Research On The Spatial Spillover Effect And Spatial Heterogeneity Impact Of Financial Development On Carbon Emissions

Nowadays,the sharp increase in carbon emissions has become a major concern of all mankind and an urgent problem to be solved.China’s high carbon emissions have attracted widespread attention from all over the world.The Chinese government has also clearly proposed the strategic goals of "Emission peak" in 2030 and "Carbon neutrality" in2060.Studying the impact of financial development on carbon emissions can not only provide decision-making reference for improving the financial market and rationally formulating financial policies,but also provide empirical support for achieving the goals of "Emission peak" and "carbon neutrality",so as to allocate resources in the whole society more rationally.This thesis analyzes the complex economic and social factors affecting carbon emissions,constructs a systematic and cross-validated spatial econometric empirical system,and studies the spatial spillover effects and spatial heterogeneity of financial development’s impact on carbon emissions.This thesis establishes an interaction framework between carbon emissions and 11 influencing factors including financial development,economy,and population,and puts forward a series of hypotheses,forming a theoretical basis for the spatial spillover effect and spatial heterogeneity of financial development on carbon emissions.Based on the STIRPAT model,a systematic and cross-validated empirical system has been constructed,which covers many models and algorithms such as non-spatial panel data model,spatial Durbin model,spatial filtering model,and spatial filtering varying coefficient model.Based on this,a systematic empirical research has been carried out,and more credible research conclusions have been drawn.In addition,in order to further study the impact mechanism and path of financial development on carbon emissions,this thesis adopts the intermediary effect test model to capture the impact path of financial development on improving air quality by promoting technology market turnover and increasing the number of patents per capita.In order to test the robustness of the model,this thesis uses methods such as eliminating some influencing variables and replacing the spatial weighting matrix to reconstruct the spatial econometric model to test the robustness of the model.The main conclusions of this thesis are as follows: 1.There is spatial autocorrelation in carbon emissions,and some explanatory variables have not only direct effects but also spatial spillover effects on carbon emissions.These explanatory variables include financial development,population,technology,industrialization,trade openness,Per capita car ownership,etc.2.The improvement of financial development level will reduce carbon emissions,the increase of population will reduce carbon emissions,the development of science and technology,and the increase of trade openness will help reduce carbon emissions.On the contrary,industrialization,per capita car ownership,housing construction area,foreign enterprises Investment has a positive impact on carbon emissions.3.In China,the relationship between economic development and carbon emissions presents an inverted "U"-shaped EKC curve.4.The coefficients of some explanatory variables on carbon emissions show obvious spatial differences.These explanatory variables include financial development,total population,industrialization,per capita car ownership,housing construction area,deposit-loan ratio,etc.Among them,the influence coefficient of financial development presents a spatial difference of "smaller in the northeast region and larger in the southwest region".This difference can be used as a geographical dividing line connecting the easternmost point of Xinjiang and the easternmost point of Fujian.