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A Cross Sectional Study of Freight Transport Demand and Rail-Truck Competition in Canada


  • Tae Hoon Oum


This article derives a rail-truck freight demand model that is consistent with the economic theory of modal choice in the price-speed-reliability space. The translog model is estimated from the cross sectional data of Canadian interregional freight flows for the eight selected commodities. Major empirical findings are: (i) The quality attributes of service significantly influence modal choice only for the relatively high-value commodities. (ii) Both the price and quality elasticities of demand and the elasticity of rail-truck substitution vary substantially from route to route as well as from commodity to commodity. This implies that CES models including Cobb-Douglas form should not be used for freight demand studies. (iii) For the relatively high-value commodities, short-haul traffic is largely dominated by the truck mode, and significant rail-truck competition exists only in the medium and long-haul markets. (iv) For the relatively low-value commodities, effective rail-truck competition exists only in the short-haul markets. Hence, the medium and long-haul markets are largely rail-dominated.

Suggested Citation

  • Tae Hoon Oum, 1979. "A Cross Sectional Study of Freight Transport Demand and Rail-Truck Competition in Canada," Bell Journal of Economics, The RAND Corporation, vol. 10(2), pages 463-482, Autumn.
  • Handle: RePEc:rje:bellje:v:10:y:1979:i:autumn:p:463-482

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    Cited by:

    1. Gorman, Michael F. & Conway, Daniel G., 2004. "Logistics Costs Based Estimation of Freight Transportation Demand," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 44(1).
    2. Larson, Richard C., 2017. "Cross-sectional surveys: Inferring total eventual time in current state using only elapsed time-to-date," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 1-13.
    3. Casavant, Ken & Jessup, Eric, 2005. "What Makes them Viable? Determining the Attributes that Offer Potential Viability to Inter-Modal Truck-Rail Facilities in Washington State," 46th Annual Transportation Research Forum, Washington, D.C., March 6-8, 2005 208221, Transportation Research Forum.
    4. Mishra, Sabyasachee & Iseki, Hiroyuki & Moeckel, Rolf, 2014. "Multi entity perspective freight demand modeling technique: Varying objectives and outcomes," Transport Policy, Elsevier, vol. 35(C), pages 176-185.
    5. Tae H. Oum & Waters, W.G. & Jong Say Yong, 1990. "A survey of recent estimates of price elasticities of demand for transport," Policy Research Working Paper Series 359, The World Bank.
    6. Babcock, Michael W. & Gayle, Philip G., 2014. "Specifying and Estimating a Regional Agricultural Railroad Demand Model," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 53(1).
    7. Bühler, Georg & Hoffmann, Tim & Wölfing, Nikolas & Schmidt, Markus, 2009. "Wettbewerb und Umweltregulierung im Verkehr: Eine Analyse zur unterschiedlichen Einbindung der Verkehrsarten in den Emissionshandel," ZEW Expertises, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research, number 110505.
    8. Train, Kenneth & Wilson, Wesley W., 2007. "Spatially Generated Transportation Demands," Research in Transportation Economics, Elsevier, vol. 20(1), pages 97-118, January.

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