Optimal Climate Policy When Damages are Unknown

42 Pages Posted: 30 Oct 2014 Last revised: 14 Nov 2016

Ivan Rudik

Cornell University - Dyson School of Applied Economics and Management

Date Written: November 13, 2016

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 produce significant, and ex-ante unknowable misspecifications. Here I develop novel recursive IAM frameworks to model damage uncertainty. I decompose the optimal carbon tax into channels capturing parametric damage uncertainty, learning, and misspecification concerns. Damage learning and using robust control to guard against potential misspecifications can both improve ex-post welfare if the IAM's damage function is misspecified. However, these ex-post welfare gains may take decades or centuries to arrive.

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 (November 13, 2016). 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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