Firm-Level Climate Change Exposure

• 成果类型: Article; Early Access
• 署名作者: Sautner, Zacharias; Van Lent, Laurence; Vilkov, Grigory; Zhang, Ruishen
• 署名单位: Frankfurt School Finance & Management; Shanghai University of Finance & Economics
• 刊物名称: JOURNAL OF FINANCE
• ISSN/ISSBN: 0022-1082
• DOI: 10.1111/jofi.13219
• 发表日期: 2023
• 关键词: risk; uncertainty; INNOVATION; return

摘要

We develop a method that identifies the attention paid by earnings call participants to firms' climate change exposures. The method adapts a machine learning keyword discovery algorithm and captures exposures related to opportunity, physical, and regulatory shocks associated with climate change. The measures are available for more than 10,000 firms from 34 countries between 2002 and 2020. We show that the measures are useful in predicting important real outcomes related to the net-zero transition, in particular, job creation in disruptive green technologies and green patenting, and that they contain information that is priced in options and equity markets.