This research contributes to understanding the effects of local government urban regulatory policy and actions of private actors on a neighborhood’s housing market using the fast-growing city of Charlotte, North Carolina, as a case study.
The first article of this research examines private actors in the rental housing market and their impact on neighborhood outcomes. The analysis focuses on how exclusionary criteria used in online rental advertisements vary spatially and how they potentially impact neighborhood outcomes. It also focuses on how various factors such as race, income, and platform (Zillow vs. Craigslist) influence the presence of exclusionary criteria in rental advertisements.
The second article situates private actors' actions within the scope of a neighborhood’s changing characteristics and their effects on a neighborhood’s capital investment exhibited through housing renovation activity. The analysis employs 10-year longitudinal parcel-level permitting data on housing renovation activity, housing and neighborhood-specific variables, and spatial statistical techniques to assess if a change in a neighborhood’s prevailing characteristics influences housing renovation activity.
The third article analyzes the effects of local government regulatory policies on a neighborhood's housing market, specifically housing code violations that are resolved with repairs. The chapter hypothesizes that housing code violations, when solved with repairs, will significantly affect a neighborhood’s housing market by increasing home sales and rental prices or contribute to the loss of affordable housing as landlords withdraw their property from the housing market. To test this hypothesis, the research uses longitudinal data on home sales prices, gross rent, housing code violations, and other housing and neighborhood-specific variables. It employs spatial statistics techniques to model their longitudinal relationships.
These three articles collectively contribute to our understanding of neighborhood housing markets analyzed through the lens of private investments and practices and urban regulatory policy adopted by local governments in fast-growing cities like Charlotte. Furthermore, these chapters create a framework that shows how spatial statistics tools, natural language processing techniques, and novel and traditional data can be used to understand the relationship between a neighborhood’s housing market and neighborhood change.