Evaluating Rental Relief During the COVID-19 Pandemic

PROJECT SUMMARY The COVID-19 pandemic triggered a sudden and severe economic shock which hit low-income households and households of color most severely. Many U.S. renter households were already housing-cost stressed, leading to fears of a wave of housing instability and evictions and related effects on other forms of hardship such as food insecurity. Given that housing instability and eviction are key social determinants of health and health disparities, overflow effects on mental health were also expected. In 2020-2021 the federal government allocated $46.6 billion in funding for the Emergency Rental Assistance Program (ERAP) to support state, county, and municipal governments in addressing rental housing difficulties. The bulk of ERAP funds must be used for financial assistance for rent and rent arrears, utility assistance and utility arrears, and a limited set of other housing-related expenses arising from the pandemic (e.g., relocation expenses); states and municipalities were otherwise given extensive flexibility over the distribution of funds. This project seeks to provide the first systematic and rigorous evaluation of the ERAP policy. The overarching goals of this study are to carefully document variation in state and local ERAP design, including timing of adoption and implementation of various rules, and to evaluate the effects of different approaches to ERAP using quasi-experimental methods that take advantage of differences across geography and across time. This study has three key aims. First, we will create a unique, publicly-accessible, and user- friendly dataset that tracks local, state, and national ERAP policies, the Rental Relief Policy Database (RRPD). Second, we will merge the RRPD with household survey data from the nationally representative Household Pulse Survey fielded by the U.S. Census Bureau throughout the pandemic. Pulse includes measures of housing instability, food insufficiency and other material hardships, and mental health. We will analyze these data using logistic regression models with state and year indicators which will allow us to estimate the causal effect of ERAP policies on critical outcomes in renter households. Third, we will link the RRPD to weekly counts of eviction filings at the Census tract or ZIP code level in 31 U.S. municipal areas. Employing sophisticated techniques-multilevel zero-inflated negative binomial models-we will evaluate the effects of state and local ERAP policies on the rate of eviction filings. Results from this work will both increase understanding of COVID-19 policy effectiveness and trends in inequities, and serve as a blueprint for additional policy and public health initiatives necessary to stabilize increasingly precarious rental housing.