Geospatial Analyses of Natural Disasters: Economic Impacts, Societal Responses, and Political Bias

This dissertation contains four separate chapters. CHAPTER 1 This chapter examines the current, lagged, and indirect effects of tropical cyclones on annual sectoral growth worldwide. The main explanatory variable is a new damage measure for local tropical cyclone intensity based on meteorological data weighted for individual sectoral exposure, which is included in a panel analysis for a maximum of 205 countries over the 1970–2015 period. I find a significantly negative influence of tropical cyclones on two sector aggregates including agriculture, as well as trade and tourism. In subsequent years, tropical cyclones negatively affect the majority of all sectors. However, the Input-Output analysis shows that production processes are sticky and indirect economic effects are limited. CHAPTER 2 People in low-lying coastal areas live under the potentially great threat of damage due to coastal flooding from tropical cyclones. Understanding how coastal population settlements react to such events is of high importance for society in order to consider future potential adaptation strategies and policies. In this study, we generate a new global hydrological data set on storm surge damage for the period 1850–2010. By combining this new data set with spatial data on human populations at a resolution of 10 km, we analyze the influence of storm surge damage on the rural, urban, and total population in low elevation coastal zones. We find that 8% of the global coastal population moved away per decade over the 1950–2010 period as a consequence of storm surges, on average. It is the urban population where we find the largest reductions (-15%). We show that the exposed coastal population has adapted over time and started to reduce its exposure in recent decades. This finding applies to most regions, with the exceptions of North America, Oceania, and Western Asia. CHAPTER 3 Allocation decisions are vulnerable to political influence, but little is known about when politicians can use their discretion to pursue their strategic goals. We show the nonlinearity of political favoritism in an exogenous framework of U.S. disaster relief. Based on a simple theoretical model, we demonstrate that political biases are most pronounced when the need for a disaster declaration is ambiguous. Exploiting the spatiotemporal randomness of all hurricane strikes in the United States from 1965–2018, we find that presidents favor areas governed by their fellow party members when allocating disaster declarations. Our nonlinear estimations reveal that political influence varies immensely with respect to storm intensity. The alignment bias for medium-strength hurricanes exceeds standard linear estimates eightfold. CHAPTER 4 We examine the design and implementation of the United Nations Flash Appeal triggered in response to the highly destructive 2015 Nepal earthquake. We consider how local need and various distortions affect the proposed project number, the proposed financial amount, and the subsequent funding decision by aid donors. Specifically, we investigate the extent to which the allocation of this humanitarian assistance follows municipalities’ affectedness and their physical and socioeconomic vulnerabilities. We then analyze potential ethnic, religious, and political distortions. Our results show that aid allocation is associated with geophysical estimates of the earthquake damage. Controlled for disaster impact, however, aid allocation shows little regard for the specific socioeconomic and physical vulnerabilities. It is also worrisome that the allocation of the flash appeal commitments favors municipalities dominated by higher castes and disadvantages those with a greater distance to the Nepali capital Kathmandu