China's Qualitative Economic Transformation 9811944369, 9789811944369

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China’s Qualitative Economic Transformation Edited by Xianming Yang

China’s Qualitative Economic Transformation

Xianming Yang Editor

China’s Qualitative Economic Transformation Translated by Fuyu Chen

Editor Xianming Yang Yunnan University Kunming, China Translated by   Fuyu Chen

Chongqing Jiaotong University Chongqing, China

Sponsored by the Chinese Fund for the Humanities and Social Sciences ISBN 978-981-19-4436-9    ISBN 978-981-19-4437-6 (eBook) https://doi.org/10.1007/978-981-19-4437-6 © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publishers, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publishers nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publishers remain neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Palgrave Macmillan imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-­01/04 Gateway East, Singapore 189721, Singapore

Contents

1 W  hy the Dynamic Evolution of China’s Comparative Advantages Must Be Accelerated  1 Xianming Yang, Ning Huang, and Sujun Shao 2 R  esource Constraints in the Dynamic Evolution of China’s Comparative Advantages 37 Xincheng Zhao 3 F  actor Substitution, Technological Progress, and the Dynamic Evolution of Chinese Manufacturing’s Comparative Advantages 61 Meng Zheng 4 O  ptimization of Human Capital Structure and the Dynamic Evolution of China’s Comparative Advantages 87 Xiaolong Tao 5 I ndustrial Agglomeration and Dynamic Evolution of China’s Comparative Advantages103 Guoqing Zhao, Yishuang Yang, and Wei Hou

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Contents

6 H  ome Market Effect, Spatial Efficiency of Industries, and the Dynamic Evolution of China’s Comparative Advantages151 Ya Li 7 M  arket Integration and the Dynamic Evolution of China’s Comparative Advantages171 Yan Liu and Fan Yuan 8 I nteractive Development of Imports and Exports and the Dynamic Evolution of China’s Comparative Advantages189 Zhijian Liu 9 U  pgrading in Global Value Chains, the Dynamic Evolution of Comparative Advantages, and China’s Position229 Ming Wu 10 N  ational Absorptive Capacity and the Dynamic Evolution of China’s Comparative Advantages257 Haibin Yang Bibliography289

List of Contributors

Xianming  Yang  Development Institute, Yunnan University, Kunming, China Ning Huang  Development Institute, Yunnan University, Kunming, China Sujun Shao  Development Institute, Yunnan University, Kunming, China Xincheng  Zhao  Development Kunming, China

Institute,

Yunnan

University,

Meng Zheng  Development Institute, Yunnan University, Kunming, China Xiaolong  Tao  School of Business and Tourism Management, Yunnan University, Kunming, China Guoqing Zhao  School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, China Yishuang Yang  Research Institute for Indian ocean Economies, Yunnan University of Finance and Economics, Kunming, China Wei Hou  Development Institute, Yunnan University, Kunming, China Ya Li  Development Institute, Yunnan University, Kunming, China Yan Liu  Development Institute, Yunnan University, Kunming, China Fan Yuan  Development Institute, Yunnan University, Kunming, China Zhijian Liu  Development Institute, Yunnan University, Kunming, China vii

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List of Contributors

Ming Wu  Development Institute, Yunnan University, Kunming, China Haibin  Yang International Business School, Yunnan University of Finance and Economics, Kunming, China Fuyu Chen  Chongqing Jiaotong University, Chongqing, China

List of Figures

Fig. 1.1 Fig. 2.1

Fig. 2.2

Fig. 2.3 Fig. 3.1 Fig. 3.2 Fig. 5.1 Fig. 5.2 Fig. 5.3

China’s Dynamic Capacity for Comparative Advantages 16 Dynamic Changes in China’s Water Resources. Source: The water resource statistics between 1981 and 1988 are the total annual runoff of rivers discounted to 0.96 of the original statistics; those between 1989 and 1996 are the surface water resources discounted to 0.96 of the original statistics; those between 1997 and 2002 are the sum of the surface water and ground water resources minus the overlap between them; and those between 2002 and 2017 are from China Statistical Yearbooks of Environment50 China’s Total Energy Production and Consumption 1978–2017. Source: China National Bureau of Statistics. China Statistical Yearbook 2017. Beijing: China Statistics Press, 2018 52 Prospect of China’s Economic Growth Against Natural Resource Constraints 55 Steps of Research 64 Scatter Diagram of the Comparative Advantages, Factor Substitution Elasticity, FDI, and R&D of Chinese Manufacturing76 Average Values of Regional Specialized Division and Agglomeration 2003–2008 119 Average Values of Regional Specialized Division and Agglomeration 2009–2016 120 Average Values of Regional Large-Scale Agglomeration 2003–2008 (%) 121

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List of Figures

Fig. 5.4 Fig. 6.1 Fig. 7.1 Fig. 8.1 Fig. 8.2

Fig. 8.3 Fig. 8.4 Fig. 9.1 Fig. 9.2 Fig. 9.3 Fig. 9.4 Fig. 9.5 Fig. 9.6 Fig. 9.7 Fig. 9.8 Fig. 9.9 Fig. 9.10 Fig. 9.11 Fig. 9.12 Fig. 9.13 Fig. 9.14 Fig. 9.15 Fig. 10.1

Average Values of Regional Large-Scale Agglomeration 2009–2016 (%) Home Market Effects of China’s Eastern, Central, and Western Regions Market Segmentation Index in China History of China’s Foreign Trade Surplus 1978–2017. Source: Website of China National Bureau of Statistics (NBS) Changes in Outstanding Funds for Foreign Exchange and Base Money Supply of China’s Central Bank. Source: The website of the People’s Bank of China; China Financial Statistics Yearbooks; and the exchange rates over the past years (adjusted and sorted by the author) Links of Foreign Trade, Capital Formation, and Dynamic Evolution of Comparative Advantages Foreign Trade, Industrial Structure Upgrading, and Dynamic Evolution of Comparative Advantages The Complex Network of Comparative Advantage Evolution and the Upgrading in Global Value Chains Dynamic Coupling Between the Upgrading in Global Value Chains and the Evolution of Comparative Advantages Index of Industrial Coupling Among China, Japan, and US Changes in the IVD Index of Chinese Industries Changes in the IVD Index of US Industries Changes in the IVD Index of Japanese Industries Changes in World Market Share of Chinese Industries Changes in World Market Share of US Industries Changes in World Market Share of Japanese Industries Changes in the Profitability of Chinese Industries Changes in the Profitability of US Industries Changes in the Profitability of Japanese Industries Contribution of Chinese Industries to the National Economy Contribution of US Industries to the National Economy Contribution of Japanese Industries to the National Economy Comparison of China’s FDI and GDP 1987–2017

122 166 181 191

195 204 209 233 234 244 245 245 246 249 249 250 250 251 251 254 254 255 271

List of Tables

Table 1.1 Table 1.2 Table 1.3 Table 1.4 Table 1.5 Table 1.6 Table 1.7 Table 1.8 Table 1.9 Table 1.10 Table 1.11 Table 2.1 Table 3.1 Table 3.2 Table 3.3 Table 4.1 Table 4.2 Table 4.3 Table 4.4

China’s Factor Accumulation, 1995–2017 9 China’s Technological Progress, 1995–2017 10 China’s Realization of Economies of Scale, 1995–2017 12 China’s Accumulation of Human Capital, 1995–2017 13 China’s Trade Policy Inclination, 1995–2017 14 China’s Dynamic Capacity for Comparative Advantages, 1995–201715 China’s Export Trade, 1995–2017 17 Revealed Comparative Advantages of China’s Export Commodities, 1995–2017 19 Comparison of Commodity Export Concentration, 1995–201721 Comparison of Commodity Diversity, 1995–2017 22 Changes in China’s NBTT, 1995–2017 25 Growth Drags of Natural Resources on Economy 49 Statistical Characteristics of Relevant Variables 75 Baseline Regression Results and Handling of Endogenous Problems77 Results of the Robustness Tests 81 Changes in China’s Comparative Advantages and Source Factors, 1995–2017 96 Results of ADF Unit Root Test 97 Results of Multiple Regression Models and Unit Root Test of Residuals 98 Results of Granger Causality Test 99

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List of Tables

Table 5.1

Measurement of Regional Agglomeration of Four Classifications of Industries, 2003–2008 117 Table 5.2 Measurement of Regional Agglomeration of Four Classifications of Industries, 2009–2016 118 Table 5.3 Significance Test of Regional Agglomeration of China’s Four Classifications of Industries, 2003–2008 123 Table 5.4 Significance Test of Regional Agglomeration of China’s Four Classifications of Industries, 2009–2016 125 Table 5.5 Provincial Averages of Comparative Advantages, 2003–2008127 Table 5.6 Provincial Averages of Comparative Advantages, 2009–2016127 Table 5.7 Contribution of Industrial Agglomeration to Dynamic Specialized Advantages in Trade, 2003–2008 132 Table 5.8 Contribution of Industrial Agglomeration to Dynamic Comparative Advantages of Imports and Exports, 2003–2008134 Table 5.9 Effects of Industrial Agglomeration on Dynamic Comparative Advantages of Export Scale, 2003–2008 137 Table 5.10 Contribution of Industrial Agglomeration to Dynamic Specialized Advantages in Trade, 2009–2016 139 Table 5.11 Contribution of Industrial Agglomeration to Dynamic Comparative Advantages of Imports and Exports, 2009–2016141 Table 5.12 Effects of Industrial Agglomeration on Dynamic Comparative Advantages of Export Scale, 2003–2008 142 Table 6.1 Overall and By-Industry Coefficients of Trade Gravity Model of Chinese Manufacturing 159 Table 6.2 Rankings and Compositions of Home Market Effects of 31 Provinces/Regions/Municipalities in China 162 Table 6.3 Composition of Home Market Effects of China’s Eastern, Central, and Western Regions 163 Table 6.4 By-Industry Home Market Effects in Descending Order 165 Table 7.1 Comparative Advantages in Sino-US Trade: SITC Classifications Correct to Two Decimal Places 184 Table 8.1 Changes in China’s Dependence on Foreign Trade (%), 1978–1997193 Table 8.2 Unit Root Test Results 212 Table 8.3 Johansen Co-Integration Relationship Test 212 Table 8.4 FDI’s “Crowding-in” and “Crowding-out” Effects on Domestic Capital 214 Table 8.5 Unit Root Test Results 215

  List of Tables 

Table 8.6 Table 8.7 Table 8.8 Table 8.9 Table 8.10 Table 8.11 Table 9.1 Table 9.2 Table 9.3 Table 9.4 Table 9.5 Table 9.6 Table 10.1 Table 10.2 Table 10.3 Table 10.4 Table 10.5 Table 10.6

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Johansen Co-Integration Relationship Test 215 Johansen Co-Integration Relationship Test 219 Unit Root Test Results 221 Johansen Co-Integration Relationship Test 221 Unit Root Test Results 222 Johansen Co-Integration Relationship Test 223 Industrial Performance Matrix of Division of Labor on the Global Value Chain 239 The World Input-Output Tables of Three Regions 242 Countries/Regions Covered by WIOTs 243 Industrial Classifications in WIOTs 243 Rankings of Chinese, Japanese, and US Industries in IVD Index247 Comparison of IVD and World Market Share of Chinese, US, and Japanese Manufacturing 253 China’s FDI and GDP, 1987–2017 270 Results of the Stationarity Test of the Variables 277 Co-Integration Test Results of Variables GROWTH, GFDI, K, H, and GFDI*OPEN1278 Co-Integration Test Results of Variables GROWTH, GFDI, K, H, and GFDI*OPEN2279 Regression Results of the Influence of Trade Openness on the Economic Growth Effect of FDI 279 By-Region Test Results of the Influence of Trade Openness on FDI’s Economic Growth Effect 281

CHAPTER 1

Why the Dynamic Evolution of China’s Comparative Advantages Must Be Accelerated Xianming Yang, Ning Huang, and Sujun Shao

1.1   The Dynamic Evolution of China’s Comparative Advantages For sustained growth, an open economy must keep dynamic its comparative advantages. This is particularly true for developing countries implementing the strategy of economic opening-up. Different from the immediate benefits of an open economy, such as the short-term effects of export and foreign exchange growth, the dynamic evolution of comparative advantages are mainly reflected in changes of the quality, quantity, organization, and allocation of growth factors. Corresponding to different stages of economic opening, new growth factors (or those different from the existing ones in quality and size) will replace the existing ones that used to support foreign investment and trade development, and will support the development of a new round of export-oriented economy,

X. Yang (*) • N. Huang • S. Shao Development Institute, Yunnan University, Kunming, China e-mail: [email protected]; [email protected]; [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 X. Yang (ed.), China’s Qualitative Economic Transformation, https://doi.org/10.1007/978-981-19-4437-6_1

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giving rise to structural upgrading and other effects. Thus, the dynamic development of comparative advantages becomes the basis of increasing returns of an open economy. On the other hand, the weakening and stagnation of comparative advantages is the fundamental reason for decrease or withdrawal of external resources, such as foreign direct investment (FDI).1 The studies and focus on the dynamic evolution of comparative advantages originate in people’s concern over economic reality. How to sustain growth of the Chinese economy? How to prevent China from becoming a loser in globalization? These are two correlated questions. Since its accession to the WTO, China’s integration with the world economy has significantly accelerated and the country has become the world’s largest FDI destination open economy that is also strongly dependent on foreign trade. However, issues such as what obstacles the country faces while trying to develop the dynamics of its comparative advantages under the opening-up policy and how to boost such development in this new phase of economic opening are still important research topics. The 2002 United Nations Trade and Development Report analyzed how, in China and other countries, being stuck at the low end of the global value chains leads to the asymmetry between growth in the value and in the volume of trade. The report argues that it is a composition fallacy to infer from competition in the export volume of FDI-driven, and labor-intensive products that there is more generalized competition. It concludes that if China does not step up its effort to realize industrial upgrade by capitalizing on FDI technology, it would be stuck competing with other developing countries at the low end of the global value chains. These conclusions alert us to the importance of assuming the global market competition perspective in our analysis of the potential pressure for China to adjust its economic structure due to its inability to fully realize the country’s comparative advantages. Since the early twenty-first century, Chinese scholars have been paying attention to the urgency of the dynamic evolution of China’s comparative advantages. For example, in view of China’s strong dependency on foreign investment, some scholars discussed the reasons for inadequate development of China’s dynamic comparative advantages by examining the special relationship between FDI and China’s trade development, market 1  United Nations Conference on Trade and Development (UNCTAD), Foreign Direct Investment Policy Boosting Development: National and International Outlook (Beijing: China Financial and Economic Publishing House, 2005).

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distortion caused by intense intra-government competition in investment policy,2 and industrial development strategies. Others were more interested in how FDI behavior can inhibit the dynamic evolution of China’s comparative advantages, especially given the impact of international manufacturing shift on China’s domestic industries.3 Obviously, there is a significant deviation between the development stage of China’s economic opening and the dynamics of its comparative advantages, which has not only caught people’s attention but also become an important starting point for studies on strategic adjustments. Since China’s entry into the WTO, its export-oriented economy has been developing rapidly, and its revealed comparative advantages (RCA) playing a prominent part. Meanwhile, the Chinese economy was marked by a path dependence on the export-oriented strategy. Under such macroscopic circumstances, it is extremely difficult to proactively adjust the export-oriented strategy for economic development, which has practically slowed down the dynamic evolution of China’s comparative advantages. The outbreak of the 2008 international financial crisis highlighted the imbalance in the world economy and had a significant impact on the Chinese economy. Against the background of economic globalization and by means of the world currency—the US dollar, it had evolved from a national financial crisis into a global one. Due to the “Triffin Dilemma” and the lack of a constraint mechanism for dollar issuance, the dollar standard system has a decreasing effect on world economic development but closely correlates the global economy with the US economy. This financial crisis has had a huge impact on the Chinese economy, exposing various structural contradictions among different regions, industries, and even enterprises in China. Meanwhile, the traditional model of growth and technological development, as well as China’s industrial structure, has suffered the impact. Clearly, in the long run, the key to sustainable economic growth is to reshape the model of development. At the same time, certain 2  Song Hong, “The Particularity Bound to Disappear: On the Integration of China with the World Economy in Light of Investment and Trade,” International Trade, no. 1 (2003): 47–50; Zhong Wei and Qin Donghai, “The Structure of International Capital Inflow and the Intense Competition Among Governments for FDI,” Management World, no. 10 (2003): 24–33. 3  Zheng Jianghuai et  al., “International Manufacturing Capital Transfer: Motivation, Technology Learning, and Policy Orientation—An Empirical Study on Supportive Industries in the Development Zone Along the Yangtze River in Jiangsu Province,” Management World, no. 11 (2005): 29–38.

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signs in China’s economic performance indicate that the Chinese economy has entered a new stage of transformation and development. To begin with, China’s advantage in cheap labor will diminish. According to estimates, it will dissipate between 2020 and 2025. By that time, the transfer of surplus labor from rural China will largely complete and the country’s labor cost will increase rapidly. By contrast, India, another populous country, has a younger and larger labor force and a lower per capita income. According to statistics of the World Bank, the GDP per capita of China was USD 5345 in 2008, and the figure for India was USD 2753. Other statistics show that the number of Chinese aged 15 to 34 was 380.11 million, accounting for 29.07% of the total population; the figure for India was 382.96 million (34.99%). Under such circumstances, there are good reasons to doubt if China’s labor-intensive industries will be able to sustain their global competitiveness. On the other hand, it is of long-term strategic value to increase investment in accumulation of human capital and to foster new advantages of quality human resources in China. Furthermore, China is faced with increasing pressure to transform its processing, trade, and production system. In the post-crisis era, it is predicted that China will go through a stage of rapid increase in its costs of environment, resources, and factors, such as land, coal, electricity, oil, and transportation, and in the RMB exchange rate. This will offset the comprehensive advantage of China’s investment environment and greatly reduce China’s appeal to cost-driven FDI. Compared with China, India is currently underdeveloped in infrastructure facilities and manufacturing productivity. Suppose India endeavors to significantly improve its infrastructure conditions and its supportive system for manufacturing in the next ten years. Then it is likely for international capital looking for low-­ cost processing and assembling bases to shift from China to India, and as a result, great changes will take place to the processing and trade system in Asia and the world. Obviously, China’s processing, trade, and production system is faced with tremendous pressure for transformation. For such a transformation, it is important to localize in China the production system of foreign investment. A possible choice will be to constantly increase the proportion of local value added in industrial output, to promote local industrial support, and to facilitate local enterprises’ growth into main parts of processing and trade. In addition, the model of innovation through technological imitation that China had adopted a long time ago has been challenged. There are

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indeed substantial increases in the value added of China’s high-tech industries and long-term growth in the export of China’s high-tech products. According to our empirical studies, however, China’s industrial enterprises above designated size are obviously insufficient in research and development (R&D) input, the proportion of their R&D expenditures in sales is much too low, and only a small fraction of such enterprises have really attached importance to R&D.  It is true that foreign-funded enterprises are in possession of larger numbers of invention patents, but the value-­ added links they allocate in China are mainly labor-intensive processing and assembling—neither is significant in terms of the technological spillover effect. In contrast, Chinese enterprises with invention patents are mainly large-sized sci-tech ones that are small in number. This has given rise to a contradiction. On the one hand, according to statistics of the Organization for Economic Co-Operation and Development (OECD), China has replaced the US as the world’s largest exporter of information and communications technology products. This is borne out by United States Bureau of the Census (USBC) data which show that a large portion of America’s imports of information and communications technology products and photoelectric products comes from China. For a certain period of time, in terms of high-tech product trade, the US deficit with China exceeded that with the rest of the world. On the other hand, for a long time, over 95% of China’s high-tech products exported to the US are realized by means of processing trade and over 90% of such products are produced by foreign-funded enterprises.4 Therefore, it will be difficult for Chinese manufacturing to transit from imitative innovation to homegrown innovation. In fact, the dynamic evolution of China’s comparative advantages affects the growth quality and the direction of development of the Chinese economy in various ways. Some scholars have pointed out that the fundamental reason why an economy might remain stuck in the “middle-income trap” is the slow evolution of its comparative advantages and the slow pace of industrial upgrade.5 Therefore, the dynamic evolution of China’s comparative advantages has serious implications for the country’s ability to 4   Zhang Yansheng, “The Post-Crisis Era: The Utmost Importance of China’s Transformation of Foreign Trade Growth Model,” International Economic Review, no. 1 (2010): 108–13. 5  Wu Yejun and Zhang Qizi, “The Evolution of Comparative Advantages and Economic Growth: An Empirical Analysis of the Argentine Economy,” China Industrial Economics, no. 2 (2012): 37–46.

