Evidence for sharp increase in the economic damages of extreme natural disasters
- aInstitute of Economics and EMbeDS–Economics and Management in the Era of Data Science, Scuola Superiore Sant’Anna Pisa, 56127 Pisa, Italy;
- bRFF-CMCC European Institute of Economics and the Environment, 20144 Milan, Italy;
- cDepartment of Geosciences, The Pennsylvania State University, University Park, PA 16802;
- dDepartment of Statistics, The Pennsylvania State University, University Park, PA 16802;
- eObservatoire Français des Conjonctures Économiques, SciencesPo, BP 85 06902, Sophia Antipolis, France
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Edited by Arild Underdal, University of Oslo, Oslo, Norway, and approved September 5, 2019 (received for review May 8, 2019)
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Significance
Observations indicate that climate change has driven an increase in the intensity of natural disasters. This, in turn, may drive an increase in economic damages. Whether these trends are real is an open and highly policy-relevant question. Based on decades of data, we provide robust evidence of mounting economic impacts, mostly driven by changes in the right tail of the damage distribution—that is, by major disasters. This points to a growing need for climate risk management.
Abstract
Climate change has increased the frequency and intensity of natural disasters. Does this translate into increased economic damages? To date, empirical assessments of damage trends have been inconclusive. Our study demonstrates a temporal increase in extreme damages, after controlling for a number of factors. We analyze event-level data using quantile regressions to capture patterns in the damage distribution (not just its mean) and find strong evidence of progressive rightward skewing and tail-fattening over time. While the effect of time on averages is hard to detect, effects on extreme damages are large, statistically significant, and growing with increasing percentiles. Our results are consistent with an upwardly curved, convex damage function, which is commonly assumed in climate-economics models. They are also robust to different specifications of control variables and time range considered and indicate that the risk of extreme damages has increased more in temperate areas than in tropical ones. We use simulations to show that underreporting bias in the data does not weaken our inferences; in fact, it may make them overly conservative.
Footnotes
- ↵1To whom correspondence may be addressed. Email: fxc11{at}psu.edu or andrea.roventini{at}santannapisa.it.
Author contributions: M.C., F.L., K.K., F.C., and A.R. designed research; M.C. and F.L. performed research; M.C. analyzed data; and M.C., F.L., K.K., F.C., and A.R. wrote the paper.
The authors declare no competing interest.
This article is a PNAS Direct Submission.
Data deposition: Code for our analyses has been deposited in GitHub, https://github.com/mcoronese/extreme-disasters.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1907826116/-/DCSupplemental.
Change History
April 15, 2021: The classifications have been updated.
- Copyright © 2019 the Author(s). Published by PNAS.
This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
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- Abstract
- The Devil Is in the Tails: From Climate Stressors to Damages
- Rightward Skewing and Tail Fattening: Economic Impacts Are Mounting
- Beyond Economic Impacts: Lives Lost
- Biases in Data May Hide Even Larger Economic Impacts
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