Measurement and Spatial Correlation Analysis of ESG Performance in Chinese Provinces

This article utilizes panel data collected from 31 provincial-level administrative regions in China over the period from 2012 to 2023. The TOPSIS-entropy weighting method is utilized to assess the environmental, social, and governance (ESG) performance of provinces. Based on this, the study employs three-dimensional kernel density estimation, the Dagum Gini coefficient, the convergence mechanism, and Moran’s I index to characterize the spatial–temporal distribution differences and convergence characteristics of provincial ESG performance. The findings reveal that the ESG performance of provinces in China shows a fluctuating upward trend, with the eastern regions outperforming the central and western regions. The Dagum Gini coefficient decomposition indicates significant differences in ESG performance across provinces, with the majority of the disparity stemming from inter-regional imbalances. Both α-convergence and β-convergence tests show no convergence trend in provincial ESG performance, with regional disparities continuing to grow. The Moran’s I index reveals a strong positive spatial correlation in ESG performance, with clustering effects observed in provinces with high and low ESG performance, respectively. This study provides evidence on regional ESG development in the emerging countries.