by Cassandra Turk

Housing intervention models intended to revitalize neighborhoods and empower homeowners are frequently observed in cities across the United States. To determine the efficacy of these programs, this study analyzes the effects of a housing intervention on the price of the home and the changes in neighborhood characteristics that may lead to neighborhood stability or instability in the long run, including the home prices, the racial makeup, the median income, and crime rates of the neighborhood. To study these characteristics and how they interact with interventions, I implement a propensity score matching model to reduce variation in unobservable characteristics and to isolate the effect of interventions on the block group characteristics of interest. In addition, I implement a non-parametric kernel regression to allow for the possibility of a non-linear relationship between home prices and home interventions. The results show significant evidence that interventions increase neighborhood home values at the bottom 10th percentile and at the median of each block group, suggesting that housing interventions do serve to increase the quality of the neighborhood. However, there is evidence that these effects taper off after a certain percent of the households in the neighborhood have been intervened upon, reducing the marginal benefit of completing a new housing intervention.

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Advisors: Professor Christopher Timmins, Professor Michelle Connolly | JEL Codes: R2, R23, J10