The persistence of shocks in GDP and the estimation of the potential economic costs of climate change. (July 2015)

• Record Type: Journal Article
• Authors: Estrada, Francisco; Tol, Richard S.J.; Gay-García, Carlos
• Is Part Of: Environmental modelling & software. Volume 69(2015:Jul.)
• Page Start: 155
• Page End: 165
• Publication Date: 2015-07
• Subjects: Integrated assessment model -- Economic costs of climate change -- Persistence of shocks -- Adaptation; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.03.010
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Integrated assessment models (IAMs) typically ignore the impact climate change could have on economic growth. The damage functions of these models assume that climate change impacts have no persistence at all, affecting only the period when they occur. Persistence of shocks is a stylized fact of macroeconomic time series and it provides a mechanism that could justify larger losses from climate change than previously estimated. Given that the degree of persistence of climate impacts is unknown, we analyze the persistence of generic shocks in observed GDP series for different world regions and compare it to that of the leading IAMs. Under the working hypothesis of interpreting the direct impact of climate change as such shocks, the implications for growth are investigated for two RCP scenarios. The way of introducing climate shocks to GDP in most IAMs can be interpreted as assuming an autonomous, costless, large and effective reactive adaptation capacity. Highlights: Most impact functions of IAMs implicitly assume that climate change impacts have no persistence. IAMs projections of the costs of climate change are highly sensitive to this assumption. Current projections of climate change costs could be highly underestimated. A simple modification of the typical damage function in IAMs is proposed to include the effects of impact persistence.