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Abstract Both the number of disasters in the U.S. and federal outlays following disasters are rising. FEMA’s Public Assistance (PA) is a key program for rebuilding damaged public infrastructure and aiding local and state governments in recovery. It is the primary post-disaster source of recovery funds. Between 2000 and 2019, more than $125B (adjusted, 2020 dollars) was awarded through PA. While all who qualify for PA should have equal opportunity to receive aid, not all do, and the factors influencing how the program has been administered are complex and multifaceted. Lacking an understanding of the factors positively associated with historical receipt of aid, there is little way to objectively evaluate the efficacy of the PA program. In this work, we evaluate the salient features that contribute to the number of county-level PA applicants and projects following disasters. We use statistical learning theory applied to repetitive flooding events in the upper Midwest between 2003 and 2018 as a case study. The results suggest that many non-disaster related indicators are key predictors of PA outlays, including the state in which the disaster occurred, the county’s prior experience with disasters, the county’s median income, and the length of time between the end of the disaster and the date when a disaster is declared. Our work suggests that indicators of PA aid are tied to exposure, bureaucratic attributes, and human behavior. For equitable distribution of aid, policymakers should explore more disaster-relevant indicators for PA distribution. 

Abstract Climate change is expected to increase the frequency and intensity of natural hazards such as hurricanes. With a severe shortage of affordable housing in the United States, renters may be uniquely vulnerable to disaster‐related housing disruptions due to increased hazard exposure, physical vulnerability of structures, and socioeconomic disadvantage. In this work, we construct a panel dataset consisting of housing, socioeconomic, and hurricane disaster data from counties in 19 states across the East and Gulf Coasts of the United States from 2009 to 2018 to investigate how the frequency and intensity of a hurricane correspond to changes in median rent and housing affordability (the interaction between rent prices and income) over time. Using a two‐stage least square random‐effects regression model, we find that more intense prior‐year hurricanes correspond to increases in median rents via declines in housing availability. The relationship between hurricanes and rent affordability is more complex, though the occurrence of a hurricane in a given year or the previous year reduces affordable rental housing, especially for counties with higher percentages of renters and people of color. Our results highlight the multiple challenges that renters are likely to face following a hurricane, and we emphasize that disaster recovery in short‐ and medium‐term should focus on providing safe, stable, and affordable rental housing assistance. 

In this study, we conduct the first comprehensive, nationwide assessment of social equity performance of multiple federal post‐ and pre‐disaster assistance programs that differ in targeted recipients, project types, forms of aid, and funding requirements. We draw on the social equity and distributive justice theory to develop and test a set of hypotheses on the influence of program design and specificity on their aid distributional patterns and equity performance. The analysis uses panel data of about 3000 US counties to examine the relationship between a county's receipt of federal assistance and its recent disaster damage, socioeconomic, demographic, political, local government, and geographic characteristics in a two‐stage random effects Tobit model. Expectedly, we find that post‐disaster grants are largely driven by recent disaster damage, while damage is simultaneously influenced by local socioeconomic conditions. For all disaster programs, disproportionately more federal aid is allocated to populous counties. For programs geared toward state and local governments and targeting community recovery and mitigation, more aid is received by counties with better socioeconomic conditions. Conversely, for programs targeting individual relief and recovery, more aid is given to counties with lower incomes and greater social vulnerability. Results also indicate that counties located in high‐risk regions receive greater outlays. These findings shed light on the varying degrees of social equity of federal disaster assistance programs tied to their cost‐share requirement, funding caps, and inherent complexity of application procedures.