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Enhancing rail direct demand models with competition between ticket types using contributions from economic theory and market research

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  • Toner, Jeremy
  • Wardman, Mark
  • Shires, Jeremy
  • Teklu, Fitsum
  • Hatfield, Andrew

Abstract

Direct demand models estimated to ticket sales data have for many years provided evidence on how key variables influence rail demand in Great Britain. Nonetheless, there has been relatively little estimation of demand models disaggregated by ticket type which would provide own and cross-price elasticities that can inform the pricing of different ticket products. We here report such enhanced models estimated on large data sets and exploiting the relationships of economic theory within a demand system. In addition, a complementary market research exercise is undertaken that itself provides ticket specific own and cross-elasticities and which also supports the estimation of models jointly based on actual and stated behaviour. We conclude that the demand systems approach can recover robust ticket specific own-elasticities but that there are econometric difficulties in estimating cross-elasticities even using supporting economic theory, so that cross-elasticities between tickets are better deduced from these own-elasticities than estimated. This contrasts with the convention in the railway industry in Great Britain where own and cross-elasticities are deduced from recommended conditional elasticity evidence. Market research also has a role to play and provides own-elasticities that, as is common, are rather larger and cross-elasticities that are a little larger than those derived from ticket sales analysis. A key feature of this work is to reconcile those two approaches by scaling the market research elasticities using ticket sales data. This further supports our conclusion that generating robust own-elasticities and deducing cross-elasticities from these is currently the most fruitful method of obtaining a full set of own- and cross-elasticities for different ticket types within a demand system framework, and that this approach is superior to the conventional single equation approach.

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  • Toner, Jeremy & Wardman, Mark & Shires, Jeremy & Teklu, Fitsum & Hatfield, Andrew, 2020. "Enhancing rail direct demand models with competition between ticket types using contributions from economic theory and market research," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 127-144.
  • Handle: RePEc:eee:transa:v:138:y:2020:i:c:p:127-144
    DOI: 10.1016/j.tra.2020.05.017
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    References listed on IDEAS

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    1. David G. Tarr, 1990. "A Modified Cournot Aggregation Condition for Obtaining Estimates of Cross-Elasticities of Demand," Eastern Economic Journal, Eastern Economic Association, vol. 16(3), pages 257-264, Jul-Sep.
    2. Sangho Choo & Taihyeong Lee & Patricia L. Mokhtarian, 2007. "Relationships Between US Consumer Expenditures on Communications and Transportation Using Almost Ideal Demand System Modeling: 1984--2002," Transportation Planning and Technology, Taylor & Francis Journals, vol. 30(5), pages 431-453, July.
    3. J. S. Dodgson, 1986. "Benefits of Changes in Urban Public Transport Subsidies in the Major Australian Cities," The Economic Record, The Economic Society of Australia, vol. 62(2), pages 224-235, June.
    4. Glaister, Stephen & Lewis, Davis, 1978. "An integrated fares policy for transport in London," Journal of Public Economics, Elsevier, vol. 9(3), pages 341-355, June.
    5. Wardman, Mark & Hatfield, Andrew & Shires, Jeremy & Ishtaiwi, Mahmoud, 2019. "The sensitivity of rail demand to variations in motoring costs: Findings from a comparison of methods," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 181-199.
    6. Wardman, Mark, 2006. "Demand for rail travel and the effects of external factors," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(3), pages 129-148, May.
    7. Whelan, Gerard & Batley, Richard & Shires, Jeremy & Wardman, Mark, 2008. "Optimal fares regulation for Britain's railways," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 807-819, September.
    8. Hetrakul, Pratt & Cirillo, Cinzia, 2014. "A latent class choice based model system for railway optimal pricing and seat allocation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 68-83.
    9. Gbadebo Oladosu, 2003. "An Almost Ideal Demand System Model of Household Vehicle Fuel Expenditure Allocation in the United States," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 1-21.
    10. repec:bla:ecorec:v:62:y:1986:i:177:p:224-35 is not listed on IDEAS
    11. Mark Wardman, 2014. "Price Elasticities of Surface Travel Demand A Meta-analysis of UK Evidence," Journal of Transport Economics and Policy, University of Bath, vol. 48(3), pages 367-384, September.
    12. van den Berg, Vincent & Kroes, Eric & Verhoef, Erik T., 2008. "Choice of season cards in public transport: a study of a Stated Preference experiment," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 40, pages 4-32.
    13. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    14. Selvanathan, E. A. & Selvanathan, Saroja, 1994. "The demand for transport and communication in the United Kingdom and Australia," Transportation Research Part B: Methodological, Elsevier, vol. 28(1), pages 1-9, February.
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    Cited by:

    1. Wardman, Mark, 2022. "Meta-analysis of price elasticities of travel demand in great britain: Update and extension," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 1-18.

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