Natural disasters and economic growth: a quantile on quantile approachNatural disasters and economic growth: a quantile on quantile approach Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2022-03-302021enNatural disasters have caused over a million of deaths and $3 trillion in economic losses during the last 20 years. However, theoretical and empirical studies have not reached a conclusion as for their effect on economic growth, and the results can best be described as mixed. The present study proposes the use of a quantile on quantile (QQ) approach to shed more light on this complex relationship. This approach combines the standard quantile regression analysis with nonparametric estimations and allows us to examine how different quantiles of natural disasters affect different quantiles of GDP growth. Using data from over 100 countries over a 30-years period, we confirm that the results of the QQ approach differ from the ones obtained by standard approaches like fixed effects regressions. We document that the relationship between the intensity of natural disasters and economic growth is mostly negative. Nonetheless, there are some exceptions to this. Our findings reveal that the effect of natural disasters can be occasionally positive, depending on the quantiles that we examine. The magnitude of the effect also differs across different combinations of the quantile of economic growth and the quantile of natural disasters. Finally, we obtain somewhat different results when we estimate separate QQ regressions for groups of countries that differ in terms of climate, economic and democratic development, and across different year lags of the natural disaster index.http://creativecommons.org/licenses/by/4.0/Annals of Operations Research306183–109Atsalakis_et_al_Ann. Oper. Res._306(1)_2021.pdfChania [Greece]Library of TUC2022-03-30application/pdf789.5 kBfree Atsalakis Georgios Ατσαλακης Γεωργιος Bouri Elie Pasiouras Fotios Πασιουρας Φωτιος Springer Natural disasters Economic growth Quantile regression