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A Quantitative Model of the Oil Tanker Market in the Arabian Gulf

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  • Lutz Kilian
  • Nikos Nomikos
  • Xiaoqing Zhou

Abstract

Using a novel dataset, we develop a structural model of the Very Large Crude Carrier (VLCC) market between the Arabian Gulf and the Far East. We study how fluctuations in oil tanker rates, oil exports, shipowner profits, and bunker fuel prices are determined by shocks to the supply and demand for oil tankers, to the utilization of tankers, and to bunker fuel costs. Our analysis shows that time charter rates respond only slightly to fuel cost shocks. In response to higher fuel costs, voyage profits decline, as cost shocks are only partially passed on to round-trip voyage rates. Oil exports from the Arabian Gulf also decline, reflecting lower demand for VLCCs. Positive utilization shocks are associated with higher profits, a slight increase in time charter rates and slightly lower fuel prices and oil export volumes. Tanker supply and tanker demand shocks have persistent effects on time charter rates, round-trip voyage rates, the volume of oil exports, fuel prices, and profits with the expected sign.

Suggested Citation

  • Lutz Kilian & Nikos Nomikos & Xiaoqing Zhou, 2020. "A Quantitative Model of the Oil Tanker Market in the Arabian Gulf," Working Papers 2015, Federal Reserve Bank of Dallas.
    • Handle: RePEc:fip:feddwp:88042
    DOI: 10.24149/wp2015
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    References listed on IDEAS

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    1. Robin Greenwood & Samuel G. Hanson, 2015. "Waves in Ship Prices and Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(1), pages 55-109.
    2. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    3. Tamvakis, Michael N. & Thanopoulou, Helen A., 2000. "Does quality pay? The case of the dry bulk market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 36(4), pages 297-307, December.
    4. Moutzouris, Ioannis C. & Nomikos, Nikos K., 2020. "Asset pricing with mean reversion: The case of ships," Journal of Banking & Finance, Elsevier, vol. 111(C).
    5. Inoue, Atsushi & Kilian, Lutz, 2022. "Joint Bayesian inference about impulse responses in VAR models," Journal of Econometrics, Elsevier, vol. 231(2), pages 457-476.
    6. Behrens, Kristian & Picard, Pierre M., 2011. "Transportation, freight rates, and economic geography," Journal of International Economics, Elsevier, vol. 85(2), pages 280-291.
    7. Myrto Kalouptsidi, 2014. "Time to Build and Fluctuations in Bulk Shipping," American Economic Review, American Economic Association, vol. 104(2), pages 564-608, February.
    8. Kilian, Lutz & Zhou, Xiaoqing, 2018. "Modeling fluctuations in the global demand for commodities," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 54-78.
    9. Regli, Frederik & Adland, Roar, 2019. "Crude oil contango arbitrage and the floating storage decision," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 100-118.
    10. Jonas E. Arias & Juan F. Rubio‐Ramírez & Daniel F. Waggoner, 2018. "Inference Based on Structural Vector Autoregressions Identified With Sign and Zero Restrictions: Theory and Applications," Econometrica, Econometric Society, vol. 86(2), pages 685-720, March.
    11. Kilian,Lutz & Lütkepohl,Helmut, 2018. "Structural Vector Autoregressive Analysis," Cambridge Books, Cambridge University Press, number 9781107196575, October.
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    Cited by:

    1. David S. Jacks & Martin Stuermer, 2021. "Dry bulk shipping and the evolution of maritime transport costs, 1850–2020," Australian Economic History Review, Economic History Society of Australia and New Zealand, vol. 61(2), pages 204-227, July.

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    More about this item

    Keywords

    Shipping; VLCC; crude oil; bunker fuel; tanker; voyage; time charter; profits; exports; pass-through entities;
    All these keywords.

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • 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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