New Research Shows Eviction Record Inaccuracies Can Skew Eviction Rates and Harm Renters

Researchers with Princeton University’s Eviction Lab published an article in Housing Policy Debate, “Inaccuracies in Eviction Records: Implications for Renters and Researchers,” which explores the prevalence of inaccuracies within court record eviction data. The article identifies distinct types of administrative errors and ambiguities that occur in eviction court records. The researchers use data from 12 states to assess how often these errors occur, how they impact eviction rates, and how errors can affect eviction research and renters themselves. The authors report that more than one-fifth of eviction records contain ambiguous or inaccurate information and that accuracy varies widely by state.

Inaccurate eviction data can have far-reaching implications for renters, eviction research, and eviction prevention policy. Research findings, for example, can be skewed if analysis does not account for eviction record inaccuracy. Additionally, because landlords are less likely to rent to individuals who have been evicted or have a history of involvement with housing court, inaccurate eviction records can make it harder for affected renters to find housing.

To assess the quality of state housing court record data, the researchers gathered 3.6 million court records from 12 states. Cases were coded for errors and ambiguity. Cases were marked unresolved if the outcome of the case was missing, opaque if the outcome of the case was ambiguous or unclear, duplicate if multiple instances of the same case occurred in the dataset, and serial if a defendant had been filed against multiple times at the same property. Unresolved and opaque cases are instances of ambiguity, whereas duplicate and serial cases incorrectly indicate that a tenant was filed against or evicted.

The authors found that 22% of records were either false or ambiguous, with inaccuracy varying by state. Connecticut’s records had the lowest inaccuracy rate at 7.4%, while South Carolina had the highest at 46.6%. The authors found that the structure of state court systems influenced the prevalence of specific types of errors. Four states had no unresolved cases, suggesting they purge unresolved cases from their system, do not release them to outside parties, or ensure that all cases are formally closed. Only 4% of cases in Hawaii were serial cases, while these made up 31%, 36%, and 43% of Pennsylvania, Virginia, and South Carolina records, respectively.

The researchers assessed how these errors affected each state’s case filing rate (the number of eviction filings divided by the number of renter households) and eviction filing rate (the number of eviction judgments divided by the number of renter households). Once state data were adjusted for false or ambiguous filings, the state eviction rates fell, on average, by 14%. The eviction rate fell most dramatically in states with a high number of false or ambiguous cases. In South Carolina, the unadjusted eviction rate is 21.3%, while the adjusted rate falls to 11.5%.

A growing body of eviction research aims to inform policy interventions and eviction prevention programs. The authors note that eviction research findings can be affected by how researchers treat false and ambiguous data. Inaccurate eviction data can also harm renters. Unadjudicated or ambiguous case outcomes may result in and eviction record for a person who has in fact never been evicted, and duplicate/serial records can make it seem as if tenants have been evicted far more times than they have.

The authors propose solutions to improve accuracy of housing court record data. They suggest that states adopt a policy of not releasing eviction data to tenant screening companies for unresolved cases. This can ensure that a housing court record does not appear for a tenant who was never actually brought to court. States can also standardize case outcome codes so that court decisions are obvious and clear. Finally, states should perform regular audits to remove or combine duplicate and serial cases.

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