(1.西南交通大学 经济管理学院，成都，610031；2.北京大学 中国经济研究中心，北京，100871)
摘要：本文利用序列DEA与方向性距离函数构造了三类碳排放绩效指数，较为精确地测算了2003～2010年我国30个省、市及自治区的碳排放绩效静态水平与动态变化，同时将结构因素划分为产业结构、工业结构、禀赋结构及能源结构等四类因素，运用面板数据计量模型就结构性调整对碳排放绩效变化和碳排放绩效省际差距的影响进行计量检验与分析，结果发现：（1）我国区域之间碳排放绩效水平极不平衡，省际之间差距较大；（2）从动态变化路径上看，我国各地区碳排放绩效整体上呈上升趋势；（3）积极推进第三产业发展，优化产业结构，深化产权制度改革，降低国有产权比重，能够在一定程度上改善碳排放绩效，合理引导资本流向，优化资本结构，对碳排放绩效提升具有重要意义。此外，降低煤炭消费比重及优化能源消费结构也能够显著提升碳排放绩效；（4）产业结构、所有制结构、禀赋结构及能源结构等因素对我国碳排放绩效省际差距的形成具有较强解释力度，从各因素贡献度上看，所有制结构因素对碳排放绩效省际差距平均贡献达到21.51%，能源结构因素达到17.99%，禀赋结构因素为14.52%，产业结构因素最小，平均贡献为2.97%。
关键字：结构性调整 碳排放绩效 贡献度
中图分类号 F124.6 文献标识码 A
Can Structural Adjustments Improve Carbon Emissions Performance?
——Evidence from Chinese Provincial Panel Data (2003~2010)
Zha jianping1, T ang fangfang1,2
(1. School of Economics and Business Administration，Southwest Jiaotong University，Chengdu 610031,China;2.China Center for Economic Research, Peking University,Beijing 100871,China.)
Abstract: The paper constructs three kinds of carbon emissions performance indices with sequential DEA and directional distance function，and accurately evaluates the static level and dynamic changes of carbon emission performance of China's 30 provinces, municipalities and autonomous regions during 2003~2010.Moreover，The paper divides the structure factors into four factors，which include industrial structure, industrial structure, endowment structure and energy structure，then uses panel data econometric model to analyse the impact of structural adjustment to carbon emissions performance change and the inter-provincial gap of carbon emissions performance.The results show that : (1) the performance level of carbon emissions among the regions of our country is extremely unbalanced，and the inter-provincial gap is enormous; (2)From the perspective of dynamic changes , regional carbon emissions performance presents a rising trend as a whole； (3)To promote the development of tertiary industry，optimize the industrial structure ，deepen reform of property rights，and reduce the proportion of state-owned property，to a certain extent, could improve the performance of carbon emissions. Besides, to guide capital flows and optimize capital structure is important to the improvement of carbon emissions performance. In addition, optimizing the structure of energy consumption and reducing coal consumption proportion could promote carbon emissions performance significantly .(4) Industrial structure, ownership structure, endowment structure and energy structure and so on have a certain influence on the inter-provincial gap of China's carbon emissions performance. From the perspective of impact contribution , the average contribution of ownership structure to the inter-provincial gaps of carbon emissions performance is 21.51%, which of energy structure and endowment structure are 17.99% and 14.52%, the industry structure is the smallest, with an average contribution of 2.97%.
Keywords: Structural Adjustment Carbon Emissions Performance Contribution
引言
作为现今全球最大的碳排放国，我国所面对的碳减排压力与日俱增。虽说从“共同但有区别责任”的原则出发，我国尚无须承担强制性减排义务，但是为了应对气候博弈的不确定性和国际贸易中可能出现的“低碳门槛”，推进碳减排工作、提升碳排放绩效自然成为我国应对未来风险的必然选择。有鉴于此，我国政府于2009年11月提出了2020年单位国内生产总值二氧化碳排放比2005年下降40%~45%的减排目标。这既是对当前国际减排呼声的回应，也符合可持续发展之要求，因而着力提升碳排放绩效对我国社会与经济的持续发展具有重要意义。迄今为止，众多国内外学者主要从结构与技术角度出发，对我国碳排放绩效的影响因素进行研究。从长远角度来看，要转变经济发展方式，走新型工业化道路，结构性调整是关键，因而结构性调整是低碳发展和经济结构升级双重压力下的必然选择。那么结构性调整对碳排放绩效产生何种性质的影响？结构性调整能否缩小碳排放绩效之间的差距？这些都是本文所要讨论的重点。
本文采用2003~2010年我国省级面板数据，运用方向性距离函数与序列DEA（Sequential DEA）方法构建了三类碳排放绩效指数，测算了全要素视角下我国碳排放绩效的静态水平与动态变化，并以碳排放绩效为被解释变量，以各结构性因素和技术水平为解释变量，构建了一个旨在解释碳排放绩效变化及其省际差异的面板数据计量模型，再利用相应的省级面板数据对模型进行计量检验与运算，最后对研究结论进行分析与总结。
