Under the background of green development,the function direction of technological innovation to green development efficiency,which includes economy,resources and environment,needs to be observed by demonstration.In th...Under the background of green development,the function direction of technological innovation to green development efficiency,which includes economy,resources and environment,needs to be observed by demonstration.In this paper,the green development efficiency of 30 provinces(cities and districts)in China from 2004 to 2017 is measured and its intertemporal changes,regional differences of green development efficiency are analyzed by using the super efficiency SBM model,further through theoretical analysis and empirical study,the influence of technological innovation on regional green development efficiency and its impact mechanism are investigated.The influence mechanisms of the technological innovation on green development efficiency are clarified and empirically tested by spatial econometric models from the perspectives of the growth sources and quantitative analysis.The results show that during the observation period,the green development efficiency in China exhibits a U-shaped variation,but there are huge regional differences with the obvious polarization in Eastern and Midwestern regions,and that technological innovation has some effect in promoting the regional green development efficiency,but not significant enough,which are heterogeneous according to the time periods and regions.展开更多
This paper studies the environmental effects of technical change using a spatial model with panel data from 284 prefecture-cities over 2004-2015 in China.We find that the effects of technical change vary across differ...This paper studies the environmental effects of technical change using a spatial model with panel data from 284 prefecture-cities over 2004-2015 in China.We find that the effects of technical change vary across different dimensions of technical change and different pollution indicators.Furthermore,we also provide robust evidence for the existence of the spatial effects of technical change on environmental pollution across cities.First,indigenous technical change displays three patterns of effects on the four pollutants:a positive effect on wastewater,a negative effect on PM_(2.5)concentrations,and an inverted U-shaped relationship with SO_(2)and soot emissions.The spatial effect of indigenous technical change promotes cleaner industrial productions(fewer emissions of SO_(2),soot and wastewater)but higher PM_(2.5)concentrations.Second,technology transfers from foreign direct investment are associated with less pollution except for wastewater,and their spatial effects are unanimously negative on all pollutants.Finally,absorptive capacity can also promote cleaner industrial production,but its spatial effects can do otherwise.Accordingly,the government should take the spatial spillover effects of technical change into account when implementing specific policies,pin down specific pollutants to make full use of the pollution-reducing effects of technical change,and improve the absorptive capacity of domestic firms.展开更多
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
It is clearly stated in the 19th people's congress that we should make the environmental protection as our national policy. Therefore, it is of great importance to study this issue. This article is going to consid...It is clearly stated in the 19th people's congress that we should make the environmental protection as our national policy. Therefore, it is of great importance to study this issue. This article is going to consider 30 provinces of China as the cross-section, and utilize the data sample from 2006 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of FDI. By using these data, this article creates a comprehensive environmental pollution index with the help of entropy. The result indicates that the effect of FDI on environment has a non-linear and spatial spillover characteristic. Before reaching the critical value, FDI has a negative effect on environment; however, with the accumulation of FDI, it will create a significant positive effect on the environment.展开更多
This paper makes an empirical analysis of the spatial spillover effect of regional economic growth by using Moran’s I and Spatial Durbin Model to study the input and output of technological progress, with the panel d...This paper makes an empirical analysis of the spatial spillover effect of regional economic growth by using Moran’s I and Spatial Durbin Model to study the input and output of technological progress, with the panel data of 21 prefecture-level cities in Guangdong Province from 2008 to 2017. The empirical results show that the spatial autocorrelation exists in the economic development of Guangdong Province, and both the input and output of scientific research innovation have a significant positive effect on the regional economic growth. Under the spatial contiguity weights matrix, the output of scientific research and innovation has a more obvious spillover effect on the economic growth of neighboring cities than the input of scientific research and innovation.展开更多
This article considers 30 provinces of China as the cross-section subjects, and utilizes the data sample from 2009 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect o...This article considers 30 provinces of China as the cross-section subjects, and utilizes the data sample from 2009 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of environmental regulation on employment. The result indicates that environmental regulation has negative effect on employment with the consideration of spatial spillover effect, and this adverse effect is not significant mathematically. With the enhance of environmental regulation, the negative impact on employment will decrease accordingly, even may eventually promote job growth, which means there may be a non-linear relationship between them. Specifically, the direct effect of environmental regulation on employment indicates that it is beneficial for job growth whereas the indirect effect illustrate that it is detrimental for employment.展开更多
基金This research is supported by Shanxi Province Philosophy and Social Science Project(Grant No.W20191012)Shanxi province Soft Science Project(Grant No.2019041015-1).
