Abstract
We analyze a stochastic dynamic finite-horizon economic model with climate change, in which the social planner faces uncertainty about future climate change and its economic damages. Our model (SDICE*) incorporates, possibly heavy-tailed, stochasticity in Nordhaus’ deterministic DICE model. We develop a regression-based numerical method for solving a general class of dynamic finite-horizon economy–climate models with potentially heavy-tailed uncertainty and general utility functions. We then apply this method to SDICE* and examine the effects of light- and heavy-tailed uncertainty. The results indicate that the effects can be substantial, depending on the nature and extent of the uncertainty and the social planner's preferences.
Original language | English |
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Pages (from-to) | 110-129 |
Number of pages | 20 |
Journal | Journal of Econometrics |
Volume | 214 |
Issue number | 1 |
Early online date | 22 May 2019 |
DOIs | |
Publication status | Published - Jan 2020 |
Funding
We are very grateful to the editor of the Journal of Econometrics, to the editors of this special issue, and to three referees for their constructive comments and suggestions that have significantly improved our paper. We are also grateful to Graciela Chichilnisky, John Einmahl, Johan Eyckmans, Reyer Gerlagh, Christian Groth, David Hendry, John Knowles, Sjak Smulders, Peter Wakker, Aart de Zeeuw, and Amos Zemel for feedback. This research was funded in part by the Netherlands Organization for Scientific Research (NWO) under grant Vidi-2009 (Laeven) and by the Social Sciences and Humanities Research Council’s Insight Development Grant 430-2015-00073 (Muris).
Keywords
- Economy–climate models
- Economy–climate policy
- Expected utility
- Heavy tails
- Uncertainty