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overcome the “middle-income trap.” With the gradual disappearance of the traditional factor dividends—such as labor, land, and other resources, China can hardly avoid the “middle-income trap” with its path dependence on traditional comparative advantages unless it can actively build up new dynamic comparative advantages. Other scholars have noted the close relationship between the dynamic evolution of comparative advantages and the upgrading of industrial structures, and argued that the country should try to exercise control over its industrial restructuring by adjusting changes in areas such as capital accumulation, technological innovation, and development of intermediate sectors where it claims comparative advantage.6 They believe that, relative to the external constraints of factor endowments, there must be an optimal path of technological progress that we must follow if we are to realize fully the potential of our comparative advantages and maintain our industrial competitiveness. Studies indicate that the dynamic evolution of comparative advantages may not be a continuous process—there may be interruptions in the course of industrial upgrade based on comparative advantages. And economies moving from middle income to high income are most likely to confront this threat. Some scholars point out that, within the framework of endogenous comparative advantages, a country’s comparative advantages may come from various sources and that, in the long run, it is in China’s interest to discover and integrate highly relevant sources of comparative advantages, especially in such a large economy.7 Obviously, during this period of growth transformation, it is particularly important and relevant to study the dynamic evolution of China’s comparative advantages. For the foreseeable future, there will be corresponding adjustments to the role of the two major factors shaping the world economy—the financial globalization and the new science and technology revolution. Globalization may slow down and major economies of the world will have a hard time making adjustments. Through the development of its export-oriented economy, China has already integrated itself with the world economy and is one of the biggest beneficiaries of 6  Gan Chunhui and Yu Dianfan, “China’s Establishment of Comparative Advantages: A Strategic Perspective,” Academic Monthly, no. 4 (2013): 14. 7  Lin Shanlang, Report on China’s Core Competitiveness: Problems, Status, Challenges, and Countermeasures (Beijing: China Development Press, 2005).

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economic globalization. It is unnecessary and impossible for China to dissociate itself from the world economy. On the contrary, China must adapt to the growth and transformation of the world economy and pursue dynamic comparative advantages amidst growth transformation. The world economic history since industrialization indicates that it is the combined effect of internal and external factors that makes development possible.8 The same is true for China. For example, China’s entry into the WTO has not only won a pass to the international market for its enterprises, but also lowered the transaction costs of its participation in international trade. Currently, China’s trade products mainly reflect its advantages of technological innovation. Yet it has also achieved distinct comparative advantages in foreign thanks to a combination of factors, including division of labor, specialization, and technological absorption, cheap labor released in a new round of “Industrious Revolution”9 under reform and opening-up, and gains from reduced cost of trade as a result of trade facilitation. It is true that the US and other developed countries have prominent advantages for technological competition on the international market, but China has its unique comparative advantages.10 Its comparative advantages are both endogenous and exogenous. In light of the dynamic evolution of comparative advantages, the primary goal of this study is to discover and analyze factors for potential growth of the Chinese economy, to find out problems in bringing into play such potential, and to seek the orientation and countermeasures for strategic adjustments, so as to achieve greater benefits in international competition.

1.2   Trends in the Dynamic Evolution of China’s Comparative Advantages This consists of changes in the dynamic capability and in the dynamic performance of China’s comparative advantages. 8  A.  G. Kenwood and A.  L. Lougheed, The Growth of the International Economy: 1820–1980, trans. Wang Chunfa (Beijing: Economic Science Press, 1995). 9  For this concept, see Giovanni Arrighi, Adam Smith in Beijing, trans. Lu Aiguo et al. (Beijing: China Social Sciences Press, 2009), 27. 10  Hua Min, “The Logic and Choices for China’s High-Speed Economic Growth,” Academic Monthly, no. 7 (2009): 51–61.

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1.2.1   Changes in China’s Capability for the Dynamic Evolution of the Country’s Comparative Advantages This part offers a comprehensive evaluation of the dynamic capability of China’s comparative advantages on the basis of factor accumulation, technological progress, realization of economies of scale, accumulation of human capital, and the orientation of its trade policy. 1.2.1.1 China’s Factor Accumulation To assess changes in China’s factor accumulation, we select growth in labor force, growth in fixed-asset investment, and the ratio of capital to labor as the indicators. From 1995 to 2017, China’s working-age population increased from 813.93 million to 998.29 million persons, up by 184.36 million persons (22.65%) or 0.93% annually. Over the same period, China’s fixed-asset investment grew from RMB 1071.1 billion to RMB 22,444.5 billion (at the 1990 constant price11), increasing by more than 20 times (RMB 21,373.3 billion) or 14.83% annually. China’s fixed-asset investment increased significantly faster than its labor force. It has resulted in a rise in the ratio of capital to labor which increased from 0.1316 in 1995 to 2.2483 in 2017, up by more than 17 times or 13.77% annually. This indicates that China’s comparative advantages in capital have been constantly strengthened. Propelled by the constant increase of these influencing factors, the indicator of China’s factor accumulation has been on the rise (See Table 1.1). Such changes in China’s capital, labor, and ratio of capital to labor have brought about changes in China’s factor accumulation. This shows that production factors are a dynamic concept and that comparative advantages based on production factors are also dynamic. The greater the changes in the factor accumulation, the more dynamic the comparative advantages and the stronger the dynamic capacity of the comparative advantages. 1.2.1.2 China’s Technological Progress To assess China’s technological progress, we select labor productivity, R&D input, and patents as the evaluation indicators. From 1995 to 2017, China’s labor productivity increased more than six times from RMB 4944 per person to RMB 29,754 per person, up by RMB 24,811 per person or 8.50% annually. Over this period, China’s invention patents authorization  All statistics in this chapter are at the 1990 constant price unless stated otherwise.

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Table 1.1  China’s Factor Accumulation, 1995–2017 Year

Labor force (million persons)

Investment (billion RMB)

Investment-to-labor ratio

Indicator

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

813.93 822.45 834.48 843.38 851.57 889.10 898.49 903.02 909.76 921.84 941.97 950.68 958.33 966.80 974.84 999.38 1002.83 1004.03 1005.82 1004.69 1003.61 1002.60 998.29

1071.1 1179.3 1262.2 1439.7 1519.3 1657.5 1866.3 2177.2 2721.2 3267.4 4051.7 4946.0 5942.2 6863.7 9137.5 9885.5 11,477.0 13,655.1 16,217.1 18,511.2 20,692.2 22,461.7 22,444.5

0.1316 0.1434 0.1513 0.1707 0.1784 0.1864 0.2077 0.2411 0.2991 0.3544 0.4301 0.5203 0.6201 0.7099 0.9373 0.9892 1.1445 1.3600 1.6123 1.8425 2.0618 2.2403 2.2483

0.0082 0.0183 0.0418 0.0631 0.0797 0.1483 0.1713 0.1892 0.2186 0.2568 0.3159 0.3591 0.4037 0.4469 0.5321 0.5945 0.6498 0.7198 0.8025 0.8726 0.9392 0.9932 0.9867

Source: National Data (http://data.stats.gov.cn/), sorted and calculated by the author

rocketed from 3.39 thousand items to 421.14 thousand items, up by 24.49% annually. Over that same period, its R&D expenditures increased from RMB 34.9 billion to RMB 1760.6 billion, up by 50 times or 19.51% annually. Meanwhile, the number of R&D personnel increased from 0.7517 million persons to 4.0346 million persons, up more than five times or by 7.93% annually. Besides, the proportion of R&D expenditures in GDP increased from 0.57% to 2.15%, up by 1.58 percentage points or 6.22% annually, and R&D personnel (per thousand employed persons) grew from 1.104 persons to 5.195 persons, up by 4.091 persons or 7.69% annually (See Table 1.2). Due to the constant increase of these factors, the indicator of China’s technological progress was on the rise over this period. As technological progress improved the marginal productivity of the production factors or nurtured scarce factors, the comparative advantages

4944 5365 5787 6168 6571 7060 7574 8211 8980 9817 10,880 12,210 13,884 15,175 16,544 18,237 19,896 21,381 22,960 24,548 26,176 27,885 29,754

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

3.39 2.98 3.49 4.73 7.64 12.68 16.30 21.47 37.15 49.36 53.31 57.79 67.95 93.71 128.49 135.11 172.11 217.11 207.69 233.23 359.32 404.21 420.14

Invention patents authorization (thousand) 34.9 40.4 50.9 55.1 67.9 89.6 104.2 128.8 154.0 196.6 245.0 300.3 371.0 461.6 580.2 706.3 868.7 1029.8 1184.7 1301.6 1417.0 1567.7 1760.6

R&D expenditures (billion RMB) 0.57 0.56 0.64 0.65 0.75 0.89 0.94 1.06 1.12 1.21 1.31 1.37 1.37 1.45 1.66 1.71 1.78 1.91 2.00 2.03 2.07 2.12 2.15

R&D expenditures in GDP (%)

2. R&D expenditures at the current prices

Notes: 1. Source: National Data (http://data.stats.gov.cn/), sorted and calculated by the author

Labor productivity (RMB/person)

Year

Table 1.2  China’s Technological Progress, 1995–2017

0.7517 0.8040 0.8312 0.7552 0.8217 0.9220 0.9565 1.0351 1.0948 1.1526 1.3648 1.5025 1.7362 1.9654 2.2913 2.5540 2.8830 3.2470 3.5330 3.7106 3.7588 3.8781 4.0336

R&D personnel (million persons) 1.104 1.166 1.190 1.069 1.151 1.279 1.314 1.413 1.485 1.552 1.828 2.004 2.305 2.601 3.022 3.356 3.773 4.233 4.590 4.803 4.853 4.997 5.195

0.0021 0.0099 0.0243 0.0199 0.0425 0.0753 0.0897 0.1188 0.1452 0.1754 0.2205 0.2571 0.3038 0.3627 0.4539 0.5121 0.5942 0.6887 0.7485 0.8016 0.8823 0.9437 0.9938

R&D personnel/ Indicator thousand persons

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became more prominent or started to transform and thus materialize the dynamic changes of the comparative advantages. That is to say, the rise in China’s technological progress is invariably accompanied by increase in the intensity of the dynamic evolution of China’s comparative advantages. 1.2.1.3 China’s Realization of Economies of Scale In order to assess China’s realization of economies of scale, we select the marginal labor-output ratio, the marginal capital-output ratio, and the specialization degree as indicators for evaluation. From 1995 to 2017, there were significant variations in China’s marginal capital-output ratio, which was on a clear downward trend. It was 3.1738 in 1995, 4.1982 in 1999—the highest in the observation period, and 0.4741 in 2009—the lowest in that period. Meanwhile, China’s marginal labor-output ratio increased considerably, rising from 0.0422  in 1995 to 0.9518  in 2017. Over that same period, there were no significant changes in China’s specialization degree, which rose first and dropped later and then rose again. It was 0.3850 in 1995, peaked at 0.3955 in 2002, and then peaked again at 0.4490  in 2017. Facilitated by changes in the marginal labor-output ratio, the marginal capital-output ratio, and the specialization degree, there were significant variations in the indictor of China’s realization of economies of scale. The economies of scale aim to raise the marginal productivity of the production factors, to lower the unit cost, and to expand the market share, so as to make the comparative advantages more prominent and realize the dynamic evolution of the comparative advantages. The variation in such indictors had some unstable effect on the degree of dynamic evolution of China’s comparative advantages (See Table 1.3). 1.2.1.4 China’s Accumulation of Human Capital In order to assess China’s accumulation of human capital, we select the number of college students per million persons, the number of hospital beds per thousand persons, and the number of professionals per thousand working-age persons as the indicators for evaluation. In our findings, the number of college students per million persons increased from 4570  in 1995 to 25,760  in 2017 by 8.18% annually, up by 21,990 persons or approximately six times. The number of hospital beds per thousand persons rose from 1.689 in 1995 to 5.722 in 2017 at an annual average rate of 5.70%, up by 4.033 or approximately four times. Over that same period, the number of professionals per thousand working-age population increased from 29.022 to 42.848 at an annual average rate of 1.78%, up

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Table 1.3  China’s Realization of Economies of Scale, 1995–2017 Year

Marginal capitaloutput ratio

Marginal laboroutput ratio

Specialization degree

Indicator

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

3.1738 3.0887 4.1179 1.7836 4.1982 2.8831 2.0330 1.6194 1.1100 1.2257 1.0593 1.1552 1.3078 1.0956 0.4741 1.7838 0.8329 0.5487 0.4973 0.5623 0.6004 0.7718 0.8489

0.0422 0.0377 0.0392 0.0388 0.0441 0.0576 0.0596 0.1042 0.1324 0.1268 0.2169 0.3121 0.3798 0.4155 0.4083 0.4817 0.4208 0.4208 0.4667 0.4674 0.6614 0.8985 0.9518

0.3850 0.3949 0.3921 0.3918 0.3936 0.3900 0.3884 0.3955 0.3822 0.3677 0.3649 0.3607 0.3464 0.3597 0.3818 0.3834 0.3837 0.3981 0.4095 0.4240 0.4387 0.4490 0.4462

0.3684 0.3915 0.4749 0.2649 0.4889 0.3643 0.2837 0.2861 0.2075 0.1687 0.1777 0.2072 0.1994 0.2364 0.2499 0.3992 0.2928 0.3143 0.3635 0.4165 0.5384 0.6739 0.6912

Source: National Data (http://data.stats.gov.cn/), sorted and calculated by the author

by 13.826 persons. Boosted by the constant increase of these indicators, China’s human capital accumulation was on the rise from 1995 to 2017 (except for the period from 2001 to 2004). Human capital exerts influence on the dynamic evolution of comparative advantages by means of the factor effect, the spillover effect, and the absorption effect. The more abundant the accumulation of human capital, the more significant these effects, and the more likely for the comparative advantages to transfer— thus the higher the dynamic degree of the comparative advantages. China’s constant increase of its human capital accumulation has provided a potent driving force for the dynamics of its comparative advantages (See Table 1.4).

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Table 1.4  China’s Accumulation of Human Capital, 1995–2017 Year

College students per million persons

Hospital beds per thousand persons

Professionals per thousand working-age population

Indicator

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

4570 4700 4820 5190 5940 7230 9310 11,460 12,980 14,200 16,130 18,160 19,240 20,420 21,280 21,890 22,530 23,350 24,180 24,880 25,240 25,300 25,760

0.689 1.785 1.887 1.995 2.108 2.229 2.356 2.490 2.490 2.560 2.620 2.703 2.829 3.046 3.315 3.580 3.840 4.240 4.550 4.850 5.110 5.368 5.722

29.022 28.892 29.354 29.607 30.017 40.055 29.806 29.831 29.483 29.332 36.930 29.740 29.932 30.569 30.611 37.002 30.842 38.817 39.310 40.108 40.965 41.865 42.848

0.0031 0.0100 0.0314 0.0521 0.0831 0.3531 0.1515 0.1970 0.2126 0.2340 0.4508 0.3179 0.3499 0.4016 0.4383 0.6225 0.5069 0.7433 0.7938 0.8487 0.8963 0.9400 0.9979

Source: National Data (http://data.stats.gov.cn/), sorted and calculated by the author

1.2.1.5 China’s Trade Policy Inclination In order to assess China’s trade policy inclination, we select the customs duty rate, the exchange rate, and the ratio of processing trade to general trade as the indicators for evaluation. Our findings show a downward trend in China’s real customs duty rate, which dropped from 2.6414% in 1995 to 2.4023% in 2017. Meanwhile, the USD-to-RMB exchange rate declined rapidly from 8.3510 in 1995 to 6.7518 in 2017. Over this period, the ratio of processing trade to general trade rose first and then dropped— it first increased from 1.0326 in 1995 to 1.4071 in 1998 and then dropped to 0.6166 in 2017. Due to such changes, there was a rapid decline in the trade policy indicator in fluctuation. Trade policy affects trading possibilities and transaction costs and thus influences the quantity and price of trade, which reveals its comparative side. A clear and stable trade policy

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Table 1.5  China’s Trade Policy Inclination, 1995–2017 Year

Real customs duty rate

USD-to-RMB exchange rate

Ratio of processing trade to general trade

Indicator

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

2.6414 2.6117 2.7060 2.6926 4.0930 4.0264 4.1694 2.8828 2.6996 2.2478 1.9644 1.8016 1.9545 2.2256 2.1624 2.1413 2.2615 2.4250 2.1734 2.3625 2.4544 2.4806 2.4023

8.3510 8.3142 8.2898 8.2791 8.2783 8.2784 8.2770 8.2770 8.2770 8.2768 8.1917 7.9718 7.6040 6.9451 6.8310 6.7695 6.4588 6.3125 6.1932 6.1428 6.2284 6.6423 6.7518

1.0326 1.3420 1.2774 1.4071 1.4012 1.3087 1.3181 1.3209 1.3286 1.3465 1.3218 1.2260 1.1469 1.0190 1.1080 1.0272 0.9109 0.8733 0.7913 0.7346 0.6567 0.6332 0.6166

0.6555 0.7849 0.7399 0.7949 0.6579 0.6232 0.6180 0.7323 0.7605 0.8467 0.8913 0.8664 0.7316 0.5123 0.5465 0.5079 0.3858 0.3163 0.3142 0.2437 0.2070 0.2551 0.2785

Source: National Data (http://data.stats.gov.cn/), sorted and calculated by the author

inclination is not only conducive to expanding the size of international trade and lowering trade costs, but also to bringing into play the existing comparative advantages and exploring new sources of comparative advantages, and thus facilitates the realization of the dynamic evolution of comparative advantages. Relatively speaking, China’s trade policy inclination is clear and stable, which ensures a strong dynamic capacity for comparative advantages (See Table 1.5). 1.2.1.6 Evaluation of China’s Dynamic Capacity for Comparative Advantages Based on changes in the afore-mentioned factors in the dynamic capacity for comparative advantages and with the assumption that all these factors

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have an equal effect on the dynamic capacity for comparative advantages, we calculate the indicator of the dynamic capacity for comparative advantages by simply using the arithmetic mean. Table 1.6 shows the results. As we can see in Table 1.6, China’s dynamic capacity for comparative advantages was generally on the rise. This trend is quite noticeable, although there were intermittent fluctuations. In the fluctuation from 1995 to 2017, it only declined in 1998, 2001, 2005–2007, and 2011, compared with the figure a year earlier. The decline in 1998 was mainly due to the fluctuation in economies of scale which was primarily caused by significant changes in the marginal output of capital. The decreases in the other years were mainly because of insufficient realization of economies of Table 1.6  China’s Dynamic Capacity for Comparative Advantages, 1995–2017 Year

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Factor Technological Economies accumulation progress of scale

0.0082 0.0183 0.0418 0.0631 0.0797 0.1483 0.1713 0.1892 0.2186 0.2568 0.3159 0.3591 0.4037 0.4469 0.5321 0.5945 0.6498 0.7198 0.8025 0.8726 0.9392 0.9932 0.9867

0.0021 0.0099 0.0243 0.0199 0.0425 0.0753 0.0897 0.1188 0.1452 0.1754 0.2205 0.2571 0.3038 0.3627 0.4539 0.5121 0.5942 0.6887 0.7485 0.8016 0.8823 0.9437 0.9938

0.3684 0.3915 0.4749 0.2649 0.4889 0.3643 0.2837 0.2861 0.2075 0.1687 0.1777 0.2072 0.1994 0.2364 0.2499 0.3992 0.2928 0.3143 0.3635 0.4165 0.5384 0.6739 0.6912

Human Trade Dynamic capital policy capacity for accumulation inclination comparative advantages 0.0031 0.0100 0.0314 0.0521 0.0831 0.3531 0.1515 0.1970 0.2126 0.2340 0.4508 0.3179 0.3499 0.4016 0.4383 0.6225 0.5069 0.7433 0.7938 0.8487 0.8963 0.9400 0.9979

0.6555 0.7849 0.7399 0.7949 0.6579 0.6232 0.6180 0.7323 0.7605 0.8467 0.8913 0.8664 0.7316 0.5123 0.5465 0.5079 0.3858 0.3163 0.3142 0.2437 0.2070 0.2551 0.2785

0.2075 0.2429 0.2625 0.2390 0.2704 0.3128 0.2628 0.3047 0.3089 0.3363 0.4112 0.4015 0.3977 0.3920 0.4441 0.5272 0.4859 0.5565 0.6045 0.6366 0.6926 0.7612 0.7896

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scale—which was also caused by a lower marginal output of capital—and the trade policies that were adverse to export (See Fig. 1.1). 1.2.2   Changes in China’s Comparative Advantages Comparative advantages are the cornerstone of international trade. The most direct form of the dynamic evolution of comparative advantages is changes in the trade volume, followed by changes in the competitiveness on the international market. 1.2.2.1 China’s Export Trade Over the past decades, China’s export trade increased rapidly and its share in the global market kept rising. Its export trade increased from USD 148.780 billion in 1995 to USD 2263.346 billion in 2017, up by 13.17% annually, which was much higher than the global average growth of 5.76%. Meanwhile, the proportion of China’s export trade in global export trade increased from 2.87% to 12.76% (See Table 1.7).

