Scandinavian Working Papers in Economics

Research Programme in Transport Economics,
Research Programme in Transport Economics

No 2020:6: Representing travel cost variation in large-scale models of long-distance passenger transport

Ida Kristoffersson (), Andrew Daly, Staffan Algers and Stehn Svalgård-Jarcem
Additional contact information
Ida Kristoffersson: Research Programme in Transport Economics, Postal: Forskningsprogrammet TRANSPORTEKONOMI, Att: VTI, Box 55685, 102 15 STOCKHOLM
Andrew Daly: University of Leeds, Postal: Forskningsprogrammet TRANSPORTEKONOMI, Att: VTI, Box 55685, 102 15 STOCKHOLM
Staffan Algers: TPMod, Postal: Forskningsprogrammet TRANSPORTEKONOMI, Att: VTI, Box 55685, 102 15 STOCKHOLM
Stehn Svalgård-Jarcem: WSP Advisory, Postal: Forskningsprogrammet TRANSPORTEKONOMI, Att: VTI, Box 55685, 102 15 STOCKHOLM

Abstract: In this paper we show that travel cost variation for long-distance travel is often substantial, even within a given mode, and we discuss why it is likely to increase further in the future. Thus, the current praxis in large-scale models to set one single travel cost for a combination of origin, destination, mode, and purpose, has potential for improvement. To tackle this issue, we develop ways of accounting for cost variation in model estimation and forecasting. For public transport, two methods are developed, where the first method focuses on improving the average fare, whereas the second method incorporates a submodel for choice of fare alternative within a demand model structure. Only the second method is consistent with random utility theory. For car, cost variation is related to long run decisions such as car type choice and employment location. Handling car cost variation therefore implies considering car type choice and workplace choice rather than different options related to a specific trip. These long-term choices can be considered using a car fleet model.

Keywords: Long-distance travel; Travel cost; Travel fare; Large-scale model; Demand model

JEL-codes: R40

16 pages, October 28, 2020

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