This study takes the panel data of 30 provinces and cities in China from 2010 to 2019 as the research object. Python software is used to analyze the text of local government work reports, and counts the frequency of words related to environmental protection and their proportion in the full text in order to measure government environmental willingness. EBM-global Malmquist model is employed to measure total factor carbon efficiency; the entropy method is used to calculate the quality index of economic development. The research results show that: (1) Government environmental willingness doesn’t promote total factor carbon efficiency, but inhibit total factor carbon efficiency. If the variable is replaced, the results are still valid. (2) The mediating effect results show that there is a channel of “enhancing government environmental willingness-reducing quality of economic development-reducing total factor carbon efficiency”. (3) The moderating effect results show that the Gini coefficient strengthens the inhibitory effect of government environmental willingness on total factor carbon efficiency, that is, with the expansion of income gap, the inhibitory effect of government environmental willingness on total factor carbon efficiency will increase. (4) The machine learning method can improve the goodness of fit to the regression, and the importance map of variables shows that the most important thing for improving the total factor carbon efficiency is to optimize the industrial structure.

Guangting Guo, Yuqing Jia, Jiahui Liu, Jingya Liu, Xueting Zhang. Can Government Environmental Willingness Promote Total Factor Carbon Efficiency?− Evidence from China’s Provincial Level. Academic Journal of Business & Management (2022) Vol. 4, Issue 8: 13-26. https://doi.org/10.25236/AJBM.2022.040803.

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