Work

Climate Sentiment and Corporate Default Risk: Evidence From Listed Firms in China’s Heavily Polluting Industries

Year: 2025

Type: article

Abstract: The complex climate risks and China’s “dual carbon” goals will definitely exert a far-reaching influence upon the growth of China’s heavily polluting firms. This paper analyzes climate sentiment’s impact on China’s bond market using the KMV model. The model predicts default probability by linking equity to asset values via Black-Scholes, providing a scientific basis for credit risk quantification in financial decisions and regulation. Meanwhile, a Naive Bayes model is employed to construct climate sentiment. As a Bayesian-based machine learning method, it is widely used in text analysis for its solid theory, simplicity, efficiency, and objectivity. We obtained over 220,000 climate-related posts as our sample by crawling the financial commentary stock bar of Eastmoney Net, with the time span ranging from January 1, 2014 to December 31, 2022. The results show that as climate sentiment becomes more positive, the credit default risk of listed heavily polluting companies rises. Climate sentiment increases the default risk of heavy polluters mainly through increased financing constraint, financing cost and market competition. The impact of climate sentiment on raising corporate default risk is greater for non-state-owned firms, larger size, and higher stock volatility.

Source: SAGE Open

DOI: 10.1177/21582440251393020

Authors: Wenwen Liu, Miaomiao Tang, Peng Zhao, Dianchen Xu, Ziyang Luo

Institution: Xihua University

Language: English

Topic: Credit Risk and Financial Regulations

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDG: Climate action

Open Access status: gold

Estimated APC paid: $1,600