Estimating Rail Commuter Preferences under Endogenous Crowding: A Population Game Approach to Train Choice in Tokyo

Abstract

We estimate commuters' preferences over schedule delay, travel time, and crowding from observed train choices on a commuter rail line in Tokyo. Because crowding is itself an outcome of these choices, we model train choice as a game in which train choices and crowding are jointly determined, and estimate the preferences by maximum likelihood using the closed-form stationary distribution of the game. Using individual-level data from Japan's 2015 Public Transport Survey for Metropolitan Areas matched with train timetables, we construct desired arrival times from reported work start times rather than inferring them from observed arrival times. We find that schedule delay costs are large relative to crowding costs. One minute of schedule delay early and late corresponds to 0.39 and 0.49 minutes of in-vehicle travel time, respectively, whereas one minute of travel at a crowding rate of 100% adds a cost equivalent to 0.04 minutes. The estimated crowding cost is, however, sensitive to the specification of desired arrival times. These results suggest that scheduling constraints are central to evaluating policies to reduce peak-hour crowding.