Transit investments and neighborhood change: On the likelihood of change

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