Allocation of Congested Rail Network Capacity: Priority Rules Versus Scarcity Premiums

Allocation of Congested Rail Network Capacity: Priority Rules Versus Scarcity Premiums


A I Czerny, K Mitusch, A Tanner, WHU - Otto Beisheim School of Management, DE



EU policy aims to increase the use of rail services by supporting competition in the rail industry. One element of this strategy is the regulation of newcomers' access to incumbents' networks. The basic framework for access regulation has been set by the EU Directive 2001/14 "...on the allocation of railway infrastructure capacity and the levying of charges for the use of railway infrastructure...." According to that directive, rail network providers should serve train operating companies with capacity in return for a minimum access charge. It may be that the demand for certain segments of the rail network exceeds capacity for given minimum access charges; following the EU's diction, these segments are congested. In the case of a congested network segment, the directive proposes the use of a scarcity premium. However, if a scarcity premium is not used, allocation of congested capacity may be based on priority rules.

In this paper, we explore the policy implications of moving from priority rules towards scarcity premiums. In particular, we explore the effects of such a policy change on total surplus, consumer surplus, and the rail network providers' revenues. Different priority rules can be applied in practice, for instance, priority can be provided to trains that increase revenues of the rail network provider (as in Germany), to passenger over freight traffic, or scheduled over non-scheduled traffic. To compare outcomes under scarcity premiums and priority rules we, however, focus on the first option, which we call ?revenue maximization?.

We consider a congested network including two rail links and follow a stationary-state congestion approach. Congestion is measured in terms of schedule stability. Delays are costly for customers and rail service providers and they are increasing in the amount of services on a given network; thus, an upper limit for services on a given rail network (capacity limit) also determines an upper limit for delays and delay costs. Note that in our framework congestion is possible even though demand does not exceed the capacity limit, which is in contrast to the EU's notion of congestion.

Moreover, we consider a monopolistic vertically integrated rail service provider with zero variable costs and positive fixed network-costs. The rail service provider serves two (representative) customers. One customer demands short-distance services and one long-distance services. The supply is exogenously determined by a regulator who fixes service charges, the capacity limit, and allocation regimes. Regimes can be of two types: (i) a service charge, no scarcity premium, and revenue maximization, and (ii) a service charge and a scarcity premium, which balances demand and capacity supply. We consider a two-stage game in which customers, first, report demand for short- and long-distance services to the rail service provider. Second, the rail service provider determines services according to regimes (i) or (ii). As a benchmark, we also consider "optimal services" that maximize total surplus or, respectively, consumer surplus for given service charges, given scarcity premium, and given capacity limit. Our key results are based on a Monte Carlo simulation.

We find that none of the two regimes considered is likely to imply optimal services, no matter whether total surplus or consumer surplus is relevant from a policy viewpoint. The simulation demonstrates that the effect of regimes on total surplus is ambiguous: if access charges are low, total surplus is greater under revenue maximization, and if access charges are high, total surplus is greater under a scarcity premium. Our simulation results are clear-cut regarding consumer surplus: consumer surplus is greater under revenue maximization than under a scarcity premium. This indicates that, from a customers' viewpoint, revenue maximization should be favored. On the other hand, a scarcity premium increases the rail network provider's revenues and, hence, contributes to cost recovery. Overall, we find that no regime dominates the other one in all respects. Hence, there is no clear ranking between scarcity premiums or priority criteria from a policy viewpoint. If total surplus is relevant, service charges are low, and cost-recovery is required, a scarcity premium should be the right choice. If total surplus is relevant and service charges are high or consumer surplus is relevant, it should be revenue maximization.

Our contribution is to develop a simple model of a congested rail network and to explore how scarcity premiums or priority rules affect short- and long-distance rail services from a policy viewpoint depending on service charges. Although both regimes considered are not likely to imply optimal services, they do represent regimes that are currently applied and should become more relevant in the future.


Association for European Transport