The Impact of Green Credit Policy on the Corporate Value of High-Polluting Enterprises
DOI:
https://doi.org/10.47852/bonviewFSI52025915Keywords:
green credit policy, high-polluting enterprises, difference-in-differences (DiD) modelAbstract
China's 1980s strategic focus on economic development initiated comprehensive reforms, propelling rapid industrialization and modernization. Concurrently, this growth, alongside accelerated urbanization and industrial advancements, has exacerbated environmental challenges, severely impacting urban areas and public health. To reconcile economic progress with environmental stewardship and mitigate associated risks, the China Banking Regulatory Commission introduced the Green Credit Guidelines in 2012. These guidelines aimed to foster green credit within banking institutions, support the transformation of traditional industries, and facilitate sustainable economic restructuring. This paper analyzes the impact of the Green Credit Guidelines’ implementation on the valuation of high-polluting enterprises following the policy's 2012 release. The analysis encompasses theoretical underpinnings, a review of existing literature, and rigorous empirical testing. For the empirical component, the study employs a dataset of nearly 30,000 observations from Chinese A-share listed companies. Categorizing firms based on industry heterogeneity, a difference-in-differences model with firm fixed effects is utilized for the empirical investigation. Robustness checks and parallel trend tests are conducted to ensure the reliability and validity of the results. The regression results indicate a statistically significant positive effect of the green credit policy on the value of high-polluting firms. This suggests that the issuance of the Guidelines has played a constructive role in promoting the transformation and upgrading of enterprises in China, thereby supporting the nation's sustainable economic development objectives.
Received: 13 April 2025 | Revised: 11 June 2025 | Accepted: 19 August 2025
Conflicts of Interest
The author declares that he has no conflicts of interest to this work.
Data Availability Statement
The data that support this work are available upon reasonable request to the corresponding author.
Author Contribution Statement
Li Jun: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition.
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