Dynamic evolution and driving forces of carbon emission efficiency in China: New evidence based on the RBM-ML model

The globe is being confronted with a tremendous challenge in the form of global warming, which is produced by emissions of carbon dioxide. To accomplish the double-sided objective of reducing carbon emissions while preserving a healthy rate of economic development, it is crucial to evaluate the driving forces of carbon emissions. In this study, the polar coordinate method is employed to improve the traditional Slacks-based Measure (SBM) method and propose a Ray SBM (RSBM). Additionally, the revised approach is paired with the Malmquist-Luenberger (ML) index to determine the carbon emission effectiveness (CFTP) of 30 prefectural regions in China between 2001 and 2019. The evolution features of the CFTP are examined by kernel density and spatial Markov chain. Moreover, according to the findings, CFTP in China has seen a moderate increase, with cutting-edge technological progress serving as the primary driver. The CFTP in eastern China is significantly lower than that in western China, and there is a discernible tendency toward the disparity becoming even wider. In addition, there is obvious club convergence in China's CFTP, which shows certain spatial agglomeration characteristics in the sample period. In accordance with the low-carbon economic theory and literature on CFTP, the variables of industrial structure, energy structure, technological progress, economic growth and environmental regulation are utilized to examine the driving factors for the spatial econometric model, and the corresponding spatial spillover effect is obvious.