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A directional relationship between freight and newbuilding markets: A panel analysis

Author

Listed:
  • Jane Jing Xu

    (Cardiff Business School, Cardiff University, Cardiff, United Kingdom)

  • Tsz Leung Yip

    (Faculty of Business, Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Hong Kong)

  • Liming Liu

    (Faculty of Business, Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Hong Kong)

Abstract

This article examines the dynamic relationship between international sea freight rate and newbuilding price by employing panel cointegration testing and estimating techniques. The primary question this article addresses is whether the goods (new ships) price and service (sea freight) rate lead or lag one another in a Granger-cause sense, or simultaneously move together. Monthly panel data on three different bulk shipping market segments over the period 1998–2009 are exploited in empirical analysis. Various panel unit root tests demonstrate that the data variables are integrated with unit roots, whereas panel cointegration techniques are used to estimate the dynamic relationship. A positive directional relationship from freight rate to newbuilding price is found, and freight rate is more sensitive to market changes than newbuilding price. These results indicate that investment in new ships is encouraged by a strong freight market.

Suggested Citation

  • Jane Jing Xu & Tsz Leung Yip & Liming Liu, 2011. "A directional relationship between freight and newbuilding markets: A panel analysis," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 13(1), pages 44-60, March.
    • Handle: RePEc:pal:marecl:v:13:y:2011:i:1:p:44-60
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    Citations

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    Cited by:

    1. Ying Kou & Liming Liu & Meifeng Luo, 2014. "Lead-lag relationship between new-building and second-hand ship prices," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(4), pages 303-327, July.
    2. Theodore Syriopoulos & Michael Tsatsaronis & Ioannis Karamanos, 2021. "Support Vector Machine Algorithms: An Application to Ship Price Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 55-87, January.
    3. Tuo Shi & Yuanman Hu & Miao Liu & Chunlin Li & Chuyi Zhang & Chong Liu, 2020. "How Do Economic Growth, Urbanization, and Industrialization Affect Fine Particulate Matter Concentrations? An Assessment in Liaoning Province, China," IJERPH, MDPI, vol. 17(15), pages 1-14, July.
    4. Payman Eslami & Kihyo Jung & Daewon Lee & Amir Tjolleng, 2017. "Predicting tanker freight rates using parsimonious variables and a hybrid artificial neural network with an adaptive genetic algorithm," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 538-550, August.
    5. Heij, C. & Knapp, S., 2012. "Dynamics in the dry bulk market," Econometric Institute Research Papers EI 2012-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Joan Mileski & Christopher Clott & Cassia Bomer Galvao & Taliese Laverne, 2020. "Technical analysis: the psychology of the market of dry bulk freight rates," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-15, December.
    7. Skantzouri, Efthymia Nefeli & Sambracos, Evangelos, 2018. "Freight Rate Volatility and Vessels Size in Tankers’ Sector," MPRA Paper 97896, University Library of Munich, Germany, revised 25 Nov 2019.

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