Collaborative Research: Effects of government-insured mortgages
- Institution
- University of Pittsburgh, PA
- Principal investigator
- Omer A Ali
- Funding
- $407K
- Duration
- 2025–2027
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Abstract
This project constructs a new dataset from county land-use records. The dataset includes information on land records from 20 counties spread across the United States over 40 years. It includes data on the Federal Housing Administration (FHA) insured and Veteran’s Administration (VA) guaranteed mortgages in these counties. The data will be publicly available to academics, decision makers, community organizations, and individuals who want to evaluate the impact of these two important federal programs. The team is also providing an initial analysis of these data to describe and analyze the spatial and demographic patterns of federal mortgage insurance. This analysis leverages individual-level borrower data and address-level property information to examine how these programs affected homeownership, wealth, and neighborhood outcomes in counties with different characteristics. The research findings have the potential to improve the functioning of mortgage markets, thereby enhancing the well-being of U.S. households. The award is jointly funded by the NSF programs in Economics, Sociology, and Human-Environment and Geographical Sciences (HEGS). The project creates a new data resource that provides the most extensive and granular data on the demographic and spatial distributions of FHA-insured and VA-guaranteed mortgages to date. Because the data include information on issued mortgages, the data allow scientists to consider the results of enacted policy rather than simply examining government agency reports and correspondence. The team is collecting and geocoding data on roughly 280,000 mortgages. They are using the data and econometric methods to provide detailed descriptive statistics on the recipients of government-insured mortgages. They also use the data to test hypotheses about the effects of FHA and VA loans on neighborhood characteristics The broader impacts include access to data and enabling science-informed discussions about issues that affect wealth accumulation, neighborhood outcomes, and intergenerational mobility. The project also involves students and early career researchers in data collection and analysis. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- Omer A AliPI
- Randall P Walsh
- Andreas Ferrara
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