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A Matching Model for the Backhaul Problem

Author

Listed:
  • Erhan Demirel

    (Vrije Universiteit Amsterdam)

  • Jos van Ommeren

    (Vrije Universiteit Amsterdam)

  • Piet Rietveld

    (Vrije Universiteit Amsterdam)

Abstract

The ‘backhaul problem’ is characterized by an imbalance in transport flows between locations. This problem is usually studied in a perfectly competitive framework, which essentially predicts that when the imbalance is sufficiently large, the freight price of transport from low demand regions to high demand regions, the so-called backhaul price, drops to zero. This result is inconsistent with empirical observations. In this paper, we develop a matching model to address this inconsistency. We argue that market friction, through search imperfections due to lack of information by carriers on the (future) demand for transport by customers, may play an important role in the determination of backhaul prices. We demonstrate that carriers are at least compensated for the time they search for customers, so the backhaul price is in general positive. The matching model is numerically applied to the inland navigation shipping market in the Rhine river area in Western-Europe. We also analyse the effects of increases in transport costs on transport flows and backhaul prices, e.g. due to climate changes.

Suggested Citation

  • Erhan Demirel & Jos van Ommeren & Piet Rietveld, 2007. "A Matching Model for the Backhaul Problem," Tinbergen Institute Discussion Papers 07-083/3, Tinbergen Institute, revised 19 Dec 2007.
  • Handle: RePEc:tin:wpaper:20070083
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    Cited by:

    1. Goh, Shao Hung & Chan, Yuxian, 2016. "Operational shadow pricing in back haul container shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 92(C), pages 3-15.
    2. Ishikawa, Jota & Tarui, Nori, 2018. "Backfiring with backhaul problems," Journal of International Economics, Elsevier, vol. 111(C), pages 81-98.
    3. Tsubota, Kenmei, 2015. "Agglomeration and directional imbalance of freight rates : the role of density economies in the transport sector," IDE Discussion Papers 488, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    4. ISHIKAWA, Jota & 石川, 城太 & TARUI, Nori & 樽井, 礼, 2015. "Backfiring with backhaul problems: Trade and Industrial Policies with Endogenous Transport Costs," Discussion paper series HIAS-E-12, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    5. Behrens, Kristian & Picard, Pierre M., 2011. "Transportation, freight rates, and economic geography," Journal of International Economics, Elsevier, vol. 85(2), pages 280-291.
    6. Felix L. Friedt & Wesley W. Wilson, 2020. "Trade, transport costs and trade imbalances: An empirical examination of international markets and backhauls," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 592-636, May.

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    More about this item

    Keywords

    Backhaul Problem; Imperfect Information; Matching Models;
    All these keywords.

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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