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Subway Ridership and Crime in New York City: A Fixed-Effects Analysis of Egohoods, 2020-2024

Publié
Serveur de preprints
Preprints.org
DOI
10.20944/preprints202512.0669.v1

Understanding how subway stations affect nearby crime is important for urban planners, transit agencies, and public safety officials who must allocate limited resources. Prior research suggests that transit nodes can increase crime by concentrating potential targets, but findings vary depending on station design, ridership levels, and time of day. This study examines whether within-place changes in subway ridership are associated with changes in recorded crime across New York City from 2020 to 2024. The unit of analysis is the quarter-mile "egohood," a buffer around each Census block centroid. Data come from NYPD complaint records, MTA ridership counts, and American Community Survey demographics. Using two-way fixed-effects models that control for stable neighborhood traits and citywide year shocks, the analysis finds that increases in ridership within the same egohood are associated with modest increases in recorded crime. Station presence alone does not predict crime once time-invariant characteristics are held constant. These findings suggest that managing passenger flows, rather than station footprint, should guide safety planning. Practical steps include improved lighting, visible staffing during peak hours, and coordination between transit agencies and local police.

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