基于SBM-DEA模型湖南省碳排放效率时空差异及影响因素分析

doi:10.13249/j.cnki.sgs.2019.05.011

摘要/Abstract

摘要：

以中部湖南省为研究区域,利用超效率SBM-DEA模型与Malmquist指数对2010~2016年湖南省14个市（州）碳排放效率和环境效率进行测度和空间差异分析,结果发现：① 从时间序列演化特征来看,除长沙市、常德市外,湖南省大部分市（州）的碳排放效率和环境效率偏低,纯技术效率的贡献较大,技术效率和规模效率发挥不足,部分地区在2010~2016年间的碳排放效率有所提高,但均低于10%的增长水平;② 从空间格局分布来看,湖南省14市（州）的效率水平差异显著,表现为碳排放效率由中部地区逐步向边缘地区进行转移和提升,而环境效率的波动性较大,整体呈现出“分散-集聚-分散”的趋势。五大能源区域中湘东地区的效率水平较高,其次为湘北地区,湘南地区与湘西地区表现为空间互补型区域,湘中地区的效率水平提升则相对滞后;③ 从影响因素的分析来看,二、三产业的作用效果不显著,生态环境、工业产业集聚和对外依存度对碳排放效率具有负向作用,技术进步则表现出积极的正向影响。最后,提出结合现有的政策引导和技术水平发展,充分发挥好各地区经济规模效应,促进生产要素在区域间的快速流动,推动技术进步成为节能减排的主要驱动等建议。

关键词: 超效率SBM-DEA模型, Malmquist指数, 碳排放效率, 环境效率, 湖南

Abstract:

Hunan Province in the central region is taken as the research area. The impact of external environment and carbon emission efficiency is focused on to pay attention to the coordination of internal space and seek effective energy saving and emission reduction path. The carbon emission efficiency and environmental efficiency of 14 cities (states) in Hunan Province are measured and the spatial differences are analyzed from 2010 to 2016 by applying Super-SBM-Nonoriented model and Malmquist index. The results show that: 1) From the point of time series evolution characteristics, the carbon efficiency and environment efficiency in the most of the cities (states) are generally low except in Changsha and Changde. Pure technical efficiency contributes more significantly, while technical efficiency and scale efficiency are inadequate. Carbon efficiency improved in parts of regions from 2010 to 2016, but all are below the 10% growth level. The reason lies in the insufficient utilization of the existing technology level and scale effect in various regions, such as the failure in rational allocation and development of economy scale and advantageous resources in the process of carbon emission control. 2) From the perspective of spatial pattern distribution, the differences of efficiency level in the 14 cities (states) in Hunan province are significant. The carbon emission efficiency is gradually transferred and improved from the central region to the marginal region. While the environmental efficiency is highly volatile, showing the trend of "decentralization-agglomeration-decentralization". Specifically, the technical efficiency of carbon emission of Xiangxi, Huaihua, Zhuzhou and Xiangtan in the Eastern Hunan is significantly enhanced, while the efficiency level of Shaoyang and Hengyang in the Central Hunan and the Southern Hunan is reduced. The efficiency level of Eastern Hunan in the five energy regions is relatively high, followed by the Northern Hunan. The Southern Hunan and the Western Hunan are spatial complementary regions, and the efficiency level of the Central Hunan is relatively lagging. 3) From the analysis of influencing factors, the effect of the second and third industries is found not significant. The ecological environment, industrial agglomeration and external dependence have negative effects on carbon emission efficiency, and technological progress shows positive effects. Finally, the suggestions as combining the existing policy guidance and technological development, giving full play to the economic scale effect of various regions, promoting the rapid flow of production factors between regions and promoting technological progress to be the main driver of energy conservation and emission reduction are put forward.

Key words: Super-SBM-Nonoriented model, Malmquist index, carbon emission performance, environmental efficiency, Hunan Province

中图分类号:

X321

王兆峰, 杜瑶瑶. 基于SBM-DEA模型湖南省碳排放效率时空差异及影响因素分析[J]. 地理科学, 2019, 39(5): 797-806.

Wang Zhaofeng, Du Yaoyao. Spatial-temporal Differences and Influencing Factors of Carbon Emission Efficiency in Hunan Province Based on SBM-DEA Model[J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(5): 797-806.

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城市	技术效率	纯技术效率	综合规模效率	环境效率	TFP指数
长沙市	1.326	1.495	1.425	1.000	1.091
株洲市	0.800	0.872	0.831	0.834	1.036
湘潭市	0.995	1.047	0.995	0.934	0.987
衡阳市	0.700	0.764	0.725	0.762	1.010
邵阳市	0.524	0.713	0.525	0.878	0.818
岳阳市	0.675	0.814	0.735	0.645	1.018
常德市	1.164	1.179	1.165	1.000	1.060
张家界市	1.410	1.691	1.545	0.748	0.899
益阳市	0.607	0.721	0.620	0.921	0.968
郴州市	0.651	0.712	0.657	0.869	1.087
永州市	0.671	0.729	0.679	0.863	0.974
怀化市	0.734	0.764	0.754	0.864	0.945
娄底市	0.594	0.625	0.600	0.842	0.974
湘西州	0.958	1.066	1.018	0.832	0.982
全省均值	0.843	0.942	0.877	0.857	0.987

地区	全要素生产率变化指数	技术效率指数	技术进步指数
湘北地区	1.015	1.001	1.015
湘东地区	1.038	1.007	1.031
湘南地区	1.024	0.975	1.049
湘中地区	0.896	0.933	0.959
湘西地区	0.942	1.010	0.932

	系数	标准差	z	P>\|z\|	[95% 置信度]
de	0.631	0.483	1.310	0.191	-0.315	1.578
ds	0.740	0.691	1.070	0.285	-0.615	2.094
lns	-0.483	0.230	-2.100	0.036^**	-0.935	-0.032
lnc	-0.198	0.100	-1.980	0.048^**	-0.394	-0.002
lnd	-0.081	0.046	-1.770	0.077^*	-0.171	0.009
j	19.263	8.923	2.160	0.031^**	1.774	36.750
常数	3.574	1.712	2.090	0.037^**	0.219	6.930
sigma_u	0.151
sigma_e	0.177
rho	0.419
Wald chi²(6)	Prob>chi²=0.0013