A Fresh Scrutiny on Openness and Per Capita Income Spillovers in Chinese Cities: A Spatial Econometric Perspective
This paper investigates openness and per capita income spillovers over 367 Chinese cities in the year 2004. Per capita income is modelled as dependent on investment, physical and social infrastructure, human capital, governmental policies and openness to the world. Our empirical analysis improves substantially the previous research in several respects: Firstly, by extending the data set to prefecture-level, it tackles the aggregation bias. Secondly, the introduction of recently developed explanatory spatial data analysis (ESDA) and spatial regression techniques allows to address misspecification issues due to spatial dependence. Thirdly, the endogeneity problem in the regression is taken into consideration through the use of generalised method of moments (GMM) estimator. Our major findings are in Chinese cities, physical and social infrastructure development, human capital and investment could be recognised as major driving sources of per capita income (i), whereas, the government expenditure ratio exerts a negative impact on per capita GDP level (ii). Our empirical findings also yield evidence on the existence of FDI and foreign trade spillovers in China (iii). These findings are robust to a number of alternative spatial weighting matrix specifications.
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- Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-33, May.
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- Thiess Buettner, 1999. "The effect of unemployment, aggregate wages, and spatial contiguity on local wages: An investigation with German district level data," Papers in Regional Science, Springer, vol. 78(1), pages 47-67.
- Danlin Yu & Yehua Dennis Wei, 2008. "Spatial data analysis of regional development in Greater Beijing, China, in a GIS environment," Papers in Regional Science, Wiley Blackwell, vol. 87(1), pages 97-117, 03.
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