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In Virginia, it is unlawful to discriminate in housing due to a person’s source of income, which was added to the Fair Housing Law on July 1, 2020. This means landlords and property managers cannot refuse to rent to someone or treat them differently based on how they pay their rent, including housing vouchers or other forms of government assistance.
Using HUD’s Picture of Subsidized Households dataset and American Community Survey, this study investigates the spatial distribution of Housing Choice Voucher (HCV) holders across the Richmond Metropolitan Area (Central Virginia) in the context of recent expansions in source of income (SOI) antidiscrimination law. Utilizing spatial analytics tools, the research evaluates whether this policy adoption has affected the geographic concentration of voucher holders. The analysis first employs ArcGIS-based cluster and outlier analysis to identify spatial hotspots of voucher use and implements Geographically Weighted Regression (GWR) pre- and post-policy to explore localized relationships between voucher concentration and various socioeconomic, housing market, and policy-related variables. The dependent variable in this study is the density of HCV households at the census tract level, while independent variables include median rent, racial and economic segregation indices, unemployment rates, housing vacancy rates, and the presence or absence of local SOI protections before statewide adoption.
Preliminary findings suggest persistent clustering of voucher holders in certain neighborhoods, despite the legislative intent to broaden housing choice. GWR results reveal significant spatial heterogeneity in the strength and direction of relationships between voucher concentration and explanatory variables—indicating that the effectiveness of SOI laws may be highly context-specific. These findings highlight the importance of localized housing policy implementation and enforcement mechanisms in achieving equitable housing outcomes.