Calculation Of Environmental Rebound Effect And Analysis Of Influencing Factors

At present,the environmental situation in China is still severe,bringing a huge crisis to economic development.In the context of a new era of building a resource saving and environment friendly society,promoting the construction of socialist ecological civilization,and high-quality economic growth,technological progress has become a key factor and important way to improve energy efficiency and reduce the total amount of environmental pollution,attracting high attention from the state and government departments.However,while technological progress can improve energy efficiency and reduce the intensity of pollution emissions,it can also cause changes in production and consumption behavior,thereby stimulating the demand for energy,causing more pollutant emissions and forming an environmental rebound effect.Therefore,measuring the environmental rebound effect and analyzing its influencing factors have important theoretical and practical significance for the smooth progress of the pollution reduction work and high-quality economic development.This thesis first summarizes the relevant research on the rebound effect,and discusses the theoretical mechanism of the formation of the environmental rebound effect.Then,it analyzes its possible impact on the environmental rebound effect from four aspects: environmental regulation,economic development,energy consumption structure,and economic openness.Secondly,this thesis constructs a measurement model of environmental rebound effect,and then uses a random frontier transcendental logarithmic production function to calculate the contribution rate of technological progress of 30 provinces in China from 2005 to 2020.At the same time,this thesis uses the entropy method to calculate the pollution emission intensity of each province over the years.Then,the calculated contribution rate of technological progress and pollution emission intensity are substituted into the measurement model of environmental rebound effect to obtain the environmental rebound effect value of each province from 2006 to2020.Finally,based on theoretical analysis,this paper selects indicators such as environmental regulation intensity,per capita GDP,urbanization rate,industrial structure,energy consumption structure,and foreign direct investment to construct a dynamic panel model,and uses systematic GMM and bias correction LSDV methods to analyze the impact factors of environmental rebound effects at the national and regional levels,respectively.The main research conclusions of this thesis include:(1)During the sample period,the overall average level of environmental rebound effect is relatively high,and the average level in the central region is higher than that in the eastern and western regions;The rebound effect of the environment in the central and western regions has shown a significant upward trend since 2018.(2)From a national perspective,the intensity of environmental regulation,the proportion of the tertiary industry,and foreign direct investment can effectively suppress the environmental rebound effect;Urbanization rate and per capita GDP will have a negative impact on the environmental rebound effect,but the statistical results are not significant;The proportion of coal consumption in the total energy consumption has a significant positive effect on the environmental rebound effect.(3)From the regional level,the impact of various indicators on the environmental rebound effect is basically consistent with the national level,but there are significant regional differences in the impact of environmental regulation intensity and the proportion of tertiary industry on the environmental rebound effect.The inhibitory effect of environmental regulation intensity in the eastern region is the strongest,while the inhibitory effect of environmental regulation intensity in the central and western regions is relatively weak.The inhibitory effect of the proportion of tertiary industry in the central and western regions is relatively strong,while the inhibitory effect of the proportion of tertiary industry in the eastern region is relatively weak.