IDEAS home Printed from https://ideas.repec.org/a/eee/jocoma/v6y2017icp16-31.html
   My bibliography  Save this article

A Markov regime-switching model of crude oil market integration

Author

Listed:
  • Kuck, Konstantin
  • Schweikert, Karsten

Abstract

This paper revisits the globalization-regionalization hypothesis for the world crude oil market. We examine long-run equilibrium relationships between major crude oil prices–WTI, Brent, Bonny Light, Dubai and Tapis–and focus on the adjustment behaviour following disequilibrium states. We account for a changing adjustment behaviour over time by using a Markov-switching vector error correction model. Our overall findings suggest that the crude oil market is globalized. Dubai turned out to be the only weakly exogenous price in all regimes, indicating its important role as a benchmark price. Furthermore, an interesting finding of our study is that the degree of market integration seems to be connected to global economic uncertainty.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:jocoma:v:6:y:2017:i:c:p:16-31
    DOI: 10.1016/j.jcomm.2017.03.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2405851316301155
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jcomm.2017.03.001?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. Zhang, Yue-Jun & Zhang, Lu, 2015. "Interpreting the crude oil price movements: Evidence from the Markov regime switching model," Applied Energy, Elsevier, vol. 143(C), pages 96-109.
    2. Höök, Mikael & Hirsch, Robert & Aleklett, Kjell, 2009. "Giant oil field decline rates and their influence on world oil production," Energy Policy, Elsevier, vol. 37(6), pages 2262-2272, June.
    3. Szymon Wlazlowski & Bjorn Hagstromer & Monica Giulietti, 2011. "Causality in crude oil prices," Applied Economics, Taylor & Francis Journals, vol. 43(24), pages 3337-3347.
    4. 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.
    5. Junsoo Lee & Mark C. Strazicich, 2003. "Minimum Lagrange Multiplier Unit Root Test with Two Structural Breaks," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1082-1089, November.
    6. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    7. 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.
    8. Reboredo, Juan C., 2011. "How do crude oil prices co-move?: A copula approach," Energy Economics, Elsevier, vol. 33(5), pages 948-955, September.
    9. Bahattin Buyuksahin & Jeffrey H. Harris, 2011. "Do Speculators Drive Crude Oil Futures Prices?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 167-202.
    10. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    11. Jan Bentzen, 2007. "Does OPEC influence crude oil prices? Testing for co-movements and causality between regional crude oil prices," Applied Economics, Taylor & Francis Journals, vol. 39(11), pages 1375-1385.
    12. Zacharias Psaradakis & Nicola Spagnolo, 2006. "Joint Determination of the State Dimension and Autoregressive Order for Models with Markov Regime Switching," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(5), pages 753-766, September.
    13. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    14. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    15. 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.
    16. Candelon, Bertrand & Joëts, Marc & Tokpavi, Sessi, 2013. "Testing for Granger causality in distribution tails: An application to oil markets integration," Economic Modelling, Elsevier, vol. 31(C), pages 276-285.
    17. Fattouh, Bassam, 2010. "The dynamics of crude oil price differentials," Energy Economics, Elsevier, vol. 32(2), pages 334-342, March.
    18. Osterwald-Lenum, Michael, 1992. "A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 461-472, August.
    19. M. A. Adelman, 1984. "International Oil Agreements," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-10.
    20. Liu, Li & Chen, Ching-Cheng & Wan, Jieqiu, 2013. "Is world oil market “one great pool”?: An example from China's and international oil markets," Economic Modelling, Elsevier, vol. 35(C), pages 364-373.
    21. Weiner, R.J., 1991. "Is the World Oil Market "One Great Pool?"," Papers 9120, Laval - Recherche en Energie.
    22. 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.
    23. Mann, Janelle & Sephton, Peter, 2016. "Global relationships across crude oil benchmarks," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 1-5.
    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. Gregory Galay & Henry Thille, 2021. "Pipeline capacity and the dynamics of Alberta crude oil price spreads," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(3), pages 1072-1102, November.
    2. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Wang, Jianqiong, 2020. "Examining the predictive information of CBOE OVX on China’s oil futures volatility: Evidence from MS-MIDAS models," Energy, Elsevier, vol. 212(C).
    3. Zhu, Bo & Liu, Jiahao & Lin, Renda & Chevallier, Julien, 2021. "Cross-border systemic risk spillovers in the global oil system: Does the oil trade pattern matter?," Energy Economics, Elsevier, vol. 101(C).
    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. Stavros Stavroyiannis, 2022. "Cointegration and ARDL specification between the Dubai crude oil and the US natural gas market," Papers 2206.03278, arXiv.org.
    6. Chen, Wang & Lu, Xinjie & Wang, Jiqian, 2022. "Modeling and managing stock market volatility using MRS-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 625-635.
    7. Nunes, Inês Carrilho & Catalão-Lopes, Margarida, 2020. "The impact of oil shocks on innovation for alternative sources of energy: Is there an asymmetric response when oil prices go up or down?," Journal of Commodity Markets, Elsevier, vol. 19(C).
    8. Sun, Chuanwang & Ding, Dan & Fang, Xingming & Zhang, Huiming & Li, Jianglong, 2019. "How do fossil energy prices affect the stock prices of new energy companies? Evidence from Divisia energy price index in China's market," Energy, Elsevier, vol. 169(C), pages 637-645.
    9. Catalin Dragomirescu-Gaina & Dionisis Philippas & Stéphane Goutte, 2022. "How to 'Trump' the energy market: evidence from the WTI-Brent spread," Working Papers halshs-03843257, HAL.
    10. Wood, Dallas & Larson, Justin & Jones, Jason