This presentation details the ongoing work by the Center for Community Partnerships at UVA to understand and address eviction trends in Virginia, a state historically plagued by high eviction rates. The speakers introduce the "Virginia Evicts Catalog," a data tool that reorients court data to analyze eviction filings from the perspective of landlords, including the prevalence of "serial nuisance filings." The core analysis compares eviction patterns and influencing factors (such as the composition of business landlords and rent burden) between 2019 (pre-pandemic) and 2024 (post-moratorium). Key findings reveal a shift in how the interaction between high concentrations of business landlords and rent burden affects eviction rates, alongside the alarming statistic that a substantial portion of filings are serial, overwhelmingly initiated by business landlords. The presentation concludes by outlining future research directions, including the development of interactive geographic tools and a deeper investigation into corporate landlord policies and automated filing practices.
Summarizing Eviction Trends in Virginia: The Role of Landlords and Community Characteristics
0:08 Introduction & Context: Speakers Samantha Towit and Dr. Michelle Clayborn from UVA's Center for Community Partnerships discuss eviction trends in Virginia, noting that in 2018, the state was home to five of the top ten evicting large cities and three of the top five mid-size cities nationally.
1:13 Harms of Eviction: Eviction, even just the act of filing, causes significant harm. It creates a permanent court record, impeding future access to housing, jobs, schools, transportation, and childcare. It also negatively impacts health and destabilizes communities.
3:40 The Virginia Evicts Catalog: This project is an ongoing, quarterly updated dashboard that re-focuses court data to identify who (which landlords) is filing evictions and how frequently. It tracks eviction filings, judgments, and "serial filings" (nuisance filings).
5:26 Impact of COVID-19 Moratoriums: Analysis of data from 2018-2024 reveals a sharp decrease in eviction filings during the COVID-19 moratoria, followed by a resurgence post-moratorium. The research specifically compares 2019 (pre-pandemic peak) and 2024 (post-moratorium) trends.
7:00 Geographic Focus & Data Tool: Legal advocates and organizers expressed a need to understand eviction geography more directly, leading to the development of a more interactive data tool emphasizing spatial patterns.
8:51 Landlord Characteristics & Influences: A Poisson model was used to examine how community and landlord characteristics influence eviction filing rates. Key variables included:
The proportion of landlords operating as a business (large agencies) versus individuals.
Rent burden (individuals paying over 30% of income on rent).
Other factors like residential mobility, college student population, rent exploitation, and racial demographics.
Overall, there were more eviction filings and landlords filing in 2019 than in 2024.
A significant shift was observed in how the interaction between high proportions of business landlords and rent burden influenced evictions. In 2019, this interaction had a negative effect (fewer evictions), possibly due to larger corporations being better able to absorb non-payments. In 2024, this same interaction showed a positive effect, suggesting an increase in filings under similar conditions.
17:09 Serial Nuisance Filings: These are defined as repeated eviction filings by the same landlord against the same tenant within a 12-month period. They are primarily used as a threat for debt collection, not actual displacement.
In 2024, 40% (approximately 56,000) of all eviction filings were classified as serial nuisance filings.
A striking 93% of these serial filings were initiated by landlords operating as a business.
Logistic regression indicated a 97% probability that a filing was serial if the plaintiff was a non-residential (business) landlord.
19:48 Next Steps & Future Research: The team plans to:
Continue building the interactive data tool for advocates and communities.
Identify landlord ownership clusters, including out-of-state owners and large portfolio holders.
Analyze data at a finer geographic resolution (zip code, block group, or even specific addresses).
Investigate additional landlord behaviors, such as the potential for automated or AI-driven eviction filings immediately upon rent non-payment.
25:32 Alternatives to Eviction: The speakers highlighted existing state and local rental assistance programs. Educating landlords about these programs can provide alternatives to immediate eviction filings.
27:41 Policy Disincentives: Advocates are pushing for policies to disincentivize evictions, such as raising eviction filing fees. Evidence suggests states with higher fees have lower eviction rates. The "prop tech" industry's influence may be encouraging landlords to view evictions and potentially vacant properties as a profitable strategy due to accumulated late fees.