TY - JOUR
T1 - Evidence for sharp increase in the economic damages of extreme natural disasters
AU - Coronese, Matteo
AU - Lamperti, Francesco
AU - Keller, Klaus
AU - Chiaromonte, Francesca
AU - Roventini, Andrea
N1 - Publisher Copyright:
© 2019 National Academy of Sciences. All rights reserved.
PY - 2019/10/22
Y1 - 2019/10/22
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85073732219&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073732219&partnerID=8YFLogxK
U2 - 10.1073/pnas.1907826116
DO - 10.1073/pnas.1907826116
M3 - Article
C2 - 31591192
AN - SCOPUS:85073732219
SN - 0027-8424
VL - 116
SP - 21450
EP - 21455
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 43
ER -