| Summary: | Since the onset of the COVID-19 pandemic, public transit ridership in the US has faced significant challenges in returning to pre-pandemic levels. Nearly $70 billion in federal relief funding has been allocated to transit departments nationwide, with major US cities using these funds to implement free transit programs. Boston, the focal point of the thesis, launched a fare free bus pilot in August 2021 which has been extended multiple times and is set to continue until 2026. The Fare Free Program has seen encouraging results, marked by increased ridership, cost savings for passengers, and reduced dwell times. The following research leverages large-scale mobility data in an effort to gain deeper insights into the impact of the fare free policy, centering its analysis on Route 28. Employing the tools of causal inference, it offers a valuable resource for planners, policymakers, and scientists seeking to analyze the effect of policy interventions through the lens of big data. Drawing on anonymized, large-scale GPS data from mobile phone users in the Boston area, the research introduces a comprehensive framework for evaluating the impact of Boston’s Fare Free Program on urban mobility behavior, expanding research beyond the scope of transit data and surveys used by the City.
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