Natural Disaster Risk and the Distributional Dynamics of Damages

LEM Working Paper Series, 2018/22

45 Pages Posted: 10 Aug 2018

See all articles by Matteo Coronese

Matteo Coronese

Scuola Superiore Sant'Anna di Pisa - Institute of Economics

Francesco Lamperti

Scuola Superiore Sant'Anna di Pisa - Institute of Economics and LEM; Fondazione Eni Enrico Mattei (FEEM)

Francesca Chiaromonte

Scuola Superiore Sant'Anna di Pisa

Andrea Roventini

Scuola Superiore Sant'Anna di Pisa - Laboratory of Economics and Management (LEM); Observatoire Français des Conjonctures Economiques (OFCE)

Date Written: July 25, 2018

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.

Keywords: natural disasters, quantile regression, economic damages, climate change

JEL Classification: Q51, Q54, Q56

Suggested Citation

Coronese, Matteo and Lamperti, Francesco and Chiaromonte, Francesca and Roventini, Andrea, Natural Disaster Risk and the Distributional Dynamics of Damages (July 25, 2018). LEM Working Paper Series, 2018/22, Available at SSRN: https://ssrn.com/abstract=3220503 or http://dx.doi.org/10.2139/ssrn.3220503

Matteo Coronese (Contact Author)

Scuola Superiore Sant'Anna di Pisa - Institute of Economics ( email )

Pisa
Italy

Francesco Lamperti

Scuola Superiore Sant'Anna di Pisa - Institute of Economics and LEM ( email )

Institute of Economics
Piazza Martiri della Liberta, n. 33
Pisa, Pisa 56127
Italy

Fondazione Eni Enrico Mattei (FEEM) ( email )

C.so Magenta 63
Milano, 20123
Italy

Francesca Chiaromonte

Scuola Superiore Sant'Anna di Pisa ( email )

Biblioteca Scuola Superiore Sant'Anna
Piazza Martiri della Liberta, n. 33
Pisa, 56127
Italy

Andrea Roventini

Scuola Superiore Sant'Anna di Pisa - Laboratory of Economics and Management (LEM) ( email )

Piazza Martiri della Liberta', 33-I-56127
Pisa
Italy

Observatoire Français des Conjonctures Economiques (OFCE)

69 Quai d'Orsay
Paris 75004
France

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
102
Abstract Views
736
Rank
472,796
PlumX Metrics