| 000 -LEADER |
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| fixed length control field |
01164nam a22001457a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
210219b ||||| |||| 00| 0 eng d |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Rudi, Ivan |
| 245 ## - TITLE STATEMENT |
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| Title |
Optimal climate policy when damages are unknown |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Place of publication, distribution, etc |
American Economic Journal: Economic Policy |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
12(2), May, 2020: p.340-373 |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
Integrated assessment models (IAMs) are economists' primary tool for analyzing the optimal carbon tax. Damage functions, which link temperature to economic impacts, have come under fire because of their assumptions that may be incorrect in significant but a priori unknowable ways. Here I develop recursive IAM frameworks to model uncertainty, learning, and concern for misspecification about damages. I decompose the carbon tax into channels capturing state uncertainty, insurance motives, and precautionary saving. Damage learning improves ex ante welfare by 750 billion USD. If damage functions are misspecified and omit the potential for catastrophic damages, robust control may be beneficial ex post. – Reproduced |
| 773 ## - HOST ITEM ENTRY |
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| Main entry heading |
American Economic Journal: Economic Policy |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
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| Subject DIP |
CLIMATE CHANGE |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Item type |
Articles |
