Assessing agglomeration economies in the Yangtze River Delta, China: A Bayesian spatial Durbin model approach
This paper estimates the elasticity of labor productivity with respect to employment density, a widely used measure of the agglomeration effect, in the Yangtze River Delta, China. A spatial Durbin model is presented that makes explicit the influences of spatial dependence and endogeneity bias in a very simple way. Results of Bayesian estimation using the data of the year 2009 indicate that the productivity is influenced by factors correlated with density rather than density itself and that spatial spillovers of these factors of agglomeration play a significant role. They are consistent with the findings of Ke (2010) and Artis, et al. (2011) that suggest the importance of taking into account spatial dependence and hitherto omitted variables.
Keywords: agglomeration economies, endogeneity, omitted variables, Bayesian, spatial Durbin model
JEL classification: C21, C51, R10, R15
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