Summary:
Since the reform and opening up, the absorption of foreign direct investment (FDI) and the integration into the global value chains (GVCs) led by multinational corporations (MNCs) have been the key driving factors for China's export expansion and rapid economic growth. However, external uncertainties, such as geopolitical conflicts, strategic competition among major powers, and public crises, have hindered the current expansion of GVCs. Security concerns have gradually become the primary consideration for MNCs in shaping investment destinations. As for China, with the rise of domestic factor costs, some foreign enterprises are relocating their production lines to neighboring countries with lower production costs. Simultaneously, many Western countries have initiated trends of “reshoring”, “friend-shoring” and “near-shoring” outsourcing of industrial chains so as to marginalize China within GVCs. In this context, the withdrawal of MNCs may pose dual hidden risks to China's “dual-circulation” economic strategy. Therefore, assessing the risk exposure resulting from the FDI withdrawal is beneficial for China to effectively establish a more resilient industrial chain division of labor system, and ultimately safeguard national economic security. Based on the global input-output tables that distinguish between domestic and foreign enterprises and the production decomposition model, this paper mainly uses the hypothetical extraction method (HEM) to comprehensively measure and compare the risk exposure induced by FDI withdrawal from 2000 to 2020, and further dissects the “dual circulation” structure of the risk exposure. The main conclusions of this paper are as follows. First, the maximum risk exposure induced by complete FDI withdrawal in China's industrial chain roughly shows an evolutionary pattern of “initial rising-subsequent falling”, in which the loss rate of value added in the domestic circulation is higher than that in the international circulation. Second, in terms of industry sectoral distribution, the risk exposure of FDI withdrawal from manufacturing industries is generally larger than that in services and primary sectors. High-R&D-intensity manufacturing industries exhibit the highest risk exposure with strong risk spillover effects. Furthermore, as for the country of origins, the potential risk exposure induced by FDI withdrawal mainly originate from developed economies such as Japan, the United States and South Korea. On a global scale, the FDI risk exposure of typical developed countries is relatively stable, while the FDI risk exposure of developing countries such as Mexico, Thailand and Viet Nam has shown a tendency to expand. In recent years, the “center-periphery” distribution of global FDI risk exposure has become more distinctive. Finally, when considering factors such as the withdrawal rate of FDI and the substitution rate of domestic enterprises, as well as the destination and the decoupling rate of FDI, the level of China's overall FDI risk exposure declines. The marginal contributions of this paper are mainly as follows. First, this paper innovatively applies the hypothetical extraction method (HEM) to measure the risk exposure arising from the FDI withdrawal capturing the complex interlinkages between foreign capital and China's dual-circulation economic system. Specifically, this paper removes foreign-owned components domestically from the input-output table, and then compares changes in the “dual-circulation” value-added before and after the removal to assess the degree of risk exposure resulting from the FDI withdrawal. Second, this paper compares the industry sectoral distribution and country origins of FDI risk exposure to identify the primary sources of hidden risks. Additionally, it makes a horizontal comparison of the FDI risk exposure across major economies and observes the spatial pattern and bilateral dynamics of global FDI risk exposure. Third, this paper enriches the extension framework of the HEM model by incorporating factors such as the withdrawal rate of FDI and the substitution rate of domestic enterprises, as well as the destination and the decoupling rate of FDI, which helps to explore feasible strategies and solutions for enhancing the resilience of China's industrial supply chains. The findings of this paper provide some policy implications. First, China should closely monitor the trends and spatial distribution of the FDI withdrawal, with a particular focus on industrial chain links within the domestic circulation that are prominently reliant on foreign capital. Meanwhile, China should enhance the diversity of FDI sources, thereby effectively diversifying the risks involved in the utilization of FDI. Second, China needs to increase innovation subsidies to support domestic basic research and key technological breakthroughs, motivating domestic enterprises to enhance their independent innovation capabilities to address their weaknesses. Third, China needs to actively establish risk buffer zones, fully activate the potential of regional cooperation platforms such as the Belt and Road Initiative (BRI) and the Regional Comprehensive Economic Partnership (RCEP), and extensively utilize third-party market resources to build a more resilient global supply chain network.
