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Normalizing economic loss from natural disasters: a global analysis

By Fabian Barthel and Eric Neumayer

Abstract

Climate change is likely to lead to an increase in the frequency and/or intensity of certain types of natural hazards, if not globally, then at least in certain regions. All other things equal, this should lead to an increase in the economic toll from natural disasters over time. Yet, all other things are not equal since affected areas become wealthier over time and rational individuals and governments undertake defensive mitigation measures, which requires normalizing economic losses if one wishes to analyze trends in economic loss from natural disasters for detecting a potential climate change signal. In this article, we argue that the conventional methodology for normalizing economic loss is problematic since it normalizes for changes in wealth over time, but fails to normalize for differences in wealth across space at any given point of time. We introduce an alternative methodology that overcomes this problem in theory, but faces many more problems in its empirical application. Applying, therefore, both methods to the most comprehensive existing global dataset of natural disaster loss, in general we find no significant upward trends in normalized disaster damage over the period 1980 to 2009 globally, regionally, for specific disasters or for specific disasters in specific regions. Due to our inability to control for defensive mitigation measures, one cannot infer from our analysis that there have definitely not been more frequent and/or more intensive weather-related natural hazards over the study period already. Moreover, it may still be far too early to detect a trend if humaninduced climate change has only just started and will gain momentum over time

Topics: GE Environmental Sciences, HC Economic History and Conditions
Publisher: Centre for Climate Change Economics and Policy and Grantham Research Institute on Climate Change and the Environment
Year: 2010
OAI identifier: oai:eprints.lse.ac.uk:37601
Provided by: LSE Research Online

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