| Low-carbon economic development has become the primary goal by all countries in the world,and its low energy consumption,low emission,low pollution and high efficiency production mode is also the inevitable choice for China to achieve high-quality development.At present,the most important contradiction in Chinese society has been transformed into the contradiction between the people’s growing need for a better life and the imbalance and insufficient development.Due to the significant differences among provinces in economic level,resource endowment,development orientation and environmental protection policies,the spatial distribution of carbon emission efficiency in China’s provinces is greatly different,and its dynamic evolution trend and key factors affecting carbon emission efficiency are different,which poses a great challenge to meeting people’s demand for a better ecological environment.This thesis will scientifical y assess the carbon emission efficiency of various provinces and regions,identify the potential direction of emission reduction,and analyze the main factors affecting regional carbon emission efficiency from a spatial perspective,so as to provide reference suggestions for China’s path optimization scheme to achieve comprehensive low-carbon transformation.The main research is listed as follows:(1)Under the framework of data envelopment analysis,carbon emission is regarded as an unexpected output,and the regional GDP of each province is taken as the expected output.With the input of energy,labor and capital,the carbon emission efficiency of 30 provinces in China from 2000 to 2016 is measured.Secondly,based on the measurement of provincial carbon emission efficiency,the dynamic evolution characteristics are analyzed and measured by using the kernel density distribution function,and the spatial autocorrelation is tested by using the Moran index to find the distribution law of its spatial effect.The results show that the overall carbon emission efficiency in China shows a slight downward trend and has recently increased,but the emission reduction situation is still different and optimistic.The main reason is the low production efficiency in the western provinces and the obvious downward trend,which is an important reason for the small decrease in the overall carbon emission efficiency.(2)The nuclear density distribution curve is used to explore the spatial distribution state of provincial carbon emission efficiency.The results show that the shape of the distribution curve has changed significantly in 2000,2012 and 2016,and the nuclear density distribution map is becoming more and more flat.Secondly,using the Moran index to test the spatial correlation of provincial carbon emission efficiency,30 provinces showed the positive spatial autocorrelationcharacteristic of “ stability → enhancement” during the sample study,and all Moran values passed the significance test,which indicates that the number of provinces in “ high concentration” and “low concentration” is the vast majority,and the number is still increasing,and the spatial positive autocorrelation characteristic is gradually increasing.(3)Through the spatial adjacency matrix,the regional linkage relationship between provinces is introduced into the model of influencing factors of carbon emission phase ratio,and the domestic technology output and foreign technology spillovers are expanded into explanatory variables to construct the spatial Dubin model of influencing factors of carbon emission efficiency.The results show that the regional GDP and patent output level of one province have obvious positive driving effects on the carbon emission efficiency in this region,while industrial structure factors and energy consumption structure factors have obvious negative effects on the carbon emission efficiency in this region.The regional GDP and patent output level of neighboring provinces have a significant positive effect on the regional carbon emission efficiency,and the energy consumption structure factors of neighboring provinces have a significant negative effect on the regional carbon emission efficiency. |
PDF Full Text Request