IDEAS home Printed from https://ideas.repec.org/a/taf/marpmg/v36y2009i6p507-523.html
   My bibliography  Save this article

An econometric analysis for container shipping market

Author

Listed:
  • Meifeng Luo
  • Lixian Fan
  • Liming Liu

Abstract

This article presents an econometric analysis for the fluctuation of the container freight rate due to the interactions between the demand for container transportation services and the container fleet capacity. The demand is derived from international trade and is assumed to be exogenous, while the fleet capacity increases with new orders made two years before, proportional to the industrial profit. Assuming the market clears each year, the shipping freight rate will change with the relative magnitude of shifts in the demand and fleet capacity. This model is estimated using the world container shipping market statistics from 1980 to 2008, applying the three-stage least square method. The estimated parameters of the model have high statistical significance, and the overall explanatory power of the model is above 90%. The short-term in-sample prediction of the model can largely replicate the container shipping market fluctuation in terms of the fleet size dynamics and the freight rate fluctuation in the past 20 years. The prediction of the future market trend reveals that the container freight rate should continue to decrease in the coming three years if the demand for container transportation services grows at less than 8%.

Suggested Citation

  • Meifeng Luo & Lixian Fan & Liming Liu, 2009. "An econometric analysis for container shipping market," Maritime Policy & Management, Taylor & Francis Journals, vol. 36(6), pages 507-523, December.
    • Handle: RePEc:taf:marpmg:v:36:y:2009:i:6:p:507-523
    DOI: 10.1080/03088830903346061
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03088830903346061
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03088830903346061?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Takuma Matsuda & Suguru Otani, 2022. "Unified Container Shipping Industry Data From 1966: Freight Rate, Shipping Quantity, Newbuilding, Secondhand, and Scrap Price," Papers 2211.16292, arXiv.org, revised Apr 2023.
    2. Nektarios A. Michail & Konstantinos D. Melas, 2021. "Sentiment-Augmented Supply and Demand Equations for the Dry Bulk Shipping Market," Economies, MDPI, vol. 9(4), pages 1-14, November.
    3. Ziaul Haque Munim & Hans-Joachim Schramm, 0. "Forecasting container freight rates for major trade routes: a comparison of artificial neural networks and conventional models," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 0, pages 1-18.
    4. Xingong Ding & Yong-Jae Choi, 2023. "Macroeconomic Effects of Maritime Transport Costs Shocks: Evidence from the South Korean Economy," Mathematics, MDPI, vol. 11(17), pages 1-26, August.
    5. Meifeng Luo & Sung-Ho Shin & Young-Tae Chang, 2017. "Duration analysis for recurrent ship accidents," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(5), pages 603-622, July.
    6. Saeed, Naima & Nguyen, Su & Cullinane, Kevin & Gekara, Victor & Chhetri, Prem, 2023. "Forecasting container freight rates using the Prophet forecasting method," Transport Policy, Elsevier, vol. 133(C), pages 86-107.
    7. Ziaul Haque Munim & Hans-Joachim Schramm, 2017. "Forecasting container shipping freight rates for the Far East – Northern Europe trade lane," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(1), pages 106-125, March.
    8. Lixian Fan & Meifeng Luo, 2013. "Analyzing ship investment behaviour in liner shipping," Maritime Policy & Management, Taylor & Francis Journals, vol. 40(6), pages 511-533, November.
    9. Panayides, Photis M. & Wiedmer, Robert, 2011. "Strategic alliances in container liner shipping," Research in Transportation Economics, Elsevier, vol. 32(1), pages 25-38.
    10. Coto-Millán, Pablo & Inglada-Pérez, Lucía & Casares, Pedro & Inglada López De Sabando, Vicente, 2018. "Modelización del transporte marítimo de contenedores/Modeling of Containerized Maritime Transport," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 36, pages 675-690, Septiembr.
    11. Chen, Gang & Rytter, Niels G.M. & Jiang, Liping & Nielsen, Peter & Jensen, Lars, 2017. "Pre-announcements of price increase intentions in liner shipping spot markets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 109-125.
    12. Changmin Jiang & Yulai Wan & Anming Zhang, 2017. "Internalization of port congestion: strategic effect behind shipping line delays and implications for terminal charges and investment," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(1), pages 112-130, January.
    13. Peter Nielsen & Liping Jiang & Niels Gorm Malý Rytter & Gang Chen, 2014. "An investigation of forecast horizon and observation fit's influence on an econometric rate forecast model in the liner shipping industry," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(7), pages 667-682, December.
    14. Alexander M. Goulielmos, 2017. "“Containership Markets”: A Comparison with Bulk Shipping and a Proposed Oligopoly Model," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 67(2), pages 47-68, April-Jun.
    15. Sinem Celik Girgin & Thanasis Karlis & Hong-Oanh Nguyen, 2018. "A Critical Review of the Literature on Firm-Level Theories on Ship Investment," IJFS, MDPI, vol. 6(1), pages 1-19, January.
    16. Ziaul Haque Munim & Hans-Joachim Schramm, 2021. "Forecasting container freight rates for major trade routes: a comparison of artificial neural networks and conventional models," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 310-327, June.
    17. Ying Kou & Meifeng Luo, 2016. "Strategic capacity competition and overcapacity in shipping," Maritime Policy & Management, Taylor & Francis Journals, vol. 43(4), pages 389-406, May.
    18. Zhou, Yusheng & Li, Xue & Yuen, Kum Fai, 2022. "Holistic risk assessment of container shipping service based on Bayesian Network Modelling," Reliability Engineering and System Safety, Elsevier, vol. 220(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:marpmg:v:36:y:2009:i:6:p:507-523. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TMPM20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.