Fig. 1.1  China’s Dynamic Capacity for Comparative Advantages

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Table 1.7  China’s Export Trade, 1995–2017 Year 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

China (billion USD) 148.780 151.048 182.792 183.712 194.931 249.203 266.098 325.596 438.228 593.326 761.953 968.978 1220.456 1430.693 1201.612 1577.754 1898.381 2048.714 2209.005 2342.293 2273.468 2097.632 2263.346

Global (billion USD) 5176.236 5410.859 5599.525 5509.646 5722.820 6452.318 6195.068 6499.786 7589.983 9223.768 10,502.489 12,127.770 14,020.770 16,148.882 12,555.786 15,302.149 18,339.071 18,512.641 18,949.886 18,985.777 16,531.558 16,031.517 17,732.796

China’s global share (%) 2.87 2.79 3.26 3.33 3.41 3.86 4.30 5.01 5.77 6.43 7.25 7.99 8.70 8.86 9.57 10.31 10.35 11.07 11.66 12.34 13.75 13.08 12.76

Source: UNCTAD database, calculated and sorted by the author

1.2.2.2 The Revealed Comparative Advantages of China’s Export Commodities According to Balassa’s index of revealed comparative advantages,12 the formula for calculation is

12   Bela Balassa. “Trade Liberalization and Revealed Comparative Advantage,” The Manchester School of Economics and Social Studies 33, (1965): 99–123.

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Xij RCAij 

n

X

ij

i 1

Xij j 1

m

n

X j 1 i 1



(1.1)

m

ij



where RCAij stands for the revealed comparative advantages of Country i in Export Commodity j, Xij for the export volume of Country i in Export Commodity j, n for the number of countries, and m for the number of export commodities. Based on statistics of the UNCTAD database and using Formula (1.1), we calculated the revealed comparative advantages of China’s export commodities (See Table 1.8). From 1995 to 2017, there were significant increases in the revealed comparative advantages of China’s manufactured products and significant decreases in those of China’s primary products. A. Manufactured products Of Chinese manufactured products, labor- and resource-intensive products were highest in the comparative advantage, followed by low-­ tech-­ intensive products. Yet the comparative advantage of labor- and resource-intensive products was declining, while that of low-tech-­intensive manufactured products was increasing in this period. Meanwhile, the comparative disadvantage of China’s high-tech-intensive manufactures had turned into a comparative advantage, but its medium-tech-intensive products remained at a comparative disadvantage. B. Primary products Chinese primary products (food, agricultural raw materials, mineral products, and fuels) were invariably at a comparative disadvantage—in particular fuels which were at the most prominent disadvantage.

0.7061 0.6763 0.6509 0.6409 0.5794 0.5322 0.5161 0.4679 0.4214 0.3680 0.3106 0.2745 0.2483 0.2259 0.2275 0.2189 0.2067 0.1890 0.1910 0.1987 0.2254 0.2596 0.2477

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

0.9224 0.9052 0.8279 0.7804 0.7592 0.8158 0.7399 0.6768 0.6012 0.5127 0.4931 0.4596 0.4147 0.3615 0.3662 0.3773 0.3811 0.3665 0.3522 0.3426 0.3376 0.3643 0.3570

Food 0.6737 0.6985 0.6552 0.5697 0.6611 0.6072 0.5053 0.4516 0.3797 0.3298 0.3382 0.3146 0.3057 0.3243 0.3345 0.3058 0.3375 0.3184 0.3121 0.3283 0.2946 0.3075 0.2881

Agricultural raw materials

Primary products

0.6251 0.5889 0.6640 0.6723 0.7052 0.6579 0.6196 0.5937 0.5957 0.6050 0.5328 0.5069 0.4055 0.4014 0.3178 0.3045 0.3091 0.2950 0.2981 0.3275 0.3251 0.3229 0.3137

Mineral products

Source: UNCTAD database, calculated and sorted by the author

Primary products

Year

0.4897 0.4583 0.4608 0.4569 0.3205 0.3031 0.3229 0.2738 0.2519 0.2187 0.1670 0.1246 0.1185 0.1249 0.1174 0.1095 0.0951 0.0822 0.0866 0.0890 0.1060 0.1342 0.1379

Fuels 1.1501 1.1567 1.1581 1.1456 1.1589 1.2014 1.1984 1.2069 1.2300 1.2667 1.3196 1.3438 1.3586 1.4292 1.4039 1.4265 1.4820 1.4986 1.4910 1.4434 1.3566 1.3288 1.3477

2.9086 2.8761 2.9179 2.7591 2.7429 2.7850 2.6450 2.5297 2.4438 2.3906 2.4470 2.5224 2.4699 2.5418 2.5203 2.5823 2.6827 2.7148 2.6536 2.5269 2.3636 2.3170 2.3092

1.5380 1.4567 1.4843 1.4506 1.4551 1.6150 1.4727 1.3369 1.3041 1.3539 1.3644 1.4689 1.5379 1.6207 1.4139 1.5387 1.6222 1.6037 1.5280 1.5716 1.5723 1.5036 1.4773

0.6213 0.6529 0.6651 0.6810 0.7372 0.7954 0.7883 0.7901 0.7599 0.7725 0.8126 0.8475 0.8755 0.9787 1.0000 0.9904 1.0350 1.0561 1.0638 1.0530 1.0111 1.0140 1.0511

0.7350 0.7811 0.7631 0.8194 0.8377 0.8711 0.9399 1.0358 1.1655 1.2702 1.3545 1.3456 1.3729 1.4155 1.3611 1.3927 1.4393 1.4637 1.4621 1.3840 1.2633 1.2353 1.2671

Manufactured Manufactured products products Labor- and Low-tech- Medium-tech- High-techresource- intensive intensive intensive intensive

Table 1.8  Revealed Comparative Advantages of China’s Export Commodities, 1995–2017

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1.2.2.3 China’s Index of Concentration on the International Market The index of international market concentration, also known as the Herfindahl-Hirschmann Index, is a measure of the market position. It can be calculated using the following formula:

Hj 

2

 xi   n  X   1 / n n , X= i 1 xi 1 1 / n i 1

(1.2)

where Hj stands for the market concentration of Country j and xi for Export Commodity i in the SITC classifications. From 1995 to 2017, China experienced considerable increases in its index of concentration on the international market. Of the largest five countries in terms of the export size, China had relatively significant increases, second only to the Netherlands. In terms of the concentration on the international market, however, it remained quite low among these five countries, only higher than the US (See Table 1.9). 1.2.2.4 China’s International Market Diversity Index The diversity index reflects the structural differences between an economy’s export commodities and the global average. The larger the index, the more different the economy’s export commodities from the global average. The index can be calculated using the degree of absolute deviation between the two structures using the following formula:



Sj 

 t hij  hi 2



where hij stands for the proportion of Export Commodity i in the commodity export of Country j, and hi for the proportion of Export Commodity i in the global commodity export. As we can see in Table 1.10, China had a rather high degree of diversity on the international market, but it tended to decrease in recent years. 1.2.2.5 China’s Net Barter Terms of Trade Net Barter Terms of Trade (NBTT), also known as the commodity terms of trade, refers to the ratio between the prices of exports and imports of a

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Table 1.9  Comparison of Commodity Export Concentration, 1995–2017 Year 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Average Average increase

China 0.0700 0.0726 0.0726 0.0745 0.0768 0.0772 0.0808 0.0878 0.1020 0.1083 0.1100 0.1096 0.1037 0.0971 0.1087 0.1065 0.0988 0.1015 0.1031 0.1006 0.1041 0.1051 0.0964 0.0943 1.4662

Germany

Japan

0.0820 0.0859 0.0880 0.0921 0.0981 0.1047 0.1000 0.1040 0.1123 0.1049 0.0956 0.0897 0.0980 0.0917 0.0942 0.0970 0.0919 0.0925 0.0925 0.0972 0.1047 0.1064 0.0990 0.0966 0.8619

Netherlands

0.1235 0.1218 0.1274 0.1345 0.1373 0.1353 0.1351 0.1487 0.1455 0.1361 0.1346 0.1421 0.1464 0.1413 0.1188 0.1251 0.1149 0.1233 0.1268 0.1269 0.1353 0.1409 0.1389 0.1331 0.5325

0.0529 0.0597 0.0617 0.0686 0.0713 0.1381 0.1261 0.1141 0.1061 0.1007 0.1014 0.1062 0.1003 0.1228 0.1213 0.1198 0.1040 0.1174 0.1125 0.0981 0.0817 0.0730 0.0746 0.0970 1.5696

US 0.0746 0.0773 0.0808 0.0881 0.0923 0.0914 0.0857 0.0845 0.0805 0.0904 0.0902 0.0755 0.0738 0.0691 0.0876 0.0820 0.0834 0.0897 0.0951 0.0955 0.0969 0.0993 0.0968 0.0861 1.1928

Source: UNCTAD database, calculated and sorted by the author

country. It reflects the variation in a country’s unit values of import in exchange for unit values of export. It can be calculated using the following formula: NBTT  100 

IPx IPm

(1.4)

where IPx stands for unit values of export and IPm for unit values of import. Generally, empirical studies of trade terms analyze the price index of both import and export commodities or that of classified import and export commodities. This is because, according to international trade

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Table 1.10  Comparison of Commodity Diversity, 1995–2017 Year 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Average Average increase

China 0.4780 0.4694 0.4663 0.4641 0.4603 0.4560 0.4539 0.4600 0.4702 0.4647 0.4612 0.4533 0.4527 0.4591 0.4559 0.4531 0.4634 0.4694 0.4674 0.4489 0.4214 0.4109 0.4125 0.4553 −0.6674

Germany 0.2784 0.2893 0.2876 0.2677 0.2709 0.2852 0.2653 0.2633 0.2792 0.2783 0.2885 0.2833 0.2920 0.3101 0.3147 0.3240 0.3362 0.3474 0.3510 0.3400 0.3194 0.3103 0.3119 0.2997 0.5180

Japan 0.3849 0.3802 0.3930 0.3796 0.3756 0.3766 0.3805 0.3707 0.4040 0.4005 0.4118 0.3820 0.4197 0.4307 0.4193 0.4326 0.4008 0.4208 0.4201 0.4577 0.4346 0.4018 0.4252 0.4045 0.4536

Netherlands 0.3419 0.3399 0.3129 0.3310 0.3336 0.3697 0.3636 0.3675 0.3506 0.3367 0.3396 0.3619 0.3398 0.3440 0.3400 0.3529 0.3413 0.3518 0.3389 0.3287 0.3288 0.3219 0.3255 0.3418 −0.2243

US 0.2706 0.2756 0.2674 0.2561 0.2573 0.2641 0.2595 0.2613 0.2578 0.2579 0.2658 0.2750 0.2683 0.2692 0.2551 0.2512 0.2551 0.2540 0.2560 0.2507 0.2462 0.2438 0.2429 0.2592 −0.4899

Source: UNCTAD database, calculated and sorted by the author

theories based on the law of comparative advantage, it is impossible for a country to export and import exactly the same commodity at the same time—there must be some difference in what it exports and imports. Therefore, there are no net barter terms of trade that specifically analyze every of the commodities exported or imported. Accordingly, the index of export and import prices in Formula 1.4 is not an individual one for a given commodity, but a composite one for all the commodities or a type of commodities. As the price index is an indicator of the quality, and, according to the principles of index compilation, the derivation of a quality index generally adopts the Laspeyres index, IPx and IPm can be respectively calculated using the following formulas:

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IPx

P Q  P Q x 1i

x 0i

x 0i

x 0i

i

i

P

Q

P

Q0mj

m 1j

IPm 

(1.5)

m 0j

j

m 0j

j

23

(1.6)

In Formula 1.5, P1xi stands for the export price of Commodity i within the report period, P0xi for the import price of Commodity i within the base period, and Q0xi for the export quantity of Commodity i within the base period. In Formula 1.6, P1mj stands for the import price of Commodity j within the report period, P0mj for the import price of Commodity j within the base period, and Q0mj for the import quantity of Commodity j within the report period. According to Formula 1.4, if we set a given year as the base period and a country’s NBTT as 100 in that year, we will be able to see the changes in its net barter terms of trade within the report period by calculating its price indexes of imports and exports. If its NBTT is greater than 100 within the report period, its trade terms have improved compared with that in the base period; if its NBTT is smaller than 100, its trade terms have deteriorated. Therefore, the NBTT does not reflect a country’s trade interest or trade position at a given time point, but the changes in its trade interest and trade position within a continuous trade process. As the term indicates, the NBTT reflects the changes in a country’s import capacity in exchange for its export of commodities, or, compared with the quantity in the base period, how many import commodities it can exchange by exporting one unit of commodities in the report period. If the NBTT increases, this country is able to exchange more import commodities with one unit of export commodities compared with the base period, or, in other words, its import capacity improves. If the NBTT decreases, this country is able to exchange less import commodities with one unit of export commodities compared with the base period, or, in other words, its import capacity declines. Nonetheless, the real economic activity is much more complicated and the changes in trade terms are the result of multiple factors. Therefore, we should not generalize about the NBTT’s influence on the trade interest of a country. Rather we must make

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specific analysis in this regard. In the course of economic growth, the deterioration of a country’s NBTT does not mean the absolute deterioration in its trade. NBTT focuses on the prices on the international market and therefore reflects changes in the international value rather than the national value. Similarly, even if the trade terms of a country remain constant, it does not necessarily follow that there is no change in its trade interest—it is probably because some changes in the trade interest caused by relevant factors (such as cost, demand, and supply) are ignored. As the NBTT describes, by means of price variation, the deterioration or improvement of a country’s competition conditions on the international market, it can directly reflect the changes in this country’s benefit from its imports in exchange for exports. A rise in the NBTT indicates relative increase in export prices or relative decrease in import prices, which means a higher value of imported goods in exchange for exported goods and, ceteris paribus, an expansion in the trade benefit. On the contrary, a decline in the NBTT indicates relative decrease in export prices or relative increase in import prices, which means a lower value of imported goods in exchange for exported goods and, ceteris paribus, a shrinkage in the trade benefit.13 Therefore, the NBTT index is the most practical indicator of the trade terms. As we can find in Table 1.11, China’s NBTT is clearly on the decline.

1.3  Research Topics on the Dynamic Evolution of China’s Comparative Advantages From a global perspective, we are currently in a development stage of multi-dimensional globalization; from China’s standpoint, it is now in a historical period of growth transformation. China’s economic growth in every stage is realized relying on the most basic comparative advantages within certain institutional frameworks. China’s position in the world economy is consistent with the size, structure, and quality of its comparative advantages. Yet, as periodical growth factors, some comparative advantages are bound to enter a stage of decreasing returns sooner or later like other production factors. Therefore, in order to sustain long-term 13  As there are too many commodities in international trade, it is impossible to use the individual price index in calculation of the price index. Usually we adopt the general price index in the form of the weighted average of many commodity prices. So the NBTT reflects not the absolute amount but the change in trade benefit.

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Table 1.11  Changes in China’s NBTT, 1995–2017 Year 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Index of export prices 100.00 101.90 102.86 99.05 96.19 95.24 92.71 89.74 91.63 99.96 102.66 106.97 112.43 121.42 113.90 116.74 129.12 131.18 130.40 130.78 127.66 116.14 117.06

Index of import prices 100.00 98.06 95.15 91.26 94.17 97.09 96.99 99.32 100.51 112.27 118.33 121.88 129.44 147.69 127.46 145.05 166.51 167.68 164.83 160.73 140.64 128.23 136.70

NBTT 100.00 103.92 108.10 108.53 102.14 98.10 95.58 90.36 91.16 89.04 86.76 87.77 86.86 82.22 89.36 80.49 77.54 78.24 79.11 81.37 90.77 90.57 85.63

Source: UNCTAD database, calculated and sorted by the author

growth of the Chinese economy through transformation, we must bring into shape new sources or new portfolios of comparative advantages. For China’s economic growth, it is necessary to rebuild its comparative advantages so as to adapt to the demands of a new stage of growth. In order to study the dynamic evolution of comparative advantages, it is necessary to understand the inherent logic of the development of the theory of comparative advantage, and it is particularly important not only to unpack the theory itself but also to trace its historical development. Starting with the attributes of comparative advantages, we will try to understand how comparative advantages is able to evolve over time by examining the development and the dynamic performance of the theory of comparative advantage and how to assess the dynamic evolution and dynamic capacity of comparative advantages. Our research will lay a solid foundation for further analysis of the contents of the dynamic evolution of

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China’s comparative advantages. What problems does China face with in the new stage of development of its comparative advantages? We must make in-depth analysis from the perspectives of the trend and challenges. How to evaluate the degree of dynamic evolution of China’s comparative advantages in the international economy? This involves its net income in the international trade and may be studied by way of a research on its trade terms. Since the two famous development economists Raúl Prebisch and Hans Singer put forward the theory of deteriorating trade terms for developing countries, there has been a protracted argument over it. As the world enters a new round of globalization, the debate about this topic has taken on new meaning and value. Through forty years of reform and opening-up, China has grown into one of the most important economies in international trade, and the relationship between China’s trade development and trade terms has become an important part of research on its dynamic comparative advantages. As the trade terms theory is rich in meaning, it is worthwhile for us to further explore how to scientifically and comprehensively estimate China’s trade terms and their changes in different stages, and whether it is feasible to take changes in the trade terms as a measurement of the dynamic comparative advantages. To meet these challenges, however, we must seek and analyze what weakens the trend of dynamic evolution of China’s comparative advantages. The effect of China’s trade and industry policies on the dynamics of its comparative advantages has always been a key focus of applied economics and theoretical studies. Yet only by making qualitative and empirical studies can we accurately evaluate the effects of such policies. Obviously, we must contemplate the path of dynamic evolution of China’s comparative advantages against the background of the dual constraints, i.e., the global economic conditions and the domestic structural adjustments. Within the analytical framework of endogenous and exogenous comparative advantages, we must lay more emphasis on improvements of the endogenous sources of comparative advantages, which are more sensitive to dynamic changes, and put forward paths for the dynamic evolution of China’s comparative advantages. This is consistent with the real changes in the sources of China’s comparative advantages. The constraint of limited natural resources on economic growth is an old topic. Since the times of Thomas R. Malthus, people have been paying attention to the influence of the depletion of natural resources—such as land, oil, and mineral resources—on growth, but growth stagnation due to the consumption of natural resources has never occurred. This is

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probably because technological progress, human capital, and the increasing scale have offset the constraint of natural resources on growth. Yet what effect will the exhaustible resources have on the dynamic evolution of China’s comparative advantages? One of the characteristics of natural resources is that they are largest in stock in the primary stage, but with the increase of resource consumption their stock decreases. Therefore, resource constraint does exist unless alternatives can be found at a large size. According to the theory of exogenous comparative advantages, the difference in resource endowments determines the comparative advantages among countries. As it is short of resources on a per capita basis, China is subject to an obvious resource constraint on the dynamics of its comparative advantages, which will impede its economic growth. Our first consideration should be given to the transformation and development of the resource-based economy. Yet the further question is how a resource-­ deficient country can obtain comparative advantages in international competition. Now that the opening economy has provided external conditions for China to break away from its resource constraints, the theory of endogenous comparative advantages must focus on how to obtain comparative advantages—other than resource advantages—under the condition of an opening economy. Endogenous comparative advantages are not necessarily related to the resource endowments of a country—they are not endowed by nature, but created by this country or acquired through hard work. Two countries similar in resource endowments can be quite different in their competitiveness. A country with better resource endowments may not be highly competitive, while a country with poor resource endowments may be highly competitive—there are plenty of such examples. Therefore, an important topic for the development strategy of a major country is how to create new competitive advantages or shake off the resource dilemma during the transformation of the resource-based economy. Fundamentally, a country’s comparative advantages are determined by its factor endowment structure. For this reason, it is believed that factor accumulation is the core of the dynamic evolution of comparative advantages.14 With the accumulation of production factors, the internal factor endowment will change, so will the comparative advantages. Under the 14  Justin Yifu Lin and Li Yongjun, “Comparative Advantages, Competitive Advantages, and the Economic Development of Developing Countries,” Management World, no. 7 (2003): 21–28.

