The global value chain（GVC）has been the main pattern of global production arrangement in the modern era of globalization since the 1960s. And during the period, China has successively become the largest trading nation, the second largest foreign investor, and one of the countries with the highest participation in GVC across the world. According to the data of ‘China Statistical Yearbook’, the number of urban and rural employees in China has maintained an average annual growth of about 2.95 million since the entry to the WTO. However, but as the 19th National Congress Report emphasizes that ‘what Chinese society now faces is the contradiction between unbalanced and inadequate development and the people’s ever-growing needs for a better life’, differences in the level of employment growth among regions, industries and types of ownership still exist in China. In fact, the employment problem has always been the biggest livelihood issue owing to its direct correlation with the welfare improvement and the stable development of the society. Therefore, to explore ways to achieve sustained employment growth through opening-up and at the same time gradually eliminate the employment gap among sectors, regions and ownership will surely be the top priority of China’s structural reform in the long term, and should be also included in the subject of further promoting opening-up and giving full play to the positive welfare effect of deeply integrating into the GVC division of labor system. From above perspectives, this paper focuses on the overall effect of the GVC embedment on not only employment growth, but also the employment structure, including heterogeneous and intrinsic influences on enterprises in different regions, industries and ownership types, thus providing more realistic and optimized path support for realizing the strategic goal of full employment for the ‘13th Five-Year Plan’. This paper uses the merged data of China’s ‘Industrial Enterprise Database’ and ‘China Customs Import and Export Database’ from 2000 to 2006 and employs propensity score matching（PSM）, difference-in-differences（DID）method as well as generalized propensity score matching（GPS）to study the effect of GVC embedment on employment. Empirical results show that GVC embedment contributes to the employment, especially in capital-intensive industries, technology-intensive enterprises and private enterprises. Furthermore, we find that GVC embedment can affect the employment effect of enterprises through three channels: export effect, intermediate substitution effect and value chain layout effect of transnational corporations. Besides, we conclude that the longer an enterprise is embedded in the global value chain, the more prominent the employment promotion effect is. Moreover, through the investigation of the continuous behavior of enterprises embedded in the GVC, the degree of GVC embedment presents an inverted U-shape relationship with employment, indicating that the marginal improvement effect changes from increasing to decreasing progressively. Finally, from an opening-up perspective, this paper provides the possibility of the following ways to ensure the employment: generally, by enhancing the depth and breadth of the GVC embedment, and improving the capability of China’s enterprises for advancing the people’s livelihood. Besides, based on current sectors, regions and ownership types with the prominent employment effect of GVC embedment, it should think about how to further mobilize the positive effects of enterprises in sectors, regions and ownership types without full use of current employment welfare effect, thereby improving the quality and effectiveness of people’s well-being accompanied by structural perfection.
The Employment Effect of Chinese Firms Embedded in GVC: Empirical Evidence Based on PSM-DID and GPS Methods
Journal of Finance and Economics Vol. 44, Issue 02, pp. 4 - 16 (2018) DOI:10.16538/j.cnki.jfe.2018.02.001
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Cite this article
Lü Yue, Lü Yunlong, Mo Weida. The Employment Effect of Chinese Firms Embedded in GVC: Empirical Evidence Based on PSM-DID and GPS Methods[J]. Journal of Finance and Economics, 2018, 44(2): 4–16.
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