Building Resilience through Equity: A 20-Year Analysis of FEMA Disaster Assistance and Structural Disparities

• In Event: Environmental Risks and Disasters: Considerations of Justice and Productivity

Abstract

Over the past two decades, the frequency of federally declared natural disasters—and the scale of corresponding federal assistance—has increased markedly. While prior research has highlighted disparities in the distribution of disaster aid by race, ethnicity, or income, often using an intersectional approach, much of this work relies on aggregated geographic units such as counties or census tracts, limiting our understanding of individual-level experiences and intersectional inequities. This study addresses that gap by leveraging a uniquely detailed, 20-year national dataset of applications to FEMA’s Individual and Households Program (IHP). We analyze more than 25 million IHP application-level data, using a comprehensive and intersectional framework that incorporates housing tenure, household income, neighborhood wealth, reported property damage, and the severity of the weather events prompting disaster declarations. Our focus is the determinants of disparities in both the likelihood of receiving aid and the amount awarded. Our two-stage empirical strategy first estimates the probability of aid receipt, controlling disaster type and intensity, and then models the conditional allocation of funds among recipients. Our preliminary findings reveal that lower-income renters are systematically less likely to receive FEMA assistance and tend to receive smaller awards than homeowners with comparable damage levels and neighborhood conditions. These results suggest the need for federal policy reforms that better account for housing tenure and income vulnerability in disaster response frameworks. Enhancing equity in disaster aid distribution—through improved eligibility criteria, targeted outreach, and renter-specific assistance—can reduce recovery gaps and improve resilience for historically marginalized populations.

Author

• Daein Kang, Georgia Institute of Technology
  Presenting Author