Assessing China's carbon emission efficiency (CEE) and analyzing efficiency state transition trends are necessary to accelerate the promotion of carbon emission reduction and achieve low carbon goals. This study evaluates China's economic and social environments by using the entropy weight method. The CEE of 30 Chinese provinces from 2006 to 2020 is measured using the three-stage slack-based model with an undesirable output. Then, this study introduces a Markov chain to explore the state transition trend of China's CEE. The research conclusions are as follows. First, compared with the social environment, the economic environment has a more significant impact on CEE. Second, the CEE of the eastern region is the highest, followed by that of the central region and the western region, which has the worst CEE. Third, the inefficiency of the central and western regions pulls down the overall CEE of China. Fourth, the state of China's CEE is gradually shifting to a high level; however, achieving a leapfrog shift is difficult.
Keywords: Carbon emission efficiency; Markov chain; State transition; Three-stage SBM model.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.