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Estimating demand variables of maritime container transport: An aggregate procedure for the Mediterranean area

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  • Russo, Francesco
  • Musolino, Giuseppe

Abstract

Demand variables of maritime container transport (throughput, transhipment and origin–destination flows) may be estimated with freight demand models. As their parameters generally vary both in time and space, models may not be transferable to geographical areas and time periods differing from that for which they are calibrated.

Suggested Citation

  • Russo, Francesco & Musolino, Giuseppe, 2013. "Estimating demand variables of maritime container transport: An aggregate procedure for the Mediterranean area," Research in Transportation Economics, Elsevier, vol. 42(1), pages 38-49.
    • Handle: RePEc:eee:retrec:v:42:y:2013:i:1:p:38-49
    DOI: 10.1016/j.retrec.2012.11.008
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    References listed on IDEAS

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    1. Francesca Medda & Gianni Carbonaro, 2007. "Growth of Container Seaborne Traffic in the Mediterranean Basin: Outlook and Policy Implications for Port Development," Transport Reviews, Taylor & Francis Journals, vol. 27(5), pages 573-587, January.
    2. Cascetta, Ennio & Nguyen, Sang, 1988. "A unified framework for estimating or updating origin/destination matrices from traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 22(6), pages 437-455, December.
    3. Nijkamp, Peter, 1975. "Reflections on gravity and entropy models," Regional Science and Urban Economics, Elsevier, vol. 5(2), pages 203-225, May.
    4. 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.
    5. Pablo Coto-Millán & José Baños-Pino & Rubén Sainz-González & Miguel Ángel Pesquera-González & Ramón Núñez-Sánchez & Ingrid Mateo-Mantecón & Pedro Casares Hontañón, 2011. "Determinants of demand for international maritime transport: An application to Spain," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 13(3), pages 237-249, September.
    6. Abdelwahab, Walid M., 1998. "Elasticities of mode choice probabilities and market elasticities of demand: Evidence from a simultaneous mode choice/shipment-size freight transport model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 34(4), pages 257-266, December.
    7. Garrido, Rodrigo A. & Mahmassani, Hani S., 2000. "Forecasting freight transportation demand with the space-time multinomial probit model," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 403-418, June.
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    Cited by:

    1. Yadong Wang & Qiang Meng, 2019. "Integrated method for forecasting container slot booking in intercontinental liner shipping service," Flexible Services and Manufacturing Journal, Springer, vol. 31(3), pages 653-674, September.
    2. Özer, Mustafa & Canbay, Şerif & Kırca, Mustafa, 2021. "The impact of container transport on economic growth in Turkey: An ARDL bounds testing approach," Research in Transportation Economics, Elsevier, vol. 88(C).
    3. Mhd Ruslan, Siti Marsila & Mokhtar, Kasypi, 2020. "An Analysis of Price Disparity: Peninsular Malaysia and Sabah," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 54(2), pages 53-66.

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    More about this item

    Keywords

    Containerized maritime freight transport; Throughput; Transhipment; Origin–destination container flows; Forecasting methods; Mediterranean area;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning

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