Using data to measure progress on housing equity goals
December 9, 2024
Image credit: Getty Images Signature
Overview
Data tools are key for identifying and addressing local housing disparities. They can also provide essential support in evaluating the efficacy and sustainability of interventions. Whether cities are evaluating the impact of equity-based programs or tracking community engagement efforts, data can play a powerful role in guiding decision-making, measuring outcomes, and promoting accountability.
Cities can track key housing indicators over time to assess the impact of local initiatives.
Several key indicators can help assess the impact of initiatives aimed at reducing housing disparities. For example, cities can leverage data from the U.S. Census to calculate the dissimilarity index, which compares the distribution of racial groups between neighborhoods in a city or metropolitan area. This index, along with the isolation index and entropy index, can reveal the extent of racial segregation in a specific area. Additionally, cities can track the Gini coefficient over time, which serves as a measure of income inequality.
Localities can also monitor more specific indicators using data sources like the American Community Survey (ACS). For example, cities can assess homeownership rates, rent burden levels, and housing quality by race, income level, and disability status. The most relevant indicators for this type of longitudinal analysis will ultimately depend on a city’s equity strategy and its intended outcomes. Explore our Housing Needs Assessment Tool for additional guidance on identifying key indicators.
Tracking indicators: CUNY Institute for State and Local Governance
In some cases, partnering with universities and other stakeholders can streamline the development and tracking of equity indicators. Since 2014, the City University of New York’s Institute for State and Local Governance has partnered with the Rockefeller Foundation to create equity indicator tools for several cities, including Dallas, TX; Oakland, CA; Pittsburgh, PA; St. Louis, MO; and Tulsa, OK. These tools allow cities to understand housing equity trends, evaluate the impact of ongoing initiatives, and allocate resources to respond to emerging needs. In Tulsa, these indicators revealed significant disparities in housing complaints, leading the city to invest $4.6 million in additional funding for housing initiatives. This investment supported property renovations and the creation of a Multi-Family Housing Team to better enforce maintenance and zoning codes. Thanks to these efforts, Tulsa has maintained a perfect score on its housing complaint indicator.
Cities can leverage geospatial data to monitor more targeted interventions.
Geospatial data can enrich efforts to analyze the impact of equity initiatives. By integrating local boundaries with demographic information, geospatial datasets serve as a valuable tool for visualizing shifts in housing disparities over time. This approach is especially useful for monitoring the efficacy of efforts that target specific neighborhoods or census tracts. For example, geospatial data can indicate whether a direct rental assistance program is actually alleviating rent burden for Black residents in a certain neighborhood, or if residents are simply moving to neighboring areas.
The ACS and the HUD eGIS storefront provide detailed datasets that cover a number of geographic areas, including census block groups and HUD grantee areas. Depending on the availability of local geospatial data, cities can go even further by monitoring the impact of equity initiatives across areas, such as unique neighborhood boundaries or special districts, which are not typically captured by HUD or the U.S. Census Bureau.
Partnering with local residents is an essential component for any data strategy.
While quantitative data can provide valuable insights, partnering with communities is essential to truly gauge whether equity initiatives are reducing disparities. Surveys, focus groups, and other forms of qualitative data can bring out lived experiences and reveal unique considerations that typical housing indicators cannot capture. For example, conversations with disabled residents may indicate that accessibility issues persist in local housing, even if homeownership rates and housing quality have increased over time. By sharing data directly with communities, localities can further elevate the perspectives of local residents, which may make interventions to address housing disparities more responsive and ultimately more effective.
Establishing community partnerships can be more costly and time-intensive than relying on a publicly available data tool. However, through relationships with local stakeholders and community groups, cities can reduce costs, build out expertise, and ultimately create a vital resource for their equity strategies.
Community partnership: Charlottesville, Virginia
Charlottesville, Virginia’s Piedmont Housing Alliance (PHA) works closely with the resident-led Advisory Committee using a feedback-driven workflow to guide the redevelopment of a federally subsidized affordable housing development. The committee is an active co-creator of the redevelopment process: all nine resident representatives must agree on a plan before it moves forward. This standard of consensus often requires multiple rounds of design iterations, in which the project’s design team drafts plans in response to the committee’s feedback, seeks input, and then makes adjustments accordingly. PHA worked with civic designer Liz Ogbu to establish the committee, and part of her ongoing work includes facilitating check-ins with residents on the Advisory Committee. These check-ins are a neutral, lower-stakes platform for residents to share feedback on the committee’s proceedings, encouraging reflection that may not surface during standard group meetings.
For more information on using data to inform housing policy, explore our Data Talks series.