers – especially in yarn production. For instance, pure cotton yarn – as a percentage of total production – fell from 86% in 1985 to slightly over 70% by the late 1990s and this share has increased slightly since then – whereas the proportion in China is 50%, similar to its production of cloth.3 Given the overwhelming promise of man-made fibers in solving their food and clothing-security dilemmas, why have two countries taken such different approaches in developing their man-made fiber industries? For one – in the period prior to economic reforms – political and policy-making elites in these two countries had very different perceptions of the man-made
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fiber industry. While the Indian government consistently perceived the industry as a “threat” to agriculture, the Chinese government enthusiastically grasped it as an opportunity. But why did their perceptions differ so dramatically if the dilemmas facing them were so similar? It is too simplistic to say that Indian policy-makers somehow made the “wrong” choice and the Chinese made the “right” one. Nor is this simply a case of a “messy,” gridlocked democracy, in which the influence of interest groups blocks government from pursuing some kind of national interest, while an “efficient” authoritarianism is able to.4 Rather – as argued below – these two states had very different institutional capacities by which to solve the dual dilemma of food and clothing constraints, and large cotton-cultivating populations. As I show below, the Chinese government used its prodigious institutional powers across agriculture, industry and commerce to foster a synthetic-fiber industry, at the same time that they ensured cotton farmers enjoyed a significant rise in real prices for cotton. Thus, while Chinese reformers were instituting market reforms, they were simultaneously availing themselves of the institutional legacies bequeathed from their socialist past to foster a major agro-industrial transformation. On the other hand, given India’s comparably free commercial markets and its greater permissiveness towards private industrial capital – relative to China at least – it was hard for policy-makers not to perceive synthetic fibers as a “threat” to cotton cultivators. This is because they lacked the institutional capacities to enact the sort of transformation that the Chinese government was able to engineer. Consequently – and until recently – Indian political elites have consistently worked to restrict private capital through the common policy levers at their disposal. Apart from their food and clothing dilemmas and the impact on their large agrarian populations, policies affecting upstream raw materials are also very important to the development of their textile industries – a critical industry to the Chinese and Indian economies, particularly in terms of employment and foreign-exchange earnings. Due to its upstream position in the value chain, the influence of raw fiber agro-industries reverberates along the entire downstream chain through to garments. Its effects are reflected in the possible range of products available for domestic consumption and – by extension – for export markets. In both fabrics and garments, India’s much narrower range of export-competitive products – compared to China – is influenced by the centrality of cotton as a fiber in the subcontinent, compared to China’s well-developed synthetic industry. In the late 1990s – just prior to the beginning of the phasing-out of the MultiFiber Agreement (MFA)–cotton-textile fabrics accounted for 38% of India’s total textile and garment exports in US dollar terms, while man-made fiber fabrics accounted for less than 10% (Saksena, 183). Among its garment exports – which accounted for the vast majority of the remaining total exports – 70% of them were cotton-based (Saksena, 196).
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While such fiber-narrowness can theoretically be overcome through imports of synthetic tow or yarns, concerns over India’s foreign-exchange limitations and their own nascent fiber industry have led the government to severely restrict their importation. Only in the past decade has the Indian synthetic-fiber industry really attained government support and made advances in the domestic and export markets.5 Furthermore – unlike China – India cannot as easily rely on imports of synthetic fabrics to supply its garment manufacturers, because it is substantially removed from the dense commercial ties that characterize East Asian global production networks.6 Given India’s physical distance from East Asia – and other centers of synthetic fabric manufacturing –, as well as the ever-increasing importance of delivery times in the global garmentsourcing business, India’s lack of a well-developed domestic man-made fiber industry has placed limits on its ability to enter and compete in noncotton garment-export markets. Lastly – and an important focus of this paper – the pricing of raw materials serves as a critical source of competitive advantage, especially among developing countries in which the costs of labor are more similar compared to advanced country manufacturing. This is particularly the case in the upstream fiber- and spinning-sectors, which are among the most capitalintensive along the value chain. Further, the costs of raw materials relative to other costs of production are very high in textiles – so fiber prices reverberate strongly along the downstream value chain.
7.3 A comparison of production costs in upstream textiles In highly competitive light industries, such as textiles, the costs of production are central to manufacturing competitiveness. A careful comparison across countries can reveal much about their industrial environments and shed light on how countries compete, based on different aspects of production. For instance – in fieldwork interviews of textile entrepreneurs and officials in India and China – the perceptions of the opposing country’s competitive advantage often rested along the axis of “raw materials versus capital costs.” Managers of major cotton-spinning firms in Shandong province – China’s second largest cotton producing province – argued that Indian spinners were fortunate to have access to cheaper, domestic cotton.7 Conversely, Indian export association officials believed that India’s competitiveness suffered because of the large differences in interest rates – and energy costs – between the two countries.8 These general observations are supported by more systematic data comparisons derived from factory surveys conducted by the International Textile Manufacturers Federation. The importance of the price of raw materials is undeniable – in both pure cotton yarn and textured polyester yarn production. Using the average costs of production across five years
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of surveys between 1999 and 2008, studies have estimated the relative contributions of raw-cotton costs and manufacturing costs to the total costs of production of pure cotton yarn across eight countries. In these surveys, manufacturing costs include labor, energy and utilities, buildings and maintenance, depreciation and capital interest rates (Anson and Brocklehurst 2009, p. 67). Predictably, only in the two advanced countries surveyed (Italy and the United States), do the manufacturing costs substantially exceed raw-material costs – due to the higher costs for labor and power.9 For India, South Korea, Brazil and Turkey, the two costs are about equal, while China and Egypt are distinctive in that their cost for raw cotton is quite high.10 When we narrow our focus to just China and India, the importance of raw-material costs takes center stage.11 The average cost of production of pure cotton yarn across three years of surveys in China was $3.00 USD/ kg – which is substantially higher than India’s $2.51 USD/kg over the same three years.12 Remarkably, this 49 cent difference is almost entirely due to differences in cotton prices. India’s cotton costs are about 52 cents less than China’s, while China’s manufacturing costs are only 3 cents less than India’s. This differential is particularly significant given that – for many countries – cotton costs constitute only half of total costs; yet for China and India, their cotton industries appear to compete largely on the basis of the price of raw cotton. The role of raw-material prices is even more central to synthetic-yarn production – given that for advanced and developing countries alike, raw materials constitute between 70–80% of total costs. In the comparison of China and India, however, the trends are reversed – as China enjoys on average a 14 cent cost advantage over India, with fully 12 of those cents derived from lower raw-material costs.13 This difference would have been much greater in the 1980s and 1990s – before India’s policy shifted towards promoting synthetic fibers. It appears that the capacity of countries to manage raw-material costs is perhaps the single most important area in which advantage can be passed to domestic textile firms. In cotton-based production, India’s low cotton prices are a key advantage over other major cotton-producing countries – such as China, Turkey and Brazil – as well as countries like Indonesia, which fully depends on cotton imports and – by extension – the global price of cotton. Nevertheless, there are other areas of advantage. The other major category considered here – manufacturing costs – covers a wide range of factors. For instance, the cost of capital – interest and depreciation costs – in China is far below those of other developing countries – while India tops the scales (Figure 7.2).14 This reflects the common understanding of China’s reliance on state banks as conduits in providing cheaper credit to targeted and local industries.15 In the late-1990s – when these data were collected – the textile
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Sources: China: GXZ (2003); Others: ITM (1998).
industry was one of these targeted industries in China, as the government sought to modernize and restructure the industry in preparation for the gradual unwinding of the Multi-Fiber Agreement (MFA)–between 1999 and 2005 – during which quantitative restrictions on global trade in textiles and apparel ended.16 Finally, the costs of labor and power consist of smaller portions of overall costs. In the relatively capital-intensive spinning sector – and especially in developing countries – labor costs predictably compose a smaller share of total costs and thus are not a real point of competitive difference between them.17 In power costs, however, India clearly lags behind the other countries in spending substantially more – a point made clear during interviews in India, when the electricity regularly shut down in the middle of the day. Power outages in India affect large and small enterprises alike and – according to interviews – energy from private power generators, required to keep the factories running, costs about twice the already high fees of public electricity.18 By contrast, some of the major spinning firms in Shandong province – such as Weiqiao’s industrial complexes in Zouping City and Binzhou City – possessed their own independent powergeneration plants.19 In their Binzhou plant, electricity was generated not
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only to power their spinning and weaving operations – which employed close to 30,000 workers – but also their aluminum plant, with enough electricity remaining to sell into the state grid. In smaller textile factories which do not possess independent power plants – like the spinning factories of the Demian Group – managers said they had no concerns over the consistent provision of power, even though they relied fully on the state grid.20 The above discussion makes clear that, on the one hand, India enjoys substantial advantage over China in the costs of raw cotton while, on the other hand, China rapidly expanded its chemical-fiber industry – which today has grown to many times larger than India’s. I argue that it is difference in state capacity which accounts for these differences. In the 1950s, China built up and strengthened an extensive system of state ministries to regulate the economy. Although not nearly as comprehensive as the Soviet version in heavy industries, China’s command economy exercised even more control than the Soviet Union in agriculture and commerce in consumer goods, such as textiles.21 While many of these have been gradually disassembled over the reform era since 1979, they have remained robust in the regulation of certain agricultural commodities – including cotton – and were critical in building China’s chemical-fiber industry. By contrast, the policy levers and state capacities available to Indian bureaucrats are far fewer and their power – relative to private commercial and industrial capital – has been far less. 22
7.4
State capacity and policy in cotton agriculture
In terms of domestic sources of raw materials, China and India share quite similar features. Historically, they are both among the largest producers of raw cotton – a trend which continues today, as they annually rank first and third in world cotton production, respectively. While China’s per hectare cotton yield has generally been two to three times higher than India’s, India devotes far more of its arable land to cotton cultivation.23 Until the ending of the MFA, both countries remained relatively self-sufficient in cotton production, only turning to global markets for relatively small amounts of imports or exports each year – at least as a percentage of total domestic production.24 Differences in the price of similar cotton varieties in China and India compared to the Cotlook A Index – a common measure of global cotton prices – illustrate well the relative advantage which agriculture bestows on India’s textile industry (Figure 7.3). The Cotlook A Index provides a baseline of global prices by calculating the five lowest-priced cotton varieties from among a basket of 19 major traded cotton varieties, produced in different countries around the world.25 For China and India, I utilize monthly price averages of the two cotton varieties which the Cotlook A incorporates as
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Agro-Industrial Transformation: Textile 165 USS/Ton 2,500 China 2,000 Cotlook A-Index
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Figure 7.3 Average monthly cotton prices: China, India and global, September 1999–April 2007 Sources: India: Cotton Corporation of India Ltd. China Cotton Index (Zhengzhou Commodity Exchange) and Cotlook A Northern Europe Price Index: GTIOne.
representative of middling cotton varieties and qualities for China and India.26 Figure 7.3 leaves little doubt that Indian spinners have consistently enjoyed lower prices than their Chinese counterparts. At no point has the price of Indian cotton exceeded Chinese cotton and in most periods Indian cotton remained cheaper than comparable global prices. This difference is perhaps slightly exaggerated, since Indian cotton is among the most contaminated in the world – adding some additional costs to the price of spinable cotton for Indian spinners (Landes et al. 2005, p. 32). Much of the difference in cotton prices between China and India is the result of government policy goals and state institutional capacities. In the case of China – for much of the reform era – the central government continued to impose strict controls on the domestic trade of cotton and key food grains. Only in the late 1990s has China appreciably begun to liberalize its controls over the cotton sector (Alpermann 2010). Although – prior to the late 1990s – China attempted to liberalize cotton markets twice – in 1985 and 1992, during most of the reform era, the central government has maintained and utilized many of the institutional structures built up during the Mao era – including a variety of production quotas, state prices and different incentives for the delivery of cotton – such as free or underpriced chemical fertilizers, diesel fuels and a complex array of price bonuses. As a result, the dramatic peaks and dips in cotton production in China quite consistently mirror the relative state prices and bonuses offered to farmers for the production of Northern grains versus cotton. For instance, the major peaks of cotton production in 1983–1985 and
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1990–1991 were also the only periods when the cotton – grain state price ratios exceeded ten-to-one. 27 Although collective farming was disbanded and usage rights were returned to farming families between 1979 and 1982, the state continued to maintain Mao era controls over production quotas, pricing, bonuses and markets in core agricultural commodities. Relative to other agricultural commodities, commerce and pricing remained quite state-controlled in food grains and cotton. The unprecedented rise in harvests and yields between 1978 and 1984 mirrors the major increments in state prices – which for cotton were raised 10% in 1978, 15% in 1979, and 10% in 1980, with an additional 5% price bonus for northern cotton regions.28 On top of these baseline price increases, the government offered even higher “bonus” prices for abovequota sales to the state which were priced at 30% above the average price offered in 1976–1978. This new pricing system – a radical departure from the anemic pricing of the Mao era – was rigged for explosive growth. This is because it operated, in a way, precisely contrary to market forces. Since the government paid higher prices for above-quota quantities, average prices continued to increase as output expanded. Since the state guaranteed the purchase of the entire cotton crop, the state incentivized ever-increasing output – regardless of demand requirements (Kelliher 1992). In addition – in order to ensure quota fulfillment – the state offered between 80 to 100 kg of chemical fertilizer for every 100 kg of cotton delivered, as well as diesel fuel and guarantees for the provision of rationed grains – which allowed farmers to specialize in cotton. Although this pricing system was modified in 1983, the basic incentive structure for farmers remained quite similar until China’s first attempt at the liberalization of cotton in 1985. Although strict controls over agricultural commerce and the new statepricing system were quite effective in transforming agricultural cultivation, they also led to enormous inefficiencies and contributed to large fiscal deficits. While the specific prices and incentives varied slightly each year, the rigged pricing system caused cotton production to skyrocket – from 2.17 million metric tons (MMT) to a record 6.26 MMT between 1978 and 1984. By 1984, cotton output severely exceeded the planned levels – so much so that China lacked the capacity to store, process or use it. In September 1984, General Secretary Hu Yaobang estimated that 3.5 million metric tons of cotton could not be stored and lay rotting in the open air. In addition to raw cotton, an additional five million metric tons of cotton cloth was laying in warehouses.29 By the end of the harvest season, China had 18.1 million bales of cotton in stock – 12 times more than in 1979 and 47% of the estimated world stocks of raw cotton!30 Since similar policies were instituted to stimulate grain production, the burden on fiscal expenditures became unbearable. Consequently – in 1985 – the central government decided to alter its system of procurement and
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purchasing prices by switching to “contracted” quotas, which imposed a defined upper limit on what the state was willing to purchase each year. Once quotas were filled, excess cotton was allowed to be sold on newly-freed cotton markets. This was the first opening of cotton markets in China since 1954 – a momentous but quickly-reversed experiment in agricultural market liberalization. In addition to changes in fixed state contracts, state prices were also reconfigured in 1985 – reducing marginal prices by between 7% and 14% in 1985 and another 2.4% in 1986. Subsidies and grain provisions were also reduced – making cotton far less attractive to farmers. Sown areas – along with output – fell off, causing serious supply shortages in these years. Unnerved by such dramatic shifts, the government quickly-reversed course – between 1987 and 1990 – by once again closing cotton markets, raising baseline prices, offering bonuses and reestablishing fertilizer, fuel and grain incentives (Blecher and Wang 1994). Predictably, sown acreage and production recovered – reaching a new peak in 1991 at 5.68 MMT. These new record peaks in the cotton harvest inspired state leaders to make a second attempt at liberalization in 1992 which – similar to the 1985 attempt – also failed. As a result, government controls remained until the end of the 1990s, when a degree of liberalization was achieved – partly due to China’s WTO accession.31 If China’s domestic production and marketing has been tightly controlled by the government, its cotton-trade policy has been even more strictly controlled during this period. In fact – up to WTO accession – the China National Textiles Import and Export Corporation has been the sole agent for all global trading of cotton for China, and has maintained strict importlicensing procedures for domestic firms – along with various tariffs.32 While China’s influence over agricultural commerce is hardly perfect – and at times has been undermined by the interests of local governments (Wedeman 2003)–the central government’s controls have ensured that – to a substantial degree – China has ably balanced the conflicting interests of agricultural cultivators and spinning mills. At times this has strongly favored Chinese cotton cultivators and at other times worked against them. As we will see shortly, these same policy levers proved crucial as China built up its man-made fiber industry – the industrial counterpart to cotton in the raw-fiber node of the textile value chain. In contrast to China, the Indian government largely lacked these institutional capacities to maintain tight controls over cotton markets. India does maintain minimum support prices (MSP) for cotton and other strategic agricultural commodities, and utilizes strategic reserves through the Cotton Corporation of India (CCI)–to stabilize market prices and defend its MSP, when necessary. However – unlike with other agricultural commodities like rice and wheat – MSP interventions in cotton are rarely acted upon in India. In general, MSP in cotton have been set substantially below actual market
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prices, and the CCI has rarely had to defend them (Saksena 2002, p. 241). That said, when MSP are raised, they can have some marginal impact on market activity, particularly for lower-quality cottons. While the MSP and the Cotton Corporation of India’s strategic reserves are crucial pillars for maintaining a minimum protective floor on cotton prices, a range of other policies and institutions generally work to suppress cotton prices in India. Overall, policy levers have been directed towards influencing the behavior of private commodity merchants in India – precisely the commercial functions which China’s government-run Supply and Marketing Cooperatives’ (SMC) fulfilled – such as local procurement and a national delivery system.33 Over the period of time addressed here, many of these policies traditionally aimed to limit private merchants’ capacity to manipulate prices by speculating on, storing and transporting large quantities of commodities. For instance, India placed restrictions on commercial credit supplied to traders in order to limit the quantity of working capital they can muster at any one time – as a way to prevent hoarding and market manipulation. A long-standing ban on futures trading in cotton has placed similar restrictions on private traders. Finally, India’s Control and Transport Order permits the Union government to intervene in the interprovincial flow of critical commodities. In terms of external trade, Indian cotton exports are handled by a relatively limited number of market agents and federations – most importantly the CCI and the Maharashtra federation.34 Cotton has long remained on the Negative List of Exports – which entails the imposition of export quotas, contract registration and minimum export prices (Saksena 2002, p. 238). Over the past decade, India has somewhat liberalized its cotton markets as many of these policy tools have been loosened or eliminated. Unfortunately, its system of agricultural-extensions services has also been progressively disassembled – leaving agricultural cultivators increasingly reliant on private merchants for information, advice and technical assistance.35
7.5 Threat or opportunity? the man-made fiber industry and state support Although cotton is a crucial raw material in textiles, it is impossible to fully appreciate the role of the upstream fiber industry without considering the man-made fiber industry – an industrial product which is simultaneously competitive and complementary to cotton agriculture.36 While there is wide variation between countries, from a global perspective, man-made fibers compose about half of the total raw fiber consumption in apparels and quite a bit more in home furnishings and industrial usages. Despite similar population pressures and threats of grain shortages, the two governments have taken opposite approaches to the man-made fiber
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industry. China and India have approximately the same absolute quantity of arable and permanent cropland. While China has about three times India’s land mass, India is one of the most arable countries in the world – with over half of its land considered arable and permanent cropland, compared to China’s 15%. Thus, they end up having quite similar quantities of total arable and permanent cropland – with India slightly above 1.5 million square kilometers, and China slightly below, though China must feed approximately 30% more people from this.37 In addition – given the long-enduring struggles of these two nations in maintaining self-sufficiency and security in food production and clothing – the man-made fiber industry offers a potential alternative in which cotton acreage can be replaced by synthetic-fiber factories – thus reserving more acreage for food production. For instance, a 300-acre synthetic-fiber factory is capable of replacing about 600,000 acres of cotton fields (Kadolph and Langford 1998, p. 69). By this means, they would be more capable of maintaining self-sufficiency in food production and clothing – enduring nationalist goals for both countries. While some man-made fibers use nonchemical feedstocks – such as wood pulp – most are derivatives of fossil-fuel by-products, composed of synthetic chemical polymers. Although derived from fossil fuels, they are by no means intensive consumers of fuels – so fuel supplies and costs are generally not reason enough for governments to inhibit their development.38 Despite these similar structural factors and nationalist goals, however, China and India could hardly have taken a more different approach to the man-made fiber industry. In contrast to the Chinese government – which has used it extensive controls to develop man-made fibers as a solution to their severe arable land constraints – until quite recently, the Indian government has consistently perceived the man-made fiber industry as a “threat” to agricultural cultivators, and has successfully circumscribed its development. While it may be easy to draw the conclusion that India took the “wrong” approach to the synthetic-fiber industry and China made the “right” decision, a more nuanced comparison highlights the fact that the transition to man-made fiber usage is more complex. Similarly to cotton agriculture, China was institutionally far more equipped to make the transition to building a synthetic-fiber industry. China’s version of state socialism gave it institutional controls over transforming the upstream fiber sector, while at the same time shielding cotton farmers from the impact of this new and competing source of textile fibers. By contrast, the Indian government had far fewer policy levers at it’s disposal to aid the successful rise of a syntheticfiber industry – while also protecting the interests of cotton farmers. Seen in this light, the Indian policy-makers’ perceptions of the synthetic industry as a “threat” to agriculture appear to be quite understandable – once we consider the policy levers available to policy-makers in guiding this
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Figure 7.4 Cotton profits (RMB/Mu) and synthetic fiber consumption as percentage of total cloth, China 1970–1991 Sources: Fiber Consumption: ZFGN (various issues); Cotton Profits: ZFGW (2003).
transformation. By examining state capacities, overly simplistic and arbitrary arguments concerning the political choices among politicians and bureaucrats can be avoided. In China, the man-made fiber industry was established extremely rapidly and very early in the reform era – though its initial planning and investments pre-dated the reform era by many years. In a few short years – between 1978 and 1983 – China’s domestic consumption patterns swung from one quite similar to India’s – based overwhelmingly on cotton fibers – to a mixed combination of pure cotton, blend, and pure synthetic fibers, similar to consumption patterns found in many advanced industrialized countries (Figure 7.4). Crucially, at the same time that China was building massive petrochemical industrial complexes, cotton farmers’ real profits rose very dramatically – from 12.5 RMB/mu of land to 101.4 RMB/mu; one mu is 1/15th an acre (Figure 7.4).39 How was such a dramatic shift towards man-made fibers affected so rapidly, while at the same time cotton farmer’s livelihoods witnessed dramatic improvements? China’s shift to man-made fiber manufacturing and consumption exhibited none of the “threats” to cotton farmers, which Indian policy-makers feared. Chinese economic policy elites – including then Premier Zhao Ziyang and the once minister of China’s textile ministry, Hao Jianxiu – expressly perceived the development of chemical fibers as crucial in achieving the multiple – often incompatible – goals of food and clothing security. According to Zhao, it was the government’s intention to stop relying on expanding cotton acreage to clothe its growing population, but to seek a shift of farmland from cotton to grain as a critical government goal.40 The chemical-fiber industry was seen positively – as the solution to China’s structural problems.
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As state elites adopted a positive attitude towards the new industry, its initial foundations were built through heavy state involvement – utilizing a range of policy tools largely unavailable to Indian bureaucratic elites. In the late 1970s and early 1980s, China shifted its overall state-industrial investments from a focus on heavy industry to light industry and agriculture (Naughton 1995; Solinger 1991). Man-made fiber factories were uniquely positioned between heavy and light industries and thus became a favored industry. Chemical fibers was one industry which bridged the light and heavy industry divide, and thus benefitted both light- and heavy-industry ministries with infusions of state capital. Starting between 1973 and 1975, six major state-financed petrochemical fiber plants – mostly polyester – were planned and financed by Beijing using limited foreign-exchange earnings. Their construction was engineered by major textile firms from Japan, France and Germany – using imported technology. While the first ones to come on line in Shanghai, Beijing, Tianjin and Liaoning were fairly small – having annual capacities of between 25,000 to 87,000 metric tons – two additional, massive plants were built in Shanghai and Jiangsu, which ranked among the largest complexes in the world at the time – with capacities of 200,000 MT and 533,000 MT, respectively.41 The quantity of investment devoted to chemical fibers was staggering. In the 1980 state plan for textiles, 21 of 34 new mills approved under the Ministry of Textile Industry (MTI) plans were devoted to increasing China’s production capacity – in a wide range of synthetic fibers – and these projects absorbed no less than 80% of the entire fiscal allocation for the textile industry.42 In addition to the above factories, these included smaller plants located in both inland and coastal regions and in more minor urban centers. While MTI and other ministries were building up production capacity, the Ministry of Commerce and China’s State Price Bureau were busy at the opposite end of the production chain, ensuring that the output from these factories would ultimately be absorbed by Chinese consumers. In November 1981, these ministries cut state retail prices for polyester – cotton and polyester – viscose fabrics by an average of 0.66 RMB/meter – the equivalent of an 8.25% to 22% price decline, depending on fabric type.43 As the larger plants’ synthetic-fiber production came on line, they instituted a second, more dramatic price reduction in January 1983 on blended and pure synthetic fabrics – ranging from 20 to 30%. At the same time, they doubled the attractiveness of synthetic fabrics to Chinese consumers by also increasing the price of pure cotton fabrics by 20% on average.44 The resulting shift in consumption patterns was rapid, as pure synthetic and blended cloth rose from 20% of total purchases in 1978 to nearly 80% in 1983! Once the State Council realized it had overshot its initial targets, it readjusted the cotton – synthetic balance once again to support cotton (Figure 7.4). At the same time that these different channels of investments and subsidies were rapidly changing consumer purchase habits away from cotton
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and towards synthetics, farmers were enjoying rising real incomes on the sale of cotton. As mentioned earlier, cotton farmers were earning record profits because the state automatically purchased as much as they produced and – through the above-quota bonus pricing system – farmers earned higher prices the more they produced. Ultimately, the state treasury financed these cotton imbalances as well as subsidies to the urban consumers via retail price modifications. China’s “smooth” transformation was accomplished through state engineering – utilizing the institutions and policy levers developed under the statist institutions of socialism, including state price-setting and the state-run commercial system. This coordinated and rapid transformation in China’s raw-material base was enacted by means of large infusions of state capital, which flowed through its industrial and commercial ministries in the form of support to state textile firms, farmers and consumers. Of course, with the many reforms of state institutions and the disbanding of most industrial ministries, it is unlikely that the Chinese state today would be able to engineer such a transformation. A comparison with India is instructive. In contrast to China, India has had to work with far fewer of these institutional and policy options – particularly with regards to controls on commercial transactions and prices. Given the much more delimited breathing space to simultaneously foster a synthetic-fiber industry, ensure a ready market for it, and protect the interests of cotton farmers, it is perhaps little wonder that Indian politicians and bureaucrats perceive the man-made fiber industry as a “threat” to agriculture, and have often worked to restrict its growth and development. Given this perception of threat, not only was public funding not forthcoming, but the state often hindered private capital investment in the industry. These restrictions were accomplished through many of the Indian government’s commonly-used policy levers. High excise duties were imposed on domestic production across the value chain – including raw synthetic fibers, yarns and fabrics. In stark contrast to China’s massive plants, licensing of man-made fiber factories – as with most industries in India – was limited to relatively small plants, which were uneconomical in a capital-intensive industry such as chemical fibers, in which minimum scale is critical. Furthermore, imports remained limited through quantitative quota restrictions and mills were restricted from sourcing viscose yarn, in order to ensure India’s relatively small available supplies flowed to handlooms. Of course, the promise of man-made fibers in alleviating India’s food security and clothing problems was hardly lost on policy-makers. In the late 1970s – when cotton was in shortage – there were tentative movements to adopt a multifiber policy approach and viscose fibers were recategorized as an Open General License item, after which quantitative import restrictions were lifted. However – as imports rose and threatened both the domestic viscose industry and cotton farmers alike – customs duties were
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quickly increased and the effective rate reached 40% by 1983.45 Subsequent textile reforms – including the 1985 Textile Policy and the 1992 Textile Development and Regulation Order – have unwound some of these restrictions by eliminating licensing, allowing fuller interfiber flexibility in factories and eliminating size constraints on new and established plants. While useful in undoing restrictions, they are hardly “positive incentives” aimed to encourage private capital – to say nothing of the sort of transition that Chinese policy-makers were able to engineer. Perhaps the closest India has come to providing incentives in India’s domestic market has been the relatively recent reduction in excise duties. When added together across the raw fiber, yarn and fabric links of the value chain, they totaled more than 70% in the mid-1990s. Between 1998 and 2004, these were reduced to around 50%–still quite a bit higher than the 20% for pure cotton products (Landes et al. 2005, p. 10). Of course, for firms with an export orientation, a much larger range of policies and incentives applied. By the mid- to late-1990s, these policy changes were beginning to realign India’s domestic industry. Larger firms with economies of scale were established as textile interests took heart from lowered excise duties by entering the market. This has reduced the costs of production and hence the prices of Indian output in comparison to equivalent imports. These same policy changes also apply to the various chemical feedstocks which serve as the main petrochemical raw materials for chemical fibers production. Thus, as an entire industrial chain, inflated domestic prices of both petrochemical feedstocks and synthetic-fiber production have substantially declined – compared to their equivalent global prices.46 While clearly signaling a change in orientation, the industry remains relatively delimited in India – particularly compared to China. Even after a decade of rapid development in synthetic-fiber manufacturing, the gap with China increased substantially after the ending of the MFA. While in the mid-1990s, China’s synthetic capacity was several times more extensive than India’s, by 2008 it was over ten times larger, and Chinese firms were maintaining only slightly lower rates of utilization than Indian firms.47 While these differences in the raw-material node remain true today, there have been some areas of limited policy convergence. As mentioned – since the late-1990s – China has been increasingly liberalizing cotton commerce at both the national level and at the procurement level – where it directly engages with farmers. In 1997, it established a commodity exchange for cotton, allowing a limited but wider range of state and non-state commercial and production units to participate. Between 1999 and 2001, it began to allow textile firms – largely medium and large state-owned firms – to purchase directly from cotton growers and farmer’s associations – as well as from local state SMC procurement stations. Similar to commodity regulation in other countries, the central government has bolstered its strategic reserves and uses more indirect means through market inter ventions
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to influence prices. To meet the requirements of WTO accession, China has also been obligated to partially open its tight trade regime through the establishment of tariff rate quotas – which started at 740,000 MT and rose to 890,000 by 2006.48 More importantly – considering China’s rapid growth in cotton imports – China was required to reduce its non-quota tariffs from 76% in 2002 to 40% in 2006. While China has twice before attempted to liberalize its cotton sector, this third attempt seems to be more permanent. Although there is some policy convergence in cotton, the ending of the MFA has created a new divergence in their cotton economies. Traditionally, both countries maintained largely closed, domestically-oriented cotton agriculture economies and entered global markets to export or import simply to balance periodic shortfalls or surpluses. However – since the early 2000s – China has become a consistent and massive importer of cotton and India has become a major exporter. For instance, since 2003 China has been importing over 1.5 million metric tons of cotton per year – over 4 million in 2005!–while its previous record import load never exceeded 850,000 metric tons –between 1994 and 1996. By contrast – between 2005 and 2008 – India began exporting on average a million metric tons per year – far above previous years.49 It is clear that the transformations occurring through the phasing-out of the MFA have worked their way back along the chain into agriculture, transforming what used to be quite similar protective agricultural strategies into divergent strategies of global integration.
