Race, Ethnicity, and Evictions in New York City: Using Publicly Available Data to Identify Disparities in the Rental Housing Market

Background: This study explores the relationship between evictions and race and ethnicity in New York City. There has been a recent surge in academic and policy interest in evictions, culminating in nation-wide eviction moratoria during COVID-19’s impact. Yet, due to difficulties accessing eviction data, little is known about the neighborhood characteristics that predict evictions. By linking multiple publicly available data sets, this study aims to understand where evictions are concentrated and whether New Yorkers of color are disproportionately affected by evictions.

Methods: This study created a zip-code-level data set that links evictions data from the New York State Office of Court Administration and NYC Open Data with income, demographic, and housing characteristics from the U.S. Census and the U.S. Department of Housing and Urban Development for 174 zip codes in New York City. This study used hierarchical ordinary least squares regression to test whether the racial and ethnic makeup of neighborhoods predicts eviction filings after accounting for housing and income characteristics. The hierarchical model had three blocks of variables: block 1 included housing and income variables only; block 2 added the share of residents who identify as Hispanic, Black, and Asian; and block 3 added the interaction between the poverty rate and the race/ethnicity variables.

Results: The regression model that included race and ethnicity (block 2) accounted for significantly more variation in eviction filing rates than the model that included housing and income variables alone (ΔR2=.22, F(3,164)<.001). Block 3 interactions explained additional significant variation (ΔR2=.04, F(3,161)<.001).In block 2, the associations between eviction filing rates and (1) the poverty rate (β=.36, p<.001), (2) the share of the residents that identify as Hispanic (β=.26, p<.001), and (3) the share of the residents that identify as Black (β=.54, p<.001) were all statistically significant. The associations between the other housing and race/ethnicity variables and eviction filings were not reliably different from zero. Block 3 indicated that the poverty rate moderates the association between the proportion of Hispanic residents and eviction filing rates (β=.34, p<.05), but not the relationship between the proportion of Black residents and eviction filing rates (β=.22, p=.085). Low-poverty neighborhoods with high and low proportions of Hispanic residents had roughly the same mean eviction filing rate (.6 and .5 respectively), while high poverty high-proportion-Hispanic neighborhoods had a much higher mean eviction filing rate (.21) than high-poverty low-Hispanic neighborhoods (.09). Neighborhoods with high proportions of Black residents had consistently larger mean eviction filing rates than neighborhoods with low proportions of Black residents, regardless of poverty rates.

Conclusions: This study found that Hispanic and Black New Yorkers are disproportionately subject to eviction filings, even when controlling for the poverty rate of the neighborhood. Black New Yorkers are hit the hardest: all neighborhoods that had high rates of Black residents, regardless of poverty rate, had higher-than-average eviction filings. Many of these same neighborhoods have been hit the hardest by the COVID-19 crisis. Policymakers should design and target COVID relief efforts to help address some of these long-standing racial injustices.