气候变化
收益
衡平法
业务
自然资源经济学
经济
财务
生态学
政治学
生物
法学
作者
Zacharias Sautner,Laurence van Lent,Grigory Vilkov,RUISHEN ZHANG
摘要
ABSTRACT 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.
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