7.6 Conclusion This paper is limited to a comparison of divergent policy paths in the raw-fiber sector of these two textile giants. A more thorough study of the electoral- and party-politics behind India’s policy-making would likely reveal that Indian government elites have also been influenced by the potential of political reprisals from agricultural and textile interests. Similarly, a closer investigation of the intricacies of China’s interministerial bureaucratic politics – especially during the first half of the reform era, when most industrial line ministries still existed – would offer a more nuanced political understanding of the origins of state policy. However, the argument presented here highlights the fact that more overtly political factors must be tied to the historical – institutional capacities available to their respective government and ministerial elites. The presence or absence of certain policy levers and institutional capacities shapes the contours of the political game – whether democratic or authoritarian – as well as the perceptions of those who wield these tools. China’s capacity to shape agricultural procurement and commerce and influence retail prices in the early reform era were particularly critical in creating a synthetic-fiber industry – and at the same time protecting cotton farmers. Indian bureaucrats simply were not bequeathed these sorts of controls from the era prior to economic reforms. In turn,
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their more delimited capacity to shape the Indian economy has influenced their perceptions and approach to synthetic fibers vis-à-vis India’s cotton economy. Furthermore – although many of the changes narrated in this paper occurred over a period of two decades – there is strong path dependence from earlier periods. For instance, it is hard to deny that China’s very rapid and early transformation into man-made fiber production strategically positioned it many years later – as it grew into a garment-exporting powerhouse. China’s first-mover advantage – among the most recent generation of late developers – has likely made it more difficult for India and other countries to reach the frontiers of export competitiveness across different product categories. This is especially the case in chemical fibers – an industry that China has developed very aggressively and continues to do so with the ending of the global system of textile and garment quotas.
Notes 1. In 2005, India was ranked 98th in per capita area of arable land and permanent cropland, while China was ranked 125th. World Resources Institute: Earth Trends Environmental Information Database online. 2. For a year-by-year tally of cotton cloth and pure cotton cloth production figures in China, see the following sources: Zhongguo Fangzhi Gongye Nianjian (various years), Zhongguo Fangzhi Gongye Fazhan Baogao (various years), Huihuang de Ershi Shiji Xin Zhongguo Dajilu: Fangzhi Juan 1949–1999, and CEIC Global Database. 3. India’s figures are calculated from Soundarapandian 2004, pp. 63, 85. For China’s figures, see references in Note 2. 4. The edited volume by Friedman and Gilley (2005) similarly resists these commonplace analyses. 5. It might be argued that the earliest signs of change can be dated to as early as the mid-1970s. In 1976, the Indian government tentatively adopted a “multifiber” policy to overcome cotton shortages and recategorized viscose-filament yarn imports under the Open General License (OGL)–by which quantitative restrictions were withdrawn. With the rising imports, however, the government returned to a more restrictive stance over the next couple of years – raising customs duties to 40% by 1983. See Uchikawa 1998, p. 66–67. 6. These ideas are developed in Gereffi 1999 and Gereffi and Memedovic 2003. 7. Interviews Dezhou City, China and Shanghai, China. 8. Interview Coimbatore, India. 9. In Italy in 2008, labor represented 35% of the total manufacturing costs and power represented 26% for cotton yarn. Ibid.: 68. The United States had the lowest costs for cotton even compared to developing countries – likely due to substantial government subsidies. 10. Although one might think that Egypt’s costs are higher due to the extra-long staple which is grown there, this is not the case since the surveys utilized the same staple lengths of cotton to avoid introducing incongruence across the surveyed countries. 11. For the following data, see Anson and Brocklehurst 2009.
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12. Since the cost of cotton is particularly sensitive to uncontrollable factors such as climate, the purpose of taking averages over multiple years is to remove some of this stochastic variance. Since China has been surveyed only in three years – 2003, 2006 and 2008 – I compare these same three years with India. 13. Anson and Brocklehurst 2009. 14. In comparing cost of production data, it is important to match products as similar as possible. China’s cost data in Figure 7.2 are from 1998 and consist of 30 count cotton yarn, while the data for the other countries are for ring-spun cotton yarn from 1997. While the yarn count for the later figures is not known, in the case of India, about 90% of its yarn production in the late-1990s consisted of less than 40 count yarns – so the comparison is quite fair. See data from Soundarapandian 2004, p. 84. That said, in 1998 when these data were gathered, Chinese firms were enjoying heavy reductions on bank-loan interest rates – so their capital costs are perhaps artificially low. India adopted a similar scheme, but only in 1999. See discussion below. 15. Mukerji (2008) sees India as just the opposite, “fiscally weak and financially strong” in the sense of chronic budget shortages which inhibit – among other things – infrastructure development, while the banking system is quite competitive and extensive. 16. Interviews Dezhou City and Gaomi City, China. 17. By contrast, this is an important competitive difference between advanced industrialized country yarn producers – like the USA, Italy and Korea – and these developing countries. 18. Interview Tirupur, India. 19. Interview in Binzhou City, China. 20. Interview Dezhou City, China. 21. See Naughton 1995. 22. This has been true since the Nehru years as Vivek Chibber’s excellent archival research has shown. See Chibber 2003. 23. Even in the 2008–2009 growing year – after years of improving yields in India – this statement remains true. In that year, India grew cotton on 2,041,000 hectares and achieved a yield of 2,400 kg/hectare. China grew cotton on only 1,295,000 hectares and achieved a yield of 6,019 kg/hectare. Calculated from USDA Cotton: World Markets and Trade, September 2009. 24. Of course, in actual quantitative terms, both countries can be quite large importers of cotton when domestic supplies fell short in supplying the massive needs of their spindle capacity. 25. Specifically, the Cotlook A Index is the average of the cheapest 5 out of 19 quotations from a selection of the main upland cottons traded internationally. They are in Memphis/East, California/Arizona, Orleans/Texas, Tanzania, Turkey, India, Uzbekistan, Paraguay, Pakistan, Côte d’Ivoire, Burkina Faso, Benin, Mali, Greece, Australia, Mexico, Syria, Brazil, China. See USDA Cotton: World Markets and Trade, September 2007, Table 8. 26. To be specific, these are Grade 329 in China and H-4 cotton in India. 27. The cotton – grain price ratio has been commonly used by the Chinese government in balancing these two critical groups of crops. The grain price is an index of prices of the main grain varieties in China. 28. Zhongguo Wujia Wenjian Xuanbian 1979–1983, p. 211. 29. Textile Asia, March, 1985, p. 105. 30. Textile Asia, August, 1985, p. 166.
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Agro-Industrial Transformation: Textile 177 31. See Bjorn Alpermann 2010. 32. Interview in Shanghai, China. 33. These SMCs were still government-run during the period covered here, though there have been important reforms of these government entities too. 34. See Saksena 239 for the quantities of cotton exported by various federations. 35. Interview Coimbatore, India. 36. While it is often noted in the United States that chemical fibers have undermined cotton agriculture over most of the 20th century – through blended fabrics – chemical fibers have also expanded the usage of cotton in textiles. 37. To be more precise, India has 1.65 million square kilometers of arable land and permanent cropland, while China has 1.35 million. Calculated from Central Intelligence Agency, World Factbooks and World Resources Institute data. 38. For instance, the United States traditionally has been the world’s largest chemical-fiber producer – nearly two-thirds of its total fiber production is some form of synthetic fiber – but the industry consumes less than 1% of total annual petroleum (Kadolph and Langford 1998, p. 95). 39. See data for these years in Zhongguo Fazhan Gaige Wei Jiage Si 2003. 40. Textile Asia, March, 1983, pp. 94–5, and Zhongguo Fangzhi Gongye Nianjian 1983, p. 181. 41. Textile Asia, January, 1982, pp. 54–55. 42. Textile Asia, March, 1980, pp. 91–92. 43. See Zhongguo Fangzhi Gongye Nianjian 1984–1985, p. 152. Calculated from Textile Asia, January, 1982, p. 56. 44. Textile Asia, March, 1983, pp. 93–94. 45. Uchikawa 2002, pp. 66–67. 46. For instance see Saksena 2002, 130, 133 to compare the prices of Indian and global polyester as well as DMT PTA and MEG – three major chemical feedstocks which are the primary manufacturing inputs to various synthetic fibers. 47. For India: Datanet India. For China: Zhongguo Fangzhi Gongye Nianjian (various years), Zhongguo Fangzhi Gongye Fazhan Baogao (various years), CEIC Global Database. 48. Interview Shanghai, China. 49. See United Nations Commodity Trade Statistics Database.
References Alpermann, Bjorn, 2010, China’s Cotton Industry: Economic Transformation and State Capacity, New York: Routledge. Aggarwal, Vinod, 1985, Liberal Protectionism: The International Politics of Organized Textile Trade, Berkeley, CA: University of California Press. Anderson, Kym, 1992, New Silk Roads: East Asia and World Textile Markets, Cambridge, UK: Cambridge University Press. Anson, Robin and Guillaume Brocklehurst, 2009, “International Comparison of Production Costs: Spinning, Texturing, Weaving and Knitting”, Textile Outlook International, 139, pp. 66–92. Blecher, Marc and Shaoguang Wang, 1994, “The Political Economy of Cropping in Maoist and Dengist China: Hebei Province and Shulu County, 1949–90”, The China Quarterly, 137, March, pp. 63–98. Central Intelligence Agency, The World Factbook, Washington, Central Intelligence Agency, Supt. of Docs., U.S. G.P.O.
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Chibber, Vivek, 2003, Locked in Place: State-Building and Late Industrialization in India, Princeton, NJ: Princeton University Press. Cotton Corporation of India Ltd., Online statistical data. Farnie, Douglas A. and David J. Jeremy, 2004, The Fibre that Changed the World: The Cotton Industry in International Perspective, 1600–1990s, New York: Oxford University Press. FEB-Fiber Economics Bureau, various issues, Fiber Organon, Roseland, NJ: Fiber Economics Bureau. Friedman, Edward and Bruce Gilley, 2005, Asia’s Giants: Comparing China and India, New York: Palgrave MacMillan. Gereffi, Gary, 1999, “International Trade and Industrial Upgrading in the Apparel Commodity Chain”, Journal of International Economics, 48 (1), pp. 37–70. Gereffi, Gary and Olga Memedovic, 2003, “The Global Apparel Value Chain: What Prospects for Upgrading by Developing Countries?” Vienna: United Nations Industrial Development Organization. GTIOne Online Database, Shenzhen ju ling xin xi ji shu you xian gong si. GXZ-Guojia Xinxi Zhongxin Zhongguo Jingji Xinxiwang, 2003, CEI Zhongguo Hangye Fazhan Baogao: Fangzhiye [CEI China Industrial Development Report: Textiles], Beijing: Zhongguo Jingji Chubanshe (Chinese). Hsueh, Lin-min, Chen-kuo Hsu and Dwight H. Perkins, 2001, Industrialization and the State: The Changing Role of the Taiwan Government in the Economy, 1945–1998, Cambridge, MA: Harvard Institute for International Development. Inoue, Ryuichiro, Hirohisa Kohama and Shujiro Urata, eds., 1993, Industrial Policy in East Asia, Tokyo: Japan External Trade Organization. ITM-International Textile Manufacturers Federation, 1998, International Production Cost Comparison: Spinning, Texturing, Weaving, Knitting, Zurich: ITMF. ISI Emerging Markets, CEIC Global Database. Kadolph, Sara J., and Anna L. Langford, 1998, Textiles, 8th Edition, Upper Saddle River, NJ: Prentice Hall. Kelliher, D., 1992, Peasant Power In China: The Era Of Rural Reform, 1979–1989, Yale University Press. Landes, Maurice, Stephen MacDonald, Santosh K. Singh and Thomas Vollrath, 2005, “Growth Prospects for India’s Cotton and Textile Industries”, Economic Research Services, United States Department of Agriculture. Lockwood, William W., 1965, The State and Economic Enterprise in Japan: Essays in the Political Economy of Growth, Princeton, NJ: Princeton University Press. McNamara, Dennis L., 1995, Textiles and Industrial Transition in Japan, Ithaca, NY: Cornell University Press. McNamara, Dennis L., 2002, Market and Society in Korea: Interest, Institution and the Textile Industry, New York: Routledge. Mukherji, Joydeep, 2008, “The Causes of Differential Development: Beyond Regime Dichotomies”, in Edward Friedman and Bruce Gilley, eds., Asia’s Giants: Comparing China and India, New York: Palgrave Macmillan. Naughton, B., 1995, Growing Out of the Plan: Chinese Economic Reform, 1978–1993, Cambridge: Cambridge University Press. People’s Bank of China, The People’s Bank of China Quarterly Statistical Bulletin. Saksena, K. D, 2002, Dynamics of India’s Textile Economy: Towards a Pragmatic Textile Policy, Delhi: Shipra. Smitka, Michael, 1998, The Textile Industry and the Rise of the Japanese Economy, New York: Garland.
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Agro-Industrial Transformation: Textile 179 Solinger, D. 1991, From Lathes to Looms: China’s Industrial Policy in Comparative Perspective, 1979–1982, Stanford, CA: Stanford University Press. Soundarapandian, M., 2004, Textile Industry Under Globalization, New Delhi: Dominant Publishers and Distributors. Uchikawa, Shuji, 1998, Indian Textile Industry: State Policy, Liberalization and Growth, New Delhi: Manohar Publishers and Distributors. United Nations, Commodity Trade Statistics Database, New York: United Nations Statistics Division. United Nations, 2006, Industrial Commodity Production Statistics Dataset, 1950–2003, New York: United Nations Statistics Division. United States Department of Agriculture, various issues, Cotton: World Markets and Trade, Washington: USDA Foreign Agricultural Service Circular Series. Wademan, Andrew, 2003, From Mao to Market: Rent Seeking, Local Protectionism, and Marketization in China, New York: Cambridge University Press. World Resources Institute, Earth Trends Environmental Information Online Database. Wujia Wenjian Xuanbian 1979–83, 1986, Guojia wujiaju wujia yanjiu, Beijing: Zhongguo cai zheng jing ji chu ban she. Wu Wenying, 1999, Huihuang de Ershi Shiji Xin Zhongguo Dajilu: Fangzhi Juan 1949– 1999 [New China’s Glorious 20th Century Chronicle: The Textile Volume 1949–1999], Beijing: Hongqi Chubanshe. ZFGN-“Zhongguo Fangzhi Gongye Nianjian” Bianji Weiyuanhui, various years, Zhongguo Fangzhi Gongye Nianjian, Beijing: Zhongguo Fangzhi Chubanshe. Zhongguo Fangzhi Gongye Xiehui, various years, Zhongguo Fangzhi Gongye Fazhan Baogao [China Textile Industry Development Report], Beijing: Zhongguo Fangzhi Chubanshe. ZFGW-Zhongguo Fazhan Gaige Weiyuanhui Jiage Si, 2003, Jianguo Yilai Quanguo Zhuyao Nongchanpin Chengben Shouyi Ziliao Huibian: 1953–1997 [Compilation of Cost and Income Data for China’s Primary Agricultural Commodities since the Founding of the PRC: 1953–1997], Beijing: Zhongguo Wujia Chubanshe.
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8 Local Finance and Governments in the Economic Development of China and India: Distribution and Economic Efficiency Kai Kajitani
8.1 The productivity of factories and two kinds of misallocation Many recent studies show that enterprises in both China and India have more problems with “misallocation” than US companies do, and this leads to low productivity. Hsieh and Klenow (2007) took enterprises’ micro-data from India (Annual Survey of Industries (ASI) 1987; 1991; 1994) and China (Annual Surveys of Industrial Production 1998; 2001; 2005) and compared it to data from the US (Census of Manufacture 1977; 1982; 1997) to analyze the degree to which misallocation of resources caused low productivity in such plants. According to their study, if plants in India and China were fully liberalized and if TFPR1 across plants in the same industry was equalized, the aggregate manufacturing TFP would improve by 86%, to reach 115% in China, 100% to 128% in India, and around 30% to 43% in the US. If plants’ efficiency had been increased to the level of US plants, Chinese plants’ TFP would have improved 50% in 1998 and 30% in 2005. This improvement in TFP might be brought about by reducing the resource misallocation. However in India, if plants have been run with the same efficiency as US plants, their TFP would have improved 40% in 1987 and 59% in 1994, which shows that there is no evidence for improvement in resource allocation during 1987 to 1994. Looking at Chinese state-owned enterprises (SOEs), the TFPR levels are much lower than those of other companies, but the share of SOEs is decreasing. So in industry overall, China’s TFPR has been improving. In India, based on the Industries (Development and Regulation) Act – which was established in 1951 – the Indian government prohibited private companies from setting up, expanding, and producing new commodities without an 180
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industrial license. This system of industrial licensing was called the “licensequota-permit-raj,” and it was criticized as a very rigid system that spoiled economic efficiency.2 Unlicensed companies faced less disparity in TFPR. This suggests that the industrial license system might distort the efficiency of resource allocation.3 In India, a more serious problem seems to be that state governments tend to intervene in the market and distort the resource allocation with their protectionist policies by, for example, regulating the labor market in the pro-worker direction or protecting some industries with an industrial licensing system. For example, Besley and Burgess (2004) show that states which amended the Industrial Disputes Act in a pro-worker direction during 1958 to 1992 experienced lower output, employment, investment and productivity in registered or formal manufacturing. In contrast, output in unregistered or informal manufacturing increased. This means that pro-worker regulation by state governments not only increased the income of workers, but also pushed them into informal work, and ultimately lowered their income. In China, by contrast, local governments could not accept such a proworker policy. However, in the reform era – especially during the 1980s – it is broadly believed that local governments adopted various protectionist policies, such as preventing transport of industrial materials – corks, cotton or silk, etc. – out of the region or objecting to the transport of manufactured goods into the region. This kind of policy, which is called “local-protectionism,” caused serious market segmentation and distortion of resource allocation. Such policies may have faded during the 1990s; however, some studies show that such local-protectionism not only still exists today, but that the trade barriers between regions are also becoming higher. For example, Young (2000) provided evidence – by examining barriers to interprovincial trade in China – that market distortions due to intervention by local governments were becoming more serious in the 1990s than in the 1980s’ reformed economy. Young cites four types of quantitative evidence on cross-provincial (i) output structure convergence, (ii) price – especially of grain – divergence, (iii) time trend of the variances of relative output, labor productivity and labor allocations and (iv) the relationship of grain yield and agricultural labor as a measure of comparative advantage. Then, Young concluded that the local governments that started requiring economic profit after fiscal decentralization – and tend to be leading creditors for local investment in secondary industry – are acting in a manner contrary to the principle of comparative advantage. According to Young, such rent-seeking activity of local governments – and disturbing of market integration – is a “razor’s edge” of market-oriented reform in China.4 Poncet (2003) also attempted to investigate whether the market in China had been gradually integrated across regions after reform, using the data of the Input-Output Table across regions in 1987, 1992, 1997. She found that
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the barrier between domestic and foreign markets had been gradually disappearing; however, the barrier across the provinces had been strengthened after reform. This result seems to imply that the domestic market in China may have segmented. There is an apparent “puzzle” presented by the fact that, in the 1990s – when the economy should have been more market oriented than in the 1980s – the finance flow across regions shrank. Although it is difficult to find the correct answer to this “puzzle,” the financial reforms in 1990 – which were promoted by the then Prime Minister Zhu Rongji to restrain inflation and strengthen the management power of the central government over macroeconomics – may be one of the important pieces of this puzzle. Through these reforms, political credit assignment by the central bank was restrained, and the finance inflow to areas lagging in economic performance shrank (see Section 8.3). In the following sections, we will analyze the efficiency of the fiscal and financial systems in China and India from the perspective of fiscal federalism (Section 8.2), and we will examine how the local governments of both countries intervene in the local economy as actors who require economic interest (Section 8.3), as well as the issue of overinvestment – which is brought about by the activity of local governments in a situation of dynamic inefficiency.
8.2 Trade-off between equity and incentive? – from the perspective of fiscal federalism 8.2.1 Two kinds of federalism To discuss the differences in the economic performances of China and India, a discussion about the “fiscal federalism” may be useful. According to Weingast (2006), there are two kinds of “fiscal federalism” – first-generation fiscal federalism (FGFF) and second-generation fiscal federalism (SGFF). FGFF is a largely normative idea which assumes that public decision makers are so generous as to maximize social welfare and to emphasize the importance of transfers for mitigating vertical and horizontal imbalances. On the other hand, SGFF assumes that public officials have goals induced by political institutions that often systematically diverge from maximizing citizens’ welfare. As to the intergovernmental transfers, FGFF tends to focus on equity considerations, and SGFF tends to emphasize their effect on growth. Weingast also insists that the attempt to correct vertical and horizontal imbalances in developing countries often means that these transfer systems exhibit poor responsiveness to localities that foster local economic growth (Weingast 2006). Some researchers who study local fiscal systems or fiscal federalism emphasize the domination of the Chinese fiscal system over that of India.
