From Section 8 to Starbucks: The Effects of Gentrification on Affordable Housing in Pittsburgh, Pennsylvania

Abstract

This dissertation examines gentrification in Pittsburgh, PA to determine if the process is reducing the amount of affordable housing for low-income groups. There has been considerable debate regarding the merits and consequences of gentrification for the economic development of cities and this research contributes to the discussion by uncovering how housing is affected in a Rust Belt city. The deindustrialized cities of the American Rust Belt have been largely ignored within the gentrification literature because of the population loss and economic slumps these metros have faced due to global restructuring of manufacturing industries. There are signs that many of these urban areas are making the shift to a postindustrial city and that people and capital may soon be returning to their downtowns. In light of the various development projects that have been implemented in places like Pittsburgh, it is important to understand how the urban form is restructured through the process of gentrification. I use various regression models, including OLS, spatial regression, and geographically weighted regression (GWR) to measure the effect of gentrification on affordable housing for three levels of low-income households. This research shows that gentrification is reducing the availability of affordable housing in the Pittsburgh metro, despite the presence of a soft housing market caused by high vacancy rates within the central city. Regression models show that the vacancy rates are likely reducing the reduction of affordable housing in various neighborhoods of the city, but that buffer of a soft housing market will most likely disappear as data show an increasing interest in moving into the city. The Pittsburgh metro area already has a shortage of extremely low-income affordable units and steps must be taken in Pittsburgh to ensure that low-income households can have affordable access to the city in the future.