2018/22 | LEM Working Paper Series | ||||||||||||||||
![]() |
|||||||||||||||||
Natural Disaster Risk and the Distributional Dynamics of Damages |
|||||||||||||||||
Matteo Coronese, Francesco Lamperti, Francesca Chiaromonte and Andrea Roventini |
|||||||||||||||||
Keywords | |||||||||||||||||
![]() |
![]() |
||||||||||||||||
natural disasters; quantile regression; economic damages; climate change
|
|||||||||||||||||
JEL Classifications | |||||||||||||||||
![]() |
![]() |
||||||||||||||||
Q51, Q54, Q56
|
|||||||||||||||||
Abstract | |||||||||||||||||
![]() |
![]() |
||||||||||||||||
Literature on climate change and extreme events has found conflicting
and often weak results on the evolution of economic damages related to
natural disasters, although climate change is likely to bring about an
increase in their magnitude (Van Aalst, 2006; IPCC, 2007, 2012). These
studies usually focus on trend detection, typically employing mean
regression techniques on yearly summed data. Using EM-DAT data, we
enrich the analysis of natural disasters’ risk by characterizing the
behavior of the entire distribution of economic (and human) losses,
especially high quantiles. We also envisage a novel normalization
procedure to control for exposure (e.g. number and value of assets at
risk, inflation), so to ensure spatial and temporal comparability of
hazards. Employing moments and quantiles analysis and non-parametric
kernel density estimations, we find a rightward shift and a
progressive right-tail fattening process of the global distribution of
economic damages both on yearly and decade aggregated data. Moreover,
a battery of quantile regressions provide evidence supporting a
substantial increase in the upper quantiles of the economic damage
distribution (upper quantiles of human losses tend to decrease
globally over time, mostly due to adaptation to storms and floods, but
with a worrying polarization between rich and poor countries). Such
estimates might be even conservative, given the nature of biases
possibly affecting the dataset. Our results shows that mean
regressions underestimate systematically the real contribution of the
right tail of the damage distribution in shaping the trend itself.
|
Downloads
|
![]() ![]() |
|
![]()
|
![]() |