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

Yikai Zhao, Jun Nagayasu and Xinyi Geng

No 143, DSSR Discussion Papers from Graduate School of Economics and Management, Tohoku University

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.

Pages: 59 pages
Date: 2024-11
New Economics Papers: this item is included in nep-ain, nep-big, nep-cfn and nep-env
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Persistent link: https://EconPapers.repec.org/RePEc:toh:dssraa:143

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