文摘Under the background of green development,the function direction of technological innovation to green development efficiency,which includes economy,resources and environment,needs to be observed by demonstration.In this paper,the green development efficiency of 30 provinces(cities and districts)in China from 2004 to 2017 is measured and its intertemporal changes,regional differences of green development efficiency are analyzed by using the super efficiency SBM model,further through theoretical analysis and empirical study,the influence of technological innovation on regional green development efficiency and its impact mechanism are investigated.The influence mechanisms of the technological innovation on green development efficiency are clarified and empirically tested by spatial econometric models from the perspectives of the growth sources and quantitative analysis.The results show that during the observation period,the green development efficiency in China exhibits a U-shaped variation,but there are huge regional differences with the obvious polarization in Eastern and Midwestern regions,and that technological innovation has some effect in promoting the regional green development efficiency,but not significant enough,which are heterogeneous according to the time periods and regions.
基金This work was supported by Chinese Academy of Social Sciences Peak Strategy Project“the Advantageous Discipline(Industrial Economics)”and Major Projects of National Social Science Foundation of China“Research on Promoting New Industrialization and Optimization and Upgradong of Economic System”[Grant number.21ZD021].
文摘This paper studies the environmental effects of technical change using a spatial model with panel data from 284 prefecture-cities over 2004-2015 in China.We find that the effects of technical change vary across different dimensions of technical change and different pollution indicators.Furthermore,we also provide robust evidence for the existence of the spatial effects of technical change on environmental pollution across cities.First,indigenous technical change displays three patterns of effects on the four pollutants:a positive effect on wastewater,a negative effect on PM_(2.5)concentrations,and an inverted U-shaped relationship with SO_(2)and soot emissions.The spatial effect of indigenous technical change promotes cleaner industrial productions(fewer emissions of SO_(2),soot and wastewater)but higher PM_(2.5)concentrations.Second,technology transfers from foreign direct investment are associated with less pollution except for wastewater,and their spatial effects are unanimously negative on all pollutants.Finally,absorptive capacity can also promote cleaner industrial production,but its spatial effects can do otherwise.Accordingly,the government should take the spatial spillover effects of technical change into account when implementing specific policies,pin down specific pollutants to make full use of the pollution-reducing effects of technical change,and improve the absorptive capacity of domestic firms.
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.
基金supported by the Hubei Province Educational Division Social Science Research Project(Grant No.15G051)
文摘It is clearly stated in the 19th people's congress that we should make the environmental protection as our national policy. Therefore, it is of great importance to study this issue. This article is going to consider 30 provinces of China as the cross-section, and utilize the data sample from 2006 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of FDI. By using these data, this article creates a comprehensive environmental pollution index with the help of entropy. The result indicates that the effect of FDI on environment has a non-linear and spatial spillover characteristic. Before reaching the critical value, FDI has a negative effect on environment; however, with the accumulation of FDI, it will create a significant positive effect on the environment.
文摘This paper makes an empirical analysis of the spatial spillover effect of regional economic growth by using Moran’s I and Spatial Durbin Model to study the input and output of technological progress, with the panel data of 21 prefecture-level cities in Guangdong Province from 2008 to 2017. The empirical results show that the spatial autocorrelation exists in the economic development of Guangdong Province, and both the input and output of scientific research innovation have a significant positive effect on the regional economic growth. Under the spatial contiguity weights matrix, the output of scientific research and innovation has a more obvious spillover effect on the economic growth of neighboring cities than the input of scientific research and innovation.
基金supported by the Hubei Province Educational Division Social Science Research Project (Grant No. 15G051)
文摘This article considers 30 provinces of China as the cross-section subjects, and utilizes the data sample from 2009 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of environmental regulation on employment. The result indicates that environmental regulation has negative effect on employment with the consideration of spatial spillover effect, and this adverse effect is not significant mathematically. With the enhance of environmental regulation, the negative impact on employment will decrease accordingly, even may eventually promote job growth, which means there may be a non-linear relationship between them. Specifically, the direct effect of environmental regulation on employment indicates that it is beneficial for job growth whereas the indirect effect illustrate that it is detrimental for employment.