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They describe the public finance system of India as an example of a fiscal transfer system without an incentive system – such that it spoils the fiscal discipline of local governments. In India, local governments have their own fiscal revenue – such as inheritance tax on farmland – but most of the important revenue – such as income tax, company tax, and customs duties – is shared with the central government according to a fixed ratio determined by the Finance Commission. The central government has the powers and responsibilities on the assignment of taxation and expenditure among states, and mandates the appointment of a Finance Commission every five years to make recommendations on tax sharing between the central government and states. Local governments also receive many subsidies from the central government, and there are issues around the coordination of transfers recommended by the Finance Commission and the Planning Commission. The Finance Commission’s goals include equity, efficiency, predictability and stability (Singh 2007, p. 5). The Finance Commission’s transfers of revenue to states reflect a series of weights for different criteria. For example – according to Singh and Srinivasan – 62.5% of tax revenue is negatively related to a state’s income – so that poorer states receive more funds – and the remainder is somewhat evenly divided among state areas, using an index of infrastructure, tax effort, and fiscal discipline (Singh and Srinivasan 2006b, Table 7). So generally, state governments have less incentive to increase their revenue efforts – especially on shared taxes – because they do not derive the full benefit of the extra resources raised under this fiscal system, in which soft budget constraints are quite serious. According to Singh (2007), for example, in 2004–2005 the states on average raised about 39% of combined government revenues, but incurred about 66% of expenditures. States financed about 58% of total revenue from their own sources – but in terms of total expenditure – the states covered only about 42% with their own revenue receipts in that year. Purfield (2004) – using panel data from India’s 15 largest states over the period of 1985 to 2000 – estimated the effect of the each state’s transfer dependence on the ratio of the budget deficit/total expenditure in each state. He found that states with greater access to central government transfers tend to have larger deficits, and this negative relationship is amplified the higher a state’s reliance on central government loans. This is evidence that fiscal transfer dependence is accompanied by the problem of moral hazard or soft budget constraints on state government. How about the fiscal system of China? The fiscal system of China in the reform era was managed to prioritize incentives for local governments to provide equality across areas. In particular, the reformed provinces possessed an independent economic base – which enabled them to resist the central government’s initiatives to undermine their fiscal independence by altering the fiscal basis of economic reform. Consequently, the function of
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fiscal redistribution across regions by the central government was weakened through the 1980s. However, these fiscal incentives played a major role in Chinese economic reform and its success. Chinese provinces had considerable fiscal independence during the initial high-growth phase in the 1980s because competition among local governments meant that their budget constraints remained quite severe, and this made the market competitive. Some empirical studies also show that the Chinese fiscal system has an advantage over other developing countries’ systems in the improvement of economic performance. Some of these studies emphasize that the marginal revenue retention of the local governments is one of the important proxies of financial decentralization. Parikh and Weingast (2003) calculated the marginal revenue retention rate for India – and the figure was between 20% and 30% for Indian states. By contrast, states in 19th century United States retained upwards of 100% of increases in revenue (Weingast 2006).5 Provinces in post-reform China retain a high proportion of revenue. Jin et al. (2005) calculated that during the high-growth period following the initial reforms (1981 to 1992), Chinese provinces on average had a marginal retention of 89% of additional tax revenue generated within the province. Furthermore, they showed that 68% of all provinces faced a marginal retention rate of 100%. They argued that the effective marginal retention rates in the new – post-1994 – system are similar to those in the early reform period. From the results of these earlier empirical studies, it appears that the differences in the financial systems of India and China are as follows. The former is a “de jure” federation and the later is a “de facto” federation. From the perspective of economic performance, the “de facto” federation dominated the “de jure” one. But, is this really a fair judgment? Actually – during the Chinese reform era – while the market economy rapidly penetrated throughout the society, the integration of the market – especially the factor market – did not progress adequately. Under such a regionally-segmented financial market, local governments were increasing their revenue by bargaining with the central government concerning revenue or rent-seeking by intervening in the market. 8.2.2 Home-bias and segmentation of financial markets: the Chinese case The problem with regional segmentation of factor markets – such as financial and labor markets among regions and sectors – is a more serious and fundamental one. With perfect capital mobility, savings from any particular region can go to the better regions to maximize returns. In other words, local savings respond to global opportunities for investment – local investment is financed by a national or international pool of capital. This is the fundamental idea of
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Feldstein and Horioka (1980) who proposed using the saving-investment correlation as a measure of capital-market integration. The Feldstein-Horioka (FH) test was initially proposed as a test of world capital-market integration, or a measure of the degree of capital mobility across countries. Boyreau-Debray and Wei (2005) applied the FH test to the financial flow across Chinese provinces. In their study, the coefficient of local saving is positive and statistically significant even when national and regional factors are controlled for. There is an increase in the slope coefficient during the 1990s. Therefore, there is no evidence of an improvement in capital-market integration. Their studies suggest that there are still significant barriers to intranational capital mobility in China. Hence, the pattern for China is closer to that of international capital movements – as opposed to the international capital mobility observed for a country such as Japan – with no internal barriers. In a world with a complete asset market and perfect capital mobility, one region can – by pooling their risks – insure against uncertainty in their incomes. Household consumption should move with aggregate consumption without idiosyncratic fluctuations. Furthermore, changes in consumption across regions should not be perfectly correlated with changes in regional resources (Boyreau-Debray and Wei 2005). According to some empirical studies,6 consumption is more strongly correlated within OECD countries – where we know ex ante that the level of financial integration is high – than between them. One generally finds that intranational risk sharing is much stronger than international risk sharing. In the previous research in the US, EU and Japan, it is clearly shown that the gap in consumption per person among provinces is smaller than the gap in GDP per person, because the temporary shock in GDP could be smoothed in various ways – such as by moving treasury funds between areas or the fluctuation of savings in each area. Boyreau-Debray and Wei (2005) investigate the existence of risk sharing across provinces by means of an OLS analysis. In their study, the changing rate of each province’s per capita consumption is a dependent variable – and “local resource limit” in per capita terms, or LRL – which is defined as GDP – I-G, where I and G are the investment rate – and government consumption per capita, respectively, is also a dependent variable. They conclude that – while evidence of increasing financial integration is clear across the OECD countries – it is much less so across the regions within China. If anything, the degree of intra-China consumption risk sharing might have declined during the last two decades. They also insist that the degree of risk sharing across the Chinese regions is high and has not improved from the 1980s to the 1990s. However, these measures are not conclusive per se. Their studies examine the degree to which capital markets are segmented within the country – due to the
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interference of local governments – and not only did this segmentation not improve since the 1990s, but it may have gotten worse. Kaijitani (2005) also carried out an econometric analysis, which uses economic indices such as GDP per person within provinces to show whether the function of consumption equalization has even been seen in China, what kind of role the fiscal and financial system played in it, and whether there was a change due to the reform – such as the introduction of a tax assignment system. Concretely, we estimate the following panel regressions.7 Δ ln GDPi,t − Δ ln BPI i,t = νD,t +αD,t + βD,t Δ ln GDPi,t + εD,t Δ ln BPIi,t − Δ ln API i,t = νT,t +αT,t + βT Δ ln GDPi,t + εT,t Δ ln APIi,t − Δ ln Ci,t = νS,t +αS,t + βS Δ ln GDPi,t + εS,t Δ ln Ci,t = νU,t + αU,t + βU Δ ln GDPi,t + εU,t Note: BPI is per capita provincial GDP before the fiscal transfer across provinces; API is per capita provincial GDP after the fiscal transfer. C stands for the consumption. νx, t is the time dummy, (x=D, T, S, U), αx, t is the provincial dummy, and εx, t is the error term. In this equation, the coefficients β D, βT, and β S refer to the incremental percentage amount of smoothing achieved at each level, that is, capital depreciation, fiscal transfer, and saving. βU refers to the amount not smoothed. If βU =0, then the real growth rate of consumption in each area does not have a correlation with the real growth rate of income – meaning that there is full risk sharing across regions. Because β D, βT, β S and βU always add up to 1, β D, βT, β S also stand for the contribution of each factor to the total consumption smoothing. From Table 8.1, we notice the result of estimation during the period of 1980 to 1993 – prior to the fiscal and financial reform. The value of βU shows that 48% of the shocks to the gross provincial product are absorbed through saving – which is the most dominant – and 44% of the shocks were not smoothed in total. However – in the period after 1994 – the result changes dramatically. During this period, the estimated value of βT, β S is not significant – meaning that the smoothing through saving and fiscal transfers that was significant in the former period was not effective. In addition, 86% of the shocks were not smoothed in total during this period – most of the income shock was not absorbed, and the risk sharing did not function. The problem of imperfect financial markets across regions is quite important to the discussion of the transfer of finance across the regions and redistribution policy conducted by the central government. The
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Table 8.1 Interregional risk-sharing in China Period
Capital depreciation (βD)
1980–2002
1980–1993
0.028
–0.036*
(0.49) Fiscal transfer (βT)
0.124* (1.88)
Saving (β S)
0.332** (3.13)
Not smoothed (βU) Number of sample
(–2.04) 0.112* (1.98) 0.478** (6.08)
1994–2002 0.140 (1.46) 0.181 (1.58) –0.177 (–0.86)
0.517**
0.441**
(8.89)
(7.64)
(6.99)
0.858**
643
391
252
Notes: The figures in parentheses are ‘t’ values. *(**) denotes significance at the 5 (and 1) % level. Source: Kajitani (2005).
background which causes such an imperfect integration of financial markets is as follows: (i) The institutional conditions for the integration of financial markets, such as the negotiation of drafts in transactions, are inadequate. (ii) The banking sector is quite “localized” – in the sense that the local branches of state-owned banks give priority to enterprises in the same region when making loans. (iii) Most of the small- and medium-size private companies that grew rapidly in the reform era are not adequately supplied with loans by the banking sector – and they mainly rely on reserved profit for investment. (iv) Because the interest rate in China is restrained by the government, the loan rate does not correctly reflect the risk and return on lending. So, the banking sector is unable to avoid lending money using the “localized” criterion. 8.2.3 Integration of financial markets: the case of India How about the regional integration of the financial or credit market in India (Table 8.2)? Singh and Srinivasan (2006a) show that there is a positive correlation between the ratio of per capita NSDP (net state domestic production) and the credit–deposit ratio and that the correlation increased dramatically between 1995 and 2001. They also investigate the growth convergence regression using states’ data, focusing on three different financial variables: FDI approvals per capita, per capita bank credit, and credit-deposit ratios. The result is as follows: any one of the financial variables taken individually is estimated to have a significant impact; however, when two or more financial variables are included, they have a positive and effective relation
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14,250 14,892 15,255
Haryana
Maharashtra Punjab
25.0 6.2
8.7
14.1
21.1
20.0
12.7
15.8
27.0
15.3
37.4
47.2
36.1
31.2
42.6
0.801 0.674
0.739
0.785
0.647
0.742
0.604
0.561
0.424
0.512
0.555
0.342
0.314
0.379
0.354
1996/97–1998/99
Index of fiscal autonomy
0.85 0.41
0.42
0.49
0.91
0.59
0.43
0.63
0.44
0.48
0.47
0.41
n.a.
0.28
0.24
2001/02
Loan/deposit ratio
2.7 2.5
3.1
3.3
4.6
5.6
3.9
4.4
5.4
3.8
2.2
2.6
0.5
1.6
2.4
1993/94–2001/02
Growth rate of NSDP per capita
Source: The NSDP per capita, its growth rate and the ratio of the population under poverty line are from Uchiyama (2006), the index of fiscal autonomy is from Yamamoto (2007), and the loan/deposit ratio is from Singh and Srinivasan (2006a).
Notes: ‘Index of fiscal autonomy’ means the ratio of a state’s own revenue to the state’s expenditure. ‘Poverty rate’ means the ratio of the population under the poverty line.
13,108
11,516
Karnataka 13,684
11,046
Kerala
Gujarat
10,590
Andhra Pradesh
Tamil Nadu
8,819 10,375
West Bengal
7,699
Madhya Pradesh
Rajasthan
6,059 6,105
Assam
5,885
Orissa
3,554
Uttar Pradesh
1999/00
2001/02
Bihar
Poverty Rate
NSDP per capita (INR)
Table 8.2 Economic data of major states in India
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to the growth of SDP. This result means that mobile domestic and foreign capital is driving growth. This result is contrary to the Chinese case – where the loan/deposit ratio has a negative correlation with the economic growth rate, as shown by Park and Sehrt (2001). The results of earlier studies are very simple – so they may not be so robust; however, it is plausible to conclude that financial transfers across regions are not seriously disturbed by the redistribution policy of governments. Besides – compared to other developing countries – in India rather well developed financial and asset markets exist, and – especially after economic liberalization – the transaction amounts and number of institutions involved have improved dramatically. Roughly speaking – although in India an adjustment in regional inequality was made through fiscal transfers rather than the financial market, in China financial transfers also played an important role. Reliance on fiscal transfers by some poor regions spoiled the incentive of these regional economies; however, from the point of view of regional integration of financial markets, India may be more advanced than China. In this sense – like Weingast – to praise China as a typical case of “market preserved federalism” and to rank India as inferior, might be a little misleading. Actually – in providing incentives to local economies – China dominated India, but China has problems such as the segmentation of financial markets and the rent-seeking action of local governments in the factor markets – such as finance and land-use rights. Several recent important political decisions – such as the establishment of a property rights law in 2007 and the promotion of transfer of usage rights for farmland in 2008 – suggest that reduction of the problem of local government’s rent-seeking action in some factor markets is one of the most urgent issues in China’s economy and politics.
8.3 8.3.1
A comparison of local public finance in China and India The expenditure structure of local public finance
In the previous section, we saw that there is “misallocation” of economic resources due to the intervention of government – especially local government – in both China and India. However, the structures which cause this misallocation are quite different in each country. This difference is deeply related to the structure of the revenue of local governments, because fiscal revenue is the most essential factor in incentives for local governments. For example – as we saw in the previous chapter – the Chinese credit market was segmented and the loans extended by the state-owned banks were deeply “localized” (Park and Sehrt 2001; Podpiera 2006). In the background of this phenomenon, there is severe competition over economic growth between local governments. Their main aim in intervening in the factor market is maximization of local fiscal revenue. This means
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that it is very important to compare the central-local relationship regarding public finance. So, now we will concentrate on the structure of local finance – especially productive expenditure. In India, “productive expenditure” refers to social services and economic services. The former include education, health care and public health, water supply, urban development, welfare of scheduled caste or tribes and social security, etc. – and the latter include agriculture and rural development, irrigation and flood control, energy, transport and communications, and science, technology and the environment and so on. The Chinese definition of “productive expenditure” is slightly different from that of India – but not significantly so. Looking at Figures 8.1 and 8.2, we can see that the productive expenditure of local governments is much more than the central government’s – in both China and India. Although the ratio of social service expenditure is quite stable between both countries, the ratio of economic service expenditure – mainly economic construction – has been continuously decreasing since the 1980s – except for recent years in India (Figures 8.3 and 8.4). This phenomenon could be related to the fact that the weight of public finance as a financial resource of fixed asset investment has been decreasing during this period. Although in India the share of the public sector in overall fixed-asset investment is dramatically decreasing, in China the share of the public sector – state-owned and collective-owned – in fixed investment is decreasing but is still at a higher level. However, the ways of financing diversified
80 70 60 50 %
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Figure 8.1 Ratio of development expenditure in India Source: Budget documents of the Government of India and the State governments, from the website of the Reserve Bank of India (http://www.rbi.org.in/home.aspx).
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Economic construction service Local Social service Expenditure for national defense
% Central
Expenditure for government administration Total Other expenditure 0
20
40
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% Figure 8.2 Structure of central and local government expenditure in China, 2006 Source: NBS, China Statistical Yearbook, 2007.
50 45 40 35 30 % 25 20 Economic Service (%) Social Service (%)
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Figure 8.3 Structure of developmental expenditure in states of India Source: Budget documents of the Government of India and the State governments, from the website of the Reserve Bank of India (http://www.rbi.org.in/home.aspx).
after the 1980s, and more and more SOEs have begun to rely on financing from banks or off-budget funds of local government. 8.3.2 Indian local finance and democracy The Indian fiscal system provides a good contrast to the Chinese system – for example, in the relationship between the autonomy of the local fiscal systems and the incentives of local governments – and it seems to be typical that “a trade-off between incentive and fairness” is adopted.
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Kai Kajitani 70 Economic construction 60
Social Service Government Administration
50 40 % 30 20
0
1980 1985 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
10
Figure 8.4 Structure of government expenditure in China Source: NBS (2005), NBS, China Statistical Yearbook, various years.
The Indian fiscal system has been suffering a serious financial deficit – both at the central and the local level. The central fiscal deficit reached 8.4% of GDP, and improvement of this is the main motive of the economic liberalization program started in 1991 (Sato 2002). After the economic liberalization, the fiscal deficit temporarily improved – but, starting in the late 1990s, the fiscal deficit of state governments expanded. It has been pointed out that behind the expansion of the states’ fiscal deficit lies the competition to reduce tax rates in order to attract foreign direct investment and the increases in public servants’ wages. A factor that strongly affects the intervention of local government into the economy is the type of political system. Generally speaking, under the democratic political system, governments tend to adopt a populist and opportunistic policy, preferring a policy for increasing the level of temporary consumption over a policy for the social or infrastructure investment for the future. Fukumi (2008) empirically analyzed how political instability distorts fiscal policy, based on the endogenous growth model – using panel data from the 14 major Indian states. He concluded that political instability in the form of polarization8 in political preference can lead to the expansion of subsidies for farmers – which is effective in obtaining votes, and shrinking of economic development expenditure. This result suggests that India cannot achieve infrastructure development unless it succeeds with such populism. Khemani (2002) studied the political-economic determining factors for fiscal deficits of state governments, based on the models of the commonpool game in federations. He found that in 15 major states of India during
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1972 to 1995, states in fact had substantially higher deficits when the government belonged to the same party as the central government. This result seems to indicate that the fiscal system in a federation has a very important effect on local governments’ incentives. 8.3.3 Rent-seeking of local governments in the reform era in China From the relationship between the market and the government, the pattern of economic development in China in the reform era can be characterized as follows. First, because the market mechanism is not perfect, there is always the chance of rent-seeking by the government through intervention. Second, given their chronic fiscal deficit, local governments attempt to maximize their non-tax revenues. Third, given the lack of an efficient financial system, the interventions by local governments into local financial markets sometimes have a fundamental effect on local economies. However, after 1994 when a series of fiscal and financial reforms were enacted, the types of intervention used by local governments changed from those in the 1980s. Roughly speaking, the main means of rent-seeking in local economies in the 1980s was intervention into local financial markets. A representative example of this pattern of intervention is development of township and village enterprises (TVEs) in the Sunan area. The relationship between interventions by local governments and the development of TVEs is as follows: (a) The enterprises can receive rent through the regulation of deposit and rental interest. (b) The local governments receive a share of rent as a “governance fee (extra budget fund)” from the TVEs. (c) The sharing of rent is linked with the growth of productivity; there is efficient competition among local governments and enterprises. (d) The rent shared by local governments may be invested in the local economy – especially for the construction of infrastructure. Actually, the Chinese industrial sector is receiving rent through loans which are primarily at a lower rate, and it must share part of its profit with local governments as an “admission fee;” the local governments, meanwhile, reserve their share as “extra budget funds” for themselves. For example, in the case of Chinese TVEs, the local governments in the lower layer – townships – may share rent with the enterprises. There are two important points. First, this process of receiving rent is quite competitive – because TVEs and local governments cannot receive any rent until they succeed in the competition against enterprises in other areas. Second, credit assignment by local governments is effective when the financial market is segmented among areas – and most TVEs must rely on loans from the local branch of the Bank of Agriculture or a credit corporation.
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In such circumstances, if the credit assigned to the TVEs by the intervention of the government is used for profitable projects and this profit is reinvested in local development, then the supply curve will shift downward in the local financial market – as the “financial restraint” theory posits. After the mid-1990s, local governments tended to intervene in real estate or land markets as the monopolistic suppliers of land-use rights. In this case, the developers and local governments could obtain monopolistic rent through the intervention into the markets of land-use rights, and agricultural laborers and urban residents bore the rent in the real-estate market. From the real-estate market, the local governments were able to obtain copious extra budget revenue – paying only the sales tax and real-estate tax – and abundant extra budget fees from the developer or real-estate sector. In particular, local governments’ revenue from selling land-use rights in the markets has been rapidly growing in recent years. This revenue is a kind of monopolistic rent that the governments get by disturbing the market. From Figure 8.5, we can see that this revenue began to grow rapidly – starting in 2002, when the land investment boom restarted – and that there is a serious distinction between the coastal area and the inland area – central and western areas – in the level of revenue. Most of this revenue was reserved by the local governments as extra budget revenue. What should we think about this revenue and the character of the Chinese real-estate market? An important point is that such rent-seeking behavior could be sustained by the special structure of the Chinese realestate market. 100 million RMB 9,000 8,000 7,000
East Center West
6,000 5,000 4,000 3,000 2,000 1,000 0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Figure 8.5 Reserved revenue of local governments by selling land-use rights Source: NBLRC various years.
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The Chinese real-estate market can be divided into three layers. The first layer is the market in which the local governments dispose of land-use rights, the second layer is the market in which the developers who obtain the land-use rights sell the real estate – such as condominiums or office buildings – and the third layer is the market consisting of transactions among end users. In the first layer, the local governments have a monopoly on the supply of the land-use rights – so the amount of the supply is lower and the price is more expensive than the market-clearing level. After determination of the supply and price of land-use rights in the first layer, rental and asset prices of real estate are determined in the second and third layers of the market. In the first layer of the market, a serious distinction exists in the price of land – depending on its usage. For example – in the case of industrial factory sites – there is serious competition among regions because of the larger elasticity of demand; the governments dispose of land-use rights at a very low price by conferring.9 By contrast – in the case of commercial or residential areas – elasticity of demand is smaller than in industrial zones, so the supply is sold at a low price by way of auction. Because of the local governments’ monopoly on the supply of land, there is no arbitrage between different uses of land (Figure 8.6). In such a situation – where the supply of land-use rights is limited by local governments – it is very likely that there will be a “bubble” in the real-estate market. In the next section, we investigate the existence of overinvestment in local economies in China and the possibility of a “rational bubble.”
P The market of the usage right for residential area
The market of the usage right for industrial zone P1
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PZ
D MC MR
O
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Figure 8.6 Price distinction in the land market of China Source: Prepared by the author.
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8.4 The problem of overinvestment and dynamic inefficiency From the discussion in the previous section, we can conclude that – compared to the pattern of intervention in the 1980s – rent-seeking through the real-estate market has tended to distort the market and adversely affect economic welfare. First, because the real-estate market is quite different from the credit market, the amount of the factor endowment is fixed – and the supply of land-use rights is basically determined by the local governments. This means that the “competition for development” among the local governments – through intervening in the real-estate market – is a kind of rent-seeking that requires a monopoly on rent. Second, the sharing of rent through the real-estate market does not link to increased productivity in the finance, enterprise or banking sectors – so intervention by the local governments into the real-estate market tends to be quite inefficient. Now we can ask a big question. Why was the Chinese economy able to achieve very high-growth performance after the 1990s – with a GDP growth rate over 10% – despite the fact that there is such inefficient rent-seeking action by the local governments? Attempting to answer this question may be beyond the scope of this paper – but we can suggest the following possibilities. After 2002–2003 – because of the global excess liquidity that invited the real-estate bubble and the catastrophe in the United States, as well as an RMB level that was lower than the market-clearing level – abundant hot money flowed into the Chinese financial market. It is plausible that this flow of hot money may have sustained the high-growth rate and also may have caused the local governments’ rent-seeking action discussed in this section. The answer to this question may be related to the existence of “dynamic inefficiency” in the Chinese economy – especially after the late 1990s. Many previous studies show that – if a competitive and decentralized economy can attain a steady state in which there is unambiguously too much capital, then Pareto improvement between different periods cannot be achieved through a market economy. Such a situation is said to be “dynamically inefficient” (Romer 1996). A Pareto improvement can be achieved by the transfer of resources from the current generation to all future generations while holding the consumption constant. Generally, a balanced growth path is dynamically inefficient if the real rate of capital return is less than the growth rate of the economy. A straightforward measure of the real rate of capital return is the real interest rate (Romer 1996). According to Abel et al. (1989), however, there is a problem with the above criteria in an uncertain world. If there is uncertainty in an economy, different assets can have different expected returns, and the real interest rate does not necessarily stand for the real rate of return. They insist that – given uncertainty – a sufficient condition for dynamic efficiency is that net capital income10 exceeds fixed-asset investment.11 Abel et al. show that – given uncertainty – these two conditions are not equivalent and that it is the comparison
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of capital income and investment – the condition that follows – that provides the correct way of testing dynamic efficiency. gross rate of fixed-asset investment > share of gross capital income on GDP
(1)
This condition (1) means that there is more investment than there is increase in capital return; in other words, there is too much capital and the economy is dynamically inefficient. Abel et al. (1989) tested whether the real economy of OECD countries – US, UK, France, German and Japan – is dynamically efficient, using data from 1960 to 1984. Their studies show that, even in an economy with a much higher investment rate – such as Japan in the 1960s – the share of gross capital income is significantly higher, so there is no evidence that the economy is dynamically efficient. However, there have been no empirical studies which test for the existence of dynamic efficiency in the recent emerging-market countries – such as China and India – using Abel, Mankiw, Summers and Zeckhauser’s criteria. In the following section, we attempt to investigate whether the condition of “dynamic efficiency” really existed in China during the reform era and in India after the 1990s. Figure 8.7 shows the difference of the gross capital profit (=rK) and gross fixed-asset investment as a percentage of the GDP in China, the US, Japan and India. According to this figure, the condition of China in terms of dynamic efficiency is not very different from the other countries until the 1990s; however – after the “southern tour” of Deng Xiaoping in 1992 – foreign direct investment rapidly increased, and China’s dynamic efficiency started to decrease. After 1998 – when the government decided to expend massive public funds on fixed investments in inland areas in order to quickly recover from the shock of the Asian financial crisis – we can see that the Chinese economy was sometimes dynamically inefficient.12 This phenomenon is quite striking compared to other countries. For example, we also tested the Indian case after the 1990s – that is, after the economic liberalization – but we did not find any symptom indicating that the Indian economy was dynamically inefficient.13 Next, we will investigate the condition of dynamic inefficiency using regional Chinese data (Figure 8.8). We can see an obvious contrast between areas. In the coastal area, the economy has been unambiguously dynamically efficient. In the central and western areas, however, the economies tend to be dynamically inefficient – especially in the western area. The western area’s overinvestment became more serious after the end of the 1990s, when the central government started to increase its investment in this area. The low investment return, the high-growth rate driven by exports, and the over-acceptance of the dollar-peg policy could be factors in the extension of the asset bubble, and the asset bubble may also contribute to the maintenance of the high-growth rate.
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Figure 8.7 Dynamic inefficiency in several countries – the difference between gross profit and investment as a percentage of GDP Notes: “China 1” uses old SNA data series, and “China 2” uses new SNA data series (SNA93), based on the 2004 economic census. Sources: Japan: Economic and Social Research Institute, Cabinet Office (http://www.esri.cao.go.jp/). US: National Economic Account, Bureau of Economic Analysis, Department of Commerce (http://www.bea.gov/). China1: DNA-NBS (1996), DNA-NBS (2003). China2: DNA-NBS (2007), NBS, China Statistical Yearbook, various years. India: Ministry of Statistics and Program Implementation, Government of India (http://mospi. gov.in/).
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0.1 0.05 0 −0.05
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Figure 8.8 Dynamic inefficiency in each region, China – the difference of gross profit and investment as a percentage of GDP Sources: DNA-NBS (2007), NBS, China Statistical Yearbook, various years.
As our investigation shows, the economy in most Chinese provinces is dynamically inefficient. This means that the increase in the asset value which was frequently seen after 2003 was a typical “rational bubble.” So, the bubble in the real-estate market which was brought about by the rentseeking activity of local governments might be efficient – in the sense that it improves people’s welfare and sustains the high growth rate. The existence of such a phenomenon may distinguish the Chinese economy after the end of the 1990s from other emerging countries like India.
8.5 Conclusion: China and India – different inefficiencies From our investigation, we can conclude that China and India confront two different kinds of inefficiency, which are brought about by the local government. In China, local governments’ budget constraints are basically severe, but they have many opportunities to secure their own revenue. It is very common for local governments to intervene in factor markets – such as financial or land markets – to obtain rent, and such rent-seeking activity distorts the allocation of resources between regions and sectors. The ratio of productive expenditure to overall expenditure is quite high, but aggressive investment by local governments brought about overinvestment. In India, local finance tends to depend on subsidies from the central government, and the central government also faces political pressure from local voters who require populist distribution. So, the budget constraints of local governments in India tend to be soft. This is the reason why India suffers from a deficit in fiscal expenditure for social infrastructure. In particular, if state governments encounter such political pressure, regional productivity may decrease because of the protectionism policies adopted by the local governments.
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Notes 1. According to Hsieh and Klenow (2007), if there are no distortions of resources, TFPR – “total factor productivity based on revenue” – does not vary across plants within the same industry. This is because, in the absence of distortions, more capital and labor should be allocated to plants with higher TFPQ – “physical TFP” – until their higher output results in a lower price and the exact same TFPR as at smaller plants. 2. In the economic liberalization process during the 1980s, a third of all companies were exempted from the regulation requiring industrial licenses in 1985, and half were exempted in 1991 when the full-scale economic liberalization started. 3. Aghion et al. (2008) showed that the results of their empirical studies could not sustain the hypothesis that the abolition of the industrial license contributed to the growth of the registered industrial sector. 4. Holz (2006) insisted that, while the phenomena Young pointed are observed in China, they are not necessarily evidence that the “protectionism” of local governments caused the regional segmentation of markets, as Young claimed. 5. Zhuravskaya (2000) calculated the marginal revenue retention rate at 10% for Russian cities. 6. For example, Iwamoto and Wincoop (2000), using data of OECD countries and Japan, investigated the international and intranational effects of risk-sharing. Doi (2000) investigated risk-sharing across Japanese counties. 7. This empirical model was basically the same as that used in Asdrubali et al. (1996) and Doi (2000). 8. “Polarization” refers to the situation in which two large parties compete for the seats in the local congress. 9. According to the announcement of the Ministry of National Land and Resources, the average price of land is 2,775 RMB per square meter in commercial areas and 1,983 RMB in residential areas, but 568 RMB in industrial zones. 10. Net capital income is measured as national income plus capital consumption allowance, less (1) employee compensation and (2) an estimate of the labor income of proprietors. 11. For the balanced growth path of an economy with certainty, this condition is the same as the comparison of the real interest rate with the growth rate, as follows: For the balanced growth path of an economy, we get n=dK/K=dY/Y (n: growth rate of population, r: interest rate). When n=dK/K > r, then if we multiply by K/Y on both sides, then (dK/K)(K/Y) > (rK)/Y. So, we get I/Y > (rK)/Y, because dK=I. This means the condition that “n > r” equal “the real investment rate is larger than the share of gross capital income”. 12. In Figure 8.9, we have two kinds of data series on the Chinese economy. “China 1” uses old SNA data sets, and “China 2” uses new SNA data sets (SNA93), based on the 2004 economic census. The most important difference between these two data sets is, in the former, “compensation of employees” includes the income of independent entrepreneurs, but the latter does not. So, the former tends to overestimate the gross capital profit, while the latter tends to underestimate it. 13. However, in Indian data, the gross capital income consists of the operating revenue and mixed income, which includes the income of independent entrepreneur as wage. According to Sato (2010), the share of entrepreneur’s wage on the mixed income could amount to one third, so the share of gross capital income on GDP in India could be considerably overestimated.
