Foreclosures and housing prices in a heterogeneous housing market: Spatial externalities, crowding-in and filtering effects over the short- and long-run

This dissertation offers a new way of conceptualizing and then estimating the potential neighborhood effects of foreclosures on nearby property values. It argues that the measured impact of foreclosures may depend upon the definition of submarkets. The traditional approach assumes homogenous housing stocks and narrowly defines submarkets spatially. This approach looks at the spatial proximity/neighborhood impacts of foreclosures. By contrast, this study uses an alternative approach that considers heterogeneous housing stocks and suggests a broader definition of submarkets that are not geographically constrained. Foreclosures add to the existing housing inventory within a submarket, regardless of location. Thus, the new approach distinguishes between the within-submarket impact of foreclosures and the filtering impact based on the idea of a quality hierarchy of submarkets. This study also discusses the problem of treating all foreclosure equally in estimating the impact. Accordingly, it hypothesizes that the impact may depend upon the length of time elapsed in the process of foreclosure. This study uses a dataset that covers twenty years of housing values from Worcester, MA, and finds that that foreclosures in the close proximity best explain the surrounding property sales price and that the interaction effects from other types of housing (multi-family) really matter. Findings from this study also suggest that the within-submarket effect is significant. However, the filtering effects are limited to certain submarkets. This study also reveals that foreclosures of single-family houses of short duration do not matter in the Worcester housing market. It also suggests that the effects of multi-family foreclosures within one-quarter mile of the subject property increase as the time length of the process increases.