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condition of economic opening-up, a country’s dynamic comparative advantages depend, to some extent, on the relative changes in the factor endowments of other countries. Yet what relationship among the factors is the most conducive to the improvement of the comparative advantages? Some economists analyzed the rapid economic growth in Japan and other East Asian countries and found that the most important driving force for the economic miracles therein is not necessarily a high-level savings rate or more efficient technological progress, but a high level of capital-labor substitution elasticity in these countries. It is thus necessary to take into consideration the relation between factor substitution and economic growth when we study the core issue of the dynamic evolution of comparative advantages, namely, factor accumulation. As for China, it has achieved a high level of capital-labor substitution elasticity and sustained rapid economic growth since the implementation of reform and opening-up. But how to realize long-term, steady economic growth under decreasing marginal returns to investment? With the development of the Chinese manufacturing—especially with the rapid growth of China’s labor- and resource-intensive industries, the prices of labor, energy, and other factors gradually increase, so do the production costs of the Chinese manufacturing.15 Therefore, we must value the capital-labor substitution elasticity in economic growth, comprehend the relationship between factor substitution and dynamic comparative advantages in the course of factor accumulation in light of factor substitution and technological progress, and realize the effective and rational allocation of factors by means of technological progress, so as to boost the dynamic evolution of China’s comparative advantages. Closely related to the factor endowment structure is human capital. The positive correlation between human capital accumulation and economic growth has long been confirmed by economists. In the theory of comparative advantages, human capital accumulation is closely related to endogenous sources, such as learning by doing, technological innovation, labor division, and professionalization. Human capital accumulation is different from physical capital accumulation in that, as Robert E. Lucas Jr. 15  From 2001 to 2010, the total costs of Chinese manufacturing (including capital, labor, energy, and input in intermediate goods) increased by 3.19 times, or approximately 13.76% annually (Statistics provided by the author). Meanwhile, the value added of Chinese manufacturing increased from RMB 3461.423 billion in 2001 to RMB 8850.267 in 2010, up by 2.56 times or an annual average of 10.99% only (The World Bank database).

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pointed out, the former follows a law—a certain degree of endeavor results in the growth of the human capital stock at a constant rate, irrelevant to the size of the existing stock.16 As Lucas further pointed out, human capital accumulation is a social phenomenon that involves human groups, and therefore poles apart from physical capital accumulation in forms.17 Yet while making further studies on the role of human capital in the dynamic mechanism of comparative advantages, we have to distinguish the concepts of human capital stock and human capital structure, which are correlated but different in meanings. Theodore W.  Schultz made a clear distinction between the two because, in his eyes, the productivity value of human capital endowment depends largely on its composition which is related to the opportunity on the market that serves it. According to Schultz, the heterogeneity of the concept of human capital is reflected in the incremental way in which wages increases with the level of professional training workers have received. In fact, he agreed that the composition of human capital has a greater influence on technological absorption and innovation than the average stock of human capital does. Of all the factors boosting economic growth and convergence of income levels, which makes a greater contribution? The human capital stock or the human capital structure? This depends on which stage of development a country is in and its socioeconomic structure. As there is abundant literature on human capital and the dynamic evolution of comparative advantages, we will focus on the role of human capital structure, highlighting the importance of the optimization of human capital composition. According to the meaning of dynamic comparative advantages, they are closely related to human capital accumulation. In our findings, apart from the fact that, as a production factor, human capital boosts comparative advantages, the structural optimization of human capital and human capital stock contribute to the realization of dynamic comparative advantages. As a source of dynamic comparative advantages, the structure of human capital was already discussed in earlier literature of economics of development. When discussing appropriate technology that matches the technological demand of a developing economy, people have come to see that the real value of localized education will exceed that of ubiquitous education. And this is in fact a matter of human capital structure. As the structure of human capital 16  Theodore W. Schultz, Origins of Increasing Returns (Beijing: Peking University Press, 2001), 25. 17  Ibid.

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underlines, different stages of development and different levels of industrialization require different types of professionals and different structures of knowledge. When human capital stock reaches a certain threshold, the rationality of human capital structure—the appropriate match with the structure of human capital demand—will play a fairly positive role on the dynamic evolution of comparative advantages. It is generally believed that the establishment of a state innovative system is important part of social innovation, without which it is impossible to directly link up the technological gap and the special knowledge gap,18 and technological innovation cannot gain effective support from intellectuals, organizations, or other social resources. Therefore, the stability and diversity of a country’s innovative system is an indicator of its capacity to boost technological accumulation. Undoubtedly, technological innovation is an important source of endogenous comparative advantages, whereas the innovative system is the source of exogenous comparative advantages. Technological progress requires support of the innovative system. An innovative system can be regional, sectoral, national, or global. In such a big country as China, whether its regional innovative systems work has a direct influence on the efficiency of the national innovative system. Based on the uneven regional development and the fundamental role of the regional innovative system in China, we will focus on the country’s regional innovative system while studying the technological innovation mechanisms. By analyzing the weaknesses in China’s regional innovative capacity, we will aim at supporting the development of regional innovative capacity, so as to facilitate the progress in China’s overall comparative advantage. Is industrial agglomeration another source of endogenous comparative advantages? The answer is yes. Agglomeration leads to economies of scale and is positively significant for the formation and development of comparative advantages. On the one hand, such agglomeration is the clustering of enterprises. It not only results in advantages of the enterprise clusters, but also gains competitive advantages for and boosts the development of individual enterprises within the aggregation area, which further facilitates the expansion and growth of the whole aggregation area. Agglomeration economies refer to the aggregation of the production of correlated products on a certain scale in a certain area, which reduces the 18  Paola Criscuolo and Rajneesh Narula, “National Absorptive Capacity and the Stage of Development,” Report at Conference on “Innovation, Learning and Technological Dynamism of Developing Countries,” (2013) Maastricht.

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production costs or transaction expenses of the enterprises. On the other hand, such agglomeration is also the concentration of factors. As enterprises aggregate, the factors also concentrate more quickly in a particular space. As it reduces the factor and transaction costs, the agglomeration of factors and enterprises can stimulate the industrial growth within a given space, giving rise to the “oasis effect.” Under the trend of deepened development of the international division of labor, regional industrial aggregation and division is the basis for establishing industrial comparative advantages. Industrial agglomeration and comparative advantages are correlated variables that determine growth. They reflect the spatial heterogeneity of industrial economic behavior and resource endowments from different perspectives. Comparative advantages are the basis of industrial agglomeration, while the cyclical growth of industrial agglomeration accumulates and creates new advantages. In this way, we can realize the dynamic evolution of comparative advantages and boost the structural upgrading of comparative advantages. In China, a big developing country, there are large gaps in its regional comparative advantages. Meanwhile, due to the heterogeneity of its industrial agglomeration, there are significant differences in its regional growth effect as well as in the speed of dynamic evolution of comparative advantages in its different regions. Therefore, the conflict and integration of dynamic evolution of comparative advantages with industrial agglomeration is the key to boosting regional growth transformation and coordinated regional development. To study the dynamic evolution of China’s comparative advantages, it is impossible to avoid industrial agglomeration in the country. Is the size of the local market a new source of comparative advantages? If there is an “excessive demand” for a commodity in a given region, such need in the regional market will produce an “amplification effect” which causes the production to exceed the demand right there and thus realizes the export of this product. This is an important concept in spatial economics—“the domestic (home) market effect.” The amplification effect of such an “excessive demand” originates in the increasing returns to scale and the agglomeration effect. In the comparative advantage model, the excessive demand for a commodity will result in its export, and in the returns-to-scale model, a region with an excessive demand will become the area of production and export of this product.19 In other words, if an 19  D. R. Davis and D. E. Weinstein, “Does Economic Geography Matter for International Specialization?” National Bureau of Economic Research, no. w5706 (1996).

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industry has a home market effect within a region, there must be a large local demand for this industry, and to choose the industrial location on that basis can most efficiently improve the efficiency of resource allocation. According to the view of the “home market effect,” we must realize that economies of scale that exceed the factor endowments are a new source of comparative advantages. A similar topic for research is how to bring into play the comparative advantage of China’s market integration. Similar to industrial agglomeration, market integration can be regarded as a source of endogenous comparative advantages because of its economies-­ of-­scale effect. As Adam Smith narrated in The Wealth of Nations, the deepening of the division of labor and the expansion of the market will give rise to economies of scale. According to Smith, all economic entities in the division of labor are both producers and consumers, and there is a self-expansion mechanism, which keeps accumulating, between the division of labor and the expansion of the market. Moreover, the division of labor in different industries has an interactive effect, causing constant improvements of professional collaboration and market dependence of the overall economy. This is the dynamic mechanism among the division of labor, increasing returns, and economies of scale. Undoubtedly, market integration will facilitate this dynamic mechanism, whereas market segmentation will impede or ruin it. Through an empirical analysis of the segmentation and integration of the Chinese market, we find that the scale economies effect generated in this process is another force that boosts the dynamic evolution of comparative advantages. When comparative advantages are studied as the basis for a country’s participation in the international trade, the interactive relationship between trade development and comparative advantages is usually ignored—even though trade in itself can be a way to obtain comparative advantages. Meanwhile, based on the expansion of the source of comparative advantages under economic opening-up, the factors of development are better positioned to break the limitation of traditional boundaries and flow worldwide. In fact, the interaction between import and export is the most important way to facilitate the formation of state capital, technological progress, and structural adjustments. Therefore, the key to a country’s realization of its dynamic transformation of comparative advantages is to effectively “settle down” the factors of development flowing among countries by means of the factor-induced and factor spillover effects in its imports and exports. A remarkable characteristic of the Chinese economy is a long-term trade surplus in the world market and the international

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economy. Such a huge trade surplus is a monetary reflection of China’s comparative advantages brought into full play. Nevertheless, China’s export-oriented economic development is not targeted at the pursuit of an enormous trade surplus. Obviously, to sustain or seek a trade surplus— which is a mercantilist goal of trade—does not conform to China’s strategy to realize its dynamic comparative advantages. Trade imbalance is against the dynamic evolution of China’s comparative advantages. A worthwhile objective of China’s trade strategy is to find the joint point between its dynamic comparative advantages and the interactive and balanced development of its imports and exports. How to realize its dynamic comparative advantages under international fragmentation of production? This is a question we have to answer. The so-called international fragmentation of production refers to the division and allocation of the production of different parts of a product in different countries or regions. That is to say, each country only finishes a certain stage of the manufactured products. As China is already a participant in international fragmentation of production, such production has become an important factor influencing the exports of China’s manufactured products. The traditional theory of international trade does not take into account international fragmentation of production and thus cannot explain the influence of international fragmentation of production on export trade. Besides, in the academic circles, studies on relevant experience of China’s export trade are mainly macroscopic analyses on the determining factors of its trade volume growth. They seldom make specific analyses at the industry level or on the characteristics of Chinese products, such as the complexity, widening, and deepening of Chinese exports. Consequently, there is a shortage of studies that combine international fragmentation of production and the product characteristics of Chinese exports. Only by analyzing the structure, complexity, and widening of exports can we deepen our studies on the effect of international fragmentation of production. Undoubtedly, international fragmentation of production has already had a significant influence on the comparative advantages of China’s manufacturing exports. At present, though, the world production system has entered a stage of global production based on the international fragmentation of production. Under such circumstances, only by embedding itself into the global division of labor can the Chinese economy integrate into the world economic system and share the benefits of economic globalization. Accordingly, our research will focus on how to follow the trend of international fragmentation of production, upgrade the Chinese economy from the labor-intensive to the

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capital-intensive link on the global industrial chain, and improve the mechanism to realize China’s comparative advantages. What is China’s position on the global value chain? This is a symbol of the degree of the dynamics of its comparative advantages. China’s position in international division of labor keeps rising, but the major reason is the constant increase in the share of Chinese industries on the international market. Generally speaking, when the proportion of technology and capital exceeds that of labor and resources in the factor intensity of a country’s exports, evolution has taken place to the comparative advantages of this country’s industries. That is, an upgrading of its value chain is under way. According to Teece and Pisano,20 the innovation power for industrial upgrade comes from the processing procedures within an enterprise, including its improvement-oriented learning and its entry into other enterprises or the regional innovation system to develop its dynamic capabilities. Such changes are a process of value-chain upgrading marked by path dependence. With the constant deepening of industrial upgrade, the links of different values added on the value chain will be spatially optimized and allocated, and all the countries and regions will be arranged in the order of their factor endowments. Therefore, the division of the global value chain is a process of matching a hierarchical system with factor endowments in different parts of the world; it is also a process of vertical and spatial reconstruction of the various value links on the global value chain. In this process, the evolution of regional factor endowments determines the position of an industry on the overall value chain, while industrial upgrade achieves technological progress and market correlation with the help of the value chain and by means of the learning effect, and shifts toward economic activities of higher values, so as to improve the competitiveness of a country or region. Chinese industries taking part in international competition by increasing their share in the world market are faced with many difficulties, such as the rise in resource prices, the decline in product prices, and the increase of international trade frictions. How to shift from quantity expansion to quality improvement? This is a question China has to answer in order to raise its position in the international division of labor. Finally, we must study the interaction between national capacity building and dynamic evolution of China’s comparative advantages. The 20  D.  J. Teece and G.  Pisano, “The Dynamic Capabilities of Firms: An Introduction,” Industrial and Corporate Change 3, no. 3 (1994):537–56.

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concept of national capacity has successively developed from technological absorptive capacity to social absorptive capacity, to national technological absorptive capability, and finally to national capacity. Each updating of this concept is closely related to the evolution of the theory of comparative advantage. The development of such capacity is in essence the development of a country’s comparative advantages. And the variation in this capacity not only means the accumulation of factors, but also changes in the institutions and mechanisms. In this study, we must pay more attention to how a country shifts from technological absorptive capacity to national capacity in the process of economic catching-up and surpassing, in particular the role of its national capacity in the dynamics of its comparative advantages. As history and economic growth prove, in the long run, it is the combination of technological gaps and national capacity that determines the potential growth rate of a country or region. Nowadays, in the context of economic globalization and rapid development of high-­ tech revolution, if we continue to formulate our development strategy and industry policy merely based on the theory of comparative advantage of exogenous resource endowments, but ignore the comparative advantages based on our national capacity, our path of growth can hardly lead us toward a developed economy, and our economic and technological structures will forever remain on the lower end of the industrial and technological chains. Therefore, we must take the improvement of China’s overall technological capacity as the starting point of its development strategy, and occupy the industrial and technological high ground. We must also painstakingly establish our comparative advantages based on a powerful national capacity instead of the static natural endowments. Only in this way can we upgrade and update our industrial structure more rapidly and realize China’s economic transformation.

1.4  Conclusions In this chapter, we have teased apart and analyzed the theory of late-­ development advantages and the theory of dynamic evolution of comparative advantages. With so many publications in this regard, we are aware that our analysis is far from being complete. Yet we can still draw the following conclusions. In the evolution of economic thought, the theory of late-development advantages provides a theoretical support and strategic stimulation for the catching-up and surpassing of the late-development countries, while

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advanced technology and technological catching-up and surpassing provide a feasible path for developing countries to realize their late-­ development advantages. Meanwhile, the linear development of technology and non-linear technological breakthroughs make room for the catching-up and surpassing strategy of the late-development countries. The linear development of technology highlights the inevitability of technological accumulation and institutional evolutions, and under the constraint of the linear development of technology, a country’s development must conform to the inherent demand of its comparative advantages. Nonetheless, the history of technological development has never denied the possibility of mutations—non-linear development of technology can be found in many fields. It is also possible for some developing countries to realize limited or overall catching-up and surpassing, although such countries are few and far between. Fundamentally, limited and overall catching-up and surpassing relies on the aggregation and development of factors of comparative advantages, but it is also largely dependent on the formation and development of the social and national capacities. Thus, a close theoretical correlation has taken shape between the late-­development advantages and the dynamic evolution of comparative advantages. A basic characteristic of the theory of late-development advantages is the dependence on technological catching-up and surpassing, but nowadays the lifecycle of advanced technologies is becoming shorter and shorter, which poses a challenge to all the economies in their attempt of catching up and surpassing. In the Internet era, this is far more obvious, and this trend is accelerating. Against this background, the formation and development of new comparative advantages is more a strategic issue than just a theoretical one.

CHAPTER 2

Resource Constraints in the Dynamic Evolution of China’s Comparative Advantages Xincheng Zhao

Resources are a hot topic in the economic circles. On the one hand, resources provide a material foundation for economic development; on the other hand, due to the finiteness of resources and the infiniteness of human being’s desire to develop economy, resources can largely constrain economic development. The theory of comparative advantages indicates that countries and regions with abundant natural resources can sustain long-term economic growth relying on their comparative advantage of natural resource endowments. According to the experience of international economic development, for developing countries participating in the international division of labor and collaboration, the evolution of their industries of comparative advantages generally follows this pattern:

X. Zhao (*) Development Institute, Yunnan University, Kunming, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 X. Yang (ed.), China’s Qualitative Economic Transformation, https://doi.org/10.1007/978-981-19-4437-6_2

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resource-intensive industries ➔ labor-intensive industries ➔ capital- and technology-intensive industries. From the perspective of temporal evolution, no country or region can stay forever in comparative advantages because they evolve dynamically. Under the influence of technological progress and labor productivity, the current industries of comparative advantages may not be as such in the future. Similarly, China’s comparative advantages are also dynamically transforming. According to the materials at hand, China has already lost its comparative advantage in resources, which has become a significant constraint on China’s economic development. This chapter will first analyze the status quo of China’s comparative advantages in resources and then provide relevant literature and methods for analysis. After that, it will empirically analyze the resource constraints on and the impediments to Chinese and regional growth. Finally, it will put forward a path to realize the dynamics of the country’s comparative advantages, namely, the economic transformation of resources.

