Exploring provincial carbon-pollutant emission efficiency in China: An integrated approach with social network analysis and spatial econometrics

Abstract

Carbon emissions and air pollutant emissions in China share common sources. A thorough examination of carbon and pollutant emissions is imperative for a comprehensive understanding. This study aims to assess carbon-pollutant emissions efficiency (CPEE) in 30 Chinese provinces from 2006 to 2020, focusing on the integration of carbon and air pollutant emissions. Previous research on CPEE is limited, and this article addresses this gap by investigating its spatiotemporal characteristics and identifying potential influencing factors. Our study employs a super-efficiency data envelopment analysis model, social network analysis, and spatial econometric models. The results indicate that: (1) During the research period, provincial CPEE in China follows a “W-shaped” trend and exhibits a “bimodal” asymmetric distribution, indicating notable regional heterogeneity. (2) Although spatial correlations are unstable and do not adhere to a strict hierarchical structure, positive spatial spillover effects are evident in the CPEE. (3) The spatial correlation network of CPEE displays various characteristics, including the Matthew effect, external preference, siphoning effect, and altruistic tendency. (4) Apart from technical input, explanatory variables affecting CPEE exert a significantly negative direct impact. Furthermore, the indirect effect of energy intensity on CPEE contradicts its direct effect when economic distance is considered in the spatial weight setting. These findings provide valuable theoretical insights and practical guidance for improving CPEE and its synergistic effects.