[1]崔晓敏、熊婉婷、杨盼盼和徐奇渊, 2022,《全球供应链脆弱性测度——基于贸易网络方法的分析》,《统计研究》第8期, 第38～52页。 [2]葛顺奇、李三川和罗伟, 2024,《贸易脱钩、关税冲击与外商撤资》,《国际贸易问题》第3期,第50～68页。 [3]顾伟男、范信言、任亚文和古恒宇, 2024,《全球半导体贸易网络结构演化及影响因素》,《地理研究》第8期, 第2194～2214页。 [4]郭娟娟、冼国明和徐邦栋, 2022,《外资进入与国内价值链地位提升》,《金融研究》第5期, 第20～37页。 [5]洪银兴和王坤沂, 2024,《新质生产力视角下产业链供应链韧性和安全性研究》,《经济研究》第6期, 第4～14页。 [6]侯俊军、岳有福和叶家柏, 2023,《供需双循环测度与中国经济平稳增长》,《统计研究》第3期, 第3～17页。 [7]罗长远和司春晓, 2020,《外商撤资的影响因素: 基于中国工业企业数据的研究》,《世界经济》第8期, 第26～53页。 [8]吕越和邓利静, 2023,《着力提升产业链供应链韧性与安全水平——以中国汽车产业链为例的测度及分析》,《国际贸易问题》第2期, 第1～19页。 [9]倪红福、钟道诚和范子杰, 2024,《中国产业链风险敞口的测度、结构及国际比较——基于生产链长度视角》,《管理世界》第4期, 第1～26+46+27～45页。 [10]彭水军、李之旭和黄鑫, 2024,《内资与外资的共生共赢——基于两个市场两种资源联动的价值链新核算框架分析》,《管理世界》第4期, 第27～51页。 [11]王群勇、李月和薛彦, 2023,《国内国际双循环生产网络的冲击传播:特征与模拟》,《中国工业经济》第7期, 第26～45页。 [12]祝坤福、余心玎、魏尚进和王直, 2022,《全球价值链中跨国公司活动测度及其增加值溯源》,《经济研究》第3期, 第136～154页。 [13]Baldwin, R. and R. Freeman, 2022, “Risks and Global Supply Chains: What We Know and What We Need to Know”, Annual Review of Economics, 14, pp. 153～180. [14]Baldwin R.,R. Freeman,A. Theodorakopoulos,2022, “Horses for Courses: Measuring Foreign Supply Chain Exposure”, NBER Working Paper,No.30525. [15]Baldwin, R., R. Freeman and A. Theodorakopoulos, 2023, “Hidden Exposure: Measuring US Supply Chain Reliance”, NBER Working Paper, No.31820. [16]Borin, A., M. Mancini and D. Taglioni, 2021, “Economic Consequences of Trade and Global Value Chain Integration: A Measurement Perspective”, World Bank Policy Research Working Paper, No.9785. [17]Dietzenbacher, E., B. van Burken and Y. Kondo, 2019, “Hypothetical Extractions from a Global Perspective”, Economic Systems Research, 31(4), pp. 505～519. [18]Giammetti, R., L. Papi, D. Teobaldelli and D. Ticchi, 2020, “The Italian Value Chain in the Pandemic: the Input-Output Impact of Covid-19 Lockdown”, Journal of Industrial and Business Economics, 47(3), pp. 483～497. [19]Inomata, S. and T. Hanaka, 2024, “Measuring Exposure to Network Concentration Risk in Global Supply Chains: Volume Versus Frequency”, Structural Change and Economic Dynamics, 68, pp. 177～193. [20]Korniyenko, Y., M. Pinat and B. Dew, 2017, “Assessing the Fragility of Global Trade”, IMF Working Papers, No. 17/30. [21]Los, B., M. P. Timmer and G. J. de Vries, 2016, “Tracing Value-Added and Double Counting in Gross Exports: Comment”, American Economic Review, 106(7), pp. 1958～1966. [22]Schultz, S., 1977, “Approaches to Identifying Key Sectors Empirically by Means of Input‐Output Analysis”, The Journal of Development Studies, 14(1), pp. 77～96. [23]Tian, K. L., Z. Y. Zhang, L. X. Zhu, C. H. Yang, J. W. He and S. T. Li, 2023, “Economic Exposure to Regional Value Chain Disruptions: Evidence from Wuhan's Lockdown in China”, Regional Studies, 57(3), pp. 525～536. [24]Wei, J. L. M., W. Q. Chen, C. K. Chen, Y. Y. Huang and L. B. Tang, 2024, “Evaluating the Bulk Commodities Supply Risk From the Perspective of Physical Trade”, Resources Policy, 93, No.105059.