2.1   The End of the Myth of Comparative Advantages of Resources Natural resources provide a material basis for economic growth and have a profound influence on it. Since the 1990s, a good many economists have explored the influences and effects of natural resources on economic growth and come to the conclusion that both resource abundance and resource shortage are constraints on economic growth. They call the former “the resource curse” and the latter “the resource constraint.” In fact, the theory of comparative advantages has also paid attention to the resource problem in economic development. Developed by David Ricardo, this theory points out that, if two countries are different in the opportunity costs for producing the same product, the one with a lower opportunity cost has a comparative advantage in producing this product. The difference in the opportunity costs makes it possible for the two countries to conduct international trade. In the international division of labor, every country produces commodities in which it has comparative advantages and takes part in international trade, and thus realizes the common growth of the economy and the welfare. According to Ricardo’s theory of comparative advantages, countries and regions of abundant natural resources have a comparative advantage in producing resource-intensive products. Such is the comparative advantage of resources. And such countries and

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regions must develop their economy in keeping with their comparative advantages and export resource-intensive products for economic growth. Generally speaking, if they choose to produce and exchange according to the principle of comparative advantages, they can ensure both the sound growth of their trade and economy and the constant improvement of their social welfare. In terms of comparative advantages of resources, however, they find it difficult to sustain such an advantage for a long time and may get stuck in “the resource curse” as the stock of natural resources is finite and the prices of natural resources are unstable on the international market. Besides, in the development of industries with a comparative advantage of resources, if the resources—such as capital and labor—are excessively aggregated in natural resource sectors, it may result in some economic problems, e.g., the “Dutch disease.” In terms of China’s natural resource endowment, an important characteristic is that it has abundant natural resources but its per capita is usually lower than the world’s average due to its huge population. In many areas with rich resource endowments in China, the main way of utilizing the comparative advantage of resource is the traditional practice of exploiting whatever the land can provide—from water and soil to minerals and forests, and the major products in foreign trade are mainly natural resource products, which are at the bottom of the industrial chain. In the initial stage of economic development, such a practice does bring rapid economic growth. Yet such growth is unsustainable when the resources are depleted after a period of large-scale development, construction, and stable prosperity. If we view and utilize the comparative advantage of resources from a static perspective, we are very likely to be stuck in the “comparative advantage trap.” In the early years of international trade, developed countries, based on their technological and economic advantages, imported natural resource products from relatively underdeveloped countries which were only able to produce and export natural resource products of low value added due to constraints of their technological and capital levels. For sustained economic growth, these natural resource exporters went on with resource exports, which increased the burden on their natural environment. As a result, developed countries realized growth of their economy and welfare at the cost of the environment of resource exporters. On the other hand, by exporting resource-intensive products in keeping with the theory of static comparative advantages, resource exporters gained a shortterm economic growth but lost the capacity for sustainable economic and

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welfare growth. In face of the conflict between the economic theory and reality, many economists started to review the theory of comparative advantages. On the one hand, comparative advantages are not static— transformations can occur with the changes in time and conditions. Under the influence of technological progress, labor productivity, and other factors, some industries of comparative advantages at present may no longer be such in the future. For example, Country A currently has a comparative advantage in producing some resource-intensive products. But as time goes by, Country B has achieved major breakthroughs in its production technology, making its opportunity cost for producing similar products lower than that of Country A. In this way, Country A has lost its resource comparative advantage. On the other hand, the static theory of comparative advantages assumes that labor productivity and comparative advantages are exogenous and temporally static on the model for study. Yet economic development is a dynamic process and the theory of comparative advantages is not always valid in the dynamic process of economic development.

2.2   Literature Review 2.2.1   Resource Constraints and the Dynamic Evolution of Comparative Advantages From Adam Smith’s theory of absolute comparative advantages to David Ricardo’s comparative cost theory, neither mentioned the position of natural resources and resource endowments in the theory of comparative advantage. It was not until Eli F. Heckscher and Bertil Ohlin put forth the factor endowment theory that natural resources and resource endowments were incorporated into the framework of the theory of comparative advantage. The Heckscher-Ohlin theory uses a model of two countries, two commodities, and two factors of production. It assumes that, with identical technologies and different factor intensities, a country produces and exports products whose production is intensive in the factor that country is abundantly endowed, and tends to import products whose production is intensive in the factor that country is poorly endowed, so the comparative advantage between the two countries originates in different factor endowments. As all the above three theories compare the closed and trading situations of a country under unlimited conditions, they are invariably static in terms of the analysis method. Nonetheless, in the era of

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globalization when the meaning of factors has been largely expanded, it is likely to get developing countries stuck in the “comparative advantage trap” if we guide their international trade with such a static theory of comparative advantage. In order to better explain the economic reality with international trade theories, we must study the theory of comparative advantage from a dynamic perspective. The theory of dynamic comparative advantage is an inference of the traditional, static theory of comparative advantages and mainly studies the factors in comparative advantages and the welfare consequences over time. Internationally, based on the origins of economic growth, studies of the dynamic theory of comparative advantage are mainly divided into factor changes and dynamic comparative advantages, technological changes and dynamic comparative advantages, and changes in other factors and dynamic comparative advantages. In this chapter, we will mainly focus on the relationship between factor changes and dynamic comparative advantages. For example, a research by Bela Balassa1 shows that the difference between countries in physical capital and human capital leads to difference in export structures and that the export structure of a underdeveloped country upgrades with the improvement of its resource endowment structure. Gene M. Grossman2 argues that human capital is the major determining factor of a country’s mode of trade, and that intellectual resource endowment is important part of comparative advantages. In his theory of the product life cycle, Raymond Vernon3 elaborates on the changes in the flow of product trade in different stages of the product life cycle. In 1955, Shinohara Miyohei4 made dynamic changes to the traditional theory of comparative advantage. According to his analysis, all economic factors—including resource endowments—change dynamically in the process of economic development. Such changes differ much from country to country, causing changes in their positions in international economy. When the changes in a country’s factor endowment turn its comparative disadvantage into a comparative advantage, this country will obtain 1  B. Balassa, “Trade Liberalization and Revealed Comparative Advantage,” The Manchester School 33, no. 2 (1965): 99–123. 2  Gene M. Grossman and Elhhanan Helpman, “Comparative Advantage and Long-Run Growth,” The American Economic Review 80, no. 4 (1990). 3  Raymond Vernon, “International Investment and International Trade in the Product Cycle,” The Quarterly Journal of Economics 80, no. 5 (1966):190–207. 4  Shinohara Miyohei, Industrial Structure, (Beijing: China Renmin University Press, 1998).

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comparative interest. Later, H. Oniki and H. Uzawa5 analyzed the influence of capital accumulation on the mode of trade. They believed that, in the long run, trade only persists when there is international difference in technology and preference—or at least one of them. According to this pattern of trade, under long-term stability and equilibrium, one country with a higher saving propensity will specialize in the production of investment products, while the other with a lower saving propensity in the production of labor-intensive products. In R. Findlay’s theory of dynamic factor endowments,6 the most important variables of economy are the population growth rate and the savings rate if all the tradables are consumer goods and the capital stock is under the control of a non-trade sector. Under stable economic development, increases in the population growth rate will reduce the capital-to-labor ratio and the production of capital-intensive products. On the other hand, the short-term influence of increase in the savings rate is indefinite—it may raise or lower the output of capital-intensive products, but in the long run, it will definitely increase the output of capital-intensive products. 2.2.2   Empirical Analysis of Resource Constraints: A Study on the Growth Drag In the neoclassical growth theory that includes natural resources, the production function is the total output Y using capital K, labor L, and natural resources R, i.e., Y = F(K, AL, R). As this production function is featured by the constant returns of scale and decreasing marginal returns, it can be expressed using per capita output, namely, y = f(k, r). Using the production function of per capita output, we can analyze the influence of resource on economic growth and dynamic comparative advantages. On the one hand, per capita output is mainly determined by per capita capital and per capita natural resource. Due to the limitation of resource endowments, natural resources cannot grow forever. This will result in a certain degree of constraint—known as the growth drag—on economic growth in the long run. On the other hand, under the same per capita capital, there are dynamic transformations between the natural resource and labor as comparative advantages. When the natural resource grows faster than labor 5  H.  Oniki and H.  Uzawa,“Patterns of Trade and Investment in a Dynamic Model of International Trade,” Review of Economic Studies 32, (1965): 15–38. 6  R. Findlay, Trade and Specialization, (Harmondsworth: Penguin, 1970).

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and thus increases the per capita natural resource, it will get more abundant in the economy. According to the trade theory, this will cause a decline in the price of capital and is therefore conducive to the development of resource-intensive sectors. On the contrary, when labor grows faster than the natural resource, labor-intensive sectors will gain rapid development. Empirical studies of resource constraints on economic growth mainly focus on natural resources’ growth drag on the economy. Nordhaus7 incorporated natural resources in the production function and analyzed two neoclassical models of growth with8 and without9 resource constraints. In his approach, the growth drag is the variation between the growth rates of the two models under stable output per worker. On that basis, he calculated the total growth drag of land and other natural resources to be 0.0024 and the growth drag of land to be 0.0006 in the US. Copeland and Taylor10 also conducted empirical analysis of the influence of land and environment on economic growth, and made policy suggestions on how to avoid the constraint of land and environment on economic growth. Bruvoll, Glomstrd, and Vennemo11 simulated Norway’s welfare loss caused by the environmental drag using the dynamic CGE (Computable General Equilibrium). They defined the environmental drag as the cost of environmental constraints on the society. Noel12 analyzed the influence of energy on economic growth using the US statistics and concluded that oil scarcity between 1889 and 1992 had a significant impact on the economic growth of the US. Martin and Mitra13 analyzed the relationship between agricultural convergence and productivity growth using the panel data of 50 countries between 1967 and 1992, and found 7  W. D. Nordhuas, “Lethal Model 2: The Limits to Growth Revisited,” Brookings Papers on Economic Activity, no. 2 (1992):1–43. 8  The case with resource constraint is a real economic condition when labor and natural resource do not grow at the same rate, resulting in the decline of available resources per worker. 9  The case without resource constraint is a reference condition when labor and natural resource grow at the same rate, resulting in constant available resources per worker. 10  Brian Copeland and Scott Taylor, “Trade, Growth and the Environment,” NBER Working Paper, no. 9823 (2003). 11  A.  Bruvoll, S.Glomstrd, and H.  Vennemo, “Environmental Drag: Evidence from Norway,” Ecological Economics 30, (1999): 235–49. 12  D.  A. Noel, “Reconsideration of Effect of Energy Scarcity on Economic Growth,” Energy, no. 1 (1995). 13  W.  Martin and D.  Mitra, “Productivity Growth and Convergence in Agriculture and Manufacturing,” Economic Development and Cultural Change 49, no 2 (2002): 403–22.

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that land improvement technology was the major part of agricultural technological progress. Nagi14 pointed out the influence of natural resources— represented by land—on economic growth. Romer15 built an analytical framework for the growth drag. His model took into consideration the constraint of land and other natural resources on per capita economic growth, and his aggregate production function was in the form of C-D, namely, Y(t) = ­K(t)αR(t)βT(t)γ[A(t)L(t)]1 − α − β − γ. Suppose the growth rates of land and natural resources with resource constraint are 0 and -b, respectively, and both are n without resource constraint, then the difference in the growth rates of output per worker under these two conditions is the growth drag of land and natural resources Drag 

b     n

1   



 b  n

1   

drag of the natural resource, and



 b  n n , where is the growth 1    1   

n is that of land resource. 1  

As Romer’s measurement and calculation of the growth drag is simple and easy to operate, many Chinese scholars tend to use his framework to study the growth drag of energy, water resource, and land resource on the Chinese economy. Besides, some scholars have analyzed the constraint of natural resources on China’s urbanization process. For example, Liu Yaobin and Chen Fei16 made appropriate transformation of Romer’s framework and estimated that the growth drag of energy, land, and water consumption on China’s urbanization is 0.30099, and those of energy consumption, land consumption and water consumption are 0.1060748, 0.003557703, and 0.191362401, respectively. They further pointed out that, were China to retain the current level of resource consumption, it would face difficulty realizing the strategic goal of urbanization by 2015.

14  L.  R. Nagi, “Barriers and the Transition to Modern Growth,” Quarterly Journal of Economics 70, no. 1 (1956): 65–94. 15  David Romer, Advanced Macroeconomics, trans. Wang Genbei (Shanghai: Shanghai University of Finance and Economics Press, 2009), 26–31. 16  Liu Yaobin and Chen Fei, “The Growth Drag of Resource Consumption on China’s Urbanization Process,” China Industrial Economics, no 11 (2007): 48–55.

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2.3  Resource Constraint and China’s Growth Drag: An Empirical Analysis Many empirical studies have proven that, as the most basic economic resource,17 natural resource does constrain economic growth. Yet due to differences in resource endowments, technological levels, and labor growth rates, different countries and regions are faced with different growth drags of natural resource. Does China, a large, rapidly developing country, face serious constraints of natural resources on its economic growth? Based on Romer’s analytical framework, this chapter will make a quantitative analysis of the constraints of natural resources on China’s economic growth, so as to provide reference for the formulation of economic and land policies in China. 2.3.1   Empirical Model Setting and Data 2.3.1.1 Model Specification There is a wide range of natural resources, including water, land, energy, minerals, etc. Out of consideration for data availability and the importance of resources in production, this chapter only takes into account water, land, and energy resources. The aggregate production function is 

Y  t   K  t  E  t  W  t  T  t   A  t  L  t  









If we take logarithm on both sides, we get ln Y  t     ln  K  t     ln  E  t     ln  W  t    ln  T  t     ln  A  t  L  t  





(2.1)

where Y(t), K(t), E(t),W(t),T(t),A(t), and L(t) stand for yield, capital stock, energy, water resource, land resource, technological progress, and labor, respectively.

17  Karl Marx once quoted William Petty’s words—“Labor is the father of wealth, and land is the mother of wealth.”—to reveal the two origins of value in use. This proves the importance of land resource to human beings.

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We make the following assumptions on the growth rates of the factors of production. A. With the economic development and better exploitation of the land area, the • land resource of a country or region grows at a relatively low rate T  t   xT  t  although its land area is fixed. B. Labor and technological progress grow at g and n, respectively, •

•

so A  t   gA  t  and L  t   nL  t  . C. Energy resources exist mainly in the form of fossil energy, so the energy endowment E(t) may be assumed as fixed, but it will decrease with their consumption. We assume the growth rate of energy consumption is b, and we can prove that this growth rate of energy consumption is the declining rate of the energy endowment. In this chapter, we will use energy consumption and the opposite of the growth rate of energy consumption to represent energy input and the growth rate of energy resources, respectively. D. The land area of a country or region is fixed, but with more and more efficient utilization of the land, land resource also grows at a low •

speed T  t   xT  t  . • E. The changes in the water resource over time are W  t   yW  t  . Within Romer’s framework, we deduce and compare the economic growth rates per worker with and without natural resource constraints, and get the growth drag of natural resources on the economy as Drag  where

 n  b 1

,

 n  b  n  x   n  y   1 1 1

 n  x 1

, and

 n  y 1

(2.2)

respectively represent the

growth drags of energy, land, and water resources on the economy, and their sum is the growth drag of natural resources on the economy. As we can find in Formula 2.2, the growth drag of natural resources on the economy is determined by the capital elasticity α, energy elasticity β, land elasticity η, and water resource elasticity γ of the output, as well as the growth rates of labor, energy consumption, land resources, and water resources. It

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increases with the increases in the capital elasticity and natural resource elasticity of the output as well as the growth rate of labor, and decreases with the increases in the growth rates of the natural resources. From this much follows. On the one hand, the growth drag of natural resources on the economy is closely related to the economy’s dependence on capital and natural resources. On the other hand, it is necessary to appropriately control population growth in order to reduce the constraints of natural resources on economic growth. According to the theory of growth accounting, the increase in input factors and technological progress are the sources of economic growth. Yet in order to lower the growth drag, labor input must not grow too quickly. So the only way to lower the growth drag of natural resources on the economy is to facilitate technological progress. 2.3.1.2 Data Specification In order to make regression analysis, we must find the corresponding data of Y(t), K(t), E(t),A(t), and L(t). Considering the availability and consistency of the data, we choose relevant statistics between 1978 and 2017 as the basis of our empirical analysis. Our statistics are mainly from the National Bureau of Statistics (NBS) database and China Statistical Yearbooks. A. We take GDP as the output. We get the provincial GDP at current prices and the GDP index from the NBS database and convert them at the 2000 constant prices. B. We use the number of employees to represent labor input, and get provincial numbers from the NBS database. C. We calculate the capital stocks using the perpetual inventory method. We adjust the provincial capital stocks in Zhang Jun et al. Estimates of Provincial Physical Capital Stocks in China: 1952–2000, and convert them at the 2000 constant prices. D. We express energy input as energy consumption and get the amounts of provincial energy consumption from the NBS database. E. The land resource statistics in this chapter is the sum of farmland, woodland, and exploitable grassland areas in China Statistical Yearbooks 1978–2017. F. The water resource statistics are from China Statistical Yearbooks and the total water resource is discounted to 0.96 of the original statistics.

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We then decide a few parameters in different models. Between 1978 and 2017, the growth rate of labor is n = 1.71%; that of water resource is y  =  0.14%; that of energy consumption is b  =  5.43%; and that of land resource is x = 0.61%. 2.3.2   Empirical Analysis Through quantitative measurement, we find that the time series of the logarithms of real GDP, capital, labor, water resource, land resource, and energy consumption are second-order integrated series and have passed the co-integration test, and that there is a co-­integration relationship, namely, a long-term equilibrium, among these time series. Using Formula 2.1, we make a regression analysis and get the capital elasticity and the output elasticity of natural resources, such as water resource, land resource, and energy consumption. We then calculate the growth drag of natural resources on the economy using Formula 2.2. When we make regression analysis of Formula 2.1, we meet the problem of auto-correlation. Accordingly, we deal with the variables using the generalized difference method and eliminate the auto-correlation by way of variable conversion. Finally, we get the following regression result: n Y  t    6.008 0.647 ln  K  t    0.348 ln  A  t  L  t    0.0135 ln  W  t    0.321 ln  T  t    0.142 ln  E  t  

 2.57 

8.19 

 4.53

1.89 

AR 1  2.394  T  statistic is 6.83  AR  2   0.956  T  staatistic is  4.28  R 2  0.98439　 D.W  1.49469　 F  6932.18

 3.46 

 2.76 

(2.3)

Based on the results of Formula 2.3, we get the capital elasticity α, energy elasticity β, land elasticity η, and water resource elasticity γ. In combination with the statistics previously obtained (i.e., the growth rate of labor n, that of energy consumption b, that of land resource x, and that of water resource y), we calculate the growth drag of natural resources on economy using Formula 2.2. The results are displayed in Table 2.1. 2.3.3   Result Analysis 2.3.3.1 The Growth Drag of Water Resource As we can find in Table 2.1, without the constraints of land and energy resources (i.e., land and energy resources grow at 1.71%), the grow drag of water resource on the economy is 0.00060. That is to say, because water

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Table 2.1  Growth Drags of Natural Resources on Economy Resource

Water resource

Land resource

Energy resource

Natural resources (Sum of the three)

Drag

0.000599

0.009915

0.028694

0.039207

resource cannot grow at the same speed with labor (i.e., with the constraint of water resource in economic growth), China’s economic growth is 0.0599% lower than that without the constraint of water resource. This result is 0.0798% lower than what Xie Shuling et al. found in 2005.18 This is because our assumption of the growth rate of water resource is different from theirs. Xie Shuling et  al. assumed that the growth rate of water resource was zero, but we calculate and find, based on the collected data, that the annual average growth rate of water resource is 0.14%. Therefore, it is improper to assume that water resource is fixed when analyzing the growth drag of water resource on the economy. The growth drag of water resource on the economy is mainly determined by four parameters: the capital elasticity α, the water resource elasticity γ, the growth rate of labor n, and the growth rate of water resource y. It rises with the increase of the first three parameters and drops with the increase of the growth rate of water resource y. Of these four parameters, the growth rate of water resource y does not improve through policy or other measures, so we will not discuss it herein. In summary, the growth drag of water resource on the economy is determined by the capital elasticity α, the water resource elasticity γ, the growth rate of labor n, and the growth rate of water resource y. To reduce the growth drag of water resource, it is necessary to lower the economy’s dependence on factor input (water resource and capital) and raise its dependence on technological progress. Figure 2.1 shows the trend of changes in China’s water resources between 1978 and 2017. As we can find in Fig. 2.1, in this period, the total water resources of China fluctuated around 2700 billion cubic meters, with no significant increase or decrease. Meanwhile, China’s labor grew quickly compared with its water resources. From 1978 to 2017, the average annual growth rate of labor reached 1.71%. This indicates a rapid decline in its water resources per worker. On the other hand, China is in a 18  Xie Shuling, Wang Zheng, and Xue Junbo, “The Growth Drags of Water and Land Resources in China’s Economic Development,” Management World, no. 7 (2005): 20–26.