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References Abel, Andrew B., N. Gregory Mankiw, Lawrence H. Summers and Richard J. Zeckhauser, 1989, “Assessing Dynamic Efficiency: Theory and Evidence”, Review of Economic Studies, 56, pp. 1–20. Aghion, Philippe, Robin Burgess, Stephen J. Redding, and Fabrizio Zilibotti, 2008, “The Unequal Effects of Liberalization: Evidence from Dismantling the License Raj in India”, American Economic Review, 98, pp. 1397–1412. Asdrubali, P., B. E. Sorensen, and O. Yosha, 1996, “Channels of Interstate Risk Sharing: United States 1963–1990”, Quarterly Journal of Economics, 111, pp. 1081–1110. Besley, Timothy and Robin Burgess, 2004, “Can Labor Regulation Hinder Economic Performance? Evidence from India”, Quarterly Journal of Economics, 119, pp. 91–134. Boyreau-Debray, G. and Shangjin Wei, 2005, “Pitfalls of a State-Dominated Financial System: The Case of China”, NBER Working Paper, No. W 11214. DNA-NBS – Department of National Accounts, National Bureau of Statistics of China, 1996, Data of Gross Domestic Product of China 1952–1995, Beijing: Zhongguo Tongji Zhubanshe (Chinese). DNA-NBS – Department of National Accounts, National Bureau of Statistics of China, 2003, Data on the Gross Domestic Product of China 1996–2002, Beijing: Zhongguo Tongji Zhubanshe (Chinese). DNA-NBS – Department of National Accounts, National Bureau of Statistics of China, 2007, Data on the Gross Domestic Product of China 1952–2004, Beijing: Zhongguo Tongji Zhubanshe (Chinese). Doi, Takeo, 2000, “Risk-Sharing among Regions, Income Distribution and Local Subsidies in Japan”, The Political Economy in Local Public Finance, Tokyo: Toyo Keizai Shinposha (Japanese). Feldstein, Martin and Charles Horioka, 1980, “Domestic Saving and International Capital Flows”, The Economic Journal, 90, pp. 314–329. Fukumi, Atsushi, 2008, “The Effect of Political Instability on Power Subsides: An Analysis of Indian States”, In Hideki Esho and Takahiro Sato, eds., India’s Globalizing Political Economy, Tokyo: The Sasakawa Peace Foundation. Holz, Carsten A., 2006, “No Razor’s Edges: Reexamining Alwyn Young’s Evidence for Increasing Inter-Provincial Trade Barriers in China”, Mimeo. Hsieh, Chang-Tai and Peter J. Klenow, 2007, “Misallocation and Manufacturing TFP in China and India”, NBER Working Paper, No. W13290. Iwamoto, Y. and E. van Wincoop, 2000, “Do Borders Matter?: Evidence from Japanese Regional Net Capital Flows”, International Economic Review, 41, pp. 241–269. Jin, Hehui, Yngyi Qian and Barry R. Weingast, 2005, “Regional Decentralization and Fiscal Incentives: Federalism, Chinese Style”, Journal of Public Economics, 89, pp. 1719–1742. Kaijitani, 2005, “China’s Fiscal and Financial Reform and Consumption Smoothing in the Provinces”, Aziya Kenkyu, 51, pp. 1–17 (Japanese). Khemani, S., 2002, “Federal Politics and Budget Deficits: Evidence from the States of India”, World Bank Policy Research Working Paper, No. 2915. NBLRC – National Bureau of Land Resources of China, Almanac of Chinese Land Resources, Beijing: Zhongguo Dizhi Zhubanshe (Chinese). NBS – National Bureau of Statistics of China, China Statistical Yearbook, Beijing: Zhongguo Tongji Zhubanshe (Chinese). NBS – National Bureau of Statistics of China 2005, China Compendium of Statistics 1949–2004, Beijing: Zhongguo Tongji Zhubanshe (Chinese).
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Parikh, Sunita A. and Barry R. Weingast, 2003, “Partisan Politics and the Structure and Stability of Federalism, Indian Style”, Working Paper, Stanford Center for International Development. Park, Albert and Kaja Sehrt, 2001, “Tests of Financial Intermediation and Banking Reform in China”, Journal of Comparative Economics, 28, pp. 608–644. Podpiera, Richard, 2006, “Progress in China’s Banking Sector Reform: Has Bank Behavior Changed?” IMF Working Paper, WP/06/71. Poncet, Sandra, 2003, “Measuring Chinese Domestic and International Integration”, China Economic Review, 14, pp. 1–21. Purfield, Catriona, 2004, “The Decentralization Dilemma in India”, IMF Working Paper, WP/04/32. Romer, David, 1996, Advanced Macroeconomics, New York: McGraw-Hill/Irwin. Sato, Takahiro, 2002, “The Macro Economics of Economic Liberalization: From the Experience of Emerging India”, in Hideki Esho, ed., Modern South Asia 2: Whither Economic Liberalization?, ed., Tokyo: Tokyo Daigaku Shuppankai (Japanese). Sato, Takahiro, 2010, “The Real-Estate Market and Asset Bubble in India”, mimeo (Japanese). Singh, Nirvikar, 2007, “Fiscal Decentralization in China and India: Competitive, Cooperative or Market Preserving Federalism?” Working Paper, Stanford Center for International Development, No. 315. Singh, Nirvikar and T. N. Srinivasan, 2006a, “Indian Federalism, Globalization and Economic Reform”, in Jessica Wallack and T. N. Srinivasan, eds., Federalism and Economic Reform: International Perspectives, pp. 301–63, Cambridge: Cambridge University Press. Singh, Nirvikar and T. N. Srinivasan, 2006b, “Federalism and Economic Development in India: An Assessment”, Working Paper, Stanford Center for International Development, No. 299. Uchiyama, Shuji, 2006, Indian Economy is Dancing, Tokyo: Ajjia Keizai Kenkyujo (Japanese). Weingast, Barry, 2006, “Second Generation Fiscal Federalism: Implications for Decentralized Democratic Governance and Economic Development”, Mimeo. Yamamoto, Iwao, 2007, Studies of the Reform of Public Finance in India as a Federal State, Fukuoka: Kyushu Daigaku Shuppannkai (Japanese). Young, Alwyn, 2000, “The Razor’s Edge: Distortions and Incremental Reform in the People’s Republic of China”, Quarterly Journal of Economic, 114, pp. 1091–1135. Zhuravskaya, E. V., 2000, “Incentives to Provide Local Public Spending, and Economic Growth in China”, Journal of Public Economics, 76 (3), pp. 337–368.
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9 The Electric Vehicle Industry in China and India: The Role of Governments for Industry Development Martin Lockström, Thomas Callarman, and Liu Lei
9.1
Introduction
With the Copenhagen discussions recently taken place, it is fair to say that the acknowledgement of global warming as a potential threat to our planet has never been greater. Despite the lack of all-embracing, world-wide consensus, the trend is nevertheless going toward a situation with strengthened control and regulatory frameworks in order to reduce greenhouse gas emissions. Recently, the G8 countries signed a treaty to reduce average global temperature by two degrees centigrade until the year 2050. However, this calls for a multilateral commitment at all levels of society – from the beginning of the supply chain starting with raw materials extractors – not ending at the final consumer, but also considering waste and disposal after consumption. Virtually all industries are affected, especially big emitters like the automotive industry. Countries like China and India are no exceptions, as they have both proclaimed far-reaching measures to address the global warming issue. Interestingly, whereas most Western countries have argued about pollution costs and consumer adoption, developing countries like China and India have embraced the current situation as an opportunity to turn greenhouse gas reduction into a business case and to take technological leadership in the field, focusing on the development of electric vehicles (EVs) and hybrids. Due to the threat from global warming, China and India – among many other nations around the world – has committed itself to reduce emissions of greenhouse gases. Furthermore, with increasing local pollution levels, increased traffic congestion, and also an ever-increasing demand for natural resources, the Chinese and Indian governments have started implementing new, tougher measures in order to mitigate the current situation. As the auto industry is responsible for a large share of local and global CO2 emissions, it is one of the target industries for tighter regulatory control. The new emission standards to be put in place over the next years mean that the whole auto industry will have to adjust – in order to be compliant. 203
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There are many ways to achieve this – for example through more efficient engines, alternative fuels, or introduction of completely new power train technologies – such as hybrid and electric vehicles. Having said the above, the aim of this paper is to examine the role of governments in the development of the electric vehicle industry in China and India. For this paper, the primary focus is on passenger and commercial vehicles – electric motorbikes and electric vehicles that are not for public road transportation are beyond the scope of this paper. In this paper, the following research questions will be addressed, namely 1) what is the current state and development of the electric vehicle industry in China and India? 2) What measures – in terms of policies and regulations – have the Chinese and Indian governments taken in order to encourage developments in the electric vehicle sector? and 3) how do China and India compare in terms of government policies related to the electric vehicle sector?
9.2 The automotive industry in China The tremendous economic growth since the liberalization of the Chinese economy in 1978 has propelled China past the United States to become the largest automotive market in the world. Nowadays, Chinese manufacturers are increasingly trying to enter the global marketplace – primarily through sales channels in Southeast Asia, Latin America and the Middle East. A contributing driving force among domestic OEMs is the fact that those who wish to enter the global marketplace have to adopt state-of-theart product technologies. Despite the lack of advanced technologies for the foreseeable future among domestic OEMs, the potential for CO2 reduction still remains high – thanks to the currently low technological maturity level. Burke (2007) claimed that a fuel economy between 40–50% is possible through “mild hybrids”1 (Francis 2009). Interestingly, most Chinese OEMs have product and technology development programs in place for electric and hybrid vehicles – as can be seen in Table 9.1. 9.2.1 Vehicle emission-control standards China started to implement emission controls regulations in the year 2000, adopting National Standard (NS) I emission standards – equivalent to the Euro I standards – countrywide (Lu et al. 2003). In 2004, China increased regulations by moving to NS II emissions. In 2008 – when the country hosted the Olympic Games – the Chinese government further enhanced the move toward stringent emission-control standards for better air quality, driving the implementation of NS IV in Beijing and NS III across the rest of China. China plans to adopt NS IV emission standards countrywide by 2010, and move to NS V – equivalent to Euro V – in 2013, thus eliminating the gap with European norms in just four years.
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Table 9.1 Chinese OEMs involved in EV development Company name
Model name Type
Battery
Range
BYD
F3DM/F6DM
Dual Mode
ET-POWER Fe battery
100 km 160 km/h (electric mode) 430 km (dual mode)
E6
PEV
ET-POWER Fe battery
400 km
160 km/h
Panda EK-1
PEV
Lithium Ion battery
80 km
65 km/h
Panda EK-2
PEV
Lithium Ion battery
180 km
150 km/h
S18
PEV
LiFePO4 battery
120–150 km
120 km/h
M1-EV
PEV
LiFePO4 battery
100 km
Tiggo3-EV
PEV
Lithium Ion battery
150 km
135 km/h
CHANGAN Mini Benben PEV
Lithium Ion battery
150 km
120 km/h
GREAT WALL
GEELY
CHERY
SAIC MOTOR
HAFEI AUTO
Max speed
GWKULLA
PEV
Lithium Ion battery
140 km
65 km/h
GWPERI
PEV
Lithium Ion battery
180 km
130 km/h
Roewe 750-FCV
FCV
Fuel cell battery
500 km
205 km/h
Shanghai
FCV
Fuel cell battery
319 km
150 km/h
Saibao
PEV
lithium ion battery
200 km
130 km/h
Notes: (1) ET-POWER Fe battery is invented by BYD with the characteristics of low cost, long cycle life and high energy density. (2) Lithium-Ion battery has high charging/discharging efficiency but produce relatively little heat, so a simple cooling system is adequate. (3) LiFePO4 battery—Lithium Iron Phosphate battery has high performance, high rate capability for all high power output application, long cycle life and high flexibility both in terms of battery application and cell design. It is widely used for EV and HEV. (4) The application of fuel-cell battery for vehicle can reduce greenhouse gas emissions and air pollutants, improve the economy of fuel. Source: Autohome (2009).
By moving from NS II to NS III, emission limits for nitrogen oxides (NOx) were reduced by 29% and particulate matter (PM) by 33%. Furthermore, the implementation of NS IV standards will reduce the emission of NOx and PM by 30% and 80% respectively – as compared to NS III standards (Hu and Guo 2010). In sum, the government intends to accelerate the implementation of tighter standards for emissions to catch up with those
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Table 9.2 China emission standards Standard
Reference
Date
Region
National Standard I National Standard II National Standard III
Euro 1 Euro 2 Euro 3
National Standard IV
Euro 4
National Standard V
Euro 5 Euro 5
01/1999 07/2004 01/2006 07/2006 09/2006 07/2007 03/2008 11/2009 2010 2012 2013
Nationwide Nationwide Beijing Shanghai Guangzhou Nationwide Beijing Shanghai Nationwide Beijing Nationwide
Note: Only applies to four-wheel Vehicles. Source: Chinaen (2008).
of North American and European countries. The implementation schedule of EU emission standards in China is summarized in Table 9.2. As of today, the Chinese domestic automotive industry is not yet globally competitive in terms of internal combustion engine (ICE) technologies (Tao 2008); most proprietary technologies originate from the foreign partners of the various joint ventures partners, such as Volkswagen, GM, BMW, Toyota, etc. (Medhi 2006). In order to give domestic-market players a fair chance to compete, the government’s emission targets are less stringent than compared to Western countries. Fortunately, the central government has acknowledged the long-term need to reduce its dependency on oil as a natural resource. Developed areas like Beijing and Shanghai usually take the lead in implementing new national standards and are then followed by the other regions. Implementation plans are commonly different from province to province and city to city. However, the effectiveness of any such targets hinge upon the stringency of implementation and penalties. More stringent emission targets in the coming years are likely, however – as the oil price in China is controlled by the state – currently around US$0.94/liter – and oil companies have little incentive to upgrade refining technology. Furthermore, the below-market price of fuel also means that the opportunity cost of using alternative energy sources is higher compared to Europe and other advanced economies. Nevertheless, as domestic OEMs start to enter the global marketplace; these have to comply with the more stringent local regulations overseas – thus further accelerating domestic technology development in China.
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9.2.2 Government support for the EVs To date, the Chinese government has invested at least RMB 100 billion – US$15 billion – in developing clean vehicle technologies and infrastructure (Garthwaite 2011). This has been done in terms of commercialization of battery electric vehicles, large-scale production of hybrid vehicles, and R&D on fuel-cell prototypes. At the same time, vehicle standards, quality and stability will be strictly controlled to meet the new requirements for city-use EVs. The role of large state-owned enterprises is helping to catalyze this development. Sixteen Chinese state-owned enterprises have set up an Electric Vehicle Industry Alliance, which is led by the State-owned Assets Supervision and Administration Commission of the State Council from August 2010. The aims of this alliance are to facilitate the unification of electric car-related technologies and build competitive Chinese electric car brands in the global market (People’s Daily 2010). In June 2007, the State Power Grid Corporation issued a plan that provided for the conversion of a certain number of public-transportation vehicles, taxis, waste-disposal trucks – among others – to EVs on a trial basis in certain cities and provinces. The plan also included the development of a nationwide network of charging stations (Chinanews 2010). Since EVs are one of the cornerstones of the future Chinese automotive industry, the government focuses heavily on the industrialization of EVs/ PHEVs and the related key components. The central government will also provide more than RMB10 billion – US$1.47 billion – for research in power train technologies. In order to promote the adoption of EVs, the government offers subsidies of RMB60,000 – US$ 8,800 – for the purchase of public EVs, such as taxis and buses. 9.2.3 Central government support Recently, the Ministry of Science and Technology has drafted the “electric vehicles twelfth five-year plan (2011–2015)” which indicates the development direction of the electric vehicle industry – emphasizing R&D on prototype, optimization and application for the EV industry, strengthening financial subsidies and seven other aspects (Zheng 2010). The relevant state departments will also launch five supporting measures for development of new energy vehicles (NEVs) in 2011, which will follow up on the new energy automotive industry policies to include the private consumer-purchase subsidies – and map out infrastructure planning. The introduction of these two policies is targeted to solve the consumption and application bottlenecks, but also as the precondition for the broad application of NEVs. In February 2006, the State Council released documents that supported the development of new energy vehicles. In the “National Guidelines on Medium- and Long-term Program for Science and Technology Development” (2006–2020), the State Council listed “low-energy consumption and new energy vehicles” as a priority topic and “hydrogen and fuel cell technologies”
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Table 9.3 The electric vehicle projects of the “863” program in the 11th Five-Year Plan Project name
Responsible company
Fuel cell vehicle
Sedan Bus
SAIC Group, Chery SAIC Group, Foton
Hybrid vehicle
Sedan
Changan, Chery, FAW, DFM, BAIHC, SMA, TJFAW, Brilliance Auto FAW, Zhongtong Bus, Wuzhoulong Bus, SAIC Group
Bus Pure electric vehicle Sedan Bus
HF Automobile Group, FAW Haima North Neoplan, Zhongtong Bus
Source: “863” energy- saving and new energy vehicles office.
During the 11th Five-Year Plan, the 863 program set up ten focus areas – including energy technologies. Within the energy category there are four technology priorities: hydrogen and fuel cell, energy efficiency, clean coal and renewable energy. A total of RMB1.12 billion – US$172 million – has been invested in these priorities, with hydrogen and efficiency technologies receiving the majority of funding (Bill, Tao et al. 2009). Meanwhile, many famous domestic OEMs have joined EV development – as can be seen in Table 9.3. In August 2008, Prof. Wan Gang – the Chairman of the Ministry of Science and Technology – stated that the Ministry would develop a largescale pilot project in ten or more cities with the objective of putting 1,000 hybrid, fuel-cell and all-electric vehicles on the roads in each of those cities and providing the necessary infrastructure for the project within a three year-period. This project is called “Ten Cities, One Thousand Cars” and aims at facilitating adoption of energy-efficient vehicles in urban environments. The first batch of Chinese cities for the EV operation include Dalian, Shanghai, Wuhan, Shenzhen, Chongqing, Changsha, Jinan, with Beijing, Tianjin and Hangzhou as the immediate candidates. These cities will have the large-scale trial run of EVs and hybrid-powered vehicles in the next few years (Zou 2008). 9.2.4 Local government support Rapid demand growth creates an urgent imperative to accelerate the development of electric vehicles (EVs), fuel-cell vehicles and other forms of low carbon transport. Because the active participation of some cities – the list for the project “Ten Cities, One Thousand Cars” has now been extended to 13 cities – now also including Hefei, Kunming and Nanchang in addition. Most of these 13 cities are located in Central and Eastern China, the distribution is relative balance (Chinacity 2010). An overview of the first batch of pilot cities on government policies and planned measures is provided in
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Table 9.4 and the volume of new energy vehicles these cities will have by 2012 is shown in Figure 9.2. Overall, the aim is to leverage the automotive industry in order to sustain continued economic growth in the country. Since the country historically has been a technology laggard, the central government sees the EV industry as an opportunity to gain technological leadership. Moreover, leadership
Table 9.4 Details of the support provided by local governments under the “Ten Cities, One Thousand Cars” policy City
Measures taken
Shanghai
Formal introduction of new energy vehicle license fee exemption policy in 2011. New energy vehicles and key components industry bases with investment of RMB 3 billion (US$440 million) is under construction.
Beijing
Alliance of new energy automotives with the aim of promoting the research and development of the vehicles founded in Beijing in 2009. Official introduction of “new energy industrial revitalization plan”
Shenzhen
Shenzhen carried out a typical electric vehicle operational technology assessment research project in March 2009, In accordance with the targets of the project, Shenzhen will invest more than RMB 50 million (US$7.3 million), planning three bus lines and put 10 hybrid buses in each line. The city will also put 20 PEVs in the city, set up a corresponding charging and testing facilities, making management standard and evaluation method to complete the assessment of business operations environment.
Zhuzhou
Zhuzhou has launched three-year action plan of energy-saving and new energy vehicle demonstration and extension. Now it has put 120 electric buses on the main road in the city. Plan to replace existing 627 city buses by electric or hybrid vehicles from 2009 to 2011. The Department of Finance will also provide bus companies a threeyear car allowance, loan interest subsidies, advance disposal of the vehicle loss of subsidies, etc. total up to RMB 60 million (US$7.8 million).
Tianjin
According to Tianjin Municipal Science & Technology Commission, this city has created a complete industrial chain, developing electric vehicles, including whole-vehicle production, key spare parts manufacturing and standards setting. The city has successfully put electric vehicles into use as taxi, police cars and cars for official business, with the total driving distance exceeding 100,000 kilometers. Three routes with electric vehicles in operation exclusively have been launched before the2008 Beijing Olympics. continued
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Table 9.4 continued Chongqing
As one of the first 13 national demonstrations and popularization of new energy vehicles pilot cities, Chongqing Municipality will promote 1,150 energy-saving and new energy vehicles before the end of 2011. Chongqing government will introduce financial assistance policies to encourage the energy-saving and new energy application in public transport, rental, service and other public services area. New energy taxi and new energy bus can enjoy the local financial subsidies, policy also clearly specifies the amount of subsidies that individuals can enjoy: the government specified Integrated Starter Generator (ISG) mild hybrid vehicle could get RMB 3, 600 (US$523) subsidies and onetime toll charges RMB 6,900 (US$1,000) subsidies, quantity is limited to one hundred.
Nanchang
Until 2012, Nanchang will promote 1,000 energy-saving and new energy vehicles in public domain and will establish support system for new energy automobile production and product after-sales service; build three electric vehicle charging stations (battery exchange stations) and 150 pure electric vehicle charging column (cabinet); set up 15 energy-saving and new energy vehicle maintenance service networks, and gradually build electric car fast-charging network. Nanchang government will actively promote the autonomous R&D and industrialization of key components for new energy vehicles and key components, trying to reach an annual output of 10,000 units of new energy automotive industry scale to achieve innovation and development of the automobile industry
Source: Automotive and Parts (2009).
in production and use of clean energy sources is also a powerful means to improve the environmental image of the country in a global context. Without doubt, fuel efficient vehicles are therefore the key in order to accomplish economic and political targets. Currently, there are more than 100 companies engaged in electric vehicle project and 2,000 companies producing EV batteries. Most of the largest domestic car makers such as SAIC, FAW, Dongfeng, Chery, Geely and BYD, already have development programs for EVs in place (Lan 2010). 9.2.5
Infrastructural construction
Since the Chinese central and local governments’ proactive attitude on industrialization of EVs, many Chinese domestic enterprises have joined the charging station constructions. China state-owned utility company State Grid Corporation of China (SGCC) plans to construct 144 electric vehicle charging stations with a total of 13,000 charging points in 2011 (Ye 2011). With support from SGCC, The city of Xian in Central China plans to build
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24,000
25,000 20,000 15,000 10,000 6,000
4,570 1,610 1,400 1,600
Kunming
Nanchang
1,000 1,000
Changsha
Hangzhou
Dalian
Changchun
Chongqing
Beijing
1,000
0
Shenzhen
2,400 3,000
Wuhan
5,000
Hefei
5,000
Jinan
Implementation plan (units)
30,000
Cities Figure 9.2 The “Ten Cities, One Thousand Cars” implementation plan for new energy vehicles in 2012 Source: Xinhua News (2009a).
four charging stations with 200 charging points and five charging stations with one hundred charging points – on trial in the city of Tianjin in East China. China Southern Power Grid (CSG) closely followed, with 89 charging stations and 29,500 charging points put into operation in late 2012 (CSG 2009; Ye 2011). 9.2.6 Consumer acceptance According to a survey conducted by Ernst & Young’s Global Automotive Industry Centre, a consultancy, showed that 60% of Chinese respondents said they would consider buying a plug-in hybrid vehicles or electric vehicles. Compared with the same survey conducted by the firm in other countries – such as U.S., Japan, Germany, Britain, Italy and France – the figure for China is nearly five times higher than the rest (Ernst and Young 2010). 9.2.7 Shortcomings in existing policies The Chinese government has been giving policy support to these new energy car manufacturers without focus. The 863 Plan formulated by the Ministry of Science and Technology is an indication that China hopes to promote FCEV, HEV and BEV technologies. However, this strategy is questioned as being too broad (Luo 2008). In contrast, many countries have a
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single strategic emphasis in specific new energy cars. For example, Japan is in favor of hybrid vehicles. Japanese car makers like Toyota, Nissan, and consumer goods maker Panasonic, will collaborate to develop a unified new-generation lithium battery which is expected to start mass production in about 2010 (Xinhua News 2009b). The USA is focusing their research on PHEVs. In 2008, General Motors announced that the Electric Power Research Institute – as well as over 30 power companies – will have a largescale cooperation, in order to accelerate the commercialization process of PHEV (Chhaya 2009). China has released some guiding documents to encourage new energy cars. However, detailed enactment on subsidizing the private purchase of new energy cars has been suspended repeatedly. Over time, the delay of policy encouragement to individual consumption of new energy cars will reduce the window of opportunity for China to invest in the EV industry (Yang 2010). Hence, the chances for Chinese car makers to take advantage of this opportunity and to catch up with global players in terms of technology are getting even slimmer.
9.3 The automotive industry in India The Indian automotive industry has experienced tremendous growth in recent years, largely due to the burgeoning middle class, and a significant increase in their disposable income. According to recent estimates, industry output is expected to reach four million units by 2013 (PriceWaterhouseCoopers 2009), to which the commercial vehicle segment will be a major contributor. Industry experts peg the Indian automobile sales growth at a compounded annual growth rate (CAGR) of 9.5% by 2010. The key challenges for the auto industry in India are high fuel costs, congested city streets, low vehicular speeds and limited driving distances. On the other hand, this also makes India an attractive market for compact-sized EVs. Furthermore, the availability of skilled engineers, low manufacturing cost and access to both hardware and software uniquely positions India as a pioneer market for EVs. So far, India has two companies involved in EV development as shown in Table 9.5. It is worth noting that the REVA is exempt from most European crash-test rules – because of its low weight and power, it is classified as a “heavy quadracycle” (category L7e) rather than “car” in Europe. This fact is a double-edged sword, however. On the one hand, the exemptions of safety regulations make it much less costly to develop compared to a conventional car. On the other hand, it also positions it in a market segment which is completely new to Western consumers. In short, it does not, and will not compete with conventional cars. As the potential of the micro-car segment in Western countries is very uncertain, so is its own potential in such markets. The same applies to China, where consumers traditionally have a preference
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Table 9.5 Indian OEMs involved in EV development Company name
Model name
Type
Battery
TATA
Tara Tiny Indica Vista EV
– PEV
REVA
Reva NXR
PEV
Reva NXG
PEV
– 100 km Super Polymer 200 km Lithium Ion Lithium Ion 160 km battery Lithium Ion 200 km battery – –
HERO
–
–
MAHINDRA
–
–
–
Range
–
Max speed 70 km/h 110 km/h 104 km/h 130 km/h – –
Note: Hero and Mahindra have the plan for EV production but so far no motorcycle type on the market. Source: Autoblog (2008).
for comfortable, aesthetic mid-sized cars. In contrast, in China consumers actually seem to prefer being without a car unless they can afford a conventional mid-sized sedan with Western standards. Those who have visited China over the last years have noticed a glaring absence of ultracompact cars in first- and second-tier cities. 9.3.1 Vehicle emission-control standards The first Indian emission regulations were idle emission limits which came into effect in 1989. These idle emission regulations were soon replaced by mass emission limits for both petrol (1991) and diesel (1992) vehicles, which were gradually tightened during the 1990s. In 2000, passenger cars and commercial vehicles had to meet Euro I equivalent India 2000 norms, while two-wheelers will be meeting one of the tightest emission norms in the world. Euro II equivalent Bharat Stage II norms have been in force since 2001 in the four cities of Delhi, Mumbai, Chennai and Kolkata (DieselNet 2008). On October 6th 2003, the National Auto Fuel Policy was announced, which envisaged a phased program for introducing Euro II-IV emission and fuel regulations by 2010 (DieselNet 2008). The implementation schedule of EU emission standards in India is summarized in Table 9.6. The above standards apply to all new four-wheel vehicles sold and registered in the respective regions. In addition, the National Auto Fuel Policy introduces certain emission requirements for interstate buses with routes originating or terminating in Delhi or the other ten cities. For two- and three-wheelers, Bharat Stage II (Euro 2 equivalent) was applicable from April 1, 2005 and Stage III (Euro 3 equivalent) standards came in effect during the period April 1, 2008, and April 1, 2010 (DieselNet 2008).
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Table 9.6 Indian emission standards Standard
Reference
Date
Region
India 2000 Bharat Stage II
Euro 1 Euro 2
Bharat Stage III
Euro 3
2000 2001 2003.04 2005.04 2005.04 2010.04
Nationwide NCR*, Mumbai, Kolkata, Chennai NCR*,10 Cities** Nationwide NCR*,10 Cities** Nationwide
Bharat Stage IV
Euro 4
2010.4
NCR*,10 Cities**
Notes: * National Capital Region (Delhi). ** Mumbai, Kolkata, Chennai, Bengaluru, Hyderabad, Ahmedabad, Pune, Surat, Kanpur and Agra. Source: DieselNet (2008).
