创新要素错配对碳排放效率的影响——基于空间溢出效应视角的研究  

Impact of the Misallocation of Innovation Factors on Carbon Emission Efficiency:Research Based on the Perspective of Spatial Spillover Effects

作　　者：田泽[1,2] 徐兴武 张瀚亓 任阳军 Tian Ze;Xu Xingwu;Zhang Hanqi;Ren Yangjun(Institute of Low Carbon Economy,Hohai University,Changzhou 213200,China;School of Business,Hohai University,Nanjing 211100,China;School of Economics and Trade,Changzhou Vocational Institution of Textile and Garment,Changzhou 213164,China)

机构地区：[1]河海大学低碳经济研究所,江苏常州213200 [2]河海大学商学院,江苏南京211100 [3]常州纺织服装职业技术学院经贸学院,江苏常州213164

出　　处：《科技管理研究》2024年第14期205-213,共9页Science and Technology Management Research

基　　金：国家社会科学基金后期资助项目“数字经济赋能制造业高质量发展和产业化实现研究”(21FJYB047);江苏省研究生科研与实践创新计划项目“全球风险冲击下我国新能源汽车产业链韧性评估与策略”(KYCX24_0796)。

摘　　要：合理配置创新要素、不断提高碳排放效率是中国在加快实现“双碳”目标过程中亟须解决的现实问题,而相关研究对其可能存在的空间效应的讨论相对不足。从理论层面剖析创新要素错配对碳排放效率的影响机制和空间溢出效应,将要素错配以一种扭曲税的形式表现,从投入产出视角通过超效率SBM模型测度碳排放效率,通过全要素生产率离散度法和数据包络分析法构建创新要素错配和碳排放效率的测度框架,基于2012—2021年中国30个省份的面板数据,利用空间杜宾模型、空间自相关检验方法实证检验创新要素错配对碳排放效率的影响及空间溢出效应,并将30个省份划为五大区域展开异质性分析。结果发现:创新要素错配显著抑制本地区碳排放效率提升并对空间关联地区的碳排放效率产生不利影响;创新要素错配对碳排放效率的影响存在地区异质性,中部和西南地区创新要素错配对本地区碳排放效率起到抑制作用,而东部和东北、西北地区的影响不明显;五大地区创新要素错配对空间关联地区的碳排放效率均起到抑制作用。据此,提出不断优化创新要素市场配置机制、有效鼓励企业开展低碳技术创新和应用、形成区域创新合力等助力中国碳排放效率提升的政策建议。Rational allocation of innovative factors and continuous improvement of the efficiency of carbon emissions are the practical problems that China needs to solve in the process of accelerating the realization of Carbon Peaking and Carbon Neutrality.However,relevant studies have provided a relatively insufficient discussion of their possible spatial effects.From a theoretical perspective,this paper analyzes the impact mechanism of misallocation of innovation factors on carbon emission efficiency from the viewpoints of government,financial markets,and enterprises.It also examines the spatial spillover efficiency of the misallocation of innovation factors on carbon emission efficiency through crowding-out effects,competition effects,and knowledge spillover effects.Methodologically,presenting the factor mismatch in the form of a distortion tax,and measuring carbon emission efficiency from the ultra-efficiency SBM model,the paper constructs a measurement framework for the misallocation of innovation factors and carbon emission efficiency by using the total factor productivity dispersion method and data envelopment analysis(DEA).Based on provincial panel data from 30 Chinese provinces from 2012 to 2021,the spatial Durbin model(SDM)and spatial autocorrelation test methods are employed to empirically examine the impact and spatial spillover effects of the misallocation of innovation factors on carbon emission efficiency.Heterogeneity analysis is conducted across five major regions for the sample areas:eastern,central,northeastern,southwestern,and northwestern China.The results show that the misallocation of innovation factors significantly inhibits the improvement of carbon emission efficiency in the region and adversely affects the carbon emission efficiency of spatially associated regions,presenting a dual negative effect.Due to differences in economic development levels,resource endowments,and institutional environments,the impact of the misallocation of innovation factors on carbon emission efficiency exhibits regional

关 键 词：创新要素错配 R&D资源配置 碳排放效率 空间溢出效应 全要素生产率离散度 低碳技术 区域创新 “双碳”目标 

分 类 号：X22[环境科学与工程—环境科学] F204[经济管理—国民经济] F224.2[文化科学] G301