Lu Han, University of Wisconsin, Madison

A growing body of literature has documented persistent racial discrimination in rental housing markets, often using audit or correspondence studies where fictitious identities request to view an apartment. However, these methods may overlook subtle forms of discrimination, such as selective advertising, where landlords selectively choose not to advertise certain units, reserving them for prospective renters they have met in person after an initial screening. This practice is difficult to detect, creating significant challenges for Fair Housing Enforcement.

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 28 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 assess the extent of discrimination through selective advertising.

Detecting selective advertising is crucial because when minorities are steered away, they lose not just an apartment but also access to amenities and job opportunities tied to a particular location, exacerbating social inequality. We find that discrimination against Black and Hispanic renters through selective advertising is particularly severe in neighborhoods with better amenities, where other forms of discriminatio

DATE: Friday, August 30, 2024

TIME: 3:30-5:00 p.m.

LOCATION: Zoom | Mtg ID: 839 0758 8533 Code: 515446