A Replication of “Weathering Corruption” ( Journal of Law and Economics, 2008)

Previous research using data on convictions for corruption-related crimes from the Public Integrity Section (PIN) of the Department of Justice points to a positive correlation between the amount of corruption in a state and the amount of federal funds provided to the state for natural disaster relief. We take a closer look at the relationship between public corruption and disaster assistance and find little support for the hypothesis that the provision of federal disaster aid increases public corruption. Our analysis suggests instead that prior evidence of such a link arises from an unexplained correlation during the 1990s between disaster aid and convictions of postal employees for crimes such as stealing mail. Convictions for postal service crimes appear to account for a large fraction of the total federal convictions reported by PIN, which could have far-reaching implications, given that the PIN data have been used so extensively in the corruption literature.

Private Support for Public Disaster Aid

Despite its growing economic and political importance, this is the first study in economics to investigate public opinion in the United States regarding both the allocation of government disaster aid to stricken households and communities as well as total expenditures by government on such aid. This is also the first study to bridge a gap in previous research on disasters by comparing and contrasting our results to related behavioral studies from political science, social psychology and sociology. Combining individual data from the 2006 General Social Survey with county-level information about the local environment of survey respondents, we estimate probit models to ascertain the magnitude and significance of the socioeconomic, demographic, political and experiential determinants of public opinion on these issues. Among other results, we find that Black survey respondents strongly support increasing total aid expenditures and aid to affected households and communities while income, age and a conservative political ideology largely exert a negative influence on these same variables. Surprisingly, the effects of prior experience with disasters and educational level have only a weak effect on the allocation of aid and none on the level of expenditures on aid. These and other results are consistent with only a portion of previous findings from other disciplines. Several implications of our results for current federal disaster policy are discussed and we also suggest directions for further research into this important topic.

Inflation Expectations and Risk Premia in Emerging Bond Markets: Evidence from Mexico

Can we reduce the damage from climate change by investing in seawalls, stilts, or other forms of adaptation? Focusing on the case of severe storms in the US, I develop a macro heterogeneous-agent model to quantify the interactions between adaptation, federal disaster policy, and climate change. The model departs from the standard climate damage function and incorporates the damage from storms as the realization of idiosyncratic shocks. I find that while the moral hazard effects from disaster aid reduce adaptation in the US economy, federal subsidies for investment in adaptation more than correct for the moral hazard. I introduce climate change into the model as a permanent increase in either or both the severity or probability of storms. Adaptation reduces the damage from this climate change by approximately one third. Finally, I show that modeling the idiosyncratic risk component of climate damage has quantitatively important implications for adaptation and for the welfare cost of climate change.

Humanitarian need drives multilateral disaster aid

As the climate changes, human livelihoods will increasingly be threatened by extreme weather events. To provide adequate disaster relief, states extensively rely on multilateral institutions, in particular the United Nations (UN). However, the determinants of this multilateral disaster aid channeled through the UN are poorly understood. To fill this gap, we examine the determinants of UN disaster aid using a dataset on UN aid covering almost 2,000 climate-related disasters occurring between 2006 and 2017. We make two principal contributions. First, we add to research on disaster impacts by linking existing disaster data from the Emergency Events Database (EM-DAT) to a meteorological reanalysis. We generate a uniquely global hazard severity measure that is comparable across different climate-related disaster types, and assess and bolster measurement validity of EM-DAT climate-related disasters. Second, by combining these data with social data on aid and its correlates, we contribute to the literature on aid disbursements. We show that UN disaster aid is primarily shaped by humanitarian considerations, rather than by strategic donor interests. These results are supported by a series of regression and out-of-sample prediction analyses and appear consistent with the view that multilateral institutions are able to shield aid allocation decisions from particular state interests to ensure that aid is motivated by need.