The economics of crowding in urban rail transport

Crowding is a major source of inconvenience for public transport users in densely populated metropolitan areas globally, while eliminating crowding requires costly investments. Crowding can be considered as a cornerstone phenomenon of public transport theory, as the interaction between demand and supply side policies. This PhD thesis aims to improve our understanding of the mechanics behind crowding, using microeconomic modelling techniques. From a demand perspective, the crucial precondition of any objective economic analysis is to reliably quantify the inconvenience caused by crowding. In pursuit of this goal, the thesis develops a statistical model to infer the user cost of crowding from metro passengers' route choice decisions. As an important intermediate research outcome, the thesis delivers a novel passenger-to-train assignment algorithm that recovers the network-level crowding pattern of a metro system. Our method is a unique contribution in the sense that it is based on large-scale automated datasets: we use smart card and automated vehicle location data only. The theoretical part of the thesis provides new insights into crowding pricing and capacity optimisation. One of the key messages of the thesis is that crowding in certain time periods and network segments is an unavoidable feature of optimal public transport provision, when demand fluctuates by time and space, but capacity cannot be differentiated between jointly served markets. We show that pricing can be an efficient tool to tackle the deficiency caused by this technological constraint. The thesis devotes special attention to two policy relevant applications: (i) the external cost of seat occupancy, an externality inversely proportional to the density of crowding, and (ii) the inefficiency of unlimited-use travel passes. Our conclusions may assist researchers and practitioners in better understanding the true cost of public transport usage and the related aspects of optimal policy design, including pricing, subsidisation and capacity provision.