Since India started implementing a formal emission-control regime as late as 1991, the country is still lagging behind more mature economies like the US and EU. Currently, they are behind Euro norms by a few years. However, as the country is gaining momentum, emission norms are step by step becoming aligned with Euro standards and vehicular technology is being upgraded accordingly. Vehicle manufacturers are also working towards bridging the gap between Euro standards and Indian emission norms. 9.3.2 Central government support The Indian government reduced excise duty on the development and manufacturing of hybrid vehicle kits from 10% to 5% in the 2011 budget (AUTOCARINDIA 2011). In 2010, the Indian government was contemplating bringing in a policy to promote electric vehicles – aiming at providing guidelines on how to promote electric and alternative fuel vehicles in the country – likely to be finalized this in 2011 (Business Standard 2010). Meanwhile, the Indian central government also provides subsidies to their domestic car makers. The government has announced a central subsidy of up to Rs75,000 for each REVA Electric Car. The beneficiaries of this subsidy are public institutions – including government organization and departments, public sector undertakings, educational institutions, hospitals, tourism and archaeological sites. Based on the specific requirements of the public institutions as per the direction of the Ministry of Non-conventional Energy Sources (MNES), REVA has introduced a modified range of models named the “REVA Eco” – which is eligible for the subsidy (Gautam 2010). 9.3.3 Local government support The Delhi government announced a 29.5% discount for the small electric car Reva in 2008. Chandigarh offered a subsidy of 15% on battery-operated
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vehicles, whereas Bangalore has taken the lead in giving a 4% VAT waiver for the initial five years after the launch of the car and on registration costs (Chowdhury 2009). The cost of the subsidy for EVs will be covered from the Air Ambience Fund – created from an environment tax of Rs0.25 (US$0.005) per liter on diesel fuel sold in Delhi. The Delhi government has already collected Rs100 million (US$2.18 million) from these taxes (Mangaonkar 2009). Buyers of EVs are eligible for a 15% subsidy on the base price of the vehicle, a value added tax (VAT) refund of 12.5% and a 2% exemption on road tax and registration fees. In total these incentives have cut the price of Reva by more than Rs100,000 (US$2,180) (Lalchandani 2008). The combination of high fuel prices and government support is steadily increasing the demand for EVs. Recent policy developments have attracted several other known and unknown market players to the market segment. For example, Tata Motors has also built a prototype EV model called Indica – whereas several foreign OEMs, such as Mitsubishi plan to launch EV models in the Indian market. Other newcomers – such as the clock-maker Ajanta Group – have begun producing electric bikes in Gujarat and have plans to make an electric car priced at Rs85,000 (US$1,853) with 70% indigenous components (India Times 2008). Industry experts see this as a challenge to Tata’s low-cost car – the Nano – reported to be priced at Rs100,000 (US$2,180). Among the global OEMs, companies such as GM, Volkswagen, Mitsubishi Motors Corp, Chrysler have also shown interest in making electric cars in the country. 9.3.4
Infrastructural construction
In 2009, the Indian union ministry of new and renewable energy announced that they will provide subsidies to a large network of charging stations established by the companies. The facilities for leasing of batteries and a central charging facility are also considered as a step forward for promotion of battery-operated vehicles (Technologyreview 2009). The Karnataka Renewable Energy Development Ltd. (KREDL) – a company wholly-owned by the state government – plans to launch a self-sustaining solar technology program in 3,900 villages in the 39 most backward areas. The solar/hybrid power plants provide power either through a local minigrid or stand-alone or are made available at a charging station – enabling residents to charge their electrical appliances (Indianexpress 2009). Some companies or small R&D firms – such as EVFuture – have done some tests on it. EVFuture – which is a south Indian R&D firm – built a solar charging station for electric vehicles in Auroville, South India in 2008. The firm is currently developing prototype vehicles of 400 W and 800 W that will be better suited for Indian road conditions (EVFuture 2010). Reva is launching a lithium-ion-battery-powered electric vehicle for the European market, along with a fast-charging station that can charge the lithium-ion battery to 90% in one hour (Faye 2009).
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9.3.5 Consumer acceptance According to Frost & Sullivan’s recent study “Voice of Indian Automotive Customers 2009: Evaluation of Powertrain Technologies in Vehicles,” the concept of electric vehicles in India is growing. Due to post-purchase concerns – such as battery life, distance traveled, maintenance cost, acceleration and top speed – only 7% of Indian vehicle owners are willing to purchase an electric vehicle in the future. Among the alternate power train technologies available, Indian vehicle-owners were more aware of LPG, CNG, and – to some extent, electric and bio-fuels. (Frost 2010). 9.3.6 Shortcomings to the policies In spite of India being a hub for inventions of such technologies, EVs have not gained popularity – owing to lack of adequate and timely support from central and state governments. The Indian government, on the other hand, only offers incentives in the form of duty concessions on electric vehicles – such as excise duty on hybrid vehicles reduced to 5% – but still the incentives seem too low for the price reduction of such vehicles (Chetan 2010).
9.4
Comparison of India and China
To compare the EV development in China and India, we have summarized the above discussion with a table to find the differences and similarities in both countries (see Table 9.7). Table 9.7 Comparison of EV development in India and China Market driver
China
India
Emission standards
Implemented emission regulations Implemented emission in 2000. regulations in 2000. Adopt NS IV in 2010. Will Adopt Bharat Stage III implement NS V in 2013. national wide and Bharat Stage IV in 10 cities in 2010.
Central government support
Issued “Automotive Industry Reduced excise duty on Restructuring and Revitalization hybrid cars, electric Plan” in 2009 with the annual vehicles and specified parts production capacity target. of electric cars. Invested RMB 4 trillion (US$585 Announced a Central billion) on new energy vehicle Subsidy for each REVA development includes EVs Electric Car for public use. The central finance supports the In 2010 Indian government demonstration and promotion will introduce guidelines of new energy cars in big and for EV development. medium cities. Subsidy for the public use of new energy vehicle. continued
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Table 9.7 continued Local government support
Most cities who took part in the Delhi government “Ten Cities, One Thousand Cars” announced discount for the program have various incentive small electric car Reva in policies and subsidies to prompt 2008 with value added tax EV (see Table 9.4). refund and exemption on road tax. Chandigarh offered the subsidy on battery-operated vehicles. Bangalore also provided discount for VAT and registration costs.
Shortcomings to Chinese government has been the polices giving policy supports to new energy car manufacturers but without a focus. Lack subsidies to private purchase of new energy cars.
Inadequate incentive policy and also lack subsidies to privation consumers.
Trial operations China officially launched the demonstration and trial run of energy-saving and new energy vehicle (“Ten Cities One Thousand Cars” Project).
No large-scale trial run of EVs in India.
Infrastructural construction
State Grid Corporation of China and China Southern Power Grid have plan to build charging stations in more than 20 cities.
Karnataka Renewable Energy Development Ltd. plans to build charging stations but not only for EV. Evfuture built a solar charging station for electric vehicles in Auroville. Reva also constructing fastcharging station for EV but only in Europe.
Consumer acceptance
60% of Chinese respondents Only 7% of Indian vehiclewould consider buying a plug-in owners are willing to hybrid vehicles or electric purchase an electric vehicle vehicles. in the future.
According to the table, we can see that China and India want to leverage new energy vehicle industrialization to their environmental protection target – but there are still various sorts of differences that will be elaborated in the following. Emission standards. Both countries have implemented emission regulations since year 2000. However, this year – 2010 – China will bring National Standard (NS) IV – equivalent to Euro 4–into effect and plans to implement
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NS V – equivalent to Euro 5–in 2013 in nationwide while India is lagging behind China as they will adopt Bharat Stage (BS) III – equivalent to Euro 3–this year and BS IV – equivalent to Euro 4 – only in ten years, without any plan for implementation of the BS Emission Standard – equivalent to Euro 5. Government support. From the Table 9.7 it can be seen that the central government in both countries introduced various incentive policies for the new energy vehicle development. China’s central government has already provided guidelines for EV development in 2009 through the “Automotive Industry Restructuring and Revitalization Plan” and the Indian government will issue similar guidelines in 2010. Meanwhile, both central governments provide subsidies to the EV consumer for the public use. The difference is that the support from China’s central government puts more emphasis on EV research and development – from domestic OEMs and universities, and EV demonstration and promotion in big cities. The Indian central government focuses on the relief of import tax for EV. Local government support. Chinese local government support mainly clusters in the cities who participated in the “Ten Cities One Thousand Cars” project – the Indian local government support centers are in Delhi, Bangalore and Chandigarh. Looking at China, Chongqing is the only city which has already introduced the subsidies for the private consumer – a clear difference with India. Moreover, most Chinese local governments have invested heavily in electric vehicle R&D and industrialization according to specific plans. The three Indian cities mentioned previously all provide subsidies to private buyers though. Shortcomings to existing polices. Both countries face similar problems in terms of lack of subsidies for private consumers. This is a very important barrier for EV development in China and India. At the same time, China seems to support too many kinds of new energy vehicle development with too little focus, potentially causing suboptimal allocation of resources. Trial operations. During the Beijing Olympics, China already started their first large-scale new energy vehicle trial run – with 595 electric vehicles. With the launch of the “Ten Cities One Thousand Cars” program, the country will promote more than 200,000 new energy vehicles – most of them electric vehicles. The Indian government has not made any plans for an electric vehicle trial operation as of today. Infrastructure construction. China’s state-owned enterprises – the State Grid Corporation of China and China Southern Power Grid – have already launched the construction of charging stations in many Chinese cities for electric vehicle use only. Though the Indian company Karnataka Renewable Energy Development Ltd. plans to build several charging stations, it is mainly to solve the problem of electricity use in remote areas in India, and these do not seem to be fit for electric vehicle charging. EVFuture has only built one EV charging station in India, and Reva constructs fast-charging stations – but only in European countries.
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220 Martin Lockström, Thomas Callarman, and Liu Lei
Consumer acceptance. According to a survey by the Ernst & Young Global Automotive Industry Centre 60% of Chinese respondents would consider buying a plug-in hybrid vehicle or electric vehicle (Ernst and Young 2010) whereas Frost & Sullivan’s recent study shows that only 7% of Indian vehicleowners are willing to purchase an electric vehicle in the future (Frost 2010). 9.4.1
Interim summary
China has long been in the top of carbon-dioxide emissions in the world and faces more pressure than other countries to reduce emissions. Therefore, the Chinese government has to formulate rigorous emission standards to control emissions, and force the auto manufacturers – especially commercial vehicle manufacturers – to upgrade their technology and bring advanced technology to domestic automobile manufacturing. It is believed that this is the key driver that the Chinese government utilizes to promote electric vehicle development in China. According to the Chinese Science and Technology Minister – who may represent the Chinese central government’s attitude toward EV development that in this industry – China and other countries are at the starting line, and the gaps in EV technology and industrialization are relatively small. If the technology level of Chinese traditional vehicles lags behind the international level by about 20 years, the corresponding gap regarding EVs is only four to five years. Moreover, China has the largest deposits of rare earth metals and the second largest reserves of lithium resources in the world – implying a comparative advantage in terms of natural resources. Furthermore, China is now the largest vehicle market – with a complex spectrum of consumer tastes. Hence, China potentially has the advantage of scale economies and factor inputs in the development of electric vehicles. The Chinese government is aware of the great potential benefits of EVs in social, energy and environmental aspects. It is also an important direction for the development of the auto industry in the future. Thus, the Chinese government has made investments in scientific research and formulated a series of laws and regulations to encourage and support auto makers, autorelated industries and research institutions, with the aim of obtaining a favorable position in the global marketplace. India is currently focusing on promoting compressed natural gas (CNG) vehicles, liquefied petroleum gas (LPG) vehicles and other forms of gaseousfuels vehicle in its alternative fuel programs as a way of evolving cleaner emissions – other conventional technologies of diesel and petrol are very slow to improve (Sabapathy 2008). By 2009, there were 11.2 million natural gas vehicles in the world, where India ranks 5th with 725,000 units (IANGV 2009). The reasons for the CNG vehicle and LPG vehicle prevalence in India are given below. The first factor is Indian government legislation enforcement. By the time India got worried about pollution – especially from vehicles – gaseous fuel seemed to be a quick solution to bring the
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pollution level down. On July 28th 1998, the Supreme Court of India ruled that the number of public buses in Delhi should reach 10,000 by April 1, 2001, and all buses – along with three wheelers and taxis – needed to be converted to CNG (Ravindra, Wauters et al. 2006). Since then, Delhi and other Indian cities have witnessed a great increase in CNG programs. Until now, there are 650,000 CNG vehicles running in India, among which more than 220,000 are located in Delhi. And there are still more cities initiating the CNG programs (Chowdhury 2009). Second, there is easy access to gas filling stations. Though CNG programs are only running in 30 cities, people can find 700 auto LPG dispensing stations in 309 cities of India. According to the Petroleum and Natural Gas Regulatory Board (PNGRB), the number of cities initiating CNG vehicles will increase more than eight times from the current 30 to 250 by 2018 (Chowdhury 2009). Third, the fuel costs are much lower than that of gasoline. In India, CNG costs are at around Rs22.00 (US$ 0.48) per kg and LPG costs are at Rs35.68 (US$ 0.78) – compared with Rs47.53 (US$ 0.92) per liter of petrol (prices as of 6th Sept. 2009 in Mumbai, India) (Singh 2009). The cost saving is immense – along with reduced emissions and environmentally friendlier cars. The different strategies for developing alternative energy vehicles in each country directly lead to the different focuses of central and local governments’ supports and a great difference in trial operations. Thus, it’s not difficult to understand why Chinese state-owned enterprises are actively investing in infrastructure constructions for electric vehicles. In turn, this potentially explains the higher consumer acceptance of NEV technologies in China compared to India.
9.5
Conclusions
At present, both the Chinese and Indian governments lead the automotive industry as cornerstones for their economic development. Meanwhile, global warming and climate change has – over the years – become one of the most pressing issues for policy makers. Most Western countries focus on development and industrialization of alternative energy vehicles. As NEVs represent a new wave of potentially disruptive technology, China and India have realized a window of opportunity – where necessary skills and capabilities can be built through a mix of technology absorption and development. In this way, the countries try to close the existing skill gap and leapfrog the technology race. This study concentrates on how these two late industrializing countries make efforts to drive an industrial revolution in their respective countries. The key driving forces here are aspects such as central and local governments’ incentives and polices, infrastructure construction and consumer acceptance. From the comparisons we can see that both governments introduced stringent polices to control auto emission and declared serious policies to
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prompt domestic EV development. At the same time, both domestic OEMs are claiming that they need incentive subsidies for the private consumers to reduce the acquisition cost. However, the Chinese central government placed specific targets and corresponding policies for the EV industrialization. For example, the China State Council made a statement with the aim that until 2011, overall technology of NEVs should reach international standards. The “Automotive Industry Restructuring and Revitalization Plan” and the “863” program provided detailed quantitative targets and financial support, with the widespread new energy vehicle trials run according to the “ten cities, one thousand cars” program. With the help of these programs, the Chinese government hopes it can facilitate the adoption of new energy vehicles by the public and give technical feedback to carmakers for improvement. All those policies connect with each other to facilitate EV industrialization. By contrast, the Indian central government has so far only provided incentives on custom duties. Hence, from a government leadership perspective, India is clearly lagging behind China. From another viewpoint, the number of Chinese companies who are engaged in EV research and development is much higher than in India. As a consequence, China will likely have a higher rate of technology accumulation than India. Several Chinese state-owned enterprises have started to build charging stations to capture the future market. In turn, with the increased pace of charging station construction in China, the promotion of EVs will be accelerated through a virtuous cycle. At the same time, Chinese consumers lead the world in electric vehicle interest – 53% more than Indian consumers. In other words, China is more advanced in terms of infrastructure and consumer acceptance aspects. Even though China seems to have overwhelming advantages in EV industrialization than India at the moment, it is too early to forecast which country will be more successful in the long run. Although skill formation and technology absorption are high in both countries, China has traditionally relied on a foreign influx of technology and expertise to a higher extent, through the use of standardized parts with little proprietary content. In contrast, the lower government pressure in India has allowed their domestic companies to build a higher degree of skills and capabilities in-house instead of seeking shortcuts and cutting corners. Nevertheless, the fact that typical Chinese mainstream cars are more closely aligned with Western consumer preferences combined with a faster rate of policy implementation and government incentives, makes it more likely that a commercial breakthrough of EVs will happen earlier in China than India. Ultimately, emerging markets like China and India will play an increasing role in the global auto sector – not only for low-cost production – but increasingly for new product development, and even more so for consumption. Regardless of which country will reach large-scale breakthrough earliest, one thing is for sure: the quest for technological leadership will permanently
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redraw the global automotive landscape. And governments will play a key role in providing the carrots and sticks to make it all happen.
Note 1. A mild hybrid – sometimes called a power-assist hybrid. There is generally a bigger battery that can store plenty of charge from regenerative braking, and an electric motor that can be used to assist the car’s engine when needed. Mild hybrids save fuel because energy that would be lost in braking is “re-used” to help accelerate. Most importantly, a mild hybrid can’t run on its electric motor alone for zero-emission low speed motoring.
References AUTOCARINDIA, 2011, “Union Budget 2011 Highlights”, http://www.autocarindia. com/news/union-budget-2011-highlights. Accessed 3 February 2011. Bill, R., K. Tao, et al., 2009, “China Has the Best Chance to Develop Electric Vehicle”, Booz & Company. Burke, A. F., 2007, “Batteries and Ultracapacitors for Electric, Hybrid, and Fuel Cell Vehicles”, Proceedings of the IEEE, 95, pp. 806–820. Business Standard, 2010, “Electric Vehicle Policy Likely This Year”, http://www.business-standard.com/india/news/electric-vehicle-policy-likely-this-year/390815/. Chen, D., 2002, “Brief Introduction to ‘863’ Programme in 10th Five Years Plan”, Renewable Energy (3), pp. 1–2. Chetan, M., 2010, “The Future of Electric Vehicles in India”, Federation of Automobile Dealers Associations. Chhaya, S. M., 2009, “Electric Transportation Update”, Electric Power Research Institute. Chinacity, 2010, “Ten Cities, One Thousand Cars’ Program Enlarged to 13 Cities”, http://www.chinacity.org.cn/csfz/csxw/54283.html. Chinaen, D., 2008, “Automobile Exhaust Gas Emission Standards”, http://www.chinaen.org/group_thread/view/id-21008, Accessed 16 November 2009. Chinanews, 2010, “Five State-Owned Enterprises Have Came to the Charging Station Marketplace”, http://www.chinanews.com.cn/auto/news/2010/03–10/2160383.shtml. Chowdhury, A. R., 2009, “India Backs Alternative Transportation Fuels”, http://www. technologyreview.in/energy/24094/. CSG, 2009, “The First Batch of Electric Vehicle Charging Stations Has Put into Operation”, https://www.csg.cn/news/compnewscon.aspx?id=18473&ItemCode=0 02001000000. Accessed 6 February 2010. Dai, F., 2009, “Strategic Research on Industrialization of Electric Vehicles”, Science & Technology Progress and Policy, 26 (16), pp. 71–73. DieselNet, 2008, “Emission Standards in India”, http://www.dieselnet.com/standards/in/. Accessed 20 November 2009. Ernst and Young, 2010, “Chinese Consumers Lead the World in Electric Vehicle Interest”, Ernst & Young Global Automotive Center. EVFuture, 2010, “Evfuture Launches Solar Charging Station for Electric Vehicles”, http://www.evfuture.com/yellow_pages/EVFuture. Faye, S., 2009, “Reva Announces Lithium-Ion Electric Car and Fast Charge Station”, http://www.thegreencarwebsite.co.uk/blog/index.php/2009/01/06/reva-announces-lithium-ion-electric-car-and-fast-charge-station/.
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224 Martin Lockström, Thomas Callarman, and Liu Lei Feigenbaum, E. A., 2003, “China’s Techno-Warriors: National Security and Strategic Competition from the Nuclear to the Information Age”, Stanford University Press. Francis, S., 2009, “What Is a Hybrid Car”, http://blog.toyota.co.uk/what-is-a-hybridcar-prius-co2-emissions. Accessed 19 December 2009. Frost, 2010, “Voice of Indian Automotive Customers 2009 on Powertrain Technologies and Health and Wellness Features in Vehicles”, in Frost and Sullivan. Garthwaite, J., 2011, “On China’s Roads (and Rails), a Move toward Greener Transit”, http://news.nationalgeographic.com/news/news/energy/2011/01/010511-chinatraffic-greener-transit/. Accessed 5 January. Gautam, S. P., 2010, “Status of the Vehicular Pollution Control Programme in India”, Ministry of Environment & Forests, Govt. of India. Hu, Y. and B. Guo, 2010, “The EuroviEmission Standards Will Impact China on Automotive Industry”, Popular Standardization (2), pp. 41–43. IANGV, 2009, “Natural Gas Vehicle Statistics”, http://www.iangv.org/tools-resources/ statistics.html. India Times, 2008, “Ajanta to Challenge Nano with Electric Car”, http://timesofindia.indiatimes.com/biz/india-business/Ajanta-to-challenge-Nano-with-electriccar/articleshow/2942510.cms. Accessed 16 December 2009. Indianexpress, 2009, “Karnataka Plans to Light up 3,900 Villages through Solar Power”, http://www.indianexpress.com/news/karnataka-plans-to-light-up-3–900villages-t/481212/. Lalchandani, N., 2008, “Delhi: 30% Subsidy on Battery-Run Vehicles”, http:// timesofindia.indiatimes.com/Delhi/Delhi_30_subsidy_on_battery-run_vehicles/ articleshow/3107878.cms. Accessed 14 January 2010. Lan, Z., 2010, “Too Many Ev Makers Will Cause Risk”, Beijing Business Today. Lei, Y., 2009, “4 Trillion Investment Fired the First Shot, Targeting New Energy Industry”, Journal of Guangxi Electric Power, 6, p. 12. Long, L., 2008, “The Electric Vehicle’s V2g”, Journal of Automobile & Parts, 41, pp. 22–23. Lu, A., et al., 2003, “China’s Auto Emission Standards Development and Strategy”, Communications Standardization (8), pp. 39–42. Luo, C., 2008, “Electric Vehicle Policies are Difficult to Bring into Effect”, Southern Metropolis Weekly, 261 (79), pp. 14–15. Mangaonkar, R., 2009, “Public Transports Get a Boost”, http://timesofindia.indiatimes.com/city/ahmedabad/Public-transports-get-a-boost/articleshow/4145863. cms. Accessed 3 December 2009. Medhi, N., 2006, “Patent Tales: Trailing Emission Control Technologies in the Developing World”, Department of Social Sciences, Center for Policy Research, The Maxwell School, Syracuse University. People’s Daily, 2010, “16 State-Owned Companies Form Electric Auto Alliance”, Accessed 4 September 2010. PriceWaterhouseCoopers, 2009, “China’s Great Leap Forward”, PricewaterhouseCoopers. Ravindra, K., E. Wauters, et al., 2006, “Assessment of Air Quality after the Implementation of Compressed Natural Gas (Cng) as Fuel in Public Transport in Delhi, India”, Environmental Monitoring and Assessment, 115 (4), pp. 405–417. Sabapathy, A., 2008, “Air Quality Outcomes of Fuel Quality and Vehicular Technology Improvements in Bangalore City, India”, Transportation Research Part D: Transport and Environment, 13 (7), pp. 449–454. Singh, G., 2009, Exploit Nature-Renewable Energy Technologies, Aditya Books Pvt. Ltd.
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The Role of Governments: Electric Vehicle 225 Tao, D. T., 2008, “Testimony before the U.S.-China Economic and Security Review Commission Regarding Research and Development and Technological Advances in Key Industries in China”, http://www.uscc.gov/hearings/2008hearings/written_ testimonies/08_07_16_wrts/08_07_16_tao_statement.php. Technologyreview, 2009, “Briefing: Transportation”, http://www.technologyreview. com/communications/24093/page1/. Wu, H., 2000, “The Progress of Communication Technology Subject of Hi-Tech Research Development Plan of China”, International Conference on Communication Technology Proceedings 2000, WCC-ICCT 2000, 1, pp. 3–4. Xinhua News, 2006, “National Guidelines on Medium- and Long-Term Program for Science and Technology Development”, http://www.gov.cn/jrzg/2006–02/09/content_183787.htm. Accessed 15 December 2009. Xinhua News, 2009a, “Beijing’s High-Tech Application Process Need Financial Support for a Large Number of Intermediary Services”, http://www.bj.xinhuanet. com/bjfs/2009–09/27/content_17824385.htm. Accessed 26 November 2009. Xinhua News, 2009b, “Germany Invested 360 Million Euros This Year to Start Car Battery Development Program”, http://www.clii.com.cn/news/content-4611.aspx. Yang, X., 2010, “The Incentive Policies for the New Energy Vehicles Is Ineffective”, Chinadaily. Ye, Y., 2011, “Sgcc Will Put More Effort on Ev Infrastructure Development”, http:// www.nffair.com/zixun/Detail.shtml?infotitle=C93DFA4733EABAA60FD5C8F7B4 8CA5D4&InfoId=B841D22CE2B899BE. Accessed 1 February 2011. Zheng, A., 2010, “China to Issue New Energy Vehicle Development Planning in Two Months”, http://autonews.gasgoo.com/china-news/china-to-issue-new-energyvehicle-development-plan-100906.shtml. Accessed 6 September 2010. Zou, S., 2008, “China Begin to Run Large-Scale Commercial Demonstration of Energy-Saving and New Energy Vehicle”, http://www.gov.cn/ztzl/2008–12/12/ content_1176720.htm. Accessed 15 December 2009.
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10 The Role of Local Government in Software and ITES Offshoring in Dalian, China Hiromi Hinata
While China’s fast growth has been fed by rapid industrialization, India’s recent growth has been led by the service sector. Software and information technology enabled services (ITES) has been one of the critical service sectors that contributed to it most. Now China is also accelerating the development and export of software and ITES in order to realize strategic adjustment of its industrial structure and take advantage of its abundant human resources. This chapter focuses on Dalian – one of the successful offshore destinations in China – to examine the role of local government in sector agglomeration and branding of the city as a global offshore destination in their effort to “catch-up” with Bangalore, the global hub of offshore operations. This study explores the factors that brought Dalian to the forefront of the software and ITES business in China, with a focus on the role of local government.
10.1 The software and ITES sector in India and China: an overview The aggregate revenue of the global software and ITES sector in 2008 was estimated at over US$1,005.8 billion, which represents growth of 7.0%. Revenue in India was estimated at US$59.6 billion, or 5.9% of global revenue, while revenue in China was estimated at US$111.4 billion, or 11.1% of global revenue. Thus, the revenue of the Indian software and ITES sector is smaller than that of China. Comparing the export revenue, however, the revenue of India is much larger than that of China. The gap is increasing and it is unlikely that China will catch-up with India in the near future. The software and ITES sector in India mainly serves the export market and – unlike China – its domestic market is small (Figure 10.1). The US and the UK remain the dominant markets for Indian exports – accounting for nearly 80% of the total. On the other hand, China’s software 226
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Local Government in Software and ITES Off-Shoring Billion USD 120
227
(%) 70 60
100
50 80 40 60 30
China (Revenue) India (Revenue) China (Export Ratio) India (Export Ratio)
40 20
8
6
7
00
00
00
00
00
3 00
00
00
5
0
4
0
2
10
1
20
Figure 10.1 Software and ITES revenues and export ratio in China and India (2001–2008, Billion USD, %) Source: NASSCOM (2009), CSIA (2009).
and ITES exports are predominantly shipped to the Japanese market, which accounts for 52% of total exports. India’s software and ITES companies are much larger in scale than their Chinese counterparts. Sales revenue for Tata Consultancy Services for the fiscal year ending in March 2009 was INR278.1 billion (US$6.0 billion), and of this, 92.2% was from international businesses. On the other hand, the sales revenue for Neusoft – China’s largest software and ITES company – was RMB3.7 billion (US$0.5 billion) in 2008, and of this, 33.9% was from international businesses. The headcounts at the top three Indian companies are around 100,000 employees. On the other hand, the largest Chinese company has recently exceeded 10,000 employees (Table 10.1). In 2008, nearly 2.2 million professionals were employed in the software and ITES sector in India, with an average growth rate reaching to 23% between 2000 and 2008. Among those professionals, 80% are engaged in offshore business. According to NASSCOM (2009), India accounts for largest share, at 28%, of the suitable global offshore talent pool. The rapid growth in industry employment has been enhanced by the growing graduate pool. The number of annual graduates in India is estimated to have grown from 2.8 million in 2003 to 3.5 million in 2008. Among the 3.5 million graduates, 514,100 are technical graduates and post graduates who
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Table 10.1 Top three Indian and Chinese software and ITES export companies Revenues
Headcount
Tata Consultancy Services
$6. 0bil.
