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Carbon emission efficiency and spatial clustering analyses in China’s thermal power industry: Evidence from the provincial level

Yan, Dan, Lei, Yalin, Li, Li, Song, Wen
Journal of cleaner production 2017 v.156 pp. 518-527
autocorrelation, carbon, energy industry, issues and policy, models, power plants, China
The power industry produces nearly 40% of China’s carbon emission, thus, this sector should be regarded as priority for carbon emission reduction. Identifying the unevenness of regional development may be crucial for increasing the carbon emission efficiency of power plants. This work evaluates the carbon emission efficiency using the Undesirable-SBM (slacks-based measure) model and data from China’s power industry in 30 provinces from 2003 to 2014. Moreover, the global Malmquist index, which consists of efficiency changes (ECs) and technical changes (TCs), is used to determine the driving factors of these changes. Finally, a spatial autocorrelation analysis that is based on Moran’s index is performed to confirm the non-equilibrium spatial distribution of the carbon emission efficiency for the power industry. The main findings are as follows: (1) compared to economically underdeveloped provinces, the wealthy eastern coastal provinces exhibit higher carbon emission efficiency; (2) the positive effects of TCs on the efficiency changes are stronger, moreover, the provinces with lower efficiency are more likely to achieve greater improvements; and (3) significant spatial correlations exist among the power sectors of the 30 provinces in terms of carbon emission efficiency; the eastern regions have relatively high efficiency and tend to have a positive spillover effect on the neighboring provinces. Therefore, technological cooperation between various regions is beneficial to ameliorate carbon emission efficiency. Finally, policy implications are provided to address such spatial discrepancies.