Transit investments and neighborhood change: On the likelihood of change

Abstract

This paper is focused on the identification of, and the dynamics associated with, neighborhoods that are more prone to undergo socioeconomic and demographic changes following rail transit investments. Utilizing data from 9 metropolitan areas that have invested in light rail between 1980 and 2010, a k-means clustering approach is used to construct discrete multivariate neighborhood typologies. Together with Markov chains, we are able to examine transitions between neighborhood types before and after the opening of a station. Results for affected neighborhoods are compared to city-wide transitions to uncover differences. Our findings suggest that there is a significant difference in transit and non-transit neighborhood transitions. There also appears to be a difference in trajectories between Walk-and-Ride and Park-and-Ride neighborhoods. While neighborhoods are largely stable over time, impoverished neighborhoods are most likely to experience changes (such as gentrification) following the opening of a transit station. The most affluent neighborhoods are the least likely to experience change but are associated with the most probable trajectory of change featuring densification. Finally, there is little evidence that socioeconomic ascent following station openings is associated with significant changes in racial composition. Knowledge about neighborhood dynamics associated with transit investments can aid policy makers and planners in achieving socioeconomic goals of transit investments.