143,000
Infosys Technologies
$4. 7bil.
105,453
Wipro Technologies
$4. 9bil.
97,000
Neusoft
$0. 5bil.
16,000
Dalian Hi-Think Computer Technology
–
5,000
HiSoft
–
5,000
Notes: (1) Revenues of Indian firms are for the fiscal year ending 31 March, 2009. (2) Revenues of Neusoft are for 2008. (3) The Chinese companies: the top three in terms of exports in 2008. Source: Prepared by the author based on the latest information available from the companies’ websites as of January 2010, or from CSIA (2009) for Dalian Hi-Think Computer Technology and HiSoft.
were awarded engineering diplomas and degrees and master’s degrees in computer science and engineering. The human capital in India is remarkable not only for its quantity but also for its quality. India is highly ranked among 133 countries by the Global Competitiveness Index on indicators such as “availability of scientists and engineers,” “quality of math and education” and “quality of management schools” (World Economic Forum 2009). Last but not least, India enjoys an advantage in English, the main language used in the development of software. The majority of tertiary education is conducted in English. India has a large supply of English-speaking information technology engineers. In China, 1,800,000 professionals were employed in the software and ITES sector at the end of 2008, an increase of 21.6% over the previous year. Among those professionals, 29.4% were engaged in offshore business (CSIA 2009). Tertiary education plays a very important role in innovation. China has made dynamic advances in tertiary education since 1999. Tertiary enrollment increased from 1 million in 1998 to 6.1 million in 2009, an increase of more than 20% per year. The tertiary enrollment rate in China reached 23%, compared to only 12% in India. China has one of the largest pools of highly educated workers, amounting to 70 million persons who have completed their tertiary education. The government places special emphasis on software- and ITES-related education. Among the 2,334 tertiary institutions in the country, nearly 80% have set up software- and ITES-related courses, such as computer science and software engineering. In 2008, more than 861,000 students graduated
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with a software major or software-related major. The Ministry of Education and the National Development and Reform Commission certified 37 tertiary institutions as “National Model Software Colleges” to strengthen practical technical and language skill training programs. China lags behind India in English language skills but has an advantage in its linguistic and geographic proximity with Japan. According to a survey report by the Japan Foundation (2009), 684,366 people were studying Japanese in 2006, an increase of 76% from the previous survey in 2003. China has the largest number of Japanese-Language Proficiency Test (JLPT) examinees of, at 207,964 examinees, among 53 countries and districts. The number of examinees in China at the highest level, JLPT level one, was 71,519, which constituted 61% of total examinees worldwide, excluding examinees in Japan. As the second largest economy with a shortage of engineers, one would expect Japan to be a large market for offshoring. Indian software and ITES companies have been targeting the Japanese market but have only acquired 13% of the market – due to high barriers for entry in terms of language and cultural compatibility, while China has acquired more than 50% of Japanese offshore market (NASSCOM- PricewaterhouseCoopers 2008). China leverages its linguistic and cultural affiliation with Japan and is consolidating its position as the destination of choice for Japanese companies for software and ITES offshoring.
10.2 Government policies and history of the sector development in China Industrial policy in China was focused on the manufacturing sectors in the 1980s and 1990s. This strong government initiative supported the dynamic growth of China as a production base. China is far ahead of India in manufacturing sector thanks to well-established hard infrastructure such as highways, ports, and electric power plants that are necessary for the development of the sector. The Chinese government recognizes the importance of strengthening its own capacity for innovation and places much importance on the development of the IT sector. In the beginning, its main focus was on hardware production; however, its focus is shifting towards software and ITES. In 2000, the State Council issued “Policies for Encouraging the Development of the Software Industry and the Integrated Circuit Industry” (No. 18, 2000, State Council, hereafter “No. 18 Document”). These policies have been formulated to encourage the development of the Chinese software industry and integrated circuit industry, strengthen creativity and international competitiveness in the information industry, spur the reformation of traditional industries and the upgrading and replacement of products and further promote the sustained, rapid and healthy development of the
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national economy. The supporting policy measures for the development of the software industry include preferential tax treatment and refunds for software businesses, favorable interest rates and a depreciation policy for software exports, easier procedures for businesspeople for foreign business trips and foreign exchange management, and financial support for certification fees for global standards such as GB/T19000-ISO9000 quality management and guarantee series of standards and CMM (Capacity Maturity Model). The “No.18 Document,” which establishes many favorable policies, is an important milestone in the history of China’s software industry. In 2002, the State Council promulgated “Outline of Action for Vitalizing the Software Industry 2002–2005” (No. 47, 2002, State Council). The following development goals to be achieved in the software industry by 2005 were set in the Action Outline: ● ●
● ● ●
● ●
Market revenue of RMB250 billion. Over 60% of the market share in locally developed software and services in the domestic market. Export revenue of US$5 billion. Development of globally competitive software products. Development of leading software companies with annual revenue above RMB5 billion. More than 800,000 sector employees. Development of indigenous innovative software products and systems.
Funds amounting to more than RMB3 billion were prepared to achieve the above goals. The Action Outline also prescribed that a certified software enterprise could immediately receive a tax refund for 3% of the valueadded tax (VAT) – exceeding the actual tax after VAT has been levied at 17% according to the legal tax rate for the sales of self-developed software products. The certified newly-established software production enterprises are exempt from enterprise income tax for their first two profit-making years, and the enterprise income tax will be levied at 50% from the third year to the fifth year. The 11th Five-Year Plan (2006–2010) positions the service sector, specifically software and ITES, as new growth poles which complement the well-developed manufacturing sector and which will strengthen the overall Chinese economy. In accordance with the general direction and guidelines for the development of the service industry as determined in the 11th Five-Year Plan, the State Council set forth its “Opinions on Accelerating the Development of the Service Industry” (No. 7, 2007, State Council). Preferential policies in finance and taxation are applied to companies engaged in the development of software, the outsourcing of information technology, and technical business processes.
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Moreover, China’s Ministry of Commerce has announced a plan called “The Thousand-Hundred-10 Project.” The goals of this project are to establish 10 cities as service-outsourcing bases, attract 100 multinational companies to offshore their services to China, and develop 1,000 local medium- and large-scale service-outsourcing companies. The measures include tax incentives, financial support for education of the workforce, quality management, and better protection of intellectual property. To boost service outsourcing, the General Office of the State Council approved Beijing, Tianjin, Shanghai, Chongqing, Dalian, Shenzhen, Guangzhou, Wuhan, Harbin, Chengdu, Nanjing, Xi’an, Jinan, Hangzhou, Hefei, Nanchang, Changsha, Daqing, Suzhou, and Wuxi as pilot service-outsourcing cities in 2009. Service companies in these 20 pilot cities are eligible for favorable polices – such as an enterprise income tax rate of 15% rather than the 25% applied elsewhere in the country, for the five years through 2013. Also, companies are eligible to receive a subsidy of up to RMB4,500 per year for every college graduate employed on a contract of at least one year.
10.3 The sector development process and the role of local government in Dalian 10.3.1
Dalian’s challenge to catch-up with Bangalore
In IDC’s Global Delivery Index – Asia/Pacific (GDI-AP) 2007 – which objectively compares and contrasts 35 cities in 18 countries in the Asia Pacific region, with the potential to be global delivery destinations – Dalian was ranked fifth overall and first among Chinese cities, outranking first-tier cities like Beijing and Shanghai (IDC 2008. See also Table 11.1 of Chapter 11). To achieve the role proposed by Premier Wen Jiabao, Dalian is making every effort to construct a global software and ITES offshoring base and to become China’s and the world’s number one city in software and ITES offshoring. Dalian – until the 1990s – had has a far weaker technological base – in absolute terms – compared to Bangalore, and also had been less significant compared to other Chinese major industrial or academic cities. To the contrary, Dalian had never played such a central role in China’s scientific or engineering development. Though the city had attracted massive amounts of Japanese manufacturing firms in electronics, they were mostly final assembly processing factories rather than the engineering bases. One of a few unique business advantages that the city had enjoyed was the historical and cultural ties with Japanese business society as the historical gateway to the Japanese colonial hinterland, Manchuria. Thus, it was not surprising that, at the end of 1990s, the Dalian government began to promote software business by leveraging Japanese outsourcing demand earlier than any other cities in China. In 2008, Dalian achieved sales revenue in the software and ITES sector of RMB30.6 billion, an increase of 42% from the previous year, with exports of US$1.1 billion, up 46%. Dalian has established a unique position within the
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software and ITES sector in China. Although the main segment in China’s software and ITES sector has been software products for the domestic market, the main segment in Dalian is software and technology services, mainly for Japan. Nearly 80% of the export revenue is from the Japanese market (DLBII and DLSIA 2009). Nearly 800 companies and 75,000 people are working in the sector. China’s top three software exporters, Neusoft Corporation, Dalian Hi-Think Computer Technology Corp. (DHC) and HiSoft Technology International, Ltd., have their operations in Dalian. Major multinational companies such as Genpact, Dell, HP, IBM, Panasonic, and Alpine have set up large-scale operations in Dalian. The successful operation of Fortune 500 companies here leads other multinational companies to acknowledge Dalian’s attractive offshore environment. The development of the software and ITES sectors in Dalian owes a great deal to consistent support from the local government. In the following, we will explore the details of the local government’s active roles and measures for the creation and promotion of the sector in Dalian. 10.3.2
Initiatives of local government in China: Dalian
With the sector having started far later in China than India, and having been far weaker industrial backgrounds embedded in Dalian, the local government of Dalian City took greater initiatives to drive the development. In fact, the strength of Dalian has been not only the government itself, but rather the interrelationships between government and related supportive parties – especially with private parties. Compared to Bangalore, strong initiatives by the local government and its highly-complement and coordinated tie-up with “government-assisted private management” and industry associations, are the major drivers that made Dalian the forerunner in China’s software and ITES offshoring sector in a rapid pace that other major clusters in China have not achieved. Dalian was the first city in China to establish a Bureau of the Information Industry, in 1998. This was even prior to the creation of the national-level administrative agency, Ministry of Information Industry, in 2000. According to our interview with officials at the Bureau in August 2009, the role of the Bureau is 1) planning industrial policy, 2) developing human resource for industry, 3) improving and raising the city’s image, and 4) promoting MNCs’ investment. 10.3.2.1
Planning the sector policy
The Dalian government started to promote the software and ITES sector in 1998, under the then Mayor Bo Xilai, later Minister of Commerce. The global offshoring market was growing, and globalization of Japan’s software development outsourcing was considered likely to occur at that time. The decision to promote the sector was made with the idea that Dalian could leverage its geographical proximity as well as its historical and cultural
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proximity to Japan so as to become a major offshore destination for Japan. In order to develop its software and ITES sector in a centralized way, the Dalian government established the Dalian Software Park in the Dalian High-Tech Zone in 1998, in the three-kilometer area. In 2003, the Dalian government announced the Lushun South Road Software Industry Belt project. The project, planned by the city government, is to expand the software and ITES cluster along Lushun South Road. Some universities are being relocated to the Lushun District to establish closer interaction with the sector. Also, the Ascendas Group from Singapore, the Shui On Group from Hong Kong, and the Neusoft Group have been invited to build their own software park. The Dalian government has initiated a strategic plan to become a global leader in the software and ITES sector. The designated goals for 2013 are achievement of the top position in China in terms of industrial aggregate maturity, higher export volume and greater competitiveness, RMB100 billion in sector revenue and US$4 billion in sector exports, and employment of 200,000 persons. The goals for 2020 are RMB300 billion in revenue, US$10 billion in export revenue, and employment of 400,000 persons. 10.3.2.2
Developing human resources for the sector
The Dalian government regards human resources as the foundation for the development of the software and ITES sector. Out of 21 universities in Dalian, 18 universities have computer and computer-related majors and 5 universities have software colleges. The government has been promoting multilevel education and training at universities, colleges, and vocational schools to enlarge the scale of software-related training. At the same time, the government regularly holds recruitment fairs in other cities, including some abroad, to match managerial personnel with jobs. The government issued “Rules for Attracting Senior Software Personnel” and secured special funds for attracting talented persons. City-level incentives include a refund of personal income tax and a subsidy for a onetime housing allowance for high-income personnel and a subsidy for enrollment in training courses. 10.3.2.3
Improving the city’s image
More cities are marketing themselves as offshore destinations. A city’s strategy in branding itself as a software and ITES offshore destination is the key to that city becoming a global leader in the software and ITES sector. Dalian has been hosting the China International Software and Information Service Fair (CISIS), the only national-level software and outsourcing exhibition approved by the State Council of the People’s Republic of China. VIPs from overseas government departments, CEOs of Global 500, well-known consultants and overseas IT associations take part in the fair each year. Dalian makes full use of this platform to raise the city’s brand image as a software and ITES offshore destination. The Dalian government held CISIS
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sub-fairs in Ireland, Japan and Australia to raise foreign countries’ interest in CISIS. Moreover, the Dalian government held seminars abroad to introduce the software and ITES sector and the business environment in Dalian. Dalian is taking the lead over other cities in China by marketing itself as an offshore destination and branding the city as a location for the software and ITES sector. The government has broadcast a television commercial campaign on the English channel of CCTV to promote the software and ITES sector of Dalian. 10.3.2.4
Promoting MNCs investment
The successful operation of globally-known MNCs in the city has induced more companies to set up offshore operation centers in Dalian. Seeing the success of Genpact in Dalian, other MNCs such as IBM, Accenture, HP, SAP and Cisco, to name a few, are following. Daily investment promotion activities are conducted by each property management company. However, local government is also taking part in investment promotion activities. Every year, the mayor and vice mayor visit the headquarters of MNCs as a part of their investment promotion activities. These promotional activities by top members of the government sometimes clinch the deal with companies considering investment in Dalian. As a part of their investment promotion, local government is very keen to improve the working and living environment of people in the sector. The mayor of Dalian invited a Singapore property management company, Ascendas, which was involved in the success of the landmark International Tech Park Bangalore (ITPB) in India, to create an international-level work and service environment. A Hong Kong real-estate management group – Shui On Group – also decided to come to Dalian after being approached by the Mayor of Dalian. The government is responsive to the needs of the sector. The development of Dalian’s software and ITES sector was so rapid that the traffic congestion became heavy during the commuting hour around the Dalian Software Park, and the government, acknowledging the problem, extended the bus route and widened the road. To better understand the needs of the sector, local government officials occasionally meet with executives of the software and ITES firms to exchange ideas on the business environment. 10.3.3
“Government assistance and private management”
Development of Dalian’s software and ITES sector has been based on a unique public-private sector cooperation model. In other Chinese cities, software parks are managed by enterprises controlled by local governments. In Dalian, however, Dalian Software Park is managed by a privately owned company – Dalian Software Park Co., Ltd. (DLSP) – a subsidiary of a local real estate development company, the Yida Group. Local government provides
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strong support, whilst the Yida Group provides development capital and management experience. The combination of the two natured competitive advantages of the park and DLSP is earning nationwide acclaim. The distinct efficiency of the privately run Dalian Software Park is apparent in its willingness and flexibility when serving customer needs. DLSP provides not only office space but also solutions to customer needs. For example, regarding office space, DLSP prepared a Built-to-Suit Building for Genpact and IBM. As a part of its corporate service, DLSP arranges periodical gatherings for IT managers and HR managers working in the park to exchange ideas and share experience. For human resource problems, DLSP conducts recruitment and employment training on behalf of its tenants. The Dalian government plans to continue leveraging private companies’ capabilities in sector development. In line with local government plan to become the top city globally as a software and ITES offshore destination, national and international enterprises such as Neusoft, Ascendas, and Shui On are developing their own software parks along the Lushun South Road Software Industry Belt. 10.3.4 Industry associations as a bridge between government and business The Dalian Software Industry Association (DSIA) has played a vital role in Dalian’s software and ITES sector. DSIA works as a bridge between the government and firms. DSIA has maintained a close relationship with the Japan Information Technology Services Industry Association (JISA) and municipal-level software-related industry associations across Japan. DSIA is very quick to respond to the problems of the sector, utilizing its frequent interaction with Japanese organizations. Market development, upgrading of human resources, quality management, and information security management are four key areas in which DSIA has been working during the past few years. Notable achievements of DSIA include implementation of the Privacy Information Protection Assessment (PIPA) certification and launching of the mutual recognition program of PIPA and the Privacy Mark of Japan Information Processing Development Corporation (JIPDEC). The Personal Information Protection Act implemented in Japan – starting in April 2005 – requires businesses to take reasonable steps to protect personal information from unauthorized disclosure, use or destruction. Due to fear of improper handling of personal information, work offshored from Japan to Dalian declined after the act was implemented in Japan. China had no certificate system for managing privacy information at that time, and so DSIA took the initiative to launch a certificate system similar to Japan’s Privacy Mark. PIPA initially started as Dalian city’s certification program, but now the central government is considering adopting PIPA as a national certification program.
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10.4
Concluding remarks
Software and ITES offshoring in China is small and immature compared to that of India. The sector is still in the early stage of development in China, and it would be premature to compete head-to-head with India. Nevertheless, in the long run, China may transform into a global leader comparable to India in the software and ITES sector. China has many strengths and advantages that promote growth – such as staunch government support, robust infrastructure, a sizeable talent pool, a solid platform for cultivating the Asian market and an untapped domestic market. As the case of Dalian has demonstrated above, local government in China may fill a critical role in sector development by taking strong initiatives. By leveraging their own strengths, cities in China may follow different trajectories from those in India and become unique global outsourcing destinations.
References CSIA – China Software Industry Association, 2009, Zhongguo Ruanjian Chanye Nianjian 2009 [Annual Report of China Software Industry 2009], Beijing: CSIA (Chinese). DLBII and DLSIA – Dalian Bureau of the Information Industry and Dalian Software Industry Association, 2009, 2008 Dalianshi Ruanjian Yu Xinxi Fuwuye Fazhan Baogao [2008 Annual Report of Dalian Software & Information Service Industry], Dalian: DLBII and DLSIA (Chinese). IDC, 2008, Global Delivery Index Asia/Pacific Report, Singapore: IDC. Japan Foundation, 2009, Summary of Results for the 2008 JLPT, Tokyo: Japan Foundation. NASSCOM – National Software and Software Service Companies, 2009, Strategic Review 2009: Annual Review of the Indian IT-BPO Sector, New Delhi: NASSCOM. NASSCOM-Pricewaterhouse Coopers, 2008, Emerging Market Series – Opportunities for Indian IT Industry: Japan. New Delhi: NASSCOM. World Economic Forum, 2009, Global Competitiveness Report 2009–2010, Geneva: World Economic Forum.
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11 The Role of Standards in Technology-Driven Commodity Chains: The Information and Communication Technology Services Industry in Dalian, China, and Bangalore, India Balaji Parthasarathy and Bharath M. Palavalli
11.1
Introduction
In July 2007, IDC (International Data Corporation), a consulting firm, developed a Global Delivery Index (GDI) to compare 35 cities in 18 countries in the Asia Pacific region as potential offshore delivery centers for information and communication technology (ICT) services. The comparison was based on 30 criteria – including cost of labor, cost of rent, language skills and turnover rate (Table 11.1). The Indian cities Bangalore, New Delhi and Mumbai were ranked first, third, and fourth while the Chinese cities Dalian, Beijing and Shanghai, were ranked fifth, sixth and seventh. IDC predicted that, by 2011, Chinese cities like Dalian would outstrip their Indian counterparts to become the most preferred global delivery locations in the world. But, the industry in Dalian does not seem to be living up to the prediction of outstripping its competitors. By 2008, Dalian slipped to ninth position in 2008 IDC’s GDI. Even as Dalian slipped, Bangalore was secure at the top, with New Delhi in second position. Among Chinese cities, it was Beijing which moved from the seventh position to the fourth position, while Shanghai retained its sixth position. Although the criteria used for the two years were not identical – and one year is too soon to come to definitive conclusions about a regional economy – regions that maintain or improve their position despite changing criteria, can claim to have a dynamic comparative advantage, whereas the same cannot be said about regions that slip in the rankings. 237
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Table 11.1 IDC’s global delivery index – Asia Pacific, 2007–2008 Position 1 2 3 4 5 6 7 8 9 10
2007 Bangalore Manila New Delhi Mumbai Dalian Shanghai Beijing Sydney Brisbane Auckland
2008 Bangalore New Delhi Manila Beijing Auckland Shanghai Mumbai Brisbane Dalian Kuala Lumpur
Note: 2008 rankings are based on different parameters. Source: http://www.businessweek.com/blogs/asiatech/archives/2007/07/ idc_says_china.html.
The relative positions of Indian and Chinese cities in the IDC list, leads us to ask: how do late industrializers in the early 21st century – such as China and India – enter the international division of labor and maintain their comparative advantage amidst changing technologies, shifting demand conditions, and new competitors? Of particular interest in connection with the ICT services industry, is the ability of late industrializers in the early 21st century to enter and move within technology-driven commodity chains (TDCCs) which are “production networks where control over technological design, standards and trajectories is the central element of business power” (O’Riain 2004, p. 643). This paper will compare the trajectories of the ICT services industry in Dalian and Bangalore to argue that being part of a production network with open standards is crucial to mobility within TDCCs. The paper will attribute Dalian’s position to the closed standards which it is forced to adopt to serve its major market in Japan. India’s advantage in ICT services provision thus far has come from its commitment to open-process standards and embracing internationally accepted technology standards. On the other hand, despite the size of China’s domestic market, a combination of technonationalism and techno-regionalism have led to the creation of proprietary technological standards that either isolate the domestic market from the international market or fragment it. The following section raises a couple of empirical questions by examining the data on Dalian’s rise as a ICT services producing region. Section 11.3 describes the regulatory and institutional changes which facilitated the rise of an ICT service industry in Dalian. Section 11.4 shows how the
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characteristics of the Japanese market, and its outsourcing and offshoring practices, have shaped firm behavior in Dalian. Section 11.5 explains the rise and dominance of Bangalore as an outcome of public policy initiatives and a reliance on open standards. Section 11.6 contrasts the experience of Dalian with those of Bangalore, Beijing and Shanghai. The essay concludes with three lessons from this comparative analysis.
11.2 The emergence of the ICT service industry in Dalian The revenues of the ICT service industry in Dalian reached 30,600 million RMB in 2008, making it the eighth largest location for the production of such services in China (Table 11.2). Although Dalian moved from being the tenth-largest location to just the eight-largest location between 2002 and 2008, Table 11.3 indicates that the local and national significance of Dalian’s ICT service industry go beyond what the absolute increase in revenues suggest. Thus, in the same period, the share of the local ICT service industry in China’s ICT service industry grew to 4.04% from 2.13% – from 1.65% in 2000 – while the contribution of the software industry to the local GDP grew from 1.67% to 6.87% – and from 0.22% in 1998. Not surprisingly, the location quotient shows that, by 2008, the ICT service industry was nearly thrice as important to the local economy as the Chinese economy. There is another aspect to the growth in revenue of the ICT service industry. By 2008, Dalian was the third largest ICT service export location from China in absolute terms (Table 11.4), while the city was only behind Shenzhen in the importance of exports to the local ICT service industry (Table 11.5). The growth of the ICT services industry in Dalian raises a couple of empirical questions. First, how did a software industry of significant importance to the local economy develop with an export focus, especially when most leading ICT services producing locations in China predominantly focus on the domestic market? The second question has to do with the historical specificity of China’s integration into the international division of labor in the ICT services industry. In contrast to India – which was the fifth largest exporter of ICT and ICT-enabled services in the world in 2007 – China was tenth (UNCTAD 2009, p. 77).1 Whereas most of India’s exports go to the US, it has had difficulty penetrating the Japanese market. According to India’s National Software and Software Services Companies (NASSCOM), although the Japanese IT outsourcing market is second only in size to the US, Japan accounts for less than 2% of India’s IT exports (NASSCOM 2008, p. 5). Further, India receives only 19% of the work outsourced by Japan, whereas China receives more than 60% (Ibid, p. 22) which, our research indicated, Dalian has benefited from. Public relations brochures in Dalian answer these questions by emphasizing the skilled labor pool provided by the 22 universities and colleges in
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1195
1005
Shenzhen
Shanghai
230
193
Xian
Tianjin
10
9
8
7
6
5
4
3
2
1
Rank
152
182
215
340
310
362
460
745
911
1174
2007
10
9
8
6
7
5
4
3
2
1
Rank
124
112
145
261
206
258
341
616
753
970
2006
9
10
8
5
7
6
4
3
2
1
Rank
108
83
103
236
135
166
242
455
560
780
2005
8
10
9
5
7
6
4
3
2
1
Rank
Source: Annual Report of Dalian Software and Information Service Industry, various years.
397
306
Dalian
Chengdu
Hangzhou
471
427
Nanjing
500
1573
Beijing
Guangzhou
2008
Location
78
62
72
183
100
109
182
302
433
520
2004
8
10
9
4
7
6
5
3
2
1
Rank
57
49
47
130
66
71
140
201
291
385
2003
8
9
10
5
7
6
4
3
2
1
Rank
Table 11.2 Leading ICT service producing locations in China, 2002–2008 (in 100 million RMB, by region and rank)
37
35
23
99
51
42
65
117
200
334
2002
8
9
10
4
6
7
5
3
2
1
Rank
Technology-Driven Commodity Chains and Standards
241
Table 11.3 National and local significance of Dalian’s ICT services industry (as a share of software revenues and GDP (in 100 million RMB) and by location quotient (LQ)) Dalian
Revenues
Significance of Dalian’s software industry
China
GDP Revenues (2)
(3)
GDP
to China, to local GDP, location quotient
(4)
(1)/(3) (%) (1)/(2) (%) (1/2)/(3/4)
Year
(1)
2008
306.0
–
7573
–
4.04
–
2007
215.0
3131
5800
24661
3.71
6.87
2006
145.0
2570
4800
21087
3.02
5.64
2.48
2005
102.7
2150
3900
18386
2.63
4.78
2.25
2004
71.9
1962
2424
15987
2.97
3.66
2.42
2003
46.7
1633
1633
13582
2.86
2.86
2.38
2002
23.4
1406
1100
12033
2.13
1.66
1.82
2001
15.3
1236
796
–
1.92
1.24
–
– 2.92
2000
9.8
1111
593
–
1.65
0.88
–
1999
5.5
1003
–
–
–
0.55
–
1998
2.0
926
–
–
–
0.22
–
Source: Annual Report of Dalian Software and Information Service Industry, various years.
Dalian – and 182 in the northeastern provinces of Liaoning, Heilongjiang and Jilin provinces.2 Further, this labor is located in close proximity to the Japanese market, and the legacy of Japanese colonization of the region has given it familiarity with the Japanese language. These explanations are akin to arguments about how the linguistic advantage conferred by British colonial rule helped the Indian software industry – with access to a large pool of highly skilled but relatively low-wage professionals – compete in English speaking markets. Similarly, the 12.5 hour difference between Indian Standard Time and Pacific Standard Time helped Indian firms undertake offshore maintenance and reengineering work for US customers after regular workers there had left for the day (Parthasarathy 2004). The linguistic and geographic factors which have serendipitously conferred advantage on the ICT services industry in both regions are what Krugman (1992) refers to as historical accidents. However, while such accidents can help regions enter global markets, the ability to remain entrenched in the international division of labor demands that any analytical explanation go from merely listing the sources of static comparative advantage to specifying the sources of dynamic comparative advantage.
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600.44 102.85 72.97 55.60 45.17 37.53 20.85 11.81
Shenzhen Shanghai Dalian Nanjing Hangzhou Beijing Chengdu Xian
1 2 3 4 5 6 7 8
Rank 286.74 95.07 55.29 29.66 29.21 35.75 12.17 5.02
2007 1 2 3 5 6 4 7 8
Rank 231.20 78.93 35.88 23.92 30.61 28.70 8.77 4.07
2006 1 2 3 6 4 5 7 8
Rank 147.42 55.69 25.39 17.20 21.29 24.57 2.54 3.28
2005 1 2 3 6 5 4 8 7
Rank 105.94 39.40 17.55 6.62 13.24 18.79 1.66 2.48
2004 1 2 4 6 5 3 8 7
Rank 48.84 21.93 9.35 – 9.44 11.42 0.25 1.66
2003
Source: Annual Report of Dalian Software and Information Service Industry, various years.
