Assessing ridership impacts of fare-free transit policies through agency- and neighborhood-level models

This study assesses the long-term effects of fare-free transit (FFT) policies on ridership, at both the agency and neighborhood levels. Using a Fixed Effects model with Instrumental Variables on data from 125 U.S. transit agencies (2011–2023), we found that partial-route and full FFT policies increased agency-level ridership by approximately 17% and 45%, respectively. Then, employing and a Spatial Durbin model with Fixed Effects on bus data from Boston, MA, USA (2021–2023), we found that neighborhoods served by FFT routes saw 26% more boardings than those served by non-FFT routes. The impact of FFT also varied by time of day, with smaller effects observed during peak hours, evenings, and weekends. By distinguishing between types of FFT policies (i.e., full, partial-population, or partial-route) and their spatial and temporal effects, this study offers actionable insights for transit agencies. These insights are particularly relevant for agencies aiming to maximize ridership growth while balancing factors, such as service coverage, serving population, and budget constraints.