Few researchers have studied integrated neighborhoods, yet these neighborhoods offer an important window into broader patterns of segregation. We explore changes in racial integration in recent decades using decennial census tract data from 1990, 2000, and 2010. We begin by examining changes in the prevalence of racially integrated neighborhoods and find significant growth in the presence of integrated neighborhoods during this time period, with the share of metropolitan neighborhoods that are integrated increasing from just under 20 percent to just over 30 percent. We then shed light on the pathways through which these changes have occurred. We find both a small increase in the number of neighborhoods becoming integrated for the first time during this period and a more sizable increase in the share of integrated neighborhoods that remained integrated. Finally, we offer insights about which neighborhoods become integrated in the first place and which remain stably integrated over time.
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.