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Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Firm‐level climate change exposure |
| Organization Unit | |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | Journal of Finance |
| Publisher | Wiley-Blackwell Publishing, Inc. |
| Geographical Reach | international |
| ISSN | 0022-1082 |
| Volume | 78 |
| Number | 3 |
| Page Range | 1449 - 1498 |
| Date | 2023 |
| Abstract Text | 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. |
| Free access at | DOI |
| Digital Object Identifier | 10.1111/jofi.13219 |
| Other Identification Number | merlin-id:23836 |
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| Keywords | Economics and Econometrics, Finance, Accounting |