Note: Original figures given in 100 million US dollars converted to RMB using conversion rates from http://fx.sauder.ubc.ca/
2008
Location
1 2 5 – 4 3 7 6
Rank
Table 11.4 Leading ICT services exporting locations in China, 2002–2008 (in 100 million RMB, by region and rank)
33.11 14.48 4.14 1.41 8.11 18.21 – 1.41
2002
1 3 5 6 4 2 – 6
Rank
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50.25% 10.23% 23.85% 11.80% 11.38% 2.39% 4.88 5.14
Shenzhen Shanghai Dalian Nanjing Hangzhou Beijing Chengdu Xian
1 5 2 3 4 8 7 6
Rank
31.48 12.76 25.72 8.19 8.59 3.04 3.93 2.76
1 3 2 5 4 7 6 8
30.70 12.81 24.74 9.27 11.73 2.96 4.26 3.63
1 3 2 5 4 8 6 7
26.33 12.24 24.65 10.36 9.02 3.15 1.88 3.95
1 3 2 4 5 7 8 6
24.47 13.05 24.37 6.07 7.24 3.61 1.66 4.00
1 3 2 5 4 7 8 6
2 3 1 4 6 7 5
16.78 10.91 19.90 7.26 2.97 0.38 3.38
2 3 1 7 4 5 6
16.55 12.38 17.99 3.35 8.19 5.45 4.02
2007 (%) Rank 2006 (%) Rank 2005 (%) Rank 2004 (%) Rank 2003 (%) Rank 2002 (%) Rank
Source: Derived from Tables 11.2 and 11.4.
2008
Share of exports in leading ICT service producing locations in China, 2002–2008 (as a percentage of revenues, by region
Location
Table 11.5 and rank)
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Balaji Parthasarathy and Bharath M. Palavalli
11.3 The context for Dalian’s emergence as an ICT service-producing region Taking advantage of the Japanese colonial legacy in Dalian, or the region’s human capital, to nurture the ICT service industry had to wait until the 1980s. This is because the region had to wait for the globalization of the industry, and for policy changes that were required after China began to reform its autarkic centrally-planned economy in 1978 – by decentralizing decision making, offering market incentives, encouraging exports and opening up to foreign investment.3 Economic reform in China made “explicit use of geography in its implementation,” in part “to make the policy more effective through external visibility and agglomeration economies” (Dicken 2007, p. 226). Thus, in 1979, the Fifth National People’s Congress backed the establishment of four Special Economic Zones (SEZs) in Shenzhen, Zhuhai, and Shantou, in Guangdong province, and in Xiamen in Fujian province to replicate the economic success of export processing zones elsewhere in newly-industrializing Asia. These SEZs were far from China’s major urban and industrial areas but close to foreign markets and overseas Chinese investors in Hong Kong, Macau and Taiwan. SEZs were open to wholly foreign-owned firms, state enterprises, equity joint ventures between foreign and local firms, or contractual ventures – where the foreign partner supplies technology and capital input with a predetermined share of return negotiated in advance. Firms were entitled to duty-free import of inputs needed for export production. Firms willing to commit investment for ten years were eligible for a tax holiday for the first profit making year, and a 50% reduction in the tax rate in the second and third years. In December 1984, the tax holiday was extended to two years while the reduced tax was applicable from the third to the fifth year. After the tax holiday, investors faced a tax rate of 15% – about half of what they would pay outside the zones. Additional tax incentives, often negotiated on a case-by-case basis, are available to firms bringing in advanced technology, to those exporting at least 70% of their output, or those involved in developing infrastructure. The experience with SEZs, led to 14 more coastal cities, including Dalian, being opened to foreign investment. Within the cities, designated Economic and Technology Development Zones (ETDZ) were established between 1984 and 1988 with the same incentives as SEZs. Outside the ETDZ in these cities, the incentives were less liberal. For instance, unless firms made technology intensive investments of US$30 million or more, they attracted a tax rate of 24% instead of 15%. Subsequently, in 1988, Dalian was also included in the Torch program, in an attempt to create what Yeung and Lo (1996) label as the Pan-Japan Sea Economic Zone. The Torch program was launched in May 1988 as part of an effort to create a decentralized science and technology system. Specifically, it was meant
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to promote innovation, by encouraging individuals to leave public-sector research institutions and establish their own nongovernmental (minying) enterprises, and to encourage greater research and development and commercialization in state owned enterprises (SOEs) (Segal 2003). Based on study trips by the Chinese Academy of Sciences, to understand the institutional foundations of innovation and entrepreneurship in Silicon Valley, the program was tied to the development of science parks and High-Technology Development Zones (HDTZs) colocated with universities. The 1992 State Basic Policy on High-Tech Industrial Zones offered tax incentives that were similar to those offered at the SEZs. In addition, firms were given preferential access to foreign exchange and allowed to establish branches overseas. The pricing of new products that were developed were freed from state control. The Torch program had limited central funding, with the administering institution, the Torch High-Technology Industry Development Center – under the Industrial Science and Technology Department of the State Science and Technology Commission – raising and channeling funds from financial institutions rather than being a funding agency. Risk funds and venture capital were also permitted within these zones. By 1993, there were 52 nationally designated HDTZs and – by 1997 – 12,606 projects were approved in five sectors, of which microelectronics and information technology accounted for 23.4% (Ibid. p. 32).4 It was within the Dalian HTDZ that the Dalian Software Park (DLSP) was established in 1998 as a wholly owned subsidiary of the Yida Group, a private real estate developer in Northeast China. DLSP is an initiative “supported by the Government, invested and run by a private company” to help promote the ICT services industry in Dalian.5 The blurred distinction between state and private enterprise that DLSP represents, typifies the importance of longterm social connections and personal ties – or guanxi – for doing business in China (Hsing 1998). While the state controls resources such as land, and undertakes administrative functions such as allocating finances, there is a symbiotic relationship as local officials also rely on businesses in the intense economic competition between provinces and local governments unleashed by decentralization policies (Fairbank and Goldman 2006). Just as new businesses cultivate relationships with powerful state actors (Wank 2001), the incentive for local officials to help local firms outperform firms from neighboring provinces holds true in software as much as in other industries (Saxenian and Quan 2005). Thus, authorities in Dalian have used state policies after economic reform to build on the competitive advantage of the region (Way 2008). One interviewee said that, “. . . the attitude of the Dalian city government has been different from other regions in China. They are happy to take the back seat and let us proceed. They provide a framework and give us the freedom to implement within the guideline.”6 The performance of the local government resulted in the appointment of the then mayor of Dalian, Bo Xilai, as Minister of Commerce between 2004 and 2007.
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DLSP uses various means to attract multinational corporations (MNCs) and local firms to Dalian. It uses the preferential policies for HTDZs and assists firms in their dealings with the local government.7 In addition, DSLP offers build-to-suit options wherein firms can specify their requirements for employees, space and infrastructure. DLSP then provides these on a contract basis until the firms are confident of establishing permanent operations on their own.8 DLSP also helps firms recruit employees through its partnerships with local universities and colleges, while its Human Resource Development Center (DLSP-HRDC) is a training and certified test center that offers both tailored and standard certification courses for employees and students seeking employment.9 With DLSP providing the physical infrastructure, and the skills training to supplement the graduates from the local universities, Dalian began to cultivate markets. In April 2000, Bo Xilain led a delegation of 13 government members and 95 business representatives to the US and Canada for a number of events.10 Dalian also hosted the first China International Software and Information Service Fair (CISIS) in 2002.11 About 100 Chinese software firms, and a handful of their Japanese counterparts, took part in this business matching exercise. The success of the fair prompted the mayor of Dalian to lead a team of companies to Japan. Since then, the fair has become an annual event and smaller versions are also held in different regions of Japan.12 Other attempts to cultivate the Japanese market include the invitation extended by the Dalian municipal government to the Japan International Cooperation Agency to establish the China-Japan Friendship Center for Human Resource Development.13 The focus of the institute – which was established in March 2006 – is to enhance the software development capabilities of Chinese workers and their understanding of the Japanese language, corporate culture and business etiquette. The attention paid to the Japanese market was not without history. In 1989, the Dalian municipal government used IBM mainframes to establish the Dalian City Computer Center (DCCC) and the Computer Application Office. The former was responsible for the digitization of records within the Dalian municipality. The latter was responsible for data processing work in Dalian and it also began to take on outsourced projects from Japan for companies such as NTT.14 However, as Tables 11.2 and 11.4 show, it was not until the initiatives from the late 1990s that an export oriented industry in the private sector began to grow. To meet the demands of a growing industry, DLSP initiated a 12 square-kilometer Phase II – whereas Phase I was about 7 square kilometers – with three new parks, including the Neusoft Institute of Technology – part of Neusoft, a software firm with a Japanese lineage, Dalian Ascendas and Dalian Tiandi. Dalian Ascendas is a joint venture between the Yida Group and Singaporebased Ascendas, with each party having an equal stake.15 Ascendas provides project management skills and marketing expertise whereas the Yida Group
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brings the experience of the first phase of DLSP. Dalian Tiandi is a joint venture between Shui On Land – a Hong Kong firm – and the Yida Group, with the latter having a 30% stake.16 Dalian Tiandi is being developed on agricultural land that has been appropriated by the government. Land acquisition was simpler due to the Yida Group’s experience with the local authorities. As an interviewee stated, “The role of a local Chinese company in most real estate partnerships is one of a sleeping partner. They are essential when it comes to dealing with the Chinese authorities for various negotiations. Acquiring land in China has never been an issue and a local real estate developer can ensure things move faster.” 17 The growth was also reflected in the changing composition and role of the Dalian Software Industry Association (DSIA).18 DSIA was established in 1992 with 50 members. Although 30 were private firms, DSIA served as a conduit for government policies. In recent years, however, it has become more of a voice for the new industry and a bridge with the government. Besides being a member of the Chinese Software Industry Association, DSIA also has strong links with the Japan Information Technology Services Industry Association and with similar foreign organizations.
11.4 The ICT services industry in Dalian and the Japanese market Although firms in Dalian can be categorized broadly as subsidiaries of Japanese MNCs, other – non-Japanese – MNCs, and Chinese firms, Japan looms large over Dalian. For instance, even the presence of non-Japanese MNCs typically takes the form of a “global support center,” partly dedicated for the Japanese market. While the first such center was established by GE – later Genpact – it was followed by others, including Dell, SAP and Cisco.19 The Japanese market also provides the business rationale for the subsidiaries of the Japanese MNCs and most Chinese firms in Dalian. Since it is this market which dictates the technological practices and, ultimately, the skill levels of these firms, understanding the offshoring and outsourcing practices of Japanese firms is essential.20 Japanese outsourcing and offshoring must be understood against the backdrop of an aging population and the productivity challenges that plague software development to make it a labor-intensive process (Parthasarathy 2004). Table 11.6 shows the labor-intensive nature of software production and the challenges of improving productivity. Even as the number of firms in Dalian grew fourfold between 2000 and 2008, and the average number of employees per firm grew from 35 to 100 (2.85 times), revenues per employee grew from 14,000 RMB to 38,300 RMB (2.7 times). This is starker when one compares the period between 2003 and 2008 – when the number of firms more than doubled from 358 to 800 (2.23 times), but the revenue per employee went up only from 30,300 RMB to 38,300 RMB (1.26 times).
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Table 11.6 ICT service firms in Dalian and their characteristics, 2000–2008 (number, average number of employees/firm, average revenue/employee in 10,000 RMB) Year
2008 2007 2006 2005 2004 2003 2002 2001 2000
Number of firms
800
700
600
520
450
358
270
220
200
Certified ‘software companies’
375
327
292
235
185
124
88
36
–
Average number of employees/firm
100
83
77
59
50
43
45
45
35
Average revenue/ employee
38.3
37.0
31.5
33.1
31.9
30.3
19.5
15.3
14.0
Source: Annual Report of Dalian Software and Information Service Industry, various years.
Similarly, between 2004 and 2008, the number of employees per firm doubled, the revenue per employee barely grew by 20%. Next, Japanese industry is characterized by high quality developed with proprietary technology and processes (NASSCOM 2008). This characteristic is also evident in the software industry (Cusumano 1991) and influences outsourcing in a couple of ways. First, it leads to a “... . Japanese focus on maintaining the proprietary knowledge base within the confines of the company. Japanese managers try and protect their risk of IP [intellectual property] theft by breaking large projects into small modules. The small project modules are outsourced to different vendors ensuring that only the client can piece them back together. Furthermore, in order to protect the IP, the Japanese ensure that the critical project design and solution architecture is kept inhouse as vendor involvement is low in these stages” (NASSCOM 2008, p. 30). According to a survey of 262 firms by the Japanese Information Technology Promotion Agency (2008), the main attributes that Japanese firms consider when deciding on offshore vendors is the latter’s ability to communicate in Japanese, followed by the quality and number of engineers. Chinese and Indian firms also find themselves at the bottom of the multi-tier subcontracting structures of Japanese keiretsu – far from the system design and integration – and with limited understanding of the final product or the standards to which it is built (NASSCOM 2008, p. 31). Even the subsidiaries of Japanese firms in Dalian are typically established to test products developed in-house in Japan, or to work on maintenance and low level systems integration for their holding companies.21 Finally, when it comes to the technical basis for vendor selection, concerns about information security are paramount (NASSCOM, op.cit.). Further, with their proprietary process standards, Japanese customers give little importance to the development process capabilities and quality procedures certified by the Software Engineering Institute’s five-level Capability Maturity
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Model (SEI-CMM), or the ISO-9000/9001–3 standards established by the International Standards Organizations (ISO), which are widely accepted in North America and in Europe.22 As an interviewee in Dalian stated, “... the nature of work undertaken for Japanese clients has to conform to their standards, and standards such as ISO and CMMi are not accepted in the Japanese market.”23 Japanese concern with information security, especially the protection of the personal information of consumers on computers and computer networks, was evident in the passage of the Protection of Personal Information Act (Act No. 57 of 2003) on May 30, 2003, and its enforcement from April 1, 2005.24 All firms handling personal information were covered by the Act and they had to establish a private information protection management system complying with Japanese Industrial Standards JIS Q 15001:2006. The certification of compliance is provided by the PrivacyMark, which is administered by the Japan Information Processing Developing Corporation (JIPDEC).25 The PrivacyMark provides visible assurance to consumers about the protection of their personal information, and social credibility to businesses sporting the mark. Since the PrivacyMark is available only for private enterprises based in Japan, DSIA developed the PIPA (Privacy Information Protection Assessment) standards based on the Japanese standard to ensure that local firms could comply with requirements in their largest market. 26 PIPA has three different standards: information security standards, information management regulations, which are used for information service management by the services industry, – and the HR Skills standard. Interactions with Japanese clients, and the presence of Japanese firms in Dalian, gave DSIA the experience to establish the standard. As Japanese firms have accepted PIPA certification, 40 firms in Dalian obtained it by August 2009. Other Chinese cities have also approached DSIA seeking the authority to grant PIPA certification.
11.5 The role of standards in the rise and dominance of Bangalore Until 1984, the ICT services and software industry in India was virtually nonexistent, due to an autarkic, SOE-dominated, import substitution led industrialization (ISI) policy regime that discouraged entrepreneurship and foreign investment and proved inimical to innovation (Sridharan 1996). Cautious efforts to liberalize these policies from the mid-1980s led to the emergence of an export-driven ICT services industry.27 What helped drive the industry was an unforeseen consequence of the ISI period. Unsuccessful domestic efforts to build a commercially viable computer system – and high duties, which were a disincentive to import – meant that mainframe computers based on proprietary standards never had a significant presence in India (Harding 1989). The few that were imported were of various vintages
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and sources. The experience gained by working on a variety of platforms in the 1970s, helped the Indians win labor-intensive contracts to maintain older systems in the 1980s and 1990s.28 Further, with the growth in computer manufacture and usage in the 1980s, Unix became the operating system of choice. As the government undertook limited computerization of some of its activities, it played a role in encouraging the use of Unix, especially in public-sector bank automation. This opportunity led to many innovations in the design of Unix-based systems (Heeks 1996). Since Unix had a profound impact on almost every commercial operating system since its development at AT&T Bell Labs in 1969, Indian engineers entered the global market with a unique advantage (Udell 1993). But, prior to 1990, exports involved little more than bodyshopping – or the practice of providing inexpensive on-site (i.e. at customer locations overseas) labor on an hourly basis, for low value-added programming services such as coding and testing.29 It was only from the early 1990s – coinciding with the provision of data communication facilities in Software Technology Parks (STPs) and greater openness to the world economy – that a territorially grounded industry emerged in India. With the establishment of the first STP, Bangalore became the leading region for the industry and came to be referred to by terms such as “India’s Silicon Valley” (IDG 2001). The STPs and the greater economic openness helped transform the industry in the 1990s. Besides attracting more MNCs to the country, the share of offshore services in software exports increased as software factories emerged in India, with the infrastructure, technology, quality processes, productivity tools, and methodologies of the customer workplace. Thus, India became home to the largest number of CMM and ISO certified firms in the world, although obtaining work in the Japanese market has remained a challenge. Nevertheless, Arora and Asundi (1999) identify two reasons why Indian firms seek quality certification. First, it is a marketing device, to signal to potential customers that the firm follows a well-defined and documented development process. Second, a well-defined process improves the ability of firms to estimate and manage the time and resources required for a project, helping them bid for larger projects, thereby expanding business. Although Arora and Asundi conclude that the relationship between certification and better rates is not very robust, they add that, for firms with an ongoing commitment to quality, getting bigger projects is a route to obtaining turnkey contracts that are more profitable. Obtaining turnkey contracts forces firms to develop substantial management skills, as they have to coordinate a much wider range of tasks than just programming, and take responsibility for the overall project schedule, quality and productivity, in contrast to bodyshopping, which is little more than resume selling. Not only did some Indian firms get better work at better rates, they also began to move away from competing on hour-based productivity to IP based productivity, by converting knowledge gained from
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development projects – in specific application areas, such as banking, retailing or telecommunications – to a customizable generic product for clients with similar needs. Indian ICT service firms and service exports continued to grow in the new millennium, despite the global slump in demand for IT products following overinvestment in the 1990s.30 The growth has been accompanied by a further qualitative shift, as the offerings of the industry are no longer limited to low-valued added services. Instead, it increasingly provides R&D services, which demand IP creation. Central to the growth of R&D services is the provision of embedded systems.31 The activities of firms in India in embedded systems can be classified into three categories (Hari and Anand 2002). In the first category are firms offering contract design services for customers. This is similar to providing software services, in which Indian firms have become competitive globally, with one crucial difference. Those providing design services are very much a part of the embedded systems production chain and interact with either the customer’s Chief Technology Officer or the R&D head. In contrast, software services that are outsourced – such as maintaining databases in domains like retailing – while contributing to essential information support systems, do not typically represent the mainstream activity of most customers. Service providers in this case tend to interact with the Chief Information Officer of their customers. In the second category are firms that generate IP to derive revenue from a customer license fee or recurring royalty payments. While this is lucrative – especially when compared to providing software services on a man-hour basis – it is not without risks. Generating IP requires familiarity with emerging standards for which participation in the relevant international standard setting bodies is valuable. Finally, there are vendors who design entire chips. While this is the most profitable category, it also requires deep pockets and, thus, is mostly the realm of MNCs such as Intel, Motorola, and Texas Instruments (TI). Chip vendors such as TI, however, do not develop their products in isolation. With the growing complexity of embedded systems and the rapid proliferation in their use, the industry is moving toward a design process that integrates reconfigurable, commodity system-on-chip platforms to offer differentiated products for a wide variety of users and application domains (Martin and Schirrmeister 2002). Platforms are a mechanism to accelerate the design and development of end-user products by providing pre-integrated, pre-verified collections of IP blocks organized into hardware-software architectures. Thus, while TI retains DSP development, in 2004, it had more than 600 independent DSP partners globally from whom it either bought IP or sought design services. Forty nine of its partners were Indian, 31 of which were Bangalore-based.32
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11.6 The impact of the Japanese market on ICT services industry in Dalian Unlike in Bangalore, the export-based ICT services industry in Dalian has not been able to make any tangible entry into markets other than in Japan. The reason, we argue, is because its strength – that is, access to the Japanese market – is also a weakness. While the market has offered growth opportunities, the unique standards adopted by Japanese firms are limiting. One interviewee stated that “... entering Japanese markets would mean adhering to individual proprietary standards, whereas entering the global market would mean adopting open standards.” 33 Working to process standards that are either closed – such as proprietary process standards – as opposed to open standards – such as CMM or ISO standards – or those that have limited recognition, such as PIPA, leads to lock-in effects (Varian et al. 2005). In Dalian these effects are manifest in the reluctance of local firms to adopt open standards to enter more competitive markets that are based on open standards.34 Firms in Bangalore had little option but to seek work overseas, both in terms of volume and scope, due to the limited domestic market (Parthasarathy 2004), despite the importance of a “walking on two legs strategy” (Schware 1992). Such a strategy entails developing a domestic market for various software application domains to help firms hone their expertise and experience locally before serving global markets, and to minimize the risk of being confined to low-value added work. Although the size of the Chinese market could potentially confer an advantage, firms in Dalian also face constraints at home. At one level, while China’s joining the World Trade Organization is changing its approach to establishing standards – especially in the ICT industry – there is the legacy of techno-nationalism (Suttmeier et al. 2006). The active role of the state in standard setting is driven by the 260 special technical committees, which directly report to the Standardization Administration of China, and 422 subcommittees consisting of 27,800 individuals who draft standards, with little foreign or public input. In the US, the government does not dictate standards setting; instead, the process is left to 450 standards developing organizations – including 150 consortia and numerous committees – to address technical requirements and 93,000 active standards.35 Thus, at the end of 2002, of the 8,931 national standards that China had along the lines of international ones, 3,794 did not complement international standards, while 2,968 were modified versions. Even if firms from Dalian participate in setting domestic standards, unique standards blunt the international scope of any domestic opportunities. At a different spatial scale, the economic competition between provinces manifests in what can be termed techno-regionalism – provinces creating their own standards to promote local firms by protecting local markets (Tschang and Xue 2005).
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But even within the Chinese context, Beijing and Shanghai are instances of how history and policy can combine to create outcomes that are different from Dalian.36 Both cities host a number of Research and Development (R&D) centers (MII 2003), despite the wages for software professionals and the attrition rate being higher in both cities.37 One result is that “... Master’s students from the university rarely find jobs in Dalian for their skill sets, they tend to move to either Shanghai or Beijing; the industry in Dalian hasn’t yet started R&D.”38 Just as Dalian used its historical advantages to enter the Japanese market, Beijing and Shanghai capitalized on their advantages, especially those conferred on them especially during the period of central planning between 1949 and 1978. While both cities are home to the largest pools of skilled labor in China – thanks to the presence of the nation’s best universities and research facilities – they capitalized on their advantages in different ways. The local government in Beijing encouraged researchers to quit their jobs with the state and to establish minying enterprises in new technology areas. While the local government provided financial and administrative support without interfering in the management of these initiatives, the entrepreneurs could fall back on the technical community in the capital to develop new ideas and technologies. Besides the local backing, the national government too was keen on transforming the capital into the political and cultural center of the country – an endeavor in which building technological capability had a crucial role. These efforts led to an agglomeration of software and internet firms in Zhongguancun – in Beijing’s Haidian district – which has been labeled China’s Silicon Valley (Zhou 2007). While Shanghai could boast of similar human capital to Beijing, it went about the task differently. Central to the local economy, which Yusuf and We (1997) describe as “the industrial workhorse of China,” were SOEs. The importance of SOEs to the local and national economies, and the political ties between the SOEs and the local bureaucracy meant that Shanghai promoted the ICT industry by reforming the SOEs rather than by encouraging minying enterprises. At the same time, since Shanghai was attempting to position itself as China’s gateway to the international economy, it attracted MNCs. The result was the creation of a production and service industry around ICT manufacturing.
11.7
Conclusions
This paper has set out to explain how late industrializing regions of the early 21st century – such as those in China and India – enter the international division of labor and maintain their comparative advantage amidst changing technologies, shifting demand conditions, and new competitors. Specifically, the focus was on the role of standards, controlling which is
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the source of power in TDCCs of ICT products and services. Drawing on the comparison of Dalian and Bangalore, the paper makes three points in this regard. First, it shows that while regions can capitalize on advantages conferred by history to become a part of TDCCs, governance of the commodity chain matters. In the case of Dalian, entering the Japanese market for ICT services has proven to be a double-edged sword. On the one hand, the Japanese market is the second largest in the world and offers a range of opportunities. Yet, the outsourcing and offshoring practices of the Japanese firms have, at least thus far, limited the scope of work that is sent offshore. Thus, Chinese firms find themselves at the bottom of the Japanese subcontracting hierarchy. The work that firms in Dalian undertake is labor-intensive and they have been unable to move into more productive activity. The negligible exposure of firms in India to the Japanese market has made them less vulnerable to the Japanese governance practices in TDCCs. Second, integration into the international division of labor on the basis of open-process standards allows firms greater access to markets and to benefit from the resulting network externalities. Catering to the proprietary process standards of their customers in Japan has made it hard for firms in Dalian to enter markets elsewhere. For firms in Bangalore – which also started off working at the bottom of the ICT service hierarchy – using open process standards allowed them, over time, to expand the scope of their work. Once convinced of the capability of Indian vendors, North American and Europe customers were willing to widen the scope of the contract to offer greater responsibility for the overall project schedule, quality and productivity. This also proved to be the first step toward developing innovative capabilities in various domains. Finally, while the literature has argued that access to a domestic market can play an important role as a platform for international markets, this paper shows how it matters: it is not the absolute size but the standards that rule at home. A vast Chinese market has not helped Dalian’s international aspirations; instead, they have been blunted by techno-nationalism and techno-regionalism, which either isolate China or fragment the domestic market. The Indian domestic market – though smaller than China’s – has offered the necessary support for exports. Even in the 1980s, the value of Indian engineers arose not merely from their ability to speak English, but because of their exposure to various platforms and their familiarity with Unix, the most influential operating system ever. More recently, start-ups and large firms (both Indian and MNCs) are driving the creation of a cluster of the embedded systems industry in Bangalore. With local firms embracing international standards and protocols for chip design, they are lodged as creators of IP in the embedded systems commodity chain. Even within China, Beijing and Shanghai show how history and policy can combine to create outcomes that are different from Dalian.
