Hidden Biases: Selective Advertising in the Rental Housing Market

A growing body of literature has documented persistent racial discrimination in rental housing markets, often using experimental (audit or correspondence) studies where fictitious identities request to view an apartment. However, these methods may overlook a subtle form of discrimination where landlords choose not to advertise certain units, instead reserving them for prospective tenants after an initial screening or other processes to select applicants based on specific attributes. These selectively unadvertised units will not appear in the sample for an experimental analysis, potentially biasing the results of such a study. In this paper, we introduce an innovative method for detecting selective advertising and analyze how this practice hinders minorities’ access to better amenities. Our approach uses a large marketing dataset to track apartment turnovers in 27 major U.S. metropolitan areas. We then match the data with a rental listings dataset to identify turnover units that were not publicly advertised. By comparing the racial composition of occupants in listed versus “hidden” units, we estimate the extent of discrimination through selective advertising. We find that this form of discrimination against Black and Hispanic renters is particularly severe in neighborhoods with better amenities, where other forms of discrimination are more restricted, and in neighborhoods nearing “tipping points” in racial composition.