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ORIGINAL RESEARCH article

Front. Sustain.

Sec. Quantitative Sustainability Assessment

Delving into How Low-Carbon Policies Ultimately Enhance Corporate ESG Performance: Evidence from China

Provisionally accepted
Yongshan  DuYongshan Du1Zihao  MaZihao Ma2Yongkang  HouYongkang Hou1*Xiaoxue  YangXiaoxue Yang1Ying  LiYing Li3
  • 1China University of Petroleum, Beijing, Beijing, China
  • 2Shanghai Normal University, Shanghai, China
  • 3Rice University, Houston, United States

The final, formatted version of the article will be published soon.

Abstract: The low-carbon city pilot policy, led by the Chinese government as a comprehensive environmental regulatory initiative aimed at promoting the sustainable development of the economy, society, and environment, contributes to the enhancement of corporate ESG performance at the micro level. Using data from Chinese A-share listed companies between 2009 and 2022, this study employs a quasi-natural experiment design, leveraging the difference-in-differences (DID) method and counterfactual estimation techniques to assess the policy's impact. The analysis reveals three key findings: (1) The low-carbon city pilot policy significantly enhances corporate ESG performance, a result that remains consistent across various robustness checks, including pre-trend and placebo tests, alternative estimation models, and methods, as well as the exclusion of other policy interferences; (2) The improvement in corporate ESG performance is driven by three main mechanisms: sustained green innovation, improved quality of corporate information disclosure, and reduced corporate agency costs; (3) The policy's impact on corporate ESG performance varies based on property rights, industry type, and firm size, indicating heterogeneity in its effects, with stronger improvements observed for state-owned enterprises, heavily polluting industries, and large firms.

Keywords: low-carbon city pilot policies, Corporate ESG, Difference-in-differences method, Counterfactual estimation, Heavily polluting industries

Received: 15 Oct 2025; Accepted: 02 Dec 2025.

Copyright: © 2025 Du, Ma, Hou, Yang and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Yongkang Hou

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.