http://doi.org/10.62220/j.ssbpa.2024.01.003
Quande Qin
ABSTRACT
The thermal power generation industry plays a crucial role in China’s energy conservation and emission reduction strategy. To effectively assess the environmental efficiency of this industry, we utilize a super efficiency slacks-based measure directional distance function integrated model in this study. Additionally, we employ the Dagum Gini coefficient and its decomposition method, the spatial Markov chain method, and stochastic convergence test method to empirically analyze the disparities, distributed dynamic evolution, and convergence of environmental efficiency within China’s thermal power industry. The study’s findings reveal several key insights. Firstly, the overall environmental efficiency of the thermal power industry is improving, although regional disparities persist. Secondly, the gap in regional spatial distribution is decreasing, with inter-regional disparities being the primary source of the environmental efficiency gap in China. Thirdly, there is a significant spatial dependence in the environmental efficiency of China’s thermal power industry. Lastly, the evolution of environmental efficiency within the thermal power industry follows a pattern of stochastic convergence. These results provide a strong basis for addressing the efficiency gap and contribute to enhancing the coordinated development of China’s thermal power industry.
KEYWORDS
Environmental efficiency; Thermal power industry; Data envelopment analysis; Disparity; Stochastic convergence