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Fig. 2.1  Dynamic Changes in China’s Water Resources. Source: The water resource statistics between 1981 and 1988 are the total annual runoff of rivers discounted to 0.96 of the original statistics; those between 1989 and 1996 are the surface water resources discounted to 0.96 of the original statistics; those between 1997 and 2002 are the sum of the surface water and ground water resources minus the overlap between them; and those between 2002 and 2017 are from China Statistical Yearbooks of Environment

stage of rapid industrialization and the growth model of this period determines its high demand on water resource input. China will have to face a severe situation of water utilization for a long time to come. Although the growth drag of water resource on the Chinese economy is currently small, it is far from negligible. 2.3.3.2 The Growth Drag of Land Resource Without the constraints of water and energy resources (i.e., land and energy resources grow at 1.71%), the growth drag of land resource on economy is 0.009915. In other words, because land resource does not grow at the same rate as labor (i.e., there exists land resource constraint in the process of economic growth), China’s economic growth is 0.9915% slower than that without land resource constraint. This result is lower than the conclusions drawn by other Chinese scholars. The growth drag of land resource on economy is 0.013201 according to Xie Shuling et al.,19 and 19  Xie Shuling, Wang Zheng, and Xue Junbo, “The Growth Drags of Water and Land Resources in China’s Economic Development,” Management World, no. 7 (2005): 20–26.

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0.0153 according to Cui Yun.20 This is mainly because the growth rate of land resource in this chapter is different from the assumption of Xie Shuling et al. They assumed that the growth rate land resource was zero. Yet as we can find by calculating the collected data, China’s land resource increased from 591.4793 million hectares in 1978 to 750.811 million hectares in 2017, up by 0.61% annually. Therefore, it is improper to assume that the land resource is fixed when analyzing the growth drag of land resource on the economy. The land resource we observe consists of farmland, woodland, exploitable grassland, and land for urban construction. There was little change in China’s woodland and exploitable grassland from 1978 to 2017, stabilizing at 262.89 million hectares and 313.33 million hectares, respectively. On the other hand, China’s farmland was on the decrease over the same period—it is an undisputable fact that China’s farmland has been decreasing year by year. In the broad sense of land resource, China’s land area is 9.6 million square kilometers and will not increase. The only thing we can do is rearrange the different uses of its land area. At present, China is faced with serious desertification and must strengthen the protection and rational exploitation of its land resource, so as to considerably alleviate the growth drag of land resource on its economy while obtaining a higher growth rate of the economy under the existing land resource conditions. 2.3.3.3 The Growth Drag of Energy on the Economy Without the constraints of land and water resources (i.e., land and water resources grow by 1.71%), the growth drag of energy resource on economy is 0.028694. In other words, because energy resource does not grow at the same rate as labor (i.e., there exists energy resource constraint in the process of economic growth), China’s economic growth is 2.8694% slower than that without energy resource constraint. Our result is a bit higher than the conclusion of Shen Kunrong et al.21 This is mainly because our estimates of the output elasticity of energy and the growth rate of energy consumption are higher than theirs. In recent years, the energy problem has become increasingly prominent in China. It mainly includes two aspects. On the one hand, energy consumption grew quickly, resulting in 20  Cui Yun, “The Growth Drag of Land Resource in Chinese Economy,” Economic Theory and Business Management, no. 11 (2007): 32–37. 21  Shen Kunrong and Li Ying, “The Growth Drag of Energy on the Chinese Economy,” Industrial Economics Research, no. 2 (2010): 1–8.

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Fig. 2.2  China’s Total Energy Production and Consumption 1978–2017. Source: China National Bureau of Statistics. China Statistical Yearbook 2017. Beijing: China Statistics Press, 2018

the rapid increase of the elasticity coefficient of energy consumption. The total energy consumption increased from 1.470 billion tons of standard coal equivalent in 2000 to 4.490 billion tons of standard coal equivalent in 2017, up by 6.79% annually. The elasticity coefficient of energy consumption jumped from 0.54 in 2000 to 1.62 in 2003 and 1.67 in 2004, and dropped to 0.44 in 2017. Figure 2.2 shows China’s total energy production and consumption. As we can see, the gap between China’s energy supply and demand has been widening since 1978, enlarging from −51.26 million tons of standard coal equivalent in 1978 to 900 million tons of standard coal equivalent in 2018. This means a significant increase in China’s energy dependence on foreign countries. On the other hand, as China’s economic development enters a new stage, people’s concern over the environment is also increasing. As a result, the extensive growth marked by high input, high consumption, high pollution, and low efficiency can no longer meet the needs of social development, and the sustained exploitation and destruction of the environment and energy and other natural resources has heralded a bleak future of sustainable growth of the Chinese economy.

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2.3.3.4 The Growth Drag of Natural Resources on the Economy The growth drag of natural resources on the economy is 0.039207. That is to say, because energy, water, and land resources do not grow at the same speed as labor (i.e., there exist constraints of energy, water, and land resources), China’s economic growth is 3.92% slower than that without natural resource constraints. 3.92% is a big figure and is worth our attention. As we can find from the formula for growth drag calculation, A. The capital elasticity of output is an important factor determining the growth drags of all sorts of natural resources on the economy, and there is a positive correlation between them—the higher the capital elasticity of output, the greater the growth drags of natural resources on the economy. In the process of production, the factor capital cannot be used alone—it must be used in combination with other production factors, the ratio of which is determined by the production technology. Usually, the greater the capital input relative to other production factors, the higher output elasticity of capital, and the more natural resources it requires to optimize resource allocation. When we take into account the finiteness of natural resources, we can find the combined effect of these two aspects—the constraints of natural resources on economic growth become much greater. B. As the model takes into account the economic growth rate per worker and meanwhile any increase in labor causes huge consumption of natural resources, the higher the growth rate of labor, the greater constraint of natural resources on economic growth. C. The output elasticity of natural resources is a direct factor in and is directly proportional to the growth drag of natural resources. This elasticity also reflects the economy’s dependence on natural resources. Intuitively, different industries have different degrees of dependence on natural resources, and reducing the share of resource-intensive industries in the overall economy can mitigate the dependence of the overall economy on resources. D. The growth rate of natural resources is another direct factor in the growth drag of natural resources. As we can see in Formula 2.2, the growth rate of natural resources is inversely proportional to that of natural resources—the higher the growth rate of natural resources, the smaller the growth drag of natural resource on the economy. Specifically, with the consumption of resources, the growth rate of non-renewable resources will be negative (it must be smaller than the

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growth rate of labor), and therefore non-­ renewable resources are bound to have a drag on economic growth. On the other hand, the growth rate of renewable resources is generally positive, and therefore, if a renewable resource grows faster than labor, it will not have a drag on economic growth. 2.3.4   China’s Economic Growth Outlook: A Forecast Based on Natural Resource Constraints Table 2.1 displays the growth drags of energy, water, and land resources on the Chinese economy. It is true that China’s economic growth is constrained by these resources. The growth drag of natural resources on the economy was 0.039207 from 1978 to 2017. That is to say, because energy, water, and land resources do not grow at the same speed as labor, China’s economic growth is 3.92% slower than that without natural resource constraints. If China did not improve its way to exploit natural resources and continued to consume them as it did between 1978 and 2017, natural resources would become a constraint on China’s economic growth in the future. From 1978 to 2017, the Chinese economy grew by 9.5% annually. Meanwhile, the Chinese labor grew by 1.71% annually. Therefore, the average annual growth rate of China’s per-worker output was approximately 7.8%. In combination with the growth drag of natural resources on the Chinese economy at 3.92%, we can predict China’s per-worker economic growth rate in the future. That is, the economic growth rate in Year (2017+n) is 7.8  ×  (1  −  3.92%)n. The results indicate that China’s perworker economic growth rate will drop below 5% by 2029 (Fig. 2.3).

2.4   Transformation of the Resource-Based Economy and Paths for the Dynamic Evolution of China’s Comparative Advantages 2.4.1   The Unsustainability of Resource-Based Comparative Advantages The so-called resource-based economy is an economic system dominated by resource-intensive industries. Its major characteristics are as follows. In terms of the regional economic structure, resource-based sectors

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Fig. 2.3  Prospect of China’s Economic Growth Against Natural Resource Constraints

(agriculture, energy, extractive industries, and primary raw materials) have an absolute advantage; in terms of the industrial system, resource-based industries are the pillars dominating the overall development of the regional economy; in terms of modes of trade, resource-based products (with resources as raw materials) dominate regional or international trade; and in terms of the input of production factors, the economic activities depend much on natural resources at a high cost of the resources and environment. In terms of the development model, a resource-based economy will first experience a period of prosperity and then enter a period of stable development. Finally, when its natural resources are depleted, its development will become lackluster. On the one hand, the basis of a resourcebased economy is the differences in resource endowments among countries or regions. In its early years, a resource-based economy will manifest an acute dependence in the degree of resource exploitation and the cyclic utilization of resources, and facilitate the formation of a typically resourcebased economic system. Most resource-based regions are usually constrained and overburdened by their resource advantages. In terms of economic performance, they are usually lower than the average growth rate. On the other hand, since the 1970s, many resource-abundant countries have more or less been afflicted by the problems of resource-based economy. As country-­specific empirical studies indicate, resource abundance has not contributed to rapid economic growth of such countries or

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regions—rather it has become a drag on the economic growth. It seems that the enrichment and prosperity of resources cannot get them out of the destiny and the iron law of economic stagnation. There are five typical problems in the development of resource-based economy: deindustrialization caused by deterioration of the trade conditions; unfair distribution of resource income; economic fluctuation and the budget dilemma caused by fluctuations in resource prices; capital flight, consumption spillover, and irrational consumption; and the cyclic development of the system and structure of the resource industries. 2.4.2   Paths for the Transformation of Resource-Based Economy When a resource-based economy has lost its comparative advantages in resources, economic transformation is a way to realize the dynamics of its comparative advantages. The industrial transformation of such an economy may follow a path of natural evolution (i.e., natural-resource-intensive ➔ labor-­intensive ➔ capital- and technology-intensive), so as to realize dynamic conversion of its comparative advantages. In fact, it does not have to follow that path of transformation, but may jump from natural-resourceintensive to capital- and technology-intensive development. Economic transformation is a process for resource-based economies to change their model of development for sustainable development, in which the resourcedependent development model, with a single structure, converts into a pluralistic model of development for new points of economic growth. In essence, it is a process of integrating all sorts of production factors, public resources, and institutions for further optimization of resource allocation. And its goal is to change the functional orientation and overall outlook of such economies, to adjust and optimize their economic structure, and to explore new paths for their development. 2.4.2.1 Dynamic Evolution of Comparative Advantages by Means of Cyclic Economy Before a resource-based economy has completely lost its comparative advantages, it can strengthen its comparative advantages in resources by developing the cyclic economy, which is one of the major paths for transforming the resource-based economy. In fact, the cyclic economy is a change in the philosophy of economic development: a transition from a model that values speed and GDP but ignores efficiency to a new model that gives equal weight to speed and efficiency and values the quality of

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economic growth; a conversion from extensive growth that values extension and expansion but ignores the meaning to intensive growth; and a shift from the traditional linear growth based on resource consumption to growth based on cyclic utilization of biological resources. Therefore, the cyclic economy may be regarded as a model of economic development that has integrated the economic growth model, the environmental governance model, the intensive utilization of resources, and environmental protection. The cycle of resource utilization (i.e., resources➔ products➔recycled resources) can create the greatest possible economic benefits using the least possible resources. In order to develop the cyclic economy, resource-based economies must establish an economic circulatory system that reuses resources several times and reduces dependence on resources. They must improve their efficiency of resource utilization and realize the transformation from a single mechanism into a comprehensive mechanism of resource utilization. They must strengthen the comprehensive utilization, reutilization, and cyclic utilization of energy resources by means of technological progress, and boost the conversion of waste into energy resources. They must conduct energy-saving management throughout the links of resource production, transportation, processing, and utilization. They must enhance the role of technological progress in every link of production, replace material input with technological input, and achieve harmony between economic development and ecological environment. 2.4.2.2 Dynamic Evolution of Comparative Advantages by Means of Industrial Upgrade For resource-based economies, the adjustment and improvement of their industrial structure means to fully and reasonably bring into play the influence of the dominant industries and to carry out longitudinal development, technological progress, and industrial transformation of the dominant resource industries, to extend the industrial chain and strengthen the intensive processing of resource products, and to increase the output efficiency of unit resource, so as to boost the sustainable growth of the regional economy and realize dynamic transformation of the comparative advantages from resource-­ intensive industries into other forms of industries. By way of industrial upgrade, resource-based economies can free themselves from dependence on non-renewable resources and realize the transformation of their leading industries from resource-intensive into non-resource-intensive industries, and thereby facilitate the

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transformation and upgrading of the resource-based economy. They can also realize the transformation from one single leading industry into multiple leading industries. By means of vertical development, technological progress, and industrial transformation of the dominant resource industries, they can extend their industrial chains, cultivate the development of emerging industries, bring into shape industrial and product systems with regional characteristics, and gradually free themselves from dependence on resource-intensive industries. 2.4.2.3 Dynamic Evolution of Comparative Advantages by Means of Structural Adjustment of Resource-Intensive Industries The various industries of an economy are different in their degrees of dependence on natural resources and their growth drag on the economy. By adjusting the industrial structure, we can reduce the growth drag of natural resources on the economy. Generally speaking, the advancement and rationalization of the industrial structure are two key parts of industrial structure adjustment. The rationalization of the industrial structure emphasizes the coordination and balance among different industries in quantitative proportions, economic and technological relations, and industrial interactions. In contrast, the advancement of the industrial structure refers specifically to the upgrading of the industrial structure, a process of transforming the lower form into the higher one of the industrial structure system. 2.4.2.4 Transformation of Comparative Advantages by Improving Capital Utilization Efficiency The dependence of economic growth on the input factors (especially capital) is an important determining factor of the growth drag of natural resources on the economy. Therefore, to reduce the economy’s dependence on capital can alleviate the constraints of natural resources on growth. Effective ways to reduce the dependence of economic growth on capital include improvement of investment efficiency, effective utilization of the capital stock, etc.

2.5   Conclusions In this chapter, we have discussed the resource constraints in the dynamic evolution of China’s comparative advantages by empirically analyzing the constraints of resources on the economy, namely, the growth drag, and the

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approach to dynamic evolution of China’s comparative advantages—the transformation of resourced-based economy, and come to the following conclusions. Countries or regions with comparative advantages in resources may perform well during the period of prosperity and stability of natural resource development, but they tend to lag behind regions with poor resource endowments in terms of economic development when their resources are depleted. Resource-abundant regions may get stuck in the “comparative advantage trap” or the “resource curse” if they develop their economy according to the static theory of comparative advantage. Therefore, it is necessary to analyze comparative advantages in resources from a dynamic perspective. The growth drag of natural resources on the economy was 0.039207. That is to say, because energy, water, and land resources do not grow at the same speed as labor, (i.e., there exist constraints of natural resources in the process of economic growth), China’s economic growth is 3.92% slower than that without natural resource constraints. 3.92% is a big figure worthy of our attention. The transformation of resource-based economy is an approach to dynamic evolution of comparative advantages. In order to realize such a transformation, we must develop the cyclic economy, boost industrial upgrade, adjust the industrial structure, and improve the efficiency of capital utilization, so as to achieve dynamic evolution of comparative advantages.

CHAPTER 3

Factor Substitution, Technological Progress, and the Dynamic Evolution of Chinese Manufacturing’s Comparative Advantages Meng Zheng

In the context of globalization, China is accelerating its integration into the global economic system by making full use of its comparative advantages and the development opportunity brought about by international industrial transfer. In this process, Chinese manufacturing is the most striking industry and has benefited most from economic globalization.1 In the development of Chinese manufacturing, however, there is still the problem of dynamic transformation of comparative advantages. In this chapter, we will make an in-depth study on this issue using the statistics of the 29 sectors of Chinese manufacturing. 1  According to calculation by HIS, a US research institute, the total output of the world’s manufacturing was USD 10 trillion in 2010. Of that figure, China accounted for 19.8%, a bit higher than that of the US (19.4%). This has been borne out by the United Nations Statistics Office. In terms of the output, China has been the world’s largest manufacturer since 2010.

M. Zheng (*) Development Institute, Yunnan University, Kunming, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 X. Yang (ed.), China’s Qualitative Economic Transformation, https://doi.org/10.1007/978-981-19-4437-6_3

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3.1   Introduction No matter in high- or middle-income countries, the development of manufacturing basically synchronizes their economic growth. If we review the history of the US manufacturing, we can find that the US—by virtue of its advanced manufacturing—had become the world’s largest manufacturer by the end of the nineteenth century and maintained its position until 2009. In the early 1950s, the US accounted for approximately 40% of the world’s manufacturing value added. In the 30 years that followed, however, due to the demand of the arms race and the upsurge of the “postindustrial society,” its share of global manufacturing reduced nearly by half. In the 1980s, the US implemented measures to rescue its manufacturing, but its proportion in the world manufacturing still lingered below 30% and even dropped below 20% when the financial crisis broke out in 2009. In sharp contrast, China has established necessary advantages for the development of its manufacturing based on its cheap labor, land, and other production factors since the implementation of its reform and opening-up in 1978. Moreover, after its entry into the WTO, China has significantly increased its proportion in the world’s manufacturing value added while the US, Germany, EU, Japan, and other developed economies underwent significant decreases. In 2010, China surpassed the US and became the largest manufacturer in the world and became the world’s second largest economy. The dynamic evolution of comparative advantages is an effective driving force for steady and sustained economic growth. As a great concern of the Chinese government, how to transform China’s comparative advantages is a key issue to address. This is because, on the one hand, since its reform and opening-up—especially in the twenty-first century, China has brought into full play its advantage in labor resources against the background of globalization and grasped the opportunity for development brought about by international industrial transfer. It has actively taken part in the international division of labor, rapidly integrated itself into the global economic system, and realized high-speed growth of its economy. As a result, China is playing an increasingly important role in the world economy. On the other hand, as quite a few scholars’ research indicates, there are some defects inherent in the traditional theory of comparative advantages, which have adverse effects on the sustained economic growth of late-development countries. That is, if developing countries participate in the international division according to the static principle of

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comparative advantages, they will find it difficult and even impossible to catch up with developed countries—it will only widen the gap and get them into the “comparative advantage trap.” Accordingly, some industrial countries in East Asia (e.g., Japan and South Korea), have made rational changes in the traditional, static principles of comparative advantages in their development and realized the transformation into dynamic comparative advantages, and thus embarked onto the road of surpassing development. At present, the Chinese manufacturing is faced with both internal and external pressures. This not only inhibits its development and is likely to get China stuck in the “comparative advantage trap,” but will make it difficult for China to upgrade from a big manufacturing country into a manufacturing powerhouse. In terms of the internal pressure, with the changes in the age structure of the Chinese population and the prominent problem of energy security, structural contradictions are still conspicuous and the competitiveness of the Chinese manufacturing, which used to sustain relying on the advantage of cheap costs, are being gradually eclipsed. In terms of the external pressure, the international financial crisis has resulted in a sluggish global economy and recovery remains tenuous. Many countries have come to realize the importance of the real economy—manufacturing in particular—in creating employment and boosting growth, and have successively implemented corresponding strategies to rejuvenate their manufacturing so as to seize the opportunity of world economic and technological development. For example, after the financial crisis, the US launched a series of measures, including the “Export Doubling Plan” and the “Reindustrialization Strategy.” Germany implemented the “Industry 4.0 Strategy” aiming at promoting the level of smart manufacturing through the integration of informatization and industrialization. In 2015, China introduced the “China Manufacturing 2025” initiative aimed at realizing the strategic goal of a manufacturing powerhouse. Yet if China continues to count on the extensive model of economic growth achieved in the past relying on labor- and resource-intensive industries, it will be difficult for Chinese manufacturing to realize smart development. Meanwhile, in view of the growth history of other countries and the evolutionary logic of their comparative advantages, the original comparative advantages can no longer support sustained growth of the Chinese economy in the new stage of development. It is thus clear that the internal and external pressures will further highlight the urgency and necessity for Chinese manufacturing to dynamically transform its comparative advantages.

