The Spatiotemporal Evolution and Driving Mechanisms of Environmental Efficiency in China's Electric Power Industry: Based on a Two-Stage DEA Model

Based on provincial panel data from 2012 to 2022, this paper uses a two-stage DEA model to measure the environmental efficiency of China's electric power industry. It combines the Dagum Gini coefficient, Kernel density estimation, and Tobit model to examine the spatial distribution pattern, regional disparities, and driving mechanisms of environmental efficiency in the industry. The results show that during the study period, the environmental efficiency of China's electric power industry exhibited a wave-like growth pattern; there were significant imbalances in environmental efficiency; and factors such as economic scale, industrial structure, technological progress, and openness to the outside world had a strong impact on environmental efficiency. Based on the findings, the paper proposes relevant countermeasures to improve the environmental efficiency of China's electric power industry and reduce regional disparities.