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Value-Enhancing Effect of Climate Change Risk Disclosure by Firms: Empirical Evidence Based on Textual Analysis and Machine Learning

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  • Wenwei Guo
  • Baoling Mo
  • Yanling Chen
  • Zicong Huang

Abstract

This study utilizes textual data from the social responsibility reports of Shanghai and Shenzhen A-share listed companies in China between 2007 and 2019. Through the application of textual analysis and machine learning technology, an index is constructed to gauge the extent of climate change risk disclosure by corporations. The paper examines the impact of climate change risk disclosure on corporate value, drawing from theoretical reasoning and empirical evidence.The findings reveal a significantly positive relationship between corporate climate change risk disclosure and corporate value, indicating the existence of a value promotion effect. Mechanism tests demonstrate that firms’ climate change risk disclosure enhances corporate transparency by attracting attention from analysts and the media. Consequently, this reduces information asymmetry and fosters an increase in corporate value. Furthermore, the study highlights that non-state-owned and high-polluting corporations exhibit a more pronounced value enhancement effect from climate change risk disclosure compared to other corporations. Additionally, corporations with highly readable and positively-toned textual information experience stronger value-promoting effects. These results provide robust empirical evidence supporting the practice of climate change risk disclosure among corporations in China.

Suggested Citation

  • Wenwei Guo & Baoling Mo & Yanling Chen & Zicong Huang, 2025. "Value-Enhancing Effect of Climate Change Risk Disclosure by Firms: Empirical Evidence Based on Textual Analysis and Machine Learning," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 61(2), pages 307-326, January.
  • Handle: RePEc:mes:emfitr:v:61:y:2025:i:2:p:307-326
    DOI: 10.1080/1540496X.2024.2381556
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