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3.2  Theoretical Analysis 3.2.1   Calculation of Capital-Labor Substitution Elasticity The elasticity of factor substitution between capital and labor is an important parameter determining the production function and is therefore a core variable of concern in this chapter. Yet it is impossible to obtain directly. All we can do is choose a suitable production function and estimate the elasticity of factor substitution. We teased apart and analyzed relevant literatures, and determined the following steps of research (For the specific method of calculation, please refer to Zheng Meng et  al.) (Fig. 3.1).2 3.2.2   Factor Substitution and the Dynamic Evolution of Comparative Advantages In this section, we will first introduce the CES (constant elasticity of substitution) production function, expressed as Formula 3.1: Yt  AF  K t ,Lt   A  aK t  1  a  Lt 

1/

(3.1)

where A > 0 > 1 > a > 0 > 1 > ψ >  − ∞. We assume that the CES production function follows the principle of constant returns to scale, so the homogeneous production function is Yt  F  K t ,Lt   Lt f  kt ,1  yt  f  kt 



Choose a translog

Estimate the

Calculate the Allen Partial

Calculate the Cross-Price

Calculate the Morishima

cost function based

parameters in the cost

Elasticity of Substitution

Elasticity (CPE) using

Substitution Elasticity (MES)

on sample needs

function

(AES) using the parameters

the AES

based on the

CES

Fig. 3.1  Steps of Research

2  Zheng Meng, Yang Xianming, and Li Bo, “Biased Technological Progress, Factor Substitution, and the Costs of Chinese Manufacturing: A Study Based on the Panel Data of 30 Trades,” Journal of Contemporary Finance and Economics, no. 2 (2015): 85–96.

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where yt  =  Yt/Lt stands for the output per worker, kt  =  Kt/Lt for the capital-labor ratio, and σ  =  1/(1  −  ψ) for the capital-labor substitution elasticity, and the marginal capital-labor substitution rate is mt = [f(kt) − kt f'(kt)]/f'(kt)] = (1 − a)kt1 − ψ/a. Then we determine the base value of the capital-labor ratio as k > 0 , that of the output per worker as y , and that of the marginal substitution rate as m > 0 . So Formula 3.1 can be standardized into







yt  f  kt   A   a   kt  1  a    1 /



 k 1  m  where A    y    k m 

and a   

1/

(3.2)

k 1 k 1  m

(3.3)

As we can find in Formula 3.2, a is a variable parameter in the production function, which is a distinct difference between the CES production function and the C-D production function. When the capital-labor ratio is at its base value, the share of capital is  t  k    We substitute Formula 3.3 into Formula 3.2, and get 1/

y   yt  f  kt     k   t 



kt

 1 k k k where    t  kt    t 1 k m k k m

(3.4) (3.5)

We further derive σ using Formula 3.4 and get f  kt 





 1 1  yt  ln 

2 2  

  1      1    ln  1       

(3.6)



As the logarithmic function y =  ln x is strictly concave (the first-order derivative>0 and the second-order derivative 0. Obviously,1 + δ > 0, so only when Country 1 chooses an appropriate level of productivity in its R&D activity can it guarantee that  h1   h2   z1   z2  0 on the left side of Formula 10.18.



 



Conclusion 2  Under the condition of opening-up, specialized R&D input influences the dynamic changes in the comparative advantages by means of the production efficiency of the R&D activity, and this influence path is free from the constraint of the initial economic size and the level of knowledge accumulation. Conclusion 3  Under the condition of opening-up, it is uncertain whether a country can obtain dynamic comparative advantages by means of specialized R&D input. If it has an absolute advantage in the R&D efficiency of a product of which it has initial comparative advantages, and if it has an absolute disadvantage in the R&D efficiency of a product of which it has initial comparative disadvantages, specialized R&D input can guarantee the obtainment of dynamic comparative advantages. If this country has an absolute advantage in the R&D efficiency of both products, it is necessary to find out its relative advantage in the R&D of either product. Only when it has a relative advantage in the R&D of the product of which it has initial comparative advantages can it guarantee the obtainment of dynamic comparative advantages by means of specialized R&D input.

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10.2   Dynamic Evolution of Comparative Advantages Based on National Absorptive Capacity: A Case Study of FDI in China Since the promulgation of the Law of the People’s Republic of China on Chinese-Foreign Equity Joint Ventures in July 1979, China has attracted large sums of FDI based on the sustained growth of the Chinese economy, the huge potential demand on the domestic market, and the abundant labor resource. At the same time, phasic changes have taken place in the regional distribution and the industrial structure of China’s foreign investment attraction, as well as the countries of origin of foreign investment. Out of consideration for the afore-mentioned theoretical backgrounds and the reality of the Chinese economy, we will start with the FDI absorptive capacity of developing host countries and make a systematic, comprehensive, and in-depth analysis of the specific mechanism of action of the determining factors of the absorptive capacity in boosting FDI’s facilitation of the economic growth of developing host countries. Moreover, we will establish a quantitative indicator system that reflects China’s FDI absorptive capacity in keeping with the conditions of the country. On that basis, we will empirically study the role of the constituent factors of the host country in the economic growth effect of FDI in China, such as its human capital stock, the development of its domestic financial market, its degree of trade openness, and its level of technological innovation. 10.2.1   FDI and China’s Economic Growth: An Overview As revealed by UNCTAD FDI Database, FDI grew by 46.1% annually between 1979 and 2017. In terms of FDI attraction, China was 122nd in the world in 1979, rose to eighth in 2000, and ranked second from 2013 to 2014. In 2017, China attracted an FDI of USD 131 billion and rose back to the second place, 120 places higher than it was in 1979. The introduction of large amounts of FDI has not only directly boosted the highspeed growth of the Chinese economy, but also contributed significantly to various aspects of the national economy, such as China’s export trade, domestic employment, and industrial structure adjustment. FDI has become one of the most important driving forces for the miraculous growth of the Chinese economy. Nonetheless, as China gives up a large part of its market, its technological level—in particular its core technology—has not been improved correspondingly, and this has become one of

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the major impediments to the growth of the Chinese economy. China has successfully attracted FDI but failed to achieve corresponding economic growth. The chief reason, it is generally believed, is that transnational corporations and developed countries have set up technical barriers and restricted the export of core technologies, and on the other hand, China is still weak in its absorption of FDI (Table 10.1 and Fig. 10.1). Table 10.1  China’s FDI and GDP, 1987–2017 Year

FDI (billion USD)

FDI (billion RMB)

FDI growth (%)

GDP (billion RMB)

GDP growth (%)

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

2.314 3.194 3.393 3.487 4.366 11.008 27.515 331.067 37.521 411.026 45.257 45.463 40.319 401.015 46.878 521.043 53.505 60.630 60.325 63.021 83.521 92.395 90.030 105.735 116.011 111.720 117.586 119.560 126.270 126.000 136.320

8.613 11.888 121.075 16.679 23.242 601.005 158.541 291.028 313.338 346.918 375.171 376.393 3331.073 337.055 388.009 436.554 442.861 501.822 494.164 502.391 553.328 641.693 614.995 715.773 749.291 705.232 716.803 734.433 784.778 813.220 920.405

3.12 38.03 6.23 2.77 25.21 152.13 149.95 22.72 11.12 11.21 8.46 0.46 −11.31 0.97 15.15 12.51 1.44 13.32 −0.50 4.47 4.63 15.96 −4.34 2.79 4.68 −5.88 1.64 2.45 6.82 3.62 13.18

1205.860 1504.280 1699.230 18,661.080 2178.150 2692.350 3533.390 48,191.090 6079.370 7117.660 7897.300 8440.230 89,671.010 9921.460 10,965.520 12,033.270 13,582.280 15,987.830 183,861.090 21,087.100 26,581.030 31,404.540 34,050.690 39,975.950 46,856.240 51,947.010 58,319.670 64,397.400 68,905.210 74,358.550 82,712.170

11.6 11.3 4.1 3.8 9.2 14.2 14.0 13.1 10.9 13.0 9.3 10.8 10.6 8.4 8.3 9.1 10.0 10.1 11.31 12.68 14.16 9.63 9.21 10.45 9.30 7.67 7.67 7.40 6.90 6.50 6.30

Source: FDI data from the website of the Chinese Ministry of Commerce; GDP and GDP growth rates from China Statistical Yearbook 2018; FDI growth rates recalculated by the author

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Fig. 10.1  Comparison of China’s FDI and GDP 1987–2017

In the short run, FDI is not a factor that boosts China’s economic growth. This is because FDI has to take a course and there is a time lag in the effect of such investment. In the long run, however, FDI contributes to China’s economic growth. FDI is not only a form of capital. Its inflow increases the overall capital resource and thus boosts China’s capital formation and economic growth. Moreover, the inflow of FDI has an effect on the transfer of advanced technology, management, sales, and operation, and thus improves the production efficiency and factor productivity. As a result, it can indirectly boost China’s economic growth. 10.2.2   China’s FDI Absorptive Capacity and the Quantitative Indicator System There are a number of problems in how FDI absorptive capacity is defined in the existing literature. First of all, they have applied the notion of the absorptive capacity of enterprise directly to the analysis of FDI, and overlooked the premise which is the economic growth effects of FDI. Secondly, such definitions of the FDI absorptive capacity are still at the microscopic enterprise level, without extending the concept to the macroscopic national or regional level. Finally, they have merely taken into consideration the technological absorptive capacity of FDI but ignored the capacity to attract FDI. As previously defined, the FDI absorptive capacity of the host country is subject to the influence of the human capital, the

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development of the financial market, and the market institution. It is almost impossible to quantify it using a single indicator, and this is bound to cause huge difficulty to its empirical test. Therefore, it is extremely important to study the factors in a country’s FDI absorptive capacity and to select the determining factors of the FDI absorptive capacity to establish a corresponding quantitative indicator system. 10.2.2.1 Factors in China’s FDI Absorptive Capacity The factors in the FDI absorptive capacity is a multi-perspective, multilevel, and multi-angle synthesis that cannot be fully reflected with one or more such factors. In this chapter, we have chosen four major determining factors to analyze their roles in the economic growth effect of FDI, namely, the host country’s trade openness, its efficiency of financial market development, its human capital conditions, and its technological innovation level. Noteworthily, although these four determining factors can approximate the FDI absorptive capacity of a country or region, it does not follow that other factors—such as infrastructure conditions, government policies, development strategies, and cultures and customs—have no influence on the FDI absorptive capacity. This chapter is but a periodical achievement of our studies on the FDI absorptive capacity. In the future, we will focus on the role of other factors in FDI’s effect on economic growth and establish a complete indicator system to fully measure the FDI absorptive capacity. 10.2.2.2 The Quantitative Indicator System of China’s FDI Absorptive Capacity After we decide the four determining factors of the FDI absorptive capacity, we will try to quantify them using relevant indicators. A. Trade openness. In their empirical studies of the conditions in China, researchers generally reflect China’s trade openness using trade dependency and export dependency. Trade dependency can test in general the influence of China’s trade openness on the economic growth effect of FDI, while export dependency can be used for further structural analysis of this influence. Besides, these two indicators can also be used to find out whether there is a substitution effect or complementary effect between China’s foreign trade and its FDI.  Referring to the methods and indicators used in existing studies, we choose the proportion of the volume of foreign trade in the GDP (OPEN1) and that of

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the total export in the GDP (OPEN2) as the proxy indicator to measure China’s trade openness. B. Financial market development. We extend the proxy indicator for the efficiency of the financial market development to cover the efficiency of the credit market development and that of the stock market development. (1) The efficiency of the credit market development. It includes the current liabilities of the financial system (LLY), which is the ratio between broad money and the GDP, an indicator to measure the size of all financial intermediaries, including the central bank, deposit money banks, and other financial institutions; commercial bank assets (BTOT), which is commercial bank assets divided by the sum of commercial bank assets and central bank assets and reflects commercial banks’ degree of distribution of social savings resources in relation to the central bank; private sector lending (PRIVCR), which is financial intermediaries’ loans to the private sector divided by the GDP and measures the capability of private financial intermediaries to distribute social savings; and bank loans (BANKCR), which is the loans of deposit money banks to the private sector divided by the GDP and measures the capability to distribute social savings of other private financial institutions—apart from the central bank, financial trust and investment companies, and financial leasing companies. In our empirical study, we use M2—the ratio of broad money supply to GDP—and LOAN—the proportion of loan balances held by financial institutions in the GDP—to reflect the development of China’s credit market. (2) The efficiency of the stock market development. According to the method of Levine and Zervos (1998),5 we measure the development of China’s stock market using the proportion of the stock market turnover—an indicator that reflects the stock market liquidity (STOCK1)— and the proportion of the total market value of stocks in the GDP—an indicator that reflects the size of the stock market (STOCK2). C. Human capital. As Narula pointed out, human capital is an important part of the absorptive capacity of the host country. Since the concept of human capital was first put forward, its measurement has always been a focus of dispute. In existing literatures, there are mainly three categories of indicators to measure human capital:

5  Levine, R. and Zervos S., “Stock Markets, Banks and Economic Growth,” American Economic Review 88, no. 3 (l998): 537–58.

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1. Indicators of human capital investment. They mainly reflect the level, structure, and form of human capital investment, such as the total investment in human capital, government investment in human capital, individual investment in human capital, and investment in education and health. In their empirical studies, Lai Mingyong et  al.6 and Zhang Binsheng chose government investment in education as the proxy indicator of China’s human capital level. 2. Indicators of human capital stock. They mainly consist of a series of indicators that reflect the level and structure of human capital stock. Of the indicators of human capital stock, the most widely used is the average years of schooling. Indicators of the structure of human capital stock refer to the proportions of population with various levels of education or work experience, including the proportions of primary school, high school, and college graduates, as well as those of technical personnel and overseas returnees. For example, Li Xing took the proportion of college students in the employees as a proxy indicator to measure provincial levels of human capital in China. 3. Indicators of human capital efficiency. As our purpose is to observe whether the economic growth effect of China’s FDI is restricted by its human capital development and to test whether the human capital of different education levels has different influences on the economic growth effect of the FDI, we have chosen the average years of schooling, the human capital with high school education, and the human capital with college education to measure the development of human capital in China. The formula used to calculate the average years of schooling (H) is: (Primary school students x6 + High school students x12 + College students x16)/ Total population. Similar to the methods used by Wang Zhipeng and Li Zinai and Yao Shujie, we have adopted the proportion of college students in the total population (H1) and that of high school students in the total population (H2) to analyze the influence of human capital of different education levels on the economic growth effect of China’s FDI.  We have extended the proxy indicator of R&D activity to 6  Lai Mingyong, Bao Qun, Peng Shuijun, and Zhang Xin. “FDI and Technological Spillover: A Study Based on the Absorptive Capacity.” Economic Research Journal, no. 8 (2005).

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cover both R&D input and R&D output. a) R&D input. In the broad sense, R&D input includes both R&D capital input and R&D personnel input of the whole society. Yet considering data availability and convenience for comparison and analysis, many scholars have merely chosen the indictor of R&D expenditures. Hence we have chosen the proportion of the national R&D expenditures in the national GDP and the ratio of provincial R&D expenditures to the provincial GDP as the proxy indicator of R&D input. Besides, government funding for science and technology also reflects the attitude of the national (provincial) government to scientific and technological activity. Therefore, in order to test the role of governmental support for science and technology in promoting China’s technological innovation and in boosting FDI’s facilitation of China’s economic growth, we have also chosen the proportions of national and provincial government funding for science and technology in the overall fiscal expenditure as another proxy indicator of R&D input. b) R&D output. At present, the indicators to measure China’s scientific and technological output mainly include the number of patent application, the number of Chinese scientific and technological papers included in the SCI, ISTP, and EI databases, and the proportion of exported high-tech products in manufactured goods. As a good part of the provincial statistics on patent application and sci-tech papers included is unavailable, we will mainly use the proportion of exported high-tech products in manufactured goods as the proxy indicator to measure R&D output. 10.2.3   FDI and China’s Economic Growth Based on the Absorptive Capacity of Trade Openness: An Empirical Analysis Using Kokko’s method7 to analyze the factors in the spillover effect of Mexico’s FDI, we multiply the indicators and regress the result as an explanatory variable, and then establish an econometric model expressed as the following formula: GROWTH  c 0  c1K  c 2 H  c 3 GDDI  c 4 GFDI OPEN  

(10.19)

 Kokko, Ari. “Technology, Market Characteristics, and Spillovers.” Journal of Development Economics 43, no. 2 (1994): 279–93. 7

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We choose and process the following indicators of variables. GROWTH. It is the growth rate of real GDP per capita and stands for the annual economic growth. The reason why we choose the real GDP per capita, instead of GDP, is that the former better reflects the endogenous growth of the economy as well as improvements in provincial technology levels. K.  It is the domestic capital stock. As the time series of China’s annual domestic capital stock is unavailable, we have learned from the method used by Balasubrananyam et al. and substituted the domestic fixed capital stock with the proportion of annual domestic fixed capital investment in the GDP. It is the total investment in fixed assets subtracted by the FDI in RMB and further reduced and adjusted using the GDP. H. It is the human capital stock. We use the average years of schooling as the proxy indicator of human capital. Theoretically, human capital stock must be positively correlated to economic growth. That is to say, the coefficient of this indicator must be positive. GFDI.  It is the proportion of FDI in GDP.  The FDI is converted into RMB using the central parity rate of the RMB against the USD with price factors reduced and eliminated using the GDP. The GDP in this indicator is real GDP after price adjustment. This indicator can be used to measure the direct role of FDI on economic growth, namely, the FDI’s role in capital accumulation for economic growth. GFDI*OPEN. It is the product of FDI and trade openness to test whether FDI’s facilitation of economic growth is influenced by trade openness. Two indictors are used to measure the degree of China’s trade openness, namely, the proportion of the volume of foreign trade in GDP (OPEN1) and that of export in GDP (OPEN2). The volume of foreign trade is converted into RMB using the central parity rate of the RMB against the USD and price factors are further reduced and eliminated using the GDP. And here GDP is also real GDP after price adjustment. ε. It is the random error. Here, we choose the statistics of time series between 1987 and 2017 as the samples for study. All the statistics are from Compilation of Statistical Data of the People’s Republic of China over the Past 55 Years (1949–2004) and China Statistical Yearbooks. The precondition for the regression analysis of the time series is the stationarity of the sample statistics, as unstable statistics of time series usually leads to spurious regression and thus

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nullifies the conclusion. For this reason, we will first make a stationarity test of the time series and, on that basis, conduct a co-integration test. If there is a co-integration relationship among the variables, we will make a regression analysis of the level value of these variables. As Table 10.2 shows, all the horizontal series of the variables are unstable at the significance level of 10%, but their first-order difference is stable. That is to say, they are all I(1) series. Therefore, we can determine the long-term stable relationship among the variables using the co-integration analysis method. As is found in our test, when the VAR model of the five variables lags two phases, the statistics of AIC and SC are the smallest, so we preliminarily determine that its lag phase is the second order. We further test the autocorrelation, heteroscedasticity, and normality of Model VAR(2) using Q, ARCH, and JB. The result shows that, when the VAR model of the variables lags two phases, it has no autocorrelation or heteroscedasticity and the residual is in normal distribution. Therefore, the VAR model that lags two phases is the optimal model. Table 10.2  Results of the Stationarity Test of the Variables Variable tested

ADF s tatistics

GROWTH ΔGROWTH GFDI ΔGFDI K ΔK H ΔH GFDI×OPEN1 ΔGFDI×OPEN1 GFDI×OPEN2 ΔGFDI×OPEN2

−2.5071 −2.9408* −0.1870 −2.2712** −2.0408 −2.1435** −2.4340 −2.8267* −2.0295 −3.1269 −1.5630 −3.3717**

Critical value at significance level 1%

5%

10%

−4.5716 −3.8868 −2.6924 −2.6998 −3.8868 −2.6998 −4.5716 −3.8868 −3.8868 −2.6998 −3.8315 −2.6998

