Feature Where to Prioritize Emergency Rental Assistance to Keep Renters in Their Homes
Subtitle
Mapping neighborhoods where low-income renters face greater risks of housing instability and homelessness to inform an equitable COVID-19 response
Display Date

Body

Update: See our equity checklist on prioritizing racial equity in emergency rental assistance programs, and contact ERAP@Urban.org for information about technical assistance support in using this tool to target outreach or funds. 



The pandemic’s economic and health impacts are exacerbating the nation’s affordable housing and homelessness crises—adding more low-income renters to the millions already at risk of eviction and homelessness and widening racial disparities in housing instability. As eviction moratoriums end and states and localities allocate emergency rental assistance funds to help renters avoid losing their homes, local leaders must decide where to prioritize their resources.

To help inform those decisions, we’ve developed the Emergency Rental Assistance Priority Index. The index estimates the level of need in a census tract by measuring the prevalence of low-income renters who are at risk of experiencing housing instability and homelessness. To do this, it examines neighborhood conditions and demographics, incorporating instability risk factors before the pandemic as well as the pandemic’s economic impacts.

The index emphasizes an equitable approach, accounting for risk factors that are higher for certain groups, particularly Black, Indigenous, and Latinx renters. These groups have been historically and systematically excluded from housing and economic opportunities and face greater health and economic impacts from COVID-19.

Local decisionmakers who want to prioritize an equitable COVID-19 response can use this tool to inform a community-based process to target areas where resources for residents and nonprofit organizations are likely to have the greatest impact on reducing housing instability and homelessness. Search for your county or Continuum of Care to see which neighborhoods should be prioritized for emergency rental assistance, or download the data and technical appendix for more information about each census tract’s housing instability risk and the indicators we used to build the index.

Body
Body

ABOUT THE DATA

Correction (May 14, 2021): Our April 5, 2021, data update uploaded improperly, meaning the data in the map have remained the same since our launch on August 25, 2020. We have corrected this error so that the map now displays the updated data. The related data catalog, however, was successfully updated on April 5, 2021. See the data catalog for more information and to view the differences between the old and new datasets.

To determine census tract–level values for our Emergency Rental Assistance Priority Index and its subindexes (Housing Instability Risk, COVID-19 Impact, and Equity), we used data from the 2015–19 American Community Survey five-year estimates, the Urban Institute’s “Where Low-Income Jobs Are Being Lost to COVID-19” data tool, and the US Department of Housing and Urban Development’s 2013–17 Comprehensive Housing Affordability Strategy dataset.

Each census tract’s index percentile is based on its state (for example, if a tract is in the 95th percentile, its index value is higher than the values of 95 percent of tracts in its state). For this reason, the Emergency Rental Assistance Priority Index percentiles in this tool and the values in the data download should not be used to compare housing instability risk in census tracts from different states.

Our index and its subindexes are built on historical census data and estimates that may not capture the current need in each neighborhood. We recommend using this tool in conjunction with a community-based process that includes examining local homelessness data and engaging stakeholders from groups and neighborhoods that local data show are disproportionately represented in evictions, homelessness, and COVID-19 infection and mortality.

We define people of color as those designated in the dataset as a race or ethnicity other than white non-Hispanic. We do not disaggregate beyond this group because of data quality concerns at the census-tract level and to ensure small subpopulations of people of color were included in the measure. We recognize the limitation of not disaggregating these data further into individual racial and ethnic groups: groups experience different housing instability risks and COVID-19 health and economic risks, and solutions should be tailored to the specific needs of each community.

People of color—especially Black, Indigenous, and Latinx people—are overrepresented among people experiencing homelessness and among people evicted from rental housing because of the US’s history of systemic and structural racism in housing access, wealth accumulation, employment, criminal justice, and other systems. Additionally, Black, Latinx, Indigenous, and Asian people are overrepresented in COVID-19 exposure, illness, and morbidity rates, and racial housing disparities are growing during the pandemic.

To ensure this tool can help local leaders target neighborhoods most at risk of homelessness and housing instability, we more heavily weight certain factors that research suggests disproportionately contribute to eviction, homelessness, and COVID-19 economic and health risks. Specifically, we weight the Housing Instability Risk subindex higher than the other subindexes, and within the Equity subindex, we weight the share of people of color higher than the other indicators.

To focus on tracts most in need of rental assistance resources, our map treats census tracts in the 0 to 49th percentiles as one group and then separates the remaining tracts into those in the 50th to 74th percentiles, the 75th to 84th percentiles, the 85th to 89th percentiles, the 90th to 94th percentiles, and the 95th to 99th percentiles. We do not display data for or include in the color scale census tracts that have no extremely low–income renters. In the few instances when Continuum of Care boundaries cross state lines, we divide the Continuum of Care into two, one for each state.

In many communities, the index may highlight tracts with large populations of university students, who would not typically be considered a high priority for emergency rental assistance. This is likely because students are often renters, might be living in crowded situations, and have low incomes. This result illustrates the need to pair the tool with local knowledge and expertise to make fully informed resource prioritization decisions.

For more information about our indicator definitions, weighting calculations, and the evidence that informs the Emergency Rental Assistance Priority Index, see the technical appendix.

PROJECT CREDITS

This feature was funded by the Melville Charitable Trust, Funders for Housing and Opportunity, and the John D. and Catherine T. MacArthur Foundation in 2020, with additional funding for updated data provided by the Schultz Family Foundation in 2021. We are grateful to them and to all our funders, who make it possible for Urban to advance its mission. The views expressed are those of the authors and should not be attributed to the Urban Institute, its trustees, or its funders. Funders do not determine research findings or the insights and recommendations of our experts.

We thank our partners in The Framework for an Equitable COVID-19 Homelessness Response—the Center on Budget and Policy Priorities, National Alliance to End Homelessness, National Health Care for the Homeless Council, National Low Income Housing Coalition, Barbara Poppe and Associates, Matthew Doherty Consulting, and National Innovation Service—for their contributions and feedback on this project. The Framework for an Equitable COVID-19 Homelessness Response encourages decisionmakers to strategically use federal rental assistance funds to help communities advance racial justice and equity while prioritizing those with the greatest need. By using funds in a strategic and targeted way, policymakers can address the public health implications of COVID-19, contain the spread of the virus, and help communities get back on track economically.

RESEARCH Samantha BatkoSolomon GreeneAjjit NarayananNicole DuBoisGraham MacDonaldAbigail WilliamsMary Cunningham, and Matthew Gerken

DESIGN Allison Feldman

DEVELOPMENT Alice Feng and Jerry Ta

EDITING Meghan Ashford-Grooms

WRITING Emily Peiffer

Download the data on Urban’s Data Catalog View this project and the code used to generate the data on GitHub