Association for Public Policy Analysis & Management

We investigate the effects of on-demand ridesharing via platforms like Uber, Lyft, and Didi Chuxing on the use of public transit systems. Our study uses trip count data for Uber, Lyft, taxi, subway, and shared bike usage in New York City. We find that on the surface, ridesharing and subway usage are positively correlated. Exploiting a series of exogenous shocks to the system – the closing of subway stations – to better isolate substitution effects, our preliminary results suggest that the average shock is associated with a 17-72% increase in the use of ridesharing, highlighting the potential for on-demand ridesharing to serve as infrastructure that helps smooth unexpected supply and demand surges. Our ongoing work studies how these substitution patterns continue in the long run, and how public transit users react to changes in the cost of ridesharing alternatives. We hope to lay a data-driven foundation to better understand how the sharing economy substitutes and complements existing and future capital-intensive transit systems.