When It Comes to Eviction and Foreclosure Data, What Do Cities and Counties Want to Know?

Data and analysis are only as good as the infrastructure in place to support their ongoing use. And this infrastructure is not built overnight. In July, we introduced the Eviction and Foreclosure Data Tool project and our intent to chronicle different aspects of building a local housing loss data infrastructure in this blog series.

In this post, we draw on the experiences of 14 cities and counties to explore the broad goals and desired uses of eviction and foreclosure data. We’re partnering with these 14 cities and counties (referred to as partner sites from here on) to develop a publicly-available data tool to generate insights about evictions and foreclosures locally.

Access to eviction and foreclosure data (which we collectively refer to as housing loss data) differs from county to county, and so does what cities and counties want to do with that data. Based on initial discussions with city and county leaders across the 14 partner sites, we found that most goals could be categorized by two broader questions:

1. What do we understand about local housing loss in our communities?
2. How do we use housing loss data to change the status quo?

Cities and counties vary in the quality, consistency and granularity of housing loss data they collect and analyze. Because cities and counties start at different points in their access, collection, and analysis of housing loss data, what partner sites hope to understand depends entirely on what they already know.

Back to Basics: Who is Losing their Home and Where?

Some partner sites, particularly those who don’t currently have access to their eviction or foreclosure data, seek a baseline understanding of housing loss rates in their cities or counties. For instance, which neighborhoods have the highest rates of housing loss, and what socio-demographic characteristics are associated with those neighborhoods? This may seem elementary, but research from New America reveals that 1 in 3 U.S. counties have no available eviction data and 1 in 8 counties have no available mortgage foreclosure data. Further, the National League of Cities found that anywhere from 22 percent to 38 percent of city officials surveyed did not know whether evictions increased or decreased in the past year.

In the absence of available data, national organizations have aggregated and provided housing loss statistics to the extent possible. Notably, Eviction Lab’s eviction rate rankings among U.S. cities put evictions on the radar of many city leaders who were either not previously aware of how many evictions were occurring or not prioritizing a response. Building off this data source, New America and DataKind developed a joint metric of evictions and foreclosures, and used pre-pandemic data to track this in a national housing loss index.

While these sources of information are immensely valuable, they are also static; the most recent Eviction Lab rankings are based on 2016 data, and the housing loss index uses pre-pandemic data that will soon be outdated. This is why ongoing analysis as opposed to a one-time analysis is critical. A one-time snapshot does not allow for the same level of assessment into what types of services and supports lead to long term housing stability, and how this changes over time.

Beyond a Baseline: Building a Deeper Understanding of Housing Loss

To advance beyond baseline measures of housing loss, some cities and counties--especially those with more advanced data collection and analysis capacity--hope to further disentangle the root causes of evictions and foreclosures. The ability to link housing loss data with local and national data sources related to health, food security, crime and violence, and COVID-19 is a start.

Data is a powerful tool to build knowledge, inform change, and create momentum. Data can force the question, “What’s next?”

Partner sites also expressed interest in how evictions and foreclosures are connected to other parts of the housing system. For instance, city and county leaders in Winston-Salem and Forsyth County, North Carolina would like to know whether evictions rise when federal subsidies on affordable housing expire, potentially drawing on the National Housing Preservation Database. Housing stakeholders in Milwaukee are interested in matching property records to court records to learn more about beneficial owners of LLCs. And several partner sites expressed a desire to assess housing code violation data and eviction data to better understand the relationship between habitability, landlord negligence and evictions.

And lastly, some sites are eager to tease out the impact of two of the main purveyors of evictions: landlords and judges. What influence do these two players have on the number of filings or noticed and the outcome of court cases? Further, are a small number of property owners responsible for a large proportion of housing loss in a neighborhood or city?

Recent analysis suggests it is the same landlords in the same buildings who are evicting tenants year after year, driving up eviction rates. In Tucson, Arizona, serial evictors executed roughly 2 out of every 3 evictions each year. As such, it is not surprising that housing leaders in Tucson and Pima County are interested in data on serial evictors and the buildings they own. Knowing this information could help housing leaders target landlords responsible for a large share of evictions and devise mitigation strategies, much like what transpired in Milwaukee last summer when one millionaire landlord drove the majority of pandemic-era eviction filings.

One issue related to building and advancing knowledge is who owns local data. Access to summarized eviction and foreclosure data is not the same as access to individual court records--or raw data--that can be leveraged to address different questions that are responsive to local housing laws and context.

Housing leaders in the City of Minneapolis rely on a public-facing dashboard maintained by the County for information on evictions. Drawing on court data from as far back as 2009, the dashboard gives a comprehensive picture of what’s happening locally, including which zip codes in the county have the highest rates of evictions and eviction filings and which landlords are filing most frequently. At the same time, this is the main source of information on evictions for city leaders in Minneapolis and the public alike. And without access to raw data that can be mapped and analyzed at more relevant units of geography, or without the ability to integrate other sources of data, analysis can be limited.

When cities and counties understand basic measures of housing loss within their communities, they can leverage this knowledge to push for change. This can take a lot of different forms, but the underlying idea is the same--how can housing loss data be deployed strategically to advocate for change and hold decision-makers accountable?

While movements for guaranteed right to counsel and just cause evictions are growing nationally, a lot of local advocacy relies on the experiences of tenants, legal aid providers, and other community organizations who have first-hand experience with housing loss. Supplementing these narratives with city or county-wide data that show disparities in where evictions are concentrated or disparities in who has legal representation could bolster support for local legislative and budget advocacy campaigns. Housing leaders in Adams County, Colorado shared that year after year, the absence of up-to-date and detailed eviction data limits funding requests for homelessness services and eviction mitigation efforts that address the scale of the problem.

Data can also be used to help policymakers evaluate and modify local laws and programs that address housing loss. To obtain more data about possible evictions, the City of Hayward, California passed an ordinance in 2019 requiring landlords to submit notices when they terminate a tenancy. Since this is the official documentation that begins the eviction process, data collected from these notices give some indication of landlord activity, including the reason for termination.

At the same time, supplementing this information with court records on eviction filings could shine a light on the number of evictions pursued compared to termination notices, and provide insight on whether landlords are complying with the ordinance. This more comprehensive data on evictions could also help identify possible interventions, including stronger enforcement beyond the existing penalties and citations, as well as mitigation strategies that help landlords and tenants avoid the eviction process altogether.

Over the long term, incorporating housing loss in broader assessment and planning tools can increase awareness, build a public narrative, and create accountability for improving housing loss over time. Many cities and counties develop and use comprehensive plans to guide development over the long-term. Though not legally binding, comprehensive plans do provide a vision for the future of housing and land use against which future development and programming are assessed. Some partner sites expressed a desire to incorporate housing loss rates and associated metrics in these long-term planning efforts, or as an input into broader indices for well-being. The City of Louisville hopes to one day be able to include evictions and eviction filing rates into a social equity index, formalizing eviction as a social determinant of equity.

Admittedly, data alone is not enough to stop housing loss. But it is a powerful tool to build knowledge, inform change, and create momentum for that change. Data forces the question, “What’s next?”, and for partner sites and other jurisdictions around the country, the answer to that question relies on what they currently know and what direction they’d like to head in.

To stay up-to-date on this project, subscribe to our monthly newsletter here, or email Sabiha Zainulbhai at zainulbhai@newamerica.org to share insights, ask questions or learn more.