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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Paper provided by LAMETA, Universtiy of Montpellier in its series Working Papers with number
08-17.
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