−3.6908 −3.0522 −1.9602 −1.9614 −3.0522 −1.9614 −3.6908 −3.0522 −3.0522 −1.9614 −3.0100 −1.9614

−3.2869 −2.6666 −1.6070 −1.6066 −2.6666 −1.6066 −3.2869 −2.6666 −2.6666 −1.6066 −2.6552 −1.6066

Form of test

Result of test

(C,T,1) (C,N,1) (N,N,1) (N,N,0) (C,N,1) (N,N,0) (C,T,1) (C,N,1) (C,N,1) (N,N,0) (C,N,0) (N,N,0)

Unstable Stable Unstable Stable Unstable Stable Unstable Stable Unstable Stable Unstable Stable

Notes: 1. All the results are calculated using the software EVIEWS6.0 2. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively 3. The form of test is (C, T, K), where C and T means that the ADF test has a constant term and a trend term, N means that it has no constant term or trend term, and K stands for the lag order determined by AIC minimization 4. △ is the difference operator

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As the co-integration test is to exert vector co-integration constraints on the unconstrained VAR model, the lag order for the co-integration test must be the optimal lag order of the unconstrained VAR model minus 1. In other words, the optimal lag order for the co-integration test is 1. We analyze the forms of the initial data and decide that there is no determined linear trend in the data space and that the co-integration equation has an intercept term but no trend term. At the same time, we also conduct the co-­integration test using the Trace Test and the Maximum Eigenvalue Test and find that there is a co-integration relationship when and only when both tests are valid. Tables 10.3 and 10.4 show the test results. As the result shows, there is at least one co-integration relationship among the variables at the confidence level of 95%, so we can make a regression analysis of the level value of the variables. We choose trade dependency (Open1) and export dependency (Open2) as the proxy indicators of trade openness to study the influence of trade opening on the economic growth effect of China’s FDI and get the following regression results (See Table 10.5). As shown by the regression results of Model 1 in Table 10.5, when it is directly regressed using GROWTH, GFDI, K, H, and GFDI*OPEN1, the D-W statistic value of the model is 0.6055. This shows that there exists a strong autocorrelation among the residual series of the regression model. If we continue to estimate the results using the OLS method, the parameter estimates will be invalid though unbiased, and consequently the significance test will become invalid. Accordingly, we add AR(1) to Model 1 Table 10.3  Co-Integration Test Results of Variables GROWTH, GFDI, K, H, and GFDI*OPEN1 Number of co-integration equation

Value of trace test

Critical value (0.05)

None* At most 1* At most 2* At most 3* At most 4*

111.6548 63.42179 30.29149 9.339535 0.714361

60.06141 40.17493 24.27596 12.32090 4.129906

Value of maximum Critical value Eigenvalue test (0.05) 48.23296 33.13030 20.95195 8.625175 0.714361

30.43961 24.15921 110.79730 11.22480 4.129906

Notes: 1. As the Trace Test and Maximum Eigenvalue Test show, there are three co-integration relationships at the significance level of 0.05 2. * indicates rejecting the null hypothesis at the significance level of 0.05

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Table 10.4  Co-Integration Test Results of Variables GROWTH, GFDI, K, H, and GFDI*OPEN2 Number of co-integration equation

Value of trace test

Critical value (0.05)

Value of maximum Eigenvalue test

Critical value (0.05)

133.0651 78.73215 45.17120 14.30737 0.871275

69.81889 410.85613 29.79707 5.49471 3.841466

54.33292 33.56095 30.86383 13.43610 0.871275

33.87687 210.58434 21.13162 14.26460 3.841466

None* At most 1* At most 2* At most 3* At most 4*

Notes: 1. As the Trace Test and Maximum Eigenvalue Test show, there are three co-integration relationships at the significance level of 0.0 2. * indicates rejecting the null hypothesis at the significance level of 0.05

Table 10.5  Regression Results of the Influence of Trade Openness on the Economic Growth Effect of FDI Explanatory variable C GFDI K H GFDI*OPEN1 GFDI*OPEN2 AR (1)

Coefficient t statistic Coefficient t statistic Coefficient t statistic Coefficient t statistic Coefficient t statistic Coefficient t statistic Coefficient t statistic

R2 adjusted F statistic D-W statistic value Threshold value of trade openness

Model 1

Model 2

Model 3

0.8048 1.9845 0.0868 1.0470 0.0436** 1.977 0.0691*** 4.9861 0.0524 0.4697

10.5127 0.3978 0.0637 1.2155 0.0125** 2.0412 0.0495*** 3.2137 −0.0790 −0.0221

1.0115*** 2.3915 −0.0489 −0.4506 0.0834* 1.7847 0.0598*** 4.7042

0.0989 1.1251

0.9915*** 31.5917 0.8901 141.4772 0.6055

0.9948 272.2289 1.8659 0.8063

Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively

0.9174 144.4078 1.6748 0.4944

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and find that the D-W statistic value is 1.8659, which basically means that there is no autocorrelation among the residual series. In the regression results of Model 2, both the adjusted R2 value and the F statistic show a good fitting degree of the model. Model 3 is a regression analysis using OPEN2 as the proxy indicator of trade openness. The result also shows a good fitting degree of the model, and the D-W statistic value indicates that there is no autocorrelation among the residual series. Thus we can analyze the influence of trade openness on the FDI’s economic growth effect using Models 2 and 3. The following is our analysis of the regression results of Model 2 and 3. 1. The influence of capital input on economic growth. As the regression result shows, both material capital input (K) and human capital input (H) significantly boost China’s economic growth. The coefficient of GFDI is positively insignificant or negative. This indicates that, as China’s total savings remain high, if we introduce foreign investment merely for the utilization of external sources of finance, it will cause negative capital accumulation and impede the increase in the aggregate investment. That is to say, the introduction of FDI has a “crowdingout effect” on domestic investment. 2. The influence of trade openness on FDI’s economic growth effect. Model 2 takes trade dependency as the indicator of trade openness, and the regression result shows that the coefficient of the cross-term GFDI*OPEN1 is negative (−0.0790). When Model 3 uses export dependency as the proxy indicator, the coefficient of the cross term GFDI*OPEN2 is positive (0.0989). Although both have failed to pass the t test at the significance level of 10%, they can roughly prove that export trade facilitates FDI to boost China’s economic growth, and, on the other hand, foreign trade has a slight negative influence on the economic growth effect of China’s FDI. 3. The threshold effect of trade openness. In regression eqs. 2 and 3, the symbols of the regression coefficients of GFDI and the cross term are opposite. This indicates that the FDI’s contribution to China’s economic growth is restricted by the threshold of China’s domestic trade openness. We then calculate the thresholds of open trade development of the models. As the results in Table 10.6 show, only when the total volume of imports and exports accounts for 80.63% or when the volume of exports accounts for 49.44% of the annual GDP can the Chinese economy benefit from FDI.

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Table 10.6  By-Region Test Results of the Influence of Trade Openness on FDI’s Economic Growth Effect Explanatory variable

National samples

Eastern samples

Central samples

Western samples

C

Coefficient t statistic GFDI Coefficient t statistic K Coefficient t statistic H Coefficient t statistic GFDI*OPEN Coefficient t statistic Hausman test Coefficient value (P value) t statistic

0.0555*** 62.8661 0.0972 1.4177 0.0095*** 4.8158 0.3625*** 28.4547 −0.0278 −1.4488 1.8299 0.7670

0.0567*** 41.5291 −0.0511*** −8.1331 0.0061* 1.8632 0.4009*** 24.1133 0.0014 1.1480 2.6152 0.6240

0.0538*** 38.9037 0.3782*** 5.4877 0.0031 0.8871 0.3618*** 13.9577 −0.0159*** −2.5207 1.1821 0.8810

0.0732*** 74.3983 0.1285** 2.0604 0.0134*** 6.3983 1.1964*** 12.1982 −0.1190*** −3.9316 0.0121 0.0000

Adjusted R2 F statistic Method of estimation Number of samples

0.7828 522.4958 IV-RE 551

0.8787 385.3297 IV-RE 209

0.8058 178.2520 IV-RE 152

0.8999 154.8018 IV-FE 190

Notes: 1. All the results are calculated using the software EVIEWS6.0 2. The values in brackets are t values of the parameters 3. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively 4. The p value is the probability of rejecting the null hypothesis (i.e., the instrumental variable-random effect) and making mistakes. We adopt the instrumental variable-individual fixed effect (IV-FE) when the probability is lower than 0.1 and the instrumental variable-individual random effect (V-RE) otherwise 5. The instrumental variables of GFDl and GFDI*OPEN lag one phase behind, and those of others are the same as the variables

From the perspective of the absorptive capacity of trade openness, this empirical analysis proves that there is a complementary relationship between China’s FDI inflow and its export trade. Trade openness measured by export dependency can facilitate FDI to boost China’s economic growth, but insignificantly. Trade openness measured by trade dependency has a slight negative influence on the economic growth effect of China’s FDI. This influence, restricted by the threshold of trade development, varies significantly from region to region. In the eastern region, the excellent foreign trade environment has boosted the play of FDI’s economic growth effect. In contrast, trade openness in the central and western regions has impeded the generation of FDI’s economic growth effect.

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Compared with the central region, the western region is more obvious in terms of such impediment. Currently, China’s export trade facilitates FDI to boost its economic growth, but its import trade has a slight negative influence on FDI’s economic growth effect. Therefore, an urgent task is to improve the national absorptive capacity under the condition of open trade and thus accelerate and facilitate FDI’s role in boosting China’s economic growth.

10.3  How to Build China’s Dynamic Comparative Advantages on the Country’s National Absorptive Capacity As the international history of economic catching-up and surpassing proves, it is the combination of technological gaps and national capacities that determines the potential growth rate of a country or region in the long run. Nowadays, as economic globalization and high-tech revolution are rapidly developing, it is adverse to the development of developing countries to merely take the exogenous, static resource endowment as the theoretical basis of their development strategy and industrial policy. It can never enable them to narrow their gaps with developed countries, but will forever keep their economic and technological structures at the downstream of the industrial and technological chains. Therefore, China must start with improving the competitiveness of its overall economy, firmly grasp the commanding heights of industry and technology, and bring into shape the dynamics of its comparative advantages based on its national absorptive capacity. Only in this way can it accelerate the upgrading of its industrial structure and realize the objective of catching-up and surpassing. Over 40  years of economic growth along with China’s reform and opening-up shows that the model of development based on catch-up indeed boosts economic growth in a certain period of time. It is through short-term economic catch-up that China has narrowed its gap with countries at the world technological frontier. Nonetheless, unless China can bring into shape effective dynamic comparative advantages in the long run, the gap between its eastern and western regions will widen due to difference in their technological capacity, and a series of problems will arise when its economy develops to the stage of technological frontier. First of all, the transfer of China’s rural surplus labor is expected to complete between 2020 and 2025, and, as a result, its labor cost will increase rapidly

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and its advantage of low-cost labor force will vanish. Secondly, in the future, the rapid rise in China’s environment, resource, and factor costs will change its comprehensive advantage in the investment environment, lower its attractiveness for cost-driven international capital, and increase the pressure for the transformation of the entire system of processing, trade, and production. Finally, in the era of globalization, the model of technological imitation long implemented by China will be faced with challenges, causing great difficulty in transition from technological imitation to independent technological innovation. Therefore, in such a transitional period, it is particularly significant to explore a strategy for transformation and development that fits China’s comparative advantages. In our view, China’s economic growth is in essence a government-led process of catch-up mainly driven by technological imitation. The validity of such a model of catch-up does not depend on GDP per capita, but on the technological gap between China and developed countries, or more exactly, on whether China has a national absorptive capacity strong enough to absorb and transform technological transfer and diffusion from developed countries. Yet reality and experience have shown that the catch-up effect based on technological imitation also weakens as the technological gap between China and the developed economies narrows. Therefore, China must transform its model of growth as soon as possible from government-led catch-up based on technological imitation to market-oriented catch-up based on technological innovation. It is in this sense that China must change in the future its model of growth that merely focuses on the speed of catch-up but ignores the capability and meaning. In terms of China’s economic growth at present, a certain degree of catch-up does boost economic growth. Yet our study also suggests that, in the long run, a country will converge on the pattern of trade under the condition of comparative advantages. In order to achieve higher income, developing countries must try their best to prolong the process of convergence to the equilibrium state of comparative advantages. On the other hand, different levels of technological gaps can lead to different roles of FDI on technological progress. In technologically developed regions with small technological gaps, the spillover effect of FDI is insignificant, but the relative elasticity of homegrown innovation is extremely high, so the innovative capacity will be the core driving force of technological progress and economic development in such regions. With the widening of the technological gaps, regions of an intermediate technological level are in the critical period of transformation from imitation to innovation. And an important

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task for local governments is to boost scientific and technological progress and transformation in these regions. In underdeveloped regions with huge technological gaps, an important measure to catch up is to enhance their infrastructure construction and strengthen their absorptive capacity. In the long run, economically catching-up countries will converge on the pattern of trade under the condition of comparative advantages. In order to achieve a higher economic growth rate, catching-up countries must try their best to prolong the process of convergence to the equilibrium state of comparative advantages.8 Based on Michael Porter’s theory of competitive advantage of nations, Justin Yifu Lin and other scholars also suggested that developing countries implement the comparative advantages strategy based on their capacities.9 Since the 2008 global financial crisis, China has transformed its growth model as an important national policy, emphasizing the path of emerging industrialization and the development of green and low-carbon economy, and improved the contribution of technological progress to economic growth. According to the goal of development in the Outline of the National Medium- and Long-Term Science and Technology Development Program (2006–2020), by 2020 the contribution rate of China’s scientific and technological progress will reach 60% and the proportion of R&D input of the whole society in GDP will increase to over 2.5%. Since 2017, the Chinese economy has been faced with a good many changes. For example, the high savings rate has declined, the advantage of low-cost labor force gradually weakened, the constraint of resource and environment significantly intensified, and it is more difficult to improve the total factor productivity. It is our view that China is now at the crossroads of economic development and the primary goal for its sustained development in the globalization era is to accelerate its economic transformation. In terms of the long-term strategy for economic development, China must establish as soon as possible dynamic comparative advantages based on its national capacity, so as to cope with challenges in the future. To begin with, China must increase its capacity for technological absorption and innovation, adopt, improve, and master existing technologies, and narrow its gap with the technological frontier. To this end, it 8  Yang Rudai and Yao Yang, “Limited Catch-up and Economic Growth,” Economic Research Journal, no. 8 (2008). 9  Justin Yifu Lin, Cai Fang, and Li Zhou, “Comparative Advantage and Development Strategy—Re-Interpreting the East Asian Miracle,” Social Sciences in China, no. 5 (1999).

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must formulate its technological absorptive capacity by improving its institutional environment, initial technological level, infrastructure, and human capital accumulation, and accelerate the development of its national capacity by means of specialized and intra-industry trade as well as the bidirectional flow of FDI.  Meanwhile, China’s high savings rate can quickly replenish its capital and facilitate high-speed technological catchup. With the improvement in its national absorptive capacity, China will bring into shape an innovative system of products and technological processes, and make technological breakthroughs in certain aspects. Furthermore, the national absorptive capacity has a positive effect on catching-up economies. It is the accumulation of the national absorptive capacity that makes true the ability to catch up. As its national absorptive capacity improves, the Chinese economy will grow at a higher speed. Nonetheless, when China reaches the stage of the technological frontier, the government’s excessive intervention in the economy will impede growth. By that time, the government must shift its attention to the development of the private economy and ensure effective allocation of resources on the market. It must also improve the utilization efficiency of factor input, increase human capital investment, intensify innovation, and turn its attention to services with a high value added, so as to inject new impetus into its economic growth. All this will help China avoid the middleincome trap. Moreover, in terms of regional technological absorptive capacity in China, the western region has a greater growth potential than the eastern region. In terms of national capacity building, the eastern region is the smallest in the growth potential, but it has strong comparative advantages in human capital and trade openness. Due to such capacity-based comparative advantages, the eastern region is far greater than the other regions in the total amount of growth. Relatively speaking, the central and western regions are low in their growth potential due to their disadvantage in the absorptive capacity, which tends to inhibit their development. Hence, the imbalance in regional economic development and in the absorptive capacity in China determines that the central and western regions must adopt different strategies of economic development that fits their technological absorptive capacities. As the history of economic growth proves, in the long run, it is the combination of the technological gap and the national absorptive capacity that determines the potential growth rate of a country or region. Nowadays, in the context of economic globalization and rapid development of high-tech revolution, if we continue to

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formulate our development strategy and industry policy merely based on the theory of comparative advantage of exogenous resource endowments but ignore the comparative advantages based on our national capacity, it will never lead us toward a developed economy, and our economic and technological structures will forever remain at the lower end of the industrial and technological chains. Therefore, China must start with improving the competitiveness of its overall economy, firmly grasp the commanding heights of industry and technology, and base its comparative advantages on a strong national absorptive capacity instead of the static natural endowment. Only in this way can it more rapidly upgrade its industrial structure and realize the transformation of its economy in the future.

10.4   Conclusions As a technologically underdeveloped country, China is now in a critical period of transformation of its economic institutions. Against this background and from the perspective of the combination of comparative advantages with development strategies, this chapter has introduced the concept of national absorptive capacity in the sense of economics and analyzed the effect of the technological absorptive capacity—in particular of the national absorptive capacity—on the formation of China’s comparative advantages. Through a discussion of the development of the theory of comparative advantage and the dynamic evolution of comparative advantages, it has analyzed the path choice for the dynamic evolution of China’s comparative advantages. Besides, it has explored the mechanism of influence of R&D activity on the dynamic changes of comparative advantages in light of the national capacity, and extended the meaning of the traditional theory of absorptive capacity. As our study has discovered, the dynamic changes of comparative advantages are determined by the exclusiveness of specialized knowledge resulting from R&D and innovative activities. Clearly, it is based on increased national capacity that economies in transition have formulated their comparative advantages by means of specialized R&D and innovation. This proves in theory that national absorptive capacity plays an extremely important role in the dynamic evolution of comparative advantages. We thus believe that, as it enters a new stage of economic opening-up, China must gain dynamic comparative advantages based on its national absorptive capacity, so as to realize its economic transformation.

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As is shown in this chapter, underdeveloped regions are capable of maintaining a certain speed of technological catch-­up as long as they have a certain technological absorptive capacity and a relatively high R&D growth rate, even if they cannot rapidly or fully utilize the technology of advanced regions. And the maintenance of such a speed is realized through the R&D accumulation of underdeveloped regions. Yet existing literatures often ignore the role of independent R&D accumulation of the underdeveloped regions, so do policy practices because they are usually from the perspective of the underdeveloped regions. In this chapter, we have proven in theory that, under certain conditions, the independent R&D accumulation of underdeveloped regions is the key factor for catching up. Besides, this chapter has empirically analyzed the influence of the factors of the absorptive capacity, such as China’s FDI absorptive capacity and technological gaps, on the dynamic changes of comparative advantages. On the one hand, China must raise its export prices while maintaining steady increase in its export volume and transform its model of export growth from extensive quantity expansion to steady quality improvement. As our regression result shows, China’s export trade facilitates the FDI’s economic growth effect, but this effect is by no means significant. This is consistent with the status quo that the rapid growth in China’s export size is mainly quantity expansion but the export prices are on the decline under the guidance of the country’s export-oriented strategy of trade development. Therefore, at the current stage when its foreign trade develops rapidly, China must adjust its guidelines for foreign trade as soon as possible, so as to avoid “immiserizing growth” and strengthen export trade’s facilitation of the FDI’s economic growth effect. China must optimize its industrial structure of export, promote its technical content and grade of export products, and increase the prices of its export. On the other hand, China must proactively adjust its trade strategy. The export-oriented strategy mainly focuses on the external demand by valuing export over import. When changes take place to the external conditions, developing countries implementing this strategy are very likely to suffer from adverse impacts. China’s export-­oriented strategy has been successful over the past decades. Under the influence of the global financial crisis, however, the domestic and international conditions are changing quietly. Accordingly, China must integrate its export development with its domestic economy, boost the formation of a unified market, and bring into being a mentality of coordinated development.

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