“Gimme Shelter”: The Role of Democracy and Institutional Quality in Disaster Preparedness

Natural disasters cause suffering for millions of people around the globe every year and as climate change unfolds the likelihood of natural catastrophes is increasing. While weather shocks, such as earthquakes, tornadoes, and floods are beyond our control, a governments’ capacity to protect populations largely determines the degree of human suffering in disasters. Democracies, with freedom of speech, broad public participation and representation, are believed to protect their populations better than non-democratic regimes. However, democratic institutions are insufficient for securing protection from disasters in contexts of corruption, poor planning and public administration incompetence. We argue that the effect of democracy on the extent of human suffering in disasters is contingent on the ability of governments to implement their tasks or the quality of implementing institutions. We test this interaction hypothesis using time series cross-sectional data from the Varieties of Democracy project, the Quality of Government dataset and data from the Center for Research on the Epidemiology of Disasters. The results show that more democracy is associated with fewer people being affected by natural disasters only in settings where institutional quality is high. When institutional quality is low, more people seem to suffer in democracies than in authoritarian states.This research project was supported by Riksbankens Jubileumsfond, Grant M13-0559:1, PI: Staffan I. Lindberg, V-Dem Institute, University of Gothenburg, Sweden; by Knut and Alice Wallenberg Foundation to Wallenberg Academy Fellow Staffan I. Lindberg, Grant 2013.0166, V-Dem Institute, University of Gothenburg, Sweden; as well as by internal grants from the Vice-Chancellor’s office, the Dean of the College of Social Sciences, and the Department of Political Science at University of Gothenburg. We performed simulations and other computational tasks using resources provided by the Notre Dame Center for Research Computing (CRC) through the High Performance Computing section and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre in Sweden. We specifically acknowledge the assistance of In-Saeng Suh at CRC and Johan Raber at SNIC in facilitating our use of their respective systems