As the major source of air pollution,sulfur dioxide(S0_(2))emissions have become the focus of global attention.However,existing studies rarely consider spatial effects when discussing the relationship between foreign ...As the major source of air pollution,sulfur dioxide(S0_(2))emissions have become the focus of global attention.However,existing studies rarely consider spatial effects when discussing the relationship between foreign direct investment(FDI)and S0_(2) emissions.This study took the Yangtze River Delta as the research area and used the spatial panel data of 26 cities in this region for 2004-2017.The study investigated the spatial agglomeration effects and dynamics at work in FDI and S0_(2) emissions by using global and local measures of spatial autocorrelation.Then,based on regression analysis using a results of traditional ordinary least squares(OLS)model and a spatial econometric model,the spatial Durbin model(SDM)with spatial-time effects was adopted to quantify the impact of FDI on S0_(2) emissions,so as to avoid the regression results bias caused by ignoring the spatial effects.The results revealed a significant spatial autocorrelation between FDI and S0_(2) emissions,both of which displayed obvious path dependence characteristics in their geographical distribution.A series of agglomeration regions were observed on the spatial scale.The estimation results of the SDM showed that FDI inflow promoted S0_(2) emissions,which supports the pollution haven hypothesis.The findings of this study are significant in the prevention and control of air pollution in the Yangtze River Delta.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41771140)National Key R&D Program of China(No.2018YFE0105900)。
文摘As the major source of air pollution,sulfur dioxide(S0_(2))emissions have become the focus of global attention.However,existing studies rarely consider spatial effects when discussing the relationship between foreign direct investment(FDI)and S0_(2) emissions.This study took the Yangtze River Delta as the research area and used the spatial panel data of 26 cities in this region for 2004-2017.The study investigated the spatial agglomeration effects and dynamics at work in FDI and S0_(2) emissions by using global and local measures of spatial autocorrelation.Then,based on regression analysis using a results of traditional ordinary least squares(OLS)model and a spatial econometric model,the spatial Durbin model(SDM)with spatial-time effects was adopted to quantify the impact of FDI on S0_(2) emissions,so as to avoid the regression results bias caused by ignoring the spatial effects.The results revealed a significant spatial autocorrelation between FDI and S0_(2) emissions,both of which displayed obvious path dependence characteristics in their geographical distribution.A series of agglomeration regions were observed on the spatial scale.The estimation results of the SDM showed that FDI inflow promoted S0_(2) emissions,which supports the pollution haven hypothesis.The findings of this study are significant in the prevention and control of air pollution in the Yangtze River Delta.
