| At present,there is a consensus around the world that climate change is mainly due to the increase of greenhouse gases in the atmosphere,especially the increase of carbon dioxide emissions.China's energy endowment is characterized by "abundant in coal and deficient in oil",which determine that the power industry mainly uses coal for power generation,and in result the carbon emission generated is especially prominent.Promoting the low-carbon development of the power industry is an inevitable choice to achieve the peak of China's emissions in 2030.The essence of carbon emission efficiency is to obtain as much social or economic benefits as possible at the lowest emission cost,this is an important goal of sustainable development.Previous studies on carbon emission efficiency or environmental efficiency are mainly based on single factor perspective,and neglected the spatial spillover effect between evaluation units.Based on this,this study regards the carbon emission efficiency of the provincial thermal power industry as the research object.The scientific question of this research is “whether there are temporal and spatial patterns in the carbon emission efficiency of the provincial thermal power industry,and what the law is.” The related empirical research is carried out around this issue.Firstly,we set up a set of provincial carbon emission efficiency assessment model which conforms to the production characteristics of thermal power industry,and calculated the carbon emission efficiency of the thermal power industry in 30 provinces(municipalities)for 2003-2014 from the static point of view.Secondly,combined with the global Malmquist productivity index method,the efficiency changes in each region are decomposed into the allocation efficiency and production technology,in order to investigate the contributing factors behind the dynamic efficiency changes.Finally,the spatial correlation analysis based on Moran index is used to verify the spatial relationship between provinces,and the results can provide different scientific guidance for the efficiency improvement of various regions.The innovative results achieved by this study mainly include:(1)Through the Undesirable-SBM model,a set of carbon emission efficiency evaluation system is constructed in accordance with the characteristics of China's energy endowment.From the perspective of total factors,labor,capital and energy consumption are used as input indicators,power generation and carbon emissions are the desirable output and undesirable output respectively,which scientifically reflects the true level of energy utilization efficiency in the power industry.Unlike conventional DEA model,the Undesirable-SBM model can put the slack variables into the objective function,which solves the effect of non-zero relaxation on the efficiency evaluation,and scientifically measure the static difference of carbon emission efficiency of China's provincial thermal power industry.The empirical results could help the government understand the developmental difference of the regional power industry.(2)The carbon emission efficiency of the thermal power industry in various provinces is quantified and sorted by the global Malmquist productivity index,thus expanding the efficiency evaluation dimension.The Malmquist index based on the distance function can decompose the carbon emission efficiency into the technology change(TC)and allocation efficiency change(EC),so as to discover the contributing factors of the dynamic efficiency changes.From the results of decomposition,the main factors contributing to carbon emission efficiency changes in power industry are different in the six major economic regions.The efficiency improvement in Northeast China,East China,Central China and South China is due to the joint role of ECs and TCs.The Northwest and South China mainly rely on the drive of TCs.At the provincial level,economic less-developed areas are more likely to achieve greater efficiency promotion.The efficiency progress of most provinces mainly come from technological innovation,which verifies the powerful driving effect of production technology.(3)The space autocorrelation model is used to identify the spatial correlation of carbon emission efficiency in China's provincial thermal power industry,which extends the application scope of spatial econometrics theory.Influenced by factors such as industrial distribution,economic development level and resource endowment,the regional differences are significant in China.The previous efficiency study ignored the geographical factor,therefore,this research adopts spatial econometric techniques to identify the spatial agglomeration type and quantifies the spatial spillover effect between adjacent regional units.The empirical results show that more provinces(municipalities)showed significant positive spatial correlations(High-High or Low-Low)geographically.The High-High clustering type are mainly located in the eastern coastal areas with relatively high level of economic development,population quality,resource efficiency and environmental management standards.The Low-Low clustering type are mainly located in the central and western regions,the technical level and resource utilization efficiency in these areas are relatively low.These results provide a scientific basis for the construction of multilateral regional exchange and cooperation mechanism.In short,there is significant differences in the distribution of carbon emission efficiency in the thermal power industry of various provinces(municipalities)in China,and spatial correlation effect is shown between the provinces,which reflects the spatial spillover of environmental policies or technologies that may exist in various regions.It is beneficial to achieve the win-win goal of economic development and environmental protection by formulating effective and fair regional efficiency policies according to the spatial agglomeration of the provincial carbon emission efficiency. |
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