Public transit has long been viewed as a great equalizer in urban life, expected to break down barriers among social groups and stimulate economic growth. However, empirical evidence on both dimensions remains limited to aggregated proxies such as property values, which may not capture actual and timely behavioral changes, particularly in the post-pandemic context. The Green Line Extension (GLX) in Somerville, Boston Metropolitan Area, which opened in December 2022, provides a natural experiment to examine these relationships. We analyze over 300,000 daily observations of points of interest (POIs) across three cities over 438 consecutive days, measuring economic vitality through daily visit counts and social cohesion through the income segregation of venue visitors. These two outcomes have rarely been studied together using granular behavioral data in the transit literature. We employ a double/debiased machine learning difference-in-differences (DMLDID) approach, which uses data-adaptive estimation to handle the nonlinear covariate-outcome relationships, where traditional linear DID would be misspecified. Our findings reveal a decoupling between the two outcomes. GLX significantly enhanced economic vitality, increasing average daily visits by approximately 23% per POI (95% CI: 13.4%–32.7%). The effects were strongest in retail trade and food service sectors. By contrast, its impact on income segregation at nearby venues was statistically insignificant, challenging the assumption that improved physical connectivity automatically promotes social mixing. The economic effects vary across sectors, while social cohesion effects are statistically insignificant in every sector examined, indicating that this decoupling holds across the sectoral composition of our study area rather than being confined to particular venue types. These findings suggest that, in this short- to mid-term post-pandemic window, transit investment alone did not advance social mixing, pointing to a potential role for complementary interventions alongside infrastructure expansion.
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Huang et al. (2026) studied this question.
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