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Notes 1. Specifically, India’s share of world IT and ICT-enabled exports in 2007 was 4.22%; the corresponding figure for China was 2.92% (UNCTAD 2009, p. 127). 2. In addition, there are 120 vocational and language training schools which – in 2006 – trained 27,000 students. 3. Unless otherwise mentioned, details of China’s economic reforms are drawn from Bell et al. (1993). 4. The others were new materials, energy, biotechnology and electromagnetic devices. 5. Interviews with DLSP, August 24, 2009. 6. Interview with Dalian Tiandi, August 24, 2009. 7. Interview with Dalian Bureau of Information Industry, August 28, 2009. 8. One firm for whom this model has worked well is CISCO. Interview with CISCO GSC, August 25, 2009. 9. Interviews with DLSP-HRDC, August 26, 2009. 10. Details of the visit are available at http://www.zaptron.com/china/dalian/visit. htm. The event was sponsored by the Ministry of Science and Technology, the Ministry of Education, the State Office of Overseas Chinese Affairs, the Liaoning Provincial Government, and the Dalian City Government. The Dalian delegation also cultivated ties with existing communities, as evident in the Silicon Valley Chinese Overseas Business Association being a part of the organizing team. 11. Information on CISIS is from interview with Dalian Software Industry Association, August 24, 2009. 12. Between 2003 and 2007, exhibition space at the fair grew from 11,000 sq.m. to 30,000 sq.m. The number of exhibitors grew from 300 to 800, with representation from 32 countries. (http://www.cisis.com.cn/news/279/ 450/ 2881/newsexdisen3558.aspx) 13. Interview with China-Japan Friendship Center for Human Resource Development, August 24, 2009. 14. Ibid. 15. Interview with Dalian Ascendas, August 25, 2009. 16. Interviews with Dalian Tiandi, August 25, 2009. 17. Interviews with Dalian Ascendas, August 25, 2009. 18. Details of DSIA’s changing role from interview with DSIA, August 24, 2009. 19. Interviews at DLSP, August 24, 2009. 20. Interview with Toyota Tsusho Electronics Dalian Co. Ltd., August 27, 2009. 21. Interview with Alpine Electronics (China) Co. Ltd. (Dalian R&D Center), August 24, 2009, and Toyota Tsusho Electronics Dalian Co. Ltd., August 27, 2009. 22. Although SEI upgraded the CMM model to CMMi (Capability Maturity Model Integration) in 2000, the broad philosophy of the five-stage model remains the same. For details, see www.sei.cmu.edu/cmm/cmm.html. 23. Interviews at the DLSP-HRDC, August 26, 2009. 24. This Act was a revised version of Act No.95 of 1988, for the Protection of Computer Processed Personal Data held by Administrative Organs, which did not apply to the private sector. See, http://privacymark.org/ privacy _ mark/about/outline_ and _purpose.html 25. JIPDEC established the PrivacyMark system in 1998, following instructions from the then Ministry of International Trade and Industry (currently Ministry of Economy, Trade and Industry (METI)). See, http://privacymark.org/privacy_ mark/about/outline_and _purpose.html
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26. Information on PIPA is from interview with DSIA, August 24, 2009. 27. Two key initiatives were the Computer Policy of November 1984, and the Computer Software Export, Development and Training Policy of December 1986 (Subramanian 1992). 28. Examples of such contracts were those requiring the reconciliation of formats, such as those involving dates, of which the Y2K problem received the widest publicity. Jones (1998) points to other format problems with older software that manifest themselves in the 1990s. One date problem had to do with resetting the counters of global positioning system (GPS) satellites used for global fund transfers. The shift to the Euro, replacing 12 European currencies, from January 1, 1999, posed a different kind of format problem. 29. Unless otherwise mentioned, the next four paragraphs draw from Parthasarathy (2004). 30. For instance, in the US, spending on IT – after growing by 16% in 2000 – fell by 6% in 2001 (Economist 2002) and – in aggregate terms – technology spending declined from nearly 5% of GDP in 2000 to about 4% by 2003 (Economist 2003). 31. An embedded system is any computer that is a component in a larger system and relies on its own microprocessor (Wolf 2002). The use of embedded systems has grown with more powerful microprocessors. They now find application in everything from consumer goods to transport equipment and industrial process control systems. In these devices, embedded systems not only take over what mechanical and dedicated electronic systems used to do, but they increasingly connect to the Internet. It is the ability to digitally capture and simulate various mechanical or other functions that makes the globalization of R&D in various domains technologically feasible. Thus, for instance, automobile firms such as General Motors and Mercedes-Benz have established R&D facilities in Bangalore. 32. Details of TI’s activities are from a personal discussion that followed a presentation by Dr. Biswadip Mitra, Managing Director, TI India, at the International Institute of Information Technology, Bangalore on 10 April 2004, and from www.ti.com/asia/docs/India 33. Interviews at Dalian Hi-Think Computer Technology Corp., August 25, 2009. 34. Interview with DSIA, August 24, 2009. 35. http://www.chinabusinessreview.com/public/0305/weeks.html 36. The discussion of Beijing and Shanghai in the next two paragraphs is from Segal (2003) unless otherwise mentioned. 37. According to the Annual Report of the Dalian Software Industry Association, the average annual pretax salary for a software development engineer in 2007 was RMB66541 in Shanghai, RMB632000 in Beijing and RMB in 47450 in Dalian (p.130). The report also provides a human resource mobility index (p.131). In 2006, the index for Shanghai was 134 (Xian = 100), Beijing 130, whereas Dalian was 110. 38. Interview with School of Software, Dalian University of Technology, 26 August 2009.
References Arora, Asish and Jay Asundi, 1999, Quality Certification and the Economics of Contract Software Development: A Study of the Indian Software Industry, Working paper 7260, Cambridge, MA: National Bureau of Economic Research.
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Bell, Michael W., Hoe Ee Khor, and Kalpana Kochhar, 1993, China at the Threshold of a Market Economy, Occasional Paper 107, International Monetary Fund. Cusumano, Michael, 1991, Japan’s Software Factories: A Challenge to U.S. Management, New York: Oxford University Press. Dicken, Peter, 2007, Global Shift: Mapping the Changing Contours of the World Economy, 5th edition, New York: Guildford Press. Economist, 2002, High-Tech Companies: IT Grows Up, 24 August, p. 45. Economist, 2003, Spending on Information Technology: Some Like it Cold, 4 October, p. 62. Fairbank, John King and Merle Goldman, 2006, China: A New History, 2nd edition, Cambridge, MA: Belknap Press. Harding, E. U., 1989, “India: After IBM’s Exit, an Industry Arose”, Software Magazine, 9 (14), pp. 48–54. Hari, P. and M. Anand, 2002, Chip’s of the block, Business World, 18 March, pp. 34–41. Heeks, Richard, 1996, India’s Software Industry: State Policy, Liberalisation and Industrial Development, New Delhi: Sage. Hsing, You-tien, 1998, Making Capitalism in China: The Taiwan Connection, New York: Oxford University Press. IDG, 2001, “India’s Silicon Valley Lures Foreign Companies”, The Industry Standard, www.industrystandard.com/article/0,1902,27396,00.html. Jones, Capers, 1998, “Bad Days for Software”, IEEE Spectrum, 35 (9), pp. 47–52. Krugman, Paul, 1992, Geography and Trade, Cambridge, MA: MIT Press. Martin, G. and Schirrmeister, F., 2002, “A Design Chain for Embedded Systems”, IEEE Computer, 35 (3), pp. 100–103. Ministry of Information Industry (MII), 2003, China Software Industry Development Report, Beijing: MII. National Association of Software and Service Companies (NASSCOM), 2008, Emerging Market Series – Opportunities for Indian IT industry in Japan, New Delhi: NASSCOM. O’Riain, Sean, 2004, “The Politics of Mobility in Technology-Driven Commodity Chains: Developmental Coalitions in the Irish Software Industry”, International Journal of Urban and Regional Research, 28 (3), pp. 642–663. Parthasarathy, Balaji, 2004, “India’s Silicon Valley or Silicon Valley’s India? Socially Embedding the Computer Software Industry in Bangalore”, International Journal of Urban and Regional Research, 28 (3), pp. 664–685. Saxenian, Annalee and Xiaohong Quan, 2005, “Government and Guanxi: The Chinese Software Industry in Transition”, In Simon Commander, ed., The Software Industry in Emerging Markets: Origins and Dynamics, Cheltenham: Edward Elgar. Schware, Robert, 1992, “Software Industry Entry Strategies for Developing Countries: A ‘walking on two legs’ Proposition”, World Development, 20 (2), pp. 13–164. Segal, Adam, 2003, Digital Dragon: High-Technology Enterprises in China, Ithaca, NY: Cornell University Press. Sridharan, E., 1996, The Political Economy of Industrial Promotion: Indian, Brazilian and Korean Electronics in Comparative Perspective 1969–1994, Westport, CT: Praeger. Subramanian, C. R., 1992, India and the Computer: A Study of Planned Development, New Delhi: Oxford University Press. Suttmeier, Richard P., Xiangkui Yao, and Alex Zixian Tan, 2006, Standards of Power? Technology, Institutions, and Politics in the Development of China’s National Standards Strategy, NBR Special Report, National Bureau of Asian Research, http://www.nbr. org/publications/specialreport/pdf/SR10.pdf
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Tschang, Ted and Xue Lin, 2005, “The Chinese Software Industry”, In Ashish Arora and Alfonso Gambardella, eds., From Underdogs to Tigers: The Rise and Growth of the Software Industry in Brazil, China, India, Ireland, and Israel, New York: Oxford University Press. Udell, J., 1993, “India’s Software Edge”, Byte, 18 (10), pp. 55–60. United Nations Conference on Trade and Development (UNCTAD), 2009, Information Economy Report 2009: Trade and Outlook in Turbulent Times, New York: United Nations. Varian, Hal R., Joseph Farrell and Carl Shapiro, 2005, The Economics of Information Technology: An Introduction, Cambridge: Cambridge University Press. Wank, David L., 2001, Commodifying Communism: Business, Trust, and Politics in a Chinese City, Cambridge: Cambridge University Press. Way, Edwin, 2008, “Bringing the (Local) State Back In: City Innovation Systems in Ji’nan and Dalian”, Draft Manuscript. Wolf, W., 2002, “What is Embedded Computing?” IEEE Computer, 35 (1), pp. 136–137. Yeung, Y.-M. and C.P. Lo, eds., 1976, Changing Southeast Asian Cities: Urbanization and the Environment in International Perspective, Singapore: Oxford University Press. Yusuf, Shahid and Weiping We, 1997, The Dynamics of Urban Growth in Three Chinese Cities, New York: Oxford University Press. Zhou, Yu, 2007, The Inside Story of China’s High-Tech Industry: Making Silicon Valley in Beijing, Lanham, MD: Rowman and Littlefield.
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Index agricultural laborers, 20, 23 agricultural sector cotton, 164–8, 172–3 productivity gap between manufacturing and, 22 agro-industrial transformation, in textile industry, 157–77 Apprenticeship Training Scheme (ATS), 109, 115 automobile industry, 6, 9, 63–78 see also electric vehicle industry China, 63–7, 77–8, 204–13 comparison of India and China, 217–21 emissions standards, 203–6, 214–15, 217–20 exports in, 74–7 foreign direct investment in, 74–7 India, 63–4, 66–9, 213–17 indigenous firms in, 64–78 Japan, 63 technology acquisition in, 69–74 Bajaj Auto Ltd., 81, 83, 84, 88, 91–3 Bangalore, 226, 231, 237–9, 249–52 barriers to entry, 41, 49–50, 52–3 Beijing, 210, 237, 253 Brazil, 158 business process outsourcing (BPO), 1, 6, 11, 20, 23 capability building see also skill formation firm-level, 80–105 in-house, 80, 93–100 interfirm, 80, 85–93, 100 through technology acquisition, 69–74 capital-labor (KL) ratio, 29–33, 37n16 capital mobility, 184–5, 189 casual workers, 144–5, 151 “catching-up,” 19, 30 Chery Automobile, 9, 64, 65, 69–71, 75–6
China agricultural policies, 165–7 automobile industry, 63–7, 77–8, 204–13, 217–21 competition in, 6–8, 23–7, 46–7 cotton production in, 165–7 domestic market in, 8, 11–12, 65, 83, 182, 206, 232, 238, 239, 254 economic development in, 11–12 economic reforms, 118 education in, 9–10, 108–19, 127, 145–6 electric vehicle industry, 207–12, 217–21 electronics and electrical industry in, 40–57 financial markets, 184–7 fiscal system, 183–4 ICT industry in, 237–56 industrial development in, 1, 4, 19, 40, 42–5 inter-firm relations, 104n4 ITES offshoring in, 226–36 labor market in, 12–13, 23 local public finance, 193–5, 199 manufacturing sector in, 11, 20–3, 26–37 market segmentation, 181–2, 184–7 market size, 50–2 market structure in, 44–52 motorcycle industry, 80–105, 81, 81–4 per capita GDP, 19 role of government in, 10–11 skill distribution, 108, 117, 127–8 skill formation, 107–8 software and ITES sector in, 226–9 synthetic-fiber industry, 168–74 textile industry, 136, 138–50, 157–77 textile policies, 159–61 wages, 96–7, 124, 142 China National Textiles Import and Export Corporation, 167
259
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260
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Chinese government education and training policies, 117–23, 127 electronics industry and, 49–50 local, 181, 183–4, 193–5 software and ITES sector and, 229–31 support for electric vehicles by, 207–13, 217–20 Chongqing, 211 clothing industry, 136 see also textile industry colonialism, 157 commoditization, 4 competition differences in, between China and India, 6–9 in electronics and electrical industries, 40–1, 56 heterogeneous, 42, 47–9 homogenous, 42, 46–7, 50 indigenous firms and, 2–3, 5–6 in manufacturing sector, 23–7 motorcycle industry, 84 new entry and, 26–7 number of firms and, 25–7 price, 23, 34–5, 84 compressed natural gas (CNG), 220–1 consumer goods, 49 consumption, 185 cotton, 142, 157–60, 162, 164–8, 170, 173–4, 176n12 Cotton Corporation of India (CII), 167–8 Craftsmen Training Scheme (CTS), 109, 115 Cultural Revolution, 118 Dalian, China, 226, 231–9 characteristics of ICT firms in, 248 emergence of ICT industry in, 239–43 ICT revenues in, 241 Japanese market and, 247–9, 252–3 Dalian Software Industry Association (DSIA), 235 Dalian Software Park (DSLP), 245–7 defense industry, 52 democracy, 191–3 deregulation, 136, 137 developmentalistic state, 5 development expenditure, 190–1
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dispersed-type networking, 86, 93, 104n4 domestic market, 9 in China, 8, 11–12, 65, 83, 182, 206, 232, 238, 239, 254 in India, 8, 12–13, 173, 226, 252 domestic migration, 14n22 dynamic inefficiency, 196–9 East Asia, 2 catching-up experiences, 5, 30 colonialism in, 157 manufacturing sector in, 20 Economic and Technology Development Zones (ETDZ), 244 economic development, 19 in China, 1, 11–12 employment growth and, 125–6 human capital and, 107 in India, 1, 12–13 education, 9–10 China, 108–19, 121–2, 127, 145–6 distribution of workers by level of, 110–11 economic growth and, 107 financing of, 122–3 general, 109 government policies on, 117–23, 127 India, 108–17, 119–23, 127, 145–7, 228 ITES-related, 228–9 quality of, 115–17 return on, 123–4 skill formation through, 107–8 teachers, 116, 121–2 vocational, 109–16, 118–19, 128, 129n10, 146 863 Program, see State High-Tech Development Plan electric vehicle industry, 6, 10–11, 203–23 consumer acceptance, 212, 217, 218, 220 global warming and, 203–4 government support for, 207–12, 215–21 infrastructural construction, 211–12, 216, 218, 219 policy shortcomings, 212–13, 217, 218, 219 Electric Vehicle Industry Alliance, 207
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Index electronics and electrical industry, 20, 26, 40–57 barriers to entry, 49–50, 52–3 competition in, 40–1, 56 development of, 42–5 market expansion, 53–4 market size, 50–2 market structure in, 45–54, 56 embedded systems, 251, 256n31 emissions standards, 203–6, 214–15, 217–20 employment growth, 125–7 informal, 125, 130n18 in manufacturing sector, 26–7, 32 in software and ITES sector, 227–8 employment exchange, 117 employment rates, 116–17 engineers, 33–4, 35, 229 English language skills, 228, 229 European Union (EU), 185 EVFuture, 216, 218 exports in automobile industry, 74–7 of manufactured goods, 139–40 software and ITES, 226–7 in textile industry, 139, 141–2, 157, 160 export zones, 141 Factory Law, 25 Feldstein-Horioka (FH) test, 185 federalism, 182–9 financial markets China, 184–7 India, 187–9 integration of, 187–9 segmentation of, 184–7 financial reforms, 182 firms demand for skills by, 125–7, 128 new entry by, 26–7 number of, and competition, 25–7 state-owned, 83, 180, 245, 253 firm size, 25, 27, 28, 36n11, 37n17 electronics industry, 51, 55 engineer ratio and, 33–4, 35 regional agglomerations, 135–7 firm/transaction-specific investment, 9 fiscal federalism, 182–9
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fiscal system China, 183–4 India, 191–3 food security, 159, 169, 172 Ford Motor Company, 64, 66 foreign direct investment, 74–7, 141 Foreign Exchange Regulation Act (FERA), 52 fuel cell vehicles, 209 Gandhi, Mohandas, 119–20, 129n11 garment industry, see textile industry Geely Automobile Holdings Ltd., 9, 64–6, 71–2, 76 gender-based segmentation, in textile industry, 143–4 General Motors India, 66 Global Delivery Index (GDI), 237, 238 globalization, 135, 136, 142–3 global production network (GPN), 2, 5, 11, 161 global warming, 203–4 government see also Chinese government; Indian government; local governments role of, 10–11 government policies in cotton agriculture, 164–8, 172–3 on education and training, 117–23, 127, 140 to promote industry, 140, 141 in software and ITES sector, 229–31 Grand River Group Co., 81, 83–5, 87, 88, 91, 92 gross capital income, 197, 200n13 Hero Honda, 81, 83, 84, 92 heterogeneous competition, 8–9, 47–9 higher education, 10, 108, 112, 124, 145 High-Technology Development Zones (HDTZs), 245, 246 Hindustan Motors, 66 homogenous competition, 4, 6–8, 23, 46–7, 50 Hong Kong, 157 Huawei Technologies Co., 4 human capital, 107, 228 human resources, 3, 9–10, 12–13, 233 hybrid vehicles, 207, 209 see also electric vehicle industry
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import substitution, 5, 140 incentives, 100 for skill acquisition, 123–4 for teachers, 121–2 wage, 96–7 India automobile industry, 63–4, 66–9, 213–21 competition in, 6–8, 23–7, 47–9 cotton policies, 167–8 domestic market in, 8, 12–13, 173, 226, 252 economic development in, 12–13 education in, 10, 108–17, 119–23, 127, 145–7, 228 electric vehicle industry, 213–21 electronics and electrical industry in, 40–57 employment growth in, 125–7 financial markets, 187–9 human capital, 228 ICT industry in, 226, 231, 237–9, 249–51 industrial development in, 1, 19, 40, 42–5, 120 industrial licensing, 180–1 labor exchange, 117 labor force participation rate, 129n2 labor market in, 12–13 liberalization reforms, 52–3 local public finance in, 191–3, 199 management style in, 9 manufacturing sector in, 22, 25, 26, 28–37 market expansion in, 53–4 market structure in, 47–9, 52–4 motorcycle industry, 80–105 per capita GDP, 19 public finance system, 173 role of government in, 10–11 service sector in, 11, 20 skill distribution, 108, 117, 127–8 skill formation, 107–8 software and ITES sector in, 226–9 support for electric vehicles by, 220–1 synthetic-fiber industry, 168–9, 172–4 textile industry, 136, 138–50, 157–77 textile policies, 159–61 wages in, 124, 142
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Indian government education and training policies, 117–23, 127 electronics industry and, 52 local, 183 state-level, 181, 183 support for electric vehicles by, 215–19 indigenous firms, 2–3 in automobile industry, 64–78 competitiveness of, 5–6 localization by, 5 technology acquisition by, 63–78 in television set industry, 45–7 Indonesia, 142 industrial clusters, 5–6, 135–7 Industrial Disputes Act, 181 industrialization, 1–2, 19, 40 China, 1, 4, 19, 40, 42–5 India, 1, 19, 40, 42–5, 120 postwar, 157 state-led, 5 industrial licensing, 180–1 Industrial Training Centers (ITCs), 109, 112 Industrial Training Institutes (ITIs), 109, 112 informal employment, 125, 130n18 information and communication technology (ICT) industries, 40, 237–56 in Bangalore, 237, 249–51 emergence of, in Dalian, 239–43 Japanese market, 241, 246–50, 252–3 role of standards in, 249–51, 252, 254 information security, 249 information technology enabled services (ITES), 226–36 in Dalian, China, 231–6 development of, in China, 231–6 government policies and, 229–31 standards in, 238 infrastructure development, 192 in-house capability building, 80, 93–100 career opportunities, 95–6 incentives, 96–7 multiskill formation, 97–8 training activities, 98–9 wage rate and liquidity, 94–5
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Index
263
innovations, 3, 4, 228 institutions, labor market, 136–7 interfirm capability building, 80, 100, 104n4 outsourcing structure, 86–9 risk sharing, 89–91 International Data Corporation (IDC), 237
ITES offshoring and, 226–36 rent-seeking by, 193–5, 196 local-protectionism, 181 local public finance, 189–95 China, 193–5, 199 expenditure structure of, 189–91 India, 191–3, 199 low-end market, 12
Japan, 2, 3, 5, 20, 31, 185, 229 automobile industry, 63 inter-firm relations, 104n4 market for ICT offshoring in, 241, 246–9, 250, 252–3 Japanese language, 229 Jialing Industrial Co., 81, 83–8, 92, 96 jobless growth, 27 job rotation, 97–8 junior college, 146
Malaysia, 140 man-made fibers, 157–62, 164, 168–74 manufacturing sector, 1, 10, 19–37 capital-labor (KL) ratio, 29–30, 32–3 in China, 11, 20, 26–37 competition in, 23–7 in East Asia, 20 employment in, 32 in India, 22, 25, 26, 28–37 labor-intensive, 20–3, 29–30 Mao Zedong, 118 market concentration, 24, 45–7 market expansion, in India, 53–4 market segmentation, 181–2 market size, 41, 50–2 China, 50–2 India, 53–4 market structure in China, 45–7, 49–52 determinants of, 49–54 in electronics and electrical industries, 45–54, 56 in India, 47–9, 52–4 middle-market segment, 12 migrant labor force, 144 migration, domestic, 14n22 minimum support prices (MSP), 167–8 misallocation, 189 productivity and, 180–2 modularization, 4 Monopolies and Restrictive Trade Practice Act (MRTPA), 52 motorcycle industry, 5–6, 9, 80–105 Multi-Fiber Agreement, 136, 160, 163, 173, 174 multinational corporations, 4, 11–12, 234, 247, 250 multiskill formation, 97–8 multisourcing, 86–9 Mumbai, 237
Karnataka Renewable Energy Development Ltd, 216, 218 Korea, 2, 3, 5, 20, 31, 157 labor exchange, 117 labor force participation rate, of women, 129n2 labor-intensive manufacturing, 20–3, 29–30 labor markets, 9–10, 12–13, 136–7 China, 23 local, 135–7 mobility in, 150 regulation of, 136, 137, 181 textile industry, 138, 143–50 labor mobility, 12, 94–5 labor productivity, 136, 142 land-use rights, 194–5, 196 liberalization reforms, 1, 49, 52–3, 192, 200n2 liquified petroleum gas (LPG), 220–1 literacy rates, 117 local governments China, 183–4 Dalian, China, 232–5 electric vehicle industry and, 209–11, 215–17 finance systems, 183–4, 189–95 India, 181, 183 intervention in markets by, 181, 194–5
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Index
Nanchang, 211 Nano, 74, 77 National Textile Policy, 141 Nehru, Jawaharlal, 120 neoliberalism, 136 Neusoft, 227 New Delhi, 237 offshoring, 226–36 in ICT industry, 237–56 in India, 249–51 Japanese market, 247–9, 250, 252–3 on-the-job training, 107, 140, 143 open standards, 238, 249–51, 252, 254 outsourcing, 4, 86–9 see also offshoring overinvestment, 196–9 Pakistan, 158 Patent Cooperation Treaty (PCT), 4 patents, 4, 13n8, 14n9 per capita GDP, 19 piece-rate system, 96–7, 98, 99, 100 polarization, 200n8 political instability, 192 power costs, 163–4 Premier Motors, 66 price competition, 4, 6–8, 23, 34–5, 84 Privacy Information Protection Assessment (PIPA), 235, 249 PrivacyMark, 249 privatization of, 144–5 productivity gap, among agricultural and nonagricultural industries, 22 increases in Chinese, 136 labor, 136, 142 misallocation and, 180–2 productivity growth, 20 profitability, 27–9 protectionist policies, 181, 200n4 pro-worker regulation, 181 public finance systems, 182–9 local, 189–95 raw-fiber producers, 157–9 raw materials, 160 pricing of, 161–8, 176n12 textile industry and, 164–8 real-estate market, in China, 194–6 regional agglomerations, 135–7, 184–7
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rent-seeking, by local governments, 193–5, 196 research and development (R&D) in electric vehicle industry, 208–9 motorcycle industry, 84–5 services, in India, 251 resource misallocation, 180–2, 189 REVA, 215, 218 reverse engineering, 3 risk sharing, 86, 89–91, 185, 187 scale economies, 140–1 schools, see education secondary education, 108, 112, 116–22, 124, 128, 139, 146 self-employment, 124 service sector, 1, 6, 10, 11 see also information and communication technology (ICT) industries competition in, 23 in India, 11, 20 Shandong province, 137–8, 143–50 Shanghai, 210, 237, 253 Shenzhen, 210 short-termism, 9 Singapore, 128, 130n19, 140 skill distribution, 107, 108, 117, 127–8 skill formation, 9–10, 107–30 see also capability building education and training policies, 117–23 globalization and, 142–3 individual incentives for, 123–4 institutional milieu of, 135–52 labor-market mobility and, 150 processes of, 145–50 in textile industry, 145–51 vocational training, 109–15 skills demand for, 125–7, 128, 136 flow of, 109–15 quality of, 115–17 stock of, 108 Skills Development Fund, 128, 130n19 small and medium-sized enterprises (SMEs), 5 small firms, 33–9, 140–1 software industry, 11, 20, 226–36 in Dalian, China, 231–6
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Index software industry – continued development of, in China, 231–6 government policies and, 229–31 standards in, 249–51 Software Technology Parks (STPs), 250 Soviet Union, 5 Special Economic Zones (SEZs), 244 state capacity policy choices and, 159–61 in textile industry, 157–77 state governments fiscal systems, 192–3 India, 183 intervention in markets by, 181 State Grid Corporation of China, 211, 218 State High-Tech Development Plan, 208–9 state-led industrialization, 5 state-owned enterprises (SOEs), 83, 180, 245, 253 suppliers affiliated, 87–8 development activities, 86, 91–3 Supply and Marketing Cooperatives (SMC), 168 Suzuki, 67–8 synthetic-fiber industries, 157–62, 164, 168–74 Taiwan, 2, 3, 5, 20, 31, 157 tariffs, 174 Tata Consultancy Services, 227 Tata Motors Limited, 9, 64, 66, 68, 73–4, 76–7 teacher shortages, 116 technological capability building, 3–4, 9–10 “catching-up,” 19 homogenization of, 19, 31–5 technology acquisition in automobile industry, 69–74 by indigenous firms, 63–78 process of, 69–74 technology-driven commodity chains (TDCCs), 238, 254 technology parks, 141 Technology Upgradation Fund Scheme (TUFS), 141 techno-nationalism, 238, 252 techno-regionalism, 238 television set industry, 41–2, 56
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265
tertiary education, 43, 108, 109, 111, 118, 119, 121, 124, 228–9 Textile Development and Regulation Order, 173 textile industry, 5–7, 10, 26, 136–52 cotton agriculture and, 164–8 gender-based segmentation, 143–4 labor costs, 163 labor markets, 143–50 man-made fibers and, 157–62, 164, 168–74 migrant labor force, 144 power costs, 163–4 production costs in, 161–4 Shandong province, 137–8, 143–50 skill formation in, 145–51 state capacity in, 157–77 Tiruppur-Coimbatore region, 137–8, 143–50 working conditions, 144–5 Textile Policy, 173 Thailand, 140, 142 Tianjin, 210 Tiruppur-Coimbatore region, 137–8, 143–50 Torch program, 244–5 total factor productivity (TFP), 180, 200n1 township and village enterprises (TVEs), 193–4 training see also education financing of, 122–3 government policies on, 117–23, 127 on-the-job, 107, 140, 143 quality of, 115–17 return on, 123–4 skill formation through, 107–8, 142 textile industry and, 145–51 vocational, 109–16, 118–19, 128, 129n10, 146 training activities, 98–9 turnover ratio, 27–9 unemployment rate, 128 United Kingdom, 226 United States, 157, 158, 185, 226 vehicle emission-control standards, 204–6, 214–15, 217–19 vertical integration, 138, 149
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vocational training, 109–16, 118–19, 128, 129n10, 146 Volkswagen, 65 Volvo Car Corporation, 64 wages China, 142 education and, 124 incentives, 96–7, 100 India, 142 low, 140 in manufacturing sector, 23 motorcycle industry, 94–5 piece-rate system, 96–7, 98, 99, 100 teacher, 121–2 textile industry, 142 women labor force participation rate, 129n2 in textile industry, 143–4
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workers demand for skilled, 125–7 incentives for, 96–7, 100 by level of education, 110–11 migrant, 144 multiskill formation, 97–8 skilled, 108–15, 117, 125–8, 136 training activities, 98–9 workforce, 12–13 casualization of, 144–5, 151 mobility, 150 working conditions, in textile industry, 144–5 World Trade Organization (WTO), 252 Yida Group, 245 Zongshen Motorcycle Group, 81, 83, 85–7, 89, 92–3
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