Spatial Econometric Analysis Of Carbon Emission Intensity And Its Driving Factors In China

In the context of global warming,for China,seeking the influencing factors of carbon emission intensity is not only an important way to achieve the goal of energy conservation and emission reduction,but also a key basis for forcing the transformation of economic development mode.Based on the extended Kaya identity,this paper calculates the carbon emissions of China's provinces from the perspective of apparent energy consumption,and then estimates the carbon emission intensity of 30 provinces in China from 1995 to 2017.The spatial adjacency matrix,geographic distance matrix and economic distance matrix are constructed according to three different distance measurement methods,and on this basis,the temporal and spatial evolution characteristics of China's carbon emission intensity are analyzed from aspects of time sequence and space.Then,the spatial econometric model is constructed for the whole country,the eastern,central and western regions and the regions with different demographic structures,which are used to discuss the influencing factors of the spatial-temporal evolution of carbon emission intensity in China's provinces from the perspective of the whole region and the locality,so as to provide the scientific basis for the government to formulate policies on energy-saving and emission reduction.Through theoretical research and empirical test above,the following conclusions are mainly drawn:(1)From the time series evolution characteristics,when China's carbon dioxide emissions continue to increase,the overall carbon emission intensity shows a downward trend at the same time,but the carbon emission intensity change characteristics are different in different provinces;The global spatial correlation test shows that under the three weight matrices,China's carbon emission intensity presents significant spatial agglomeration characteristics,but this spatial agglomeration gradually declines over time.(2)From the perspective of spatial evolution characteristics,the regional characteristics of high carbon emission intensity in the north and low carbon emission intensity in the south is gradually broke down,and the local spatial correlation test further confirmed the fact that the spatial agglomeration of carbon emission intensity in China's provinces gradually weakened.(3)The spatial correlation between provinces with similar position is stronger than that between provinces with similar economic level,that is,geographical location has a more significant impact on the spatial correlation of carbon emission intensity.(4)In the national level,the improvement of the per capita GDP,technical level,and urban residents' engel coefficient can reduce the regional carbon intensity,the improvement of population density,urbanization rate and industrial structure,energy structure can increase the regional carbon intensity,Aging,urbanization,engel coefficient of urban residents,energy structure and industrial structure have significant spatial effects on carbon emission intensity of surrounding areas.(5)Estimation results in the east,middle and west area show that the spatial effect of demographic factors plays a significant role in carbon intensity in the eastern and middle region,raise the level of population agglomeration can promote the efficiency of carbon emissions of eastern and central regions in each province and surrounding provinces,coordination between regional promote economic development and technological progress,optimize the residents'consumption structure is the key to reducing carbon intensity in the western region of China.(6)For regions with high urbanization and aging levels but slow development,the optimization of residents' consumption structure can significantly reduce carbon intensity;For regions with slow urbanization and serious aging,the spatial effects of population density and industrial structure are significant,improving the level of population aggregation and optimizing industrial structure are the keys to reducing carbon intensity.For regions with rapid urbanization but not serious aging,the spatial effect of economic development level and industrial structure is significant,full use of urbanization dividends to promote economic and industrial upgrading can effectively reduce carbon intensity.Finally,summarize research conclusions and policy suggestions,and explains the deficiencies and research prospects of this study.