Research Paper on Racial Neighborhood Context of Eviction Filing Rates in Maryland
By Lear Burton, Doctoral Student (bio)
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Despite the scale and seriousness of the issue, eviction has been called a “hidden housing problem” since a lack of data diminishes visibility on the issue (Hartman & Robinson 2004). This has been especially true in Maryland where the full extent of the court-based eviction landscape has been unclear. However, in 2022, Maryland enacted a new law requiring the District Court to collect and report eviction case data for the whole state. The first full year of data was for 2023. Maryland is one of the least affordable states for renters (National Low Income Housing Coalition 2024), and until now, has not had any statewide research done on evictions.
Eviction is a central mechanism that lays bare the exploitation of housing working-class people under capitalism (Deluca 2022, Desmond 2015, Garboden 2023). Landlords, especially ones with large ownership portfolios, use evictions to control and exploit tenants for economic gain (Balzarini & Boyd 2021, Garboden & Rosen 2019, Immergluck et al. 2020, Raymond et al. 2016). Not only does the act of eviction have immediate consequences on an individual’s basic need for housing, it also affects their health (Desmond & Kimbro 2015, Hatch & Yun 2021, Vasquez et al. 2017), the likelihood of future forced displacement (Desmond et al. 2015), and it increases the likelihood of homelessness and lowers future earnings (Collinson et al. 2023). Beyond the outcomes for individuals, eviction shapes neighborhoods by making them less stable and disrupting community and social networks (van Holm & Monaghan 2021).
More than just the acute physical removal of people from their homes, eviction encompasses “the ongoing set of relations between the landlord and tenant that lead sometimes to a formal eviction, but far more frequently to a filing that changes the power dynamic, or an informal eviction” (Deluca and Rosen 2022). Informal evictions are ways that landlords remove tenants outside of the legal system by incentivizing, threating, or doing drastic things like taking off tenant’s doors to pressure them to leave (Desmond 2016, Hartman & Robinson 2003). There is a lack of data on informal evictions, however scholars estimate that for each formal eviction there may be more than 5.5 informal evictions (Gromis & Desmond 2021). Despite its inadequacies, court-based eviction data is useful due to the lack of data on other types of evictions.
Using 2023 eviction data for the state of Maryland, the current study aims to answer the question: How does neighborhood racial composition (measured three ways in percent of census tract that is Black, Asian, and Hispanic) associate with neighborhood eviction filing rates in Maryland? To answer this question, I first aggregate eviction data by census tract and then combine it with 2023 five-year American Community Survey (ACS) detailing tract level information on demographics and housing characteristics. I then run ordinary least squares regression models to examine the association of neighborhood racial composition and other demographic and housing variables on the log of neighborhood-level eviction filing rate. I define the eviction filing rate as the number of eviction fillings per 1000 people within a given census tract.
I find strong support that in Maryland, higher shares of a neighborhood population that is Black, Hispanic, and Asian were all associated with higher neighborhood eviction filing rates even while controlling for housing markets, socioeconomic status, and neighborhood decline. Neighborhood level socioeconomic variables such as median household income and percent of the tract that is female headed households with children did have significant associations with eviction filing rates, though they did not have a significant mediation effect on any of the race coefficients.
These findings are in line with past research on eviction, a higher share of Black residents in a neighborhood is associated with higher eviction filing rates (Lens et al. 2020). The current study finds that within Maryland the share of Hispanic residents and Asian residents has a similarly sized positive effect as share of Black residents on the neighborhood eviction filing rate. The association equates to about a 20 percent increase in expected eviction rate for each 10 percent increase in Black, Hispanic, or Asian share of the neighborhood (respectively, and while controlling for the two other racial groups). The association is especially strong and meaningful for share of a neighborhood that is Black, since there are many majority-Black neighborhoods within Maryland. Figure 1 shows the expected neighborhood eviction filing rate by share of the census tract that is Black while controlling for housing market and socioeconomic variables.
Maryland is a particularly compelling case study on racial inequality in housing due to the prevalence of wealthy Black neighborhoods. The two wealthiest majority Black counties in the United States are Charles ($105,087 median income) and Prince George’s ($98,027 median income) Counties in Maryland. The presence of wealthy majority Black neighborhoods in these Counties did not offset the well-observed national trend that a higher share of Black residents in a neighborhood is associated with higher eviction filing rates.