School of Management, China University of Mining & Technology (Beijing), Beijing, China.
State Key Laboratory of Precision Measuring Technology and Instrument, Tianjin University, Tianjin, China.
PLoS One. 2021 May 5;16(5):e0250994. doi: 10.1371/journal.pone.0250994. eCollection 2021.
China's carbon emission performance has significant regional heterogeneity. Identified the sources of carbon emission performance differences and the influence of various driving factors in China's eight economic regions accurately is the premise for realizing China's carbon emission reduction goals. Based on the provincial panel data from 2005 to 2017, the super-efficiency SBM model and Malmquist model are constructed in this paper to measure regional carbon emission performance's static and dynamic changes. After that, the Theil index is used to distinguish the impact of inter-regional and intra-regional differences on different regions' carbon emissions performance. Finally, by introducing the Tobit model, the effect of various driving factors on carbon emission performance differences is analyzed quantitatively. The results show that: (1) There are significant differences in different regions' carbon emission performance, but the overall carbon emission performance presents an upward fluctuation trend. Malmquist index decomposition results show substantial differences in technology progress index and technology efficiency index in different regions, leading to significant carbon emission performance differences. (2) Overall, inter-regional differences contribute the most to the overall carbon emission performance, up to more than 80%. Among them, the inter-regional and intra-regional differences in ERMRYR contributed significantly. (3) Through Tobit regression analysis, it is found that residents' living standards, urbanization level, ecological development degree, and industrial structure positively affect carbon emission performance. On the contrary, energy intensity presents an apparent negative correlation on carbon emission performance. Therefore, to improve the carbon emission performance, we should put forward targeted suggestions according to the characteristics of different regional development stages, regional carbon emission differences, and influencing driving factors.
中国的碳排放绩效具有显著的区域异质性。准确识别中国八大经济区域碳排放绩效差异的来源和各种驱动因素的影响，是实现中国碳排放减排目标的前提。本文基于 2005-2017 年省级面板数据，构建了超效率 SBM 模型和 Malmquist 模型，以衡量区域碳排放绩效的静态和动态变化。之后，采用 Theil 指数来区分区域间和区域内差异对不同地区碳排放绩效的影响。最后，通过引入 Tobit 模型，定量分析了各种驱动因素对碳排放绩效差异的影响。结果表明：（1）不同地区的碳排放绩效存在显著差异，但总体呈波动上升趋势。Malmquist 指数分解结果表明，不同地区的技术进步指数和技术效率指数存在较大差异，导致碳排放绩效差异显著。（2）总体而言，区域间差异对整体碳排放绩效的贡献最大，超过 80%。其中，东部沿海地区和东北地区的 ERMRYR 区域间和区域内差异贡献较大。（3）通过 Tobit 回归分析发现，居民生活水平、城市化水平、生态发展程度和产业结构对碳排放绩效呈正相关，而能源强度则与碳排放绩效呈显著负相关。因此，为了提高碳排放绩效，应根据不同区域发展阶段、区域碳排放差异和影响驱动因素的特点，提出有针对性的建议。
