Modeling regional disparity and the reverse commute

Abstract

• A dimension reduction approach is employed to model the reverse commute. • Greater distances between origin and destination predict the reverse commute. • Higher percent of population African American at origin predict reverse commute. • Lower incomes at origin and higher incomes at destination predict reverse commute. • Effect of metropolitan fragmentation on reverse commute is unclear. This paper measures a) whether the reverse commute – a commute where a worker travels from a home location in the city to a workplace location in the suburbs – is characterized by a uniquely disparate socioeconomic and demographic space between home and workplace, and b) what role greater fragmentation between municipalities in a region might play in this theoretically inequitable circumstance. We employ administrative origin–destination data from the metropolitan Philadelphia, PA area and contemporary dimension reduction methodologies to model the likelihood of an origin destination pair being classified as a reverse commute. Particular attention is given to interactions between socioeconomic and metropolitan fragmentation terms and non-linear specifications of predictor variables. Greater socioeconomic and demographic disparity between home and work geographies is found to uniquely predict the reverse commute. We also find that fragmentation at the metropolitan scale has a multidimensional impact in relation to this socio-economic difference. Together, our findings appear to signal that, while greater regional socioeconomic disparity does indeed correlate with the reverse commute, greater metropolitan fragmentation may not. This portrait highlights new areas for transport research around political fragmentation and makes the case for renewed, equity-oriented policy investment in the reverse commuting problem.