How does auditing outgoing officials' natural resource asset management policies affect carbon emission efficiency? Evidence from a debiased machine learning model

Abstract

Reducing carbon emissions to improve environmental quality has been the Chinese government's unwavering dedication in recent years. Several policies have been implemented with the objective of driving carbon reduction. The implementation of the outgoing leadership natural resources audit policy has played a pivotal role in encouraging local government officials to prioritize both economic and environmental development in their pursuit of performance metrics. However, whether the implementation of this policy contributes to an enhancement in carbon emission efficiency requires further empirical validation. This study, utilizing panel data from 282 cities across China, explores the potential impact of the audit policy (specifically referring to the outgoing leadership natural resources asset audit policy, without ambiguity) on carbon emission efficiency through the application of a debiased machine learning model. The results of the study show that the audit policy has been crucial in greatly raising the regional level of carbon emission efficiency. Furthermore, mechanistic analysis results suggest that the audit policy can enhance regional carbon emission efficiency by influencing green innovation and raising government environmental awareness and green financial levels. Based on the heterogeneity analysis, the regions east of the Hu Line, cities with low levels of corruption, less stringent economic growth objectives, and areas with high levels of public environmental concern are the areas where auditing rules have the greatest influence on carbon emission efficiency. In conclusion, based on the comprehensive results of this study, a series of policy recommendations are presented to further advance China's efforts in carbon reduction, ultimately achieving a more sustainable balance between economic and environmental development objectives.