Transit-induced commercial gentrification: Causal inference through a difference-in-differences analysis of business microdata

Abstract

A plethora of studies has explored the relationship between transit investments and property prices, but very little is known about how new transit projects and transit-oriented development affect nearby businesses and whether they contribute to commercial gentrification. This research presents a quasi-experimental econometric framework for studying transit-induced commercial gentrification from project announcement to post operation using business microdata. Previous urban economics and planning research informs the identification of retail and service business categories associated with the phenomenon of commercial gentrification, including local businesses, chain stores, and businesses offering non-essential or upscale products. Negative binomial models with a difference-in-differences specification enable the temporal and spatiotemporal analysis of business entries, exits, and turnover and the estimation of transit-induced impacts. The developed methodology is demonstrated through an empirical example: the study of the effects of the LYNX Blue light rail line in Charlotte, NC, over a 20-year period. Our study makes a significant contribution to the limited quantitative research on transit and commercial gentrification and is the first to focus on the causal relationship between the two. The application of the analysis framework to other metropolitan areas with transit systems in the future will inform transportation and urban planners on the type of businesses that could be primarily affected and the timing and extent of these effects, and help them design effective and targeted business assistance programs.