Transit Networks & Housing Affordability: A Network-Based Econometric Analysis of Tract-Level Rent Burdens

Abstract

As nearly half of American renters spend more than 30 percent of their income on housing, cities have increasingly turned to public transit investment as a tool for expanding opportunity. The neighborhoods that gain the most connectivity, however, may be the ones that ultimately get priced out. This thesis investigates that tension empirically, using the 2019 Red Line Bus Rapid Transit expansion of Indianapolis's IndyGo system as a discrete network shock. Modeling the transit system as a graph and computing stop-level centrality measures before and after the expansion, this approach yields a tract-level measure of connectivity change that captures not just whether a neighborhood gained new stops, but how its position within the broader network shifted. This network-based approach, applied within a quasi-experimental framework, offers a more structurally grounded lens for studying transit's housing market consequences than conventional proximity-based methods allow. A Difference-in-Differences framework confirms that tracts experiencing the largest centrality gains exhibit persistently higher rent burden following the expansion, with effects that emerge roughly one year after the shock and remain stable over the subsequent four years. Notably, this pattern holds for centrality measures that capture global network position but not for degree centrality, pointing to a key mechanism: affordability pressure is driven not by the addition of nearby stops, but by a neighborhood becoming more deeply embedded in the broader transit network. Together, these findings suggest that the housing market consequences of transit investment are both broader and more structurally determined than conventional impact assessments recognize, with implications for how planners identify and respond to affordability pressure before it sets in.