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Spatial Correlation And Influencing Factors Analysis On Carbon Emission Abatement Capacity At Provincial Level In China Based On SDM Model

Posted on:2019-04-27Degree:MasterType:Thesis
Country:ChinaCandidate:Y WangFull Text:PDF
GTID:2381330626451948Subject:Business Administration
Abstract/Summary:PDF Full Text Request
As the largest developing country in the world,China has experienced sustained and rapid economic growth since the reform and opening up,and has now become the world's second largest economy.However,at the same time,China's energy consumption and carbon emissions are also growing,facing increasing pressure from the international community and domestic public opinion.And for this,the Chinese government has made a series of efforts to reduce carbon emissions and stabilize economic growth at the same time.In this paper,we take the economic development and carbon emission data of 30 provinces,autonomous regions and municipalities in China from 1997 to 2016 as the research object,constructs the carbon emission abatement capacity index(CACI),and use the method of spatial econometrics to analysis whether the carbon emission reduction potential at the provincial level has spatial agglomeration.Furthermore,this paper identifies the key factors of China's provincial carbon emission abatement potential through spatial SDM model,and analyzes the mechanism and spatial spillover effects of these influencing factors.Finally,this paper provides theoretical support and policy advice for regional governments to set carbon emission reduction targets and strengthen regional carbon reduction cooperation.The conclusions of this paper are as follows:(1)Since 1997,China's overall carbon emission has continued to rise,and has not yet reached the peak,but the growth rate has noticeably slowed down.From the perspective of spatial distribution,the carbon emission of different regions also show great gaps.Shandong,Jiangsu,Guangdong,Hebei,Shanxi and Liaoning have the high average carbon emissions during the research period,accounting for the 40.45% of national total carbon emissions;Tianjin,Jiangxi,Beijing,Chongqing,Ningxia,Qinghai and Hainan have lower overall carbon emissions,accounting for the 8.55% of the national total carbon emissions.(2)There are obvious regional differences in the carbon emission abatement index.During 1997-2016,the carbon emission reduction potentials of all provinces and regions in China showed an slightly decreasing trend,but the carbon emission reduction costs and potential levels were significantly different.The distribution is also not balanced.In general,Ningxia,Shanghai,Shanxi,Qinghai and Tianjin have large implementation space for emission reduction policies.The emission reduction potential of these five regions accounts for 33.4% of the national carbon dioxide emission reductions,and have significant influence to the national reduction target.(3)The carbon emission abatement potential at the provincial level shows significant positive spatial agglomeration effect.At the same time,with the increasing frequency of economic activities across regions,the interactions among regions are becoming more and more important.The spatial agglomeration of carbon emission reduction potential in various regions is also strengthening at the provincial level.The local spatial autocorrelation is relatively stable,with the most provinces are in the “high-high” cluster and the “low-low” cluster quadrant.(4)The level of economic development,population agglomeration,energy intensity and investment of R&D all have significant effect in promoting regional carbon emission reduction potential,and its impact is diminishing;urbanization has a significant negative effect on carbon emission reduction potential.The influence of foreign trade degree and industry structure on the carbon emission potential is not significant.Further analysis found that the level of economic development,energy intensity and industrial structure have significant spatial spillover effects on the carbon emission reduction potential at the provincial level in China,and the spatial spillover effects of economic development level and energy intensity are negative,the spatial spillover effect of industrial structure is positive.
Keywords/Search Tags:Carbon emission abatement capacity, SDM model, Spillover effects, Influencing factors
PDF Full Text Request
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