To Advance Mutually Beneficial Education and Housing Solutions, Start with the Data

Housing policy and education policy can reinforce each other’s outcomes. Housing policy shapes the neighborhoods where schools are and those schools' student demographics. Education policy affects the quality of schools and the resources available to students, which then can affect housing prices and zoning patterns. Nevertheless, these policy areas suffer from misalignment across funding, governance, and implementation.

One piece of this misalignment stems from inadequate data on how housing and education policy levers interact. Leveraging these data can help policymakers develop more effective strategies for improving outcomes for children and decreasing demographic and socioeconomic segregation. Using resources such as the Toolkit for Housing and Education Partnerships, housing practitioners can assist local school districts in navigating available data, identifying shared goals, and enhancing alignment to foster collaboration and address housing-related challenges effectively.

Last fall, the Urban Institute launched a peer-learning initiative with Bridges Collaborative and seven school districts across the country interested in Promoting Racial Equity in Schools by Understanding Segregation (PRESUNG). Many in the cohort were looking to address this data gap; they expressed the need for more localized, student-level information to adequately identify and target reforms.

We compiled a list of national data sources that are available at various other small geographies and can still be valuable when leveraged or used to inform decisions. Housing practitioners and local school districts can use these sources improve coordination between housing and education policies to effectively address shared objectives.

Data sources on housing affordability

Housing costs can limit a household’s resources for other expenses, and they also drive local property taxes, which fund public schools. The following sources can help education stakeholders determine local housing composition.

• American Community Survey. This ongoing survey provides annual information on the number of household units, household members, rent prices, average home prices, and more.
• Home Mortgage Disclosure Act.These data cover US mortgage applications and denials by applicant demographics, including race and gender. They show the number of mortgage applicants, reasons for denial, and characteristics of mortgages at the county and metropolitan statistical area levels.
• Comprehensive Housing Affordability Strategy. This database is maintained by the US Department of Housing and Urban Development (HUD) and demonstrates the extent of housing problems and housing needs, particularly for households with low incomes.

Data from the following publicly funded programs that address housing affordability can also help school districts understand the communities they serve, especially families with low incomes.

• The Low-Income Housing Tax Credit (LIHTC) Program. This program is an indirect federal subsidy used to finance the construction and rehabilitation of low-income affordable rental housing. Financed projects must meet eligibility requirements for at least 30 years after project completion. It includes property- and tenant-level data, such as on unit size, unit mix, and location of individual projects.
• Assisted Housing: National and Local. These data summarize public and assisted housing units, including LIHTC units, housing choice voucher (HCV) units, and various other multifamily assisted, or privately owned, project-based housing units that provide rental housing owned by private landlords who receive subsidies from HUD.
• Resident Characteristics Report. This report summarizes aggregate demographic and income information about households who reside in public housing or receive Section 8 assistance.
• HCVs by tract. HCVs help households with very low incomes find private-market housing.
• HUD Income Limits and Fair Market Rents. These county- and metropolitan-level estimates from HUD identify the income limits that determine eligibility for assisted housing programs

Data sources on housing insecurity

The following sources can help school districts understand the prevalence of students experiencing homelessness and housing insecurity and help them provide the supports necessary to meet their unique needs.

• Eviction Lab data base. These data capture eviction filings (not actual evictions) at the county level. Filings do not necessarily contain information on the outcome of the case, so they may not correlate directly to the evictions within a place. But they do provide insight into overall instability.
• Point in time count. These data approximate the number of people who experienced homelessness in a geographic region on a single night and are represented at the continuum of care level, which often coincides with the county level.
• Homeless Management Information System services. These data detail the number of people who seek and receive homeless services during a month.
• McKinney-Vento Act. These data capture the number of students experiencing homelessness within a school or school district.
• Fair Housing data and mapping tool: Affirmatively Furthering Fair Housing data have indicators on Fair Housing enforcement and outreach, segregation and integration, disparities in access to opportunities, racially and ethnically concentrated areas of poverty, and information on housing needs and displacement risks.

Data sources on social mobility

Research shows children in families with low incomes who experience upward socioeconomic mobility tend to have improved educational achievement, higher graduation rates, and increased access to opportunities that can positively shape their long-term prospects and break the cycle of intergenerational poverty.

The Opportunity Atlas includes maps and the underlying data for upward mobility from poverty based on geography and family socioeconomic status, as well as other variables related to mobility. The data focus on geographies that provide social mobility (census tracts or neighborhood level and all zip codes).

Data sources on neighborhood and environmental quality

The quality of one’s lived environment, as well as the policies that govern it, significantly affect student outcomes. For example, restrictive zoning can limit affordable housing availability, exacerbating educational inequities, but inclusive zoning practices can foster diverse communities and enhance educational opportunities for all students. And neighborhood-level environmental conditions are closely tied to students’ educational success.

• Zoning Insights. These data detail about land-use regulatory practices such as residential zoning density, impact fees, and accessory dwelling units.
• Environmental Health Hazard Index. These data capture the proximity to environmental hazards (such as brownfield sites) in a neighborhood.
• Air Quality Index Publications. Environmental Protection Agency data on the quality of air quality at the county level was most recently collected in 2014.

Accessible data are the first step toward informed solutions

Housing and educational outcomes are inextricably linked, but policymakers and other stakeholders can’t develop shared goals without access to the same data. These resources can be a starting place for decisionmakers to identify shared needs and create targeted solutions that advance student success and housing stability.