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Expected utility and catastrophic risk in a stochastic economy-climate model

  • Masako Ikefuji
  • , Roger Laeven
  • , Jan Magnus
  • , Chris Muris

Research output: Contribution to journalSpecial issue (Academic Journal)peer-review

10 Citations (Scopus)
207 Downloads (Pure)

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 languageEnglish
Pages (from-to)110-129
Number of pages20
JournalJournal of Econometrics
Volume214
Issue number1
Early online date22 May 2019
DOIs
Publication statusPublished - Jan 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    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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