submitted on 2025-10-26, 08:55 and posted on 2025-10-26, 08:57authored byShabeen Afsar Basha, Ramzi Benkraiem, Hamdi Ben-Nasr, Abdullah-Al Masum
<p dir="ltr">Using machine-learning-based measures for political and <u>climate risks </u>derived from corporate conference calls, we discover a link between the two in a large sample of US firms from 2002 to 2021. Our findings suggest that firms facing higher political risk are more susceptible to climate risk. Additionally, we find that a firm's emitter category <u>industry</u> classification and exposure to environmental litigation can exacerbate this situation, while <u>managerial ability</u> helps reduce the impact. Furthermore, political lobbying and donations effectively check corporate climate risk, but only under non-partisan conditions. Importantly, our findings are robust to concerns of reverse causality, sample selection bias, and measurement errors.</p><h2>Other Information</h2><p dir="ltr">Published in: International Review of Financial Analysis<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.irfa.2025.104282" target="_blank">https://dx.doi.org/10.1016/j.irfa.2025.104282</a></p>
Funding
Open Access funding provided by the Qatar National Library.