Regional determinants of FDI in China: a new approach with recent data
We empirically investigate the factors that drive the uneven regional distribution of foreign direct investment (FDI) inflows to Chinaâ€™s 31 provinces from 1995 to 2006. The aim of this paper is to explain the investment patterns in (partly) foreign funded firms across these provinces. We use factor analysis and derive four factors that may drive FDI: institutions, labor costs, market potential, and geography. The factor analysis then structures our dataset to concentrate on these four clusters consisting of 42 province specific and time -varying items. Factor analysis not only helps us to identify the latent dimensions which are not apparent from direct study, but also facilitates econometrics with reduced number of variables. We apply fixed effects panel estimation and GMM to account for endogeneity. In line with theoretical predictions we find that foreign investors choose and invest more in provinces with better institutions, lower labor costs, and larger market size. Nonlinear results denote that the positive effects of infrastructure and market potential on FDI are complementary to each other, which is in line with the economic geography literature. In particular the effect of market size on FDI is larger in provinces with better institutions. Sub-sample study confirms the existences of a large disparity between East and West. In the poorer large western provinces FDI is strongly driven by the geographical factor in contrast to the east of China where institutions play a significant role to build the â€˜factory of the worldâ€™. Robustness tests indicate that two sub-dimensions of institutions, namely infrastructure and governance, are important to determine the location choice of FDI in China.
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- Jushan Bai & Serena Ng, 2000.
"Determining the Number of Factors in Approximate Factor Models,"
Boston College Working Papers in Economics
440, Boston College Department of Economics.
- Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
- Forni, Mario, et al, 2001.
"Coincident and Leading Indicators for the Euro Area,"
Royal Economic Society, vol. 111(471), pages C62-85, May.
- Lucrezia Reichlin & Mario Forni & Marc Hallin & Marco Lippi, 2001. "Coincident and leading indicators for the Euro area," ULB Institutional Repository 2013/10137, ULB -- Universite Libre de Bruxelles.
- Belderbos,R. & Carree,M., 2000.
"The Location of Japanese Investments in China: Agglomeration Effects, Keiretsu, and Firm Heterogeneity,"
002, Maastricht University, Netherlands Institute of Business Organization and Strategy Research (NIBOR).
- Belderbos, Rene & Carree, Martin, 2002. "The Location of Japanese Investments in China: Agglomeration Effects, Keiretsu, and Firm Heterogeneity," Journal of the Japanese and International Economies, Elsevier, vol. 16(2), pages 194-211, June.
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