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1、微观视角下居民消费碳排放结构及影响因素研究基于PLSSEM模型的实证分析一、本文概述Overviewofthisarticle随着全球气候变化问题的日益严重，减少碳排放、实现低碳发展已成为全球共识。作为世界上最大的发展中国家，中国的碳排放问题备受关注。其中，居民消费碳排放作为碳排放的重要组成部分，其结构及影响因素研究对于推动中国低碳转型具有重要意义。本文旨在从微观视角出发，深入探讨中国居民消费的碳排放结构及其影响因素，以期为相关政策制定提供科学依据。Withtheincreasingseverityofglobalclimatechange,reducingcarbonemissionsand
2、achievinglow-carbondevelopmenthasbecomeaglobalconsensus.Astheworld5slargestdevelopingcountry,China,Scarbonemissionshaveattractedmuchattention.Amongthem,theconsumptionofcarbonemissionsbyresidentsisanimportantcomponentofcarbonemissions,andthestudyofitsstructureandinfluencingfactorsisofgreatsignificanc
3、eforpromotingChina,slow-carbontransformation.ThisarticleaimstoexplorethecarbonemissionstructureandinfluencingfactorsofChineseresidents,consumptionfromamicroperspective,inordertoprovidescientificbasisforrelevantpolicyformulation.具体而言，本文利用PLS-SEM(偏最小二乘结构方程模型)这一先进的统计分析工具，对居民消费碳排放问题进行了实证分析。PLS-SEM模型结合了偏
4、最小二乘回归(PLS)和结构方程模型(SEM)的优点，能够处理复杂系统中的因果关系，并有效处理变量间的多重共线性问题，因此在社会科学研究中得到了广泛应用。Specifically,thisarticleusesPLS-SEM(PartialLeastSquaresStructuralEquationModeling),anadvancedstatisticalanalysistool,toempiricallyanalyzetheissueofcarbonemissionsfromhouseholdconsumption.ThePLS-SEMmodelcombinestheadvantages
5、ofpartialleastsquaresregression(PLS)andstructuralequationmodeling(SEM),whichcanhandlecausalrelationshipsincomplexsystemsandeffectivelyhandlemulticollinearityproblemsbetweenvariables.Therefore,ithasbeenwidelyusedinsocialscienceresearch.通过构建PLS-SEM模型，本文不仅分析了居民消费碳排放的结构特征，还深入探讨了影响居民消费碳排放的关键因素。这些因素包括但不限于
6、居民消费水平、消费结构、能源消费结构、技术进步、政策引导等。通过对这些因素的综合分析，本文旨在为政策制定者提供有针对性的建议，以促进居民消费模式的低碳转型，从而推动整个社会的可持续发展。ByconstructingaPLS-SEMmodel,thisarticlenotonlyanalyzesthestructuralcharacteristicsofcarbonemissionsfromresidentialconsumption,butalsodelvesintothekeyfactorsaffectingcarbonemissionsfromresidentialconsumption.
7、Thesefactorsincludebutarenotlimitedtohouseholdconsumptionlevel,consumptionstructure,energyconsumptionstructure,technologicalprogress,policyguidance,etc.Throughacomprehensiveanalysisofthesefactors,thisarticleaimstoprovidetargetedrecommendationsforpolicymakerstopromotethelow-carbontransformationofhous
8、eholdconsumptionpatternsandpromotethesustainabledevelopmentoftheentiresociety.本文从微观视角出发，利用PLS-SEM模型对居民消费碳排放结构及影响因素进行了深入研究。本文的研究结果将有助于我们更好地理解居民消费碳排放的内在机制，为相关政策制定提供科学依据，为推动中国的低碳转型和可持续发展做出贡献。Thisarticleconductsin-depthresearchonthestructureandinfluencingfactorsofcarbonemissionsfromhouseholdconsumptionu
9、singthePLS-SEMmodelfromamicroperspective.TheresearchresultsofthisarticlewillhelpIISbetterunderstandtheinternalmechanismofcarbonemissionsfromhouseholdconsumption,providescientificbasisforrelevantpolicyformulation,andcontributetopromotingChina,slow-carbontransformationandsustainabledevelopment.二、文献综述1
10、.iteraturereview在全球气候变化和碳排放问题日益严重的背景下，居民消费碳排放逐渐成为研究热点。国内外学者对居民消费碳排放的结构和影响因素进行了广泛而深入的研究。Againstthebackdropofincreasinglysevereglobalclimatechangeandcarbonemissions,consumercarbonemissionshavegraduallybecomearesearchhotspot.Domesticandforeignscholarshaveconductedextensiveandin-depthresearchonthestruct
11、ureandinfluencingfactorsofcarbonemissionsfromresidentialconsumption.早期的研究主要关注于居民消费碳排放总量的变化及其与经济发展的关系。随着研究的深入，学者们开始关注居民消费碳排放的结构性问题，即不同消费类别对碳排放的贡献度及其动态变化。例如，食品、交通、住房等消费类别对碳排放的影响程度及其演变趋势成为了研究的重点。这些研究为我们理解居民消费碳排放的结构性特征提供了重要的参考。Earlyresearchmainlyfocusedonthechangesintotalcarbonemissionsfromhouseholdcons
12、umptionandtheirrelationshipwitheconomicdevelopment.Withthedeepeningofresearch,scholarshavebeguntopayattentiontothestructuralissuesofhouseholdconsumptioncarbonemissions,namelythecontributionanddynamicchangesofdifferentconsumptioncategoriestocarbonemissions.Forexample,theimpactofconsumptioncategoriess
13、uchasfood,transportation,andhousingoncarbonemissionsandtheirevolutionarytrendshavebecomeafocusofresearch.Thesestudiesprovideimportantreferencesforustounderstandthestructuralcharacteristicsofcarbonemissionsfromresidentialconsumption.同时，对于居民消费碳排放的影响因素的研究也取得了丰硕的成果。学者们从多个角度探讨了影响居民消费碳排放的因素，包括人口规模、经济发展、技术
14、进步、消费结构、政策环境等。其中，人口规模和经济发展对居民消费碳排放的影响得到了广泛认可。随着能源结构和消费模式的转变，技术进步和消费结构对碳排放的影响逐渐显现。Atthesametime,fruitfulresultshavebeenachievedinthestudyoftheinfluencingfactorsofcarbonemissionsfromresidentialconsumption.Scholarshaveexploredthefactorsthataffecthouseholdconsumptioncarbonemissionsfrommultipleperspectiv
15、es,includingpopulationsize,economicdevelopment,technologicalprogress,consumptionstructure,policyenvironment,etc.Amongthem,theimpactofpopulationsizeandeconomicdevelopmentonhouseholdconsumptioncarbonemissionshasbeenwidelyrecognized.Withthetransformationofenergystructureandconsumptionpatterns,theimpact
16、oftechnologicalprogressandconsumptionstructureoncarbonemissionsisgraduallybecomingapparent.近年来，随着模型方法的不断创新，越来越多的学者开始运用先进的统计模型对居民消费碳排放进行深入研究。其中，PLSTEM模型作为一种集多元线性回归、路径分析和结构方程模型于一体的综合性分析方法，具有处理复杂变量关系、揭示潜在机制和路径等优点，因此在居民消费碳排放研究中得到了广泛应用。PLS-SEM模型能够同时考虑多个影响因素，揭示各因素之间的相互作用关系，为我们更深入地理解居民消费碳排放的影响机制提供了有力工具。Inrecentyears,withthecontinuousinnovationofmodelingmethods,moreandmorescholarshavebeguntouseadvancedstatisticalmodelstoconductin-depthresearchonhouseholdcons
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