IDEAS home Printed from https://ideas.repec.org/a/eee/ecanpo/v72y2021icp492-505.html
   My bibliography  Save this article

Brent–Dubai oil spread: Basic drivers

Author

Listed:
  • Yuksel Haliloglu, Ebru
  • Sahin, Serkan
  • Berument, M. Hakan

Abstract

This study aims to assess and quantify the effects of potential economic drivers on the Brent–Dubai price spread using the time-dependent Kalman filtering technique. To understand the pricing mechanism of crude oils, it is necessary to distinguish the driving forces of the world oil market. The Brent–Dubai price spread is selected as a global indicator representing trends in world oil trade and global economic activities. The estimates suggest that the global economic activities represented by the world trade index, world oil demand, world steel production, the number of world airline passengers and regional dynamics proxied by the growth rate of China over the US and the Euro Area have explanatory power on the Brent–Dubai spread.

Suggested Citation

  • Yuksel Haliloglu, Ebru & Sahin, Serkan & Berument, M. Hakan, 2021. "Brent–Dubai oil spread: Basic drivers," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 492-505.
  • Handle: RePEc:eee:ecanpo:v:72:y:2021:i:c:p:492-505
    DOI: 10.1016/j.eap.2021.09.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0313592621001326
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eap.2021.09.014?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.

