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Measuring Climate Policy Uncertainty with LLMs: New Insights into Corporate Bond Credit Spreads

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  • Yikai Zhao
  • Jun Nagayasu
  • Xinyi Geng

Abstract

This study examines the impact of climate policy uncertainty (CPU) on credit spreads using data from corporate bonds listed on the Chinese exchange market between 2008 and 2022. We innovatively apply large language models (LLMs) to construct a firm-level CPU index based on disclosure texts and validateits effectiveness. We find that a CPU rise widens a firm’s credit spreads by exacerbating financial distress. Although disclosing environmental, social, and governance (ESG) information moderate CPU’s effect on credit spreads, controversies in ESG ratings amplify it. Finally, heterogeneity analyses reveal that CPU’s effect on wideningbond spreads is more pronounced for traditional bonds, short- to medium-term bonds, nonstate-owned enterprises, and issuing firms with dispersed supply chains.

Suggested Citation

  • Yikai Zhao & Jun Nagayasu & Xinyi Geng, 2024. "Measuring Climate Policy Uncertainty with LLMs: New Insights into Corporate Bond Credit Spreads," DSSR Discussion Papers 143, Graduate School of Economics and Management, Tohoku University.
    • Handle: RePEc:toh:dssraa:143
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