Optimal Climate Policy When Damages are Unknown

40 Pages Posted: 30 Oct 2014 Last revised: 3 Dec 2018

See all articles by Ivan Rudik

Ivan Rudik

Cornell University - Dyson School of Applied Economics and Management

Date Written: December 2, 2018

Abstract

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 ex ante 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 $2 trillion. If damage functions are misspecified and omit the potential for catastrophic damages, robust control may be beneficial ex post.

Keywords: climate, damages, Knightian uncertainty, robust control, sparse grid, integrated assessment

JEL Classification: H23, Q54, Q58

Suggested Citation

Rudik, Ivan, Optimal Climate Policy When Damages are Unknown (December 2, 2018). Available at SSRN: https://ssrn.com/abstract=2516632 or http://dx.doi.org/10.2139/ssrn.2516632

Ivan Rudik (Contact Author)

Cornell University - Dyson School of Applied Economics and Management ( email )

Ithaca, NY
United States

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