This paper addresses a critical but almost unexamined aspect of the Low Income Housing Tax Credit (LIHTC) program—whether its use (and in particular, the siting of developments in high poverty/high minority neighborhoods), is associated with increased racial segregation. Using data from HUD and the census, supplemented with data on the racial composition of LIHTC tenants in three states, we examine three potential channels through which the LIHTC could affect segregation: where LIHTC units are built relative to where other low income households live, who lives in these tax credit developments, and changes in neighborhood racial composition in neighborhoods that receive tax credit projects. The evidence on each of these channels suggests that LIHTC projects do not contribute to increased segregation, even those in high poverty neighborhoods. On net, we find that increases in the use of tax credits are associated with declines in racial segregation at the metropolitan level.
The U.S. Department of Housing and Urban Development’s strategic plan identifies the use of “housing as a platform for improving quality of life” as one of its five strategic goals. It further establishes a sub-goal to improve educational outcomes and early learning and development for children in HUD-assisted housing. This paper is intended to advise HUD about how to use readily available data to create a metric for school quality. This metric is the measure of success in providing “access to schools scores at or above the local average” for children in assisted households. The researchers recommend a ratio that compares the test scores of the elementary schools nearest subsidized households to the test scores of other schools in that same county or metropolitan area, with perhaps a comparison to the schools nearest other renters or low-income households. Using this local-comparison ratio can overcome differences in state methodologies for evaluating schools, differences in homeownership rates across metropolitan areas, and differences in income levels. This score will allow HUD to identify metropolitan areas to target for mobility efforts and to track progress over time.