    References listed on IDEAS

    as
    1. Nikolaos Milonas & Thomas Henker, 2001. "Price spread and convenience yield behaviour in the international oil market," Applied Financial Economics, Taylor & Francis Journals, vol. 11(1), pages 23-36.
    2. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2010. "Analyzing and forecasting volatility spillovers, asymmetries and hedging in major oil markets," Energy Economics, Elsevier, vol. 32(6), pages 1445-1455, November.
    3. Shawkat M. Hammoudeh & Bradley T. Ewing & Mark A. Thompson, 2008. "Threshold Cointegration Analysis of Crude Oil Benchmarks," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 79-96.
    4. Fattouh, Bassam, 2010. "The dynamics of crude oil price differentials," Energy Economics, Elsevier, vol. 32(2), pages 334-342, March.
    5. Xiaoyong Xiao & Jing Huang, 2018. "Dynamic Connectedness of International Crude Oil Prices: The Diebold–Yilmaz Approach," Sustainability, MDPI, vol. 10(9), pages 1-16, September.
    6. Lu, Feng-bin & Hong, Yong-miao & Wang, Shou-yang & Lai, Kin-keung & Liu, John, 2014. "Time-varying Granger causality tests for applications in global crude oil markets," Energy Economics, Elsevier, vol. 42(C), pages 289-298.
    7. Harvey,Andrew C., 1991. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521405737, October.
    8. Liu, Siyao & Fang, Wei & Gao, Xiangyun & An, Feng & Jiang, Meihui & Li, Yang, 2019. "Long-term memory dynamics of crude oil price spread in non-dollar countries under the influence of exchange rates," Energy, Elsevier, vol. 182(C), pages 753-764.
    9. Bekiros, Stelios D. & Diks, Cees G.H., 2008. "The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality," Energy Economics, Elsevier, vol. 30(5), pages 2673-2685, September.
    10. Kentaka Aruga, 2015. "Testing the International Crude Oil Market Integration with Structural Breaks," Economics Bulletin, AccessEcon, vol. 35(1), pages 641-649.
    11. Li, Sufang & Zhang, Hu & Yuan, Di, 2019. "Investor attention and crude oil prices: Evidence from nonlinear Granger causality tests," Energy Economics, Elsevier, vol. 84(C).
    12. Zhang, Bing, 2013. "Are the crude oil markets becoming more efficient over time? New evidence from a generalized spectral test," Energy Economics, Elsevier, vol. 40(C), pages 875-881.
    13. Kuck, Konstantin & Schweikert, Karsten, 2017. "A Markov regime-switching model of crude oil market integration," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 16-31.
    14. Kaufmann, Robert K. & Ullman, Ben, 2009. "Oil prices, speculation, and fundamentals: Interpreting causal relations among spot and futures prices," Energy Economics, Elsevier, vol. 31(4), pages 550-558, July.
    15. Bradley Ewing & Cynthia Lay Harter, 2000. "Co-movements of Alaska North Slope and UK Brent crude oil prices," Applied Economics Letters, Taylor & Francis Journals, vol. 7(8), pages 553-558.
    16. Neil A. Wilmot, 2013. "Cointegration in the Oil Market among Regional Blends," International Journal of Energy Economics and Policy, Econjournals, vol. 3(4), pages 424-433.
    17. S. Gurcan Gulen, 1997. "Regionalization in the World Crude Oil Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 109-126.
    18. M. A. Adelman, 1984. "International Oil Agreements," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-10.
    19. Zhang, Dayong & Ji, Qiang & Kutan, Ali M., 2019. "Dynamic transmission mechanisms in global crude oil prices: Estimation and implications," Energy, Elsevier, vol. 175(C), pages 1181-1193.
    20. Param Silvapulle & Imad A. Moosa, 1999. "The relationship between spot and futures prices: Evidence from the crude oil market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(2), pages 175-193, April.
    21. Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "Oil prices and global factor macroeconomic variables," Energy Economics, Elsevier, vol. 59(C), pages 198-212.
    22. Jia, Xiaoliang & An, Haizhong & Fang, Wei & Sun, Xiaoqi & Huang, Xuan, 2015. "How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective," Energy Economics, Elsevier, vol. 49(C), pages 588-598.
    23. Weiner, R.J., 1991. "Is the World Oil Market "One Great Pool?"," Papers 9120, Laval - Recherche en Energie.
    24. Robert J. Weiner, 1991. "Is the World Oil Market "One Great Pool"?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 95-108.
    25. S. Gurcan Gulen, 1999. "Regionalization in the World Crude Oil Market: Further Evidence," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 125-139.
    26. Malin Song & Kuangnan Fang & Jing Zhang & Jianbin Wu, 2019. "The Co-movement Between Chinese Oil Market and Other Main International Oil Markets: A DCC-MGARCH Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1303-1318, December.
    27. Kaufmann, Robert K. & Banerjee, Shayan, 2014. "A unified world oil market: Regions in physical, economic, geographic, and political space," Energy Policy, Elsevier, vol. 74(C), pages 235-242.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Cui, Jinxin & Maghyereh, Aktham, 2023. "Time-frequency dependence and connectedness among global oil markets: Fresh evidence from higher-order moment perspective," Journal of Commodity Markets, Elsevier, vol. 30(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Duan, Kun & Ren, Xiaohang & Wen, Fenghua & Chen, Jinyu, 2023. "Evolution of the information transmission between Chinese and international oil markets: A quantile-based framework," Journal of Commodity Markets, Elsevier, vol. 29(C).
    2. Neil A. Wilmot, 2013. "Cointegration in the Oil Market among Regional Blends," International Journal of Energy Economics and Policy, Econjournals, vol. 3(4), pages 424-433.
    3. Niyati Bhanja & Samia Nasreen & Arif Billah Dar & Aviral Kumar Tiwari, 2022. "Connectedness in International Crude Oil Markets," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 227-262, January.
    4. Jiasha Fu & Hui Qiao, 2022. "The Time-Varying Connectedness Between China’s Crude Oil Futures and International Oil Markets: A Return and Volatility Spillover Analysis," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 341-376, December.
    5. Atanu Ghoshray and Tatiana Trifonova, 2014. "Dynamic Adjustment of Crude Oil Price Spreads," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    6. Cui, Jinxin & Maghyereh, Aktham, 2023. "Time-frequency dependence and connectedness among global oil markets: Fresh evidence from higher-order moment perspective," Journal of Commodity Markets, Elsevier, vol. 30(C).
    7. Galay, Gregory, 2019. "Are crude oil markets cointegrated? Testing the co-movement of weekly crude oil spot prices," Journal of Commodity Markets, Elsevier, vol. 16(C).
    8. Kuck, Konstantin & Schweikert, Karsten, 2017. "A Markov regime-switching model of crude oil market integration," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 16-31.
    9. Zhang, Qi & Di, Peng & Farnoosh, Arash, 2021. "Study on the impacts of Shanghai crude oil futures on global oil market and oil industry based on VECM and DAG models," Energy, Elsevier, vol. 223(C).
    10. Kaufmann, Robert K. & Banerjee, Shayan, 2014. "A unified world oil market: Regions in physical, economic, geographic, and political space," Energy Policy, Elsevier, vol. 74(C), pages 235-242.
    11. Lee, Chien-Chiang & Zhou, Hegang & Xu, Chao & Zhang, Xiaoming, 2023. "Dynamic spillover effects among international crude oil markets from the time-frequency perspective," Resources Policy, Elsevier, vol. 80(C).
    12. Ji, Qiang & Fan, Ying, 2016. "Evolution of the world crude oil market integration: A graph theory analysis," Energy Economics, Elsevier, vol. 53(C), pages 90-100.
    13. An, Sufang & Gao, Xiangyun & An, Haizhong & An, Feng & Sun, Qingru & Liu, Siyao, 2020. "Windowed volatility spillover effects among crude oil prices," Energy, Elsevier, vol. 200(C).
    14. Zhang, Dayong & Ji, Qiang & Kutan, Ali M., 2019. "Dynamic transmission mechanisms in global crude oil prices: Estimation and implications," Energy, Elsevier, vol. 175(C), pages 1181-1193.
    15. Niyati Bhanja & Arif Billah Dar & Aviral Kumar Tiwari, 2018. "Do Global Crude Oil Markets Behave as One Great Pool? A Cyclical Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 219-241, November.
    16. Bertrand Candelon & Marc Joëts & Sessi Tokpavi, 2012. "Testing for crude oil markets globalization during extreme price movements," Post-Print hal-01411687, HAL.
    17. Kaufmann, Robert K. & Dees, Stephane & Mann, Micheal, 2009. "Horizontal and vertical transmissions in the US oil supply chain," Energy Policy, Elsevier, vol. 37(2), pages 644-650, February.
    18. Caporin, Massimiliano & Fontini, Fulvio & Talebbeydokhti, Elham, 2019. "Testing persistence of WTI and Brent long-run relationship after the shale oil supply shock," Energy Economics, Elsevier, vol. 79(C), pages 21-31.
    19. Ayman Omar, 2015. "West Texas Intermediate and Brent Spread during Organization of the Petroleum Exporting Countries Supply Disruptions," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 693-703.
    20. Reboredo, Juan C., 2011. "How do crude oil prices co-move?: A copula approach," Energy Economics, Elsevier, vol. 33(5), pages 948-955, September.

    More about this item

    Keywords

    Brent–Dubai oil spread; Growth of China; Kalman filter; Oil demand; Trade index;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    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:eee:ecanpo:v:72:y:2021:i:c:p:492-505. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/economic-analysis-and-policy .

    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.