Evaluation of China’s provincial eco-efficiency with the explainable boosting machine (EBM) model and Tobit regression

Abstract

The explainable boosting machine (EBM) model measures China’s provincial eco-efficiency, and the Tobit regression model reveals internal driving factors to provide consultation for promoting China’s green development based on the panel data of 30 provinces from 2000 to 2018. The findings of this article are as follows: provincial-level regional ecological efficiency is low, growth is slow, regional differentiation is significant, and development still has a trend of incoordination and multi-polarization. From the perspective of global autocorrelation, the Moran index is significantly positive, and the province eco-efficiency of the first grade presents a positive spatial correlation and has the characteristics of spatial agglomeration. The regression analysis results show that the economic level, the FDI, the level of technological innovation, and the level of human capital are the main influencing factors of eco-efficiency, and there are spatial differences. Relevant suggestions are based on the status and influencing factors of the unbalanced development heterogeneity of provincial eco-efficiency in China.