A Spatial Econometric Approach to Studying Regional Air Pollution in China
摘要
Using spatial econometric method,this paper investigates the mutual influence of air pollution among 31 Chinese provincial regions,together with the effects of energy mix and economic variations.Global spatial autocorrelation analysis reveals that significant positive spatial correlation exists for air pollution;Local spatial autocorrelation analysis indicates that pollution aggregation hot spots are concentrated in Beijing-Tianjin-Hebei region,the Yangtze River Delta and part of the central region between these two economic growth poles.This paper believes that industrial relocation is a major reason behind such distribution of air pollution in China as it has deepened the spatial correlation between interregional economy and pollution,which will further give rise to the spatial spillover effect of pollution.With the creation of the regression model of spatial and Environmental Kuznets Curve,the authors discovered that the level of pollution is closely related to energy mix and industrial structure.In addition,the inverted U-shape relationship between air pollution and economic development as demonstrated by previous studies does not exist or is yet to appear in China,where continuous growth of per capita GDP is accompanied by an increasing level of pollution.According to empirical analysis,the improvement of environmental quality at the expense of industrial relocation to neighboring regions is temporary.Due to the existence of spillover effect of pollution,regions that have enforced tighter environmental regulation such as Beijing and Tianjin are unable to acquire all benefits from such regulation.Treatment of air pollution necessitates interregional joint prevention and control.In the long run,adjusting energy mix and optimizing industrial structure are the key to fighting air pollution.But in the short run,reducing the consumption of inferior coal is the most effective option for China,which has seen multiple-fold increase in imports of inferior coal each year.