Abstract
We empirically investigate the factors that drive the uneven regional distribution
of foreign direct investment (FDI) inflows to China’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 ‘factory of the world’. Robustness tests indicate that two sub-dimensions of institutions, namely infrastructure and governance, are
important to determine the location choice of FDI in China.
of foreign direct investment (FDI) inflows to China’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 ‘factory of the world’. Robustness tests indicate that two sub-dimensions of institutions, namely infrastructure and governance, are
important to determine the location choice of FDI in China.
| Original language | English |
|---|---|
| Place of Publication | Utrecht |
| Publisher | UU USE Tjalling C. Koopmans Research Institute |
| Number of pages | 32 |
| Publication status | Published - Sept 2009 |
Publication series
| Name | Discussion Paper Series / Tjalling C. Koopmans Research Institute |
|---|---|
| No. | 23 |
| Volume | 09 |
| ISSN (Electronic) | 2666-8238 |
Keywords
- FDI
- China
- factors analysis
- regional and spatial distribution of FDI
- location choice