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Can green credit policies reduce enterprise risk? Evidence from China

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  • Peng, Changhong
  • Chen, Dongjing
  • Jia, Daizheng
  • Liu, Qiao
  • Xu, Xin

Abstract

Environmental regulatory policies have changed the original living environment and development trajectory of enterprises. In the context of increasingly complex and variable macroeconomics, it is crucial to identify the impact of environmental regulatory policies on enterprise risk. The Green Credit Guidelines (GCGs) issued by the China Banking Regulatory Commission in 2012 are important practices for the country to introduce financial means into the environmental field. Using this policy as a quasinatural experiment and on the basis of data from Chinese A-share listed companies from 2008 to 2021, an empirical test was conducted to examine the impact of green credit policies on enterprise risk. The study found that green credit policies can significantly curb the risk of heavily polluting enterprises. The heterogeneity analysis found that the effect of green credit policies on curbing the risk of heavily polluting enterprises is more significant for state-owned enterprises and large-scale enterprises. Moderation effect analysis revealed that both external media attention and internal governance can enhance the inhibitory effect of green credit policies on the risk of heavily polluting enterprises. Mechanism analysis showed that green credit policies can reduce the risk of heavily polluting enterprises by promoting diversified operations, advancing enterprise transformation and upgrading, and reducing the mismatch between short-term loans and long-term investments. This research provides a theoretical basis and empirical evidence for further promoting the implementation of green credit policies and preventing and resolving enterprise risk.

Suggested Citation

  • Peng, Changhong & Chen, Dongjing & Jia, Daizheng & Liu, Qiao & Xu, Xin, 2025. "Can green credit policies reduce enterprise risk? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 97(C).
    • Handle: RePEc:eee:finana:v:97:y:2025:i:c:s1057521924007348
    DOI: 10.1016/j.irfa.2024.103802
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