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Estimation of Climate Change Damage Functions for 140 Regions in the GTAP 9 Database

Roberto Roson and Martina Sartori

Journal of Global Economic Analysis, 2016, vol. 1, issue 2, 78-115

Abstract: Climate change damage (or, more correctly, impact) functions relate variations in temperature (or other climate variables) to economic impacts in various dimensions, and are at the basis of quantitative modeling exercises for the assessment of climate change policies. This document provides a summary of results from a series of meta-analyses aimed at estimating parameters for six specific damage functions, referring to: sea level rise, agricultural productivity, heat effects on labor productivity, human health, tourism flows, and households' energy demand. All parameters of the damage functions are estimated for each of the 140 countries and regions in version 9 of the Global Trade Analysis Project (GTAP 9) Data Base. To illustrate the salient characteristics of the estimates, the change in real gross domestic product is approximated for the different effects, in all regions, corresponding to an increase in average temperature of +3�C. After considering the overall impact, the paper highlights which factor is the most significant one in each country, and elaborates on the distributional consequences of climate change.

Keywords: Climate change; Integrated assessment; Computable general equilibrium; Damage function; Climate impacts (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (28)

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Related works:
Working Paper: Estimation of climate change damage functions for 140 regions in the GTAP9 database (2016) Downloads
Working Paper: Estimation of climate change damage functions for 140 regions in the GTAP9 database (2016) Downloads
Working Paper: Estimation of climate change damage functions for 140 regions in the GTAP9 database (2016) Downloads
Working Paper: Estimation of climate change damage functions for 140 regions in the GTAP9 database (2016) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:gta:jnlgea:v:1:y:2016:i:2:p:78-115

DOI: 10.21642/JGEA.010202AF

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