Corruption Kills: Global Evidence from Natural Disasters

15 Pages Posted: 2 Nov 2023

See all articles by Serhan Cevik

Serhan Cevik

International Monetary Fund (IMF)

João Tovar Jalles

University of Lisbon; International Monetary Fund (IMF); Technical University of Lisbon (UTL) - Research Unit on Complexity and Economics (UECE)

Abstract

Natural disasters are inevitable, but humanitarian and economic losses are determined largely by policy preferences and institutional underpinnings that shape the quality of public infrastructure (including emergency responses and healthcare services) and govern business practices and the adherence to building codes. In this paper, we empirically investigate whether corruption increases the loss of human lives caused by natural disasters, using a large panel of 135 countries during the period 1980–2020. The econometric analysis provides convincing evidence that corruption increases the number of disaster-related deaths, after controlling for economic, demographic, healthcare and institutional factors. That is, the higher the level of corruption in a given country, the greater the number of fatalities as a share of population due to natural disasters. Our results show that the devastating impact of corruption on loss of human lives caused by natural disasters is significantly greater in developing countries, which are even more vulnerable to nonlinear effects of corruption.

Keywords: Corruption, institutions, natural disasters, fatalities

JEL Classification: D31, D73, H41, P16, Q54

Suggested Citation

Cevik, Serhan and Jalles, João Tovar, Corruption Kills: Global Evidence from Natural Disasters. IMF Working Paper No. 2023/220, Available at SSRN: https://ssrn.com/abstract=4619838 or http://dx.doi.org/10.5089/9798400256820.001

Serhan Cevik (Contact Author)

International Monetary Fund (IMF) ( email )

700 19th Street, N.W.
Washington, DC 20431
United States

João Tovar Jalles

University of Lisbon ( email )

R. Branca Edmée Marques
Dept. Plant Biology
Lisboa, 1600-276
Portugal

International Monetary Fund (IMF) ( email )

700 19th Street, N.W.
Washington, DC 20431
United States

Technical University of Lisbon (UTL) - Research Unit on Complexity and Economics (UECE)

Rua Miguel Lupi, 20
Lisboa, 1200-781
Portugal

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