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 |
|---|---|
| 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 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Research Groups and Themes
- ECON Econometrics
- ECON CEPS Data
Keywords
- Economy-climate models
- Economy-climate policy
- Expected utility
- Heavy tails
- Uncertainty
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