2017-2018 Research Grants

  • To Whom Housing Policies Provide Stable Housing: Examining Housing Assistance Recipients and Leavers

    By analyzing the Panel Study of Income Dynamics data combined with the Assisted Housing Database, this study examines potential variations in the roles of housing programs in alleviating housing instability. Specifically, this study particularly focuses on examining the associations between the five statuses related to receiving or leaving housing assistance and subsequent housing instability experience. These statuses include households that: (1) reside in a public or project-based subsidized housing (PH) unit; (2) leave a PH unit; (3) receive a Housing Choice Voucher (HCV); (4) leave the HCV program; and (5) are unsubsidized but income-eligible for housing assistance. Results reveal that, although all housing assistance recipients are less likely to experience housing instability than income-eligible unsubsidized households, HCV recipients are relatively more likely to experience housing instability than PH residents. Moreover, those who made their transitions off the assistance do not significantly differ from income-eligible unsubsidized households.

  • Estimating the Effect of Residential Foreclosure on Neighborhood Housing Prices: A Spatial Analysis

    From 2006 to 2010, the number of foreclosures nationwide grew to levels not seen since the Great Depression. Prior literature has made the claim that the negative externalities of foreclosures on neighboring house prices constitute a market failure, and thus a justification for government intervention. Yet it is not clear that foreclosures have a universal impact on house prices. Traditional hedonic price models and spatial lag models provide an average estimate of each foreclosure on housing prices. We argue that foreclosure is simply a proxy for one or more mechanisms that lead to a downward effect on housing prices and that the impact of the mechanisms varies from neighborhood to neighborhood. Using Zillow data on housing prices and foreclosures in Ohio between 2006 and 2014, we combine a traditional hedonic housing price model with Geographically Weighted Regression (GWR) techniques to investigate how the impact of foreclosures on housing prices vary across space. We find substantial variation in the impact of foreclosures on housing prices, with coefficients and t-statistics ranging from -5.3 to 2.6 and from - 25.24 to 4.36, respectively. In a secondary analysis of neighborhood-level drivers of this variation, we find that a foreclosure has a greater negative impact in a high-income neighborhood than it does in a low-income neighborhood, all else constant. Likewise, newer neighborhoods are also experience a more negative spillover effect than neighborhoods with older housing stock. Contrary to the previous empirical findings, however, the property crime rate is not negatively associated with the spillover effect. Rather, some models shows that the rate mitigates the negative spillover effect of foreclosure incidents. This paper contributes to literature on the effect of foreclosures on housing prices, housing policy, and using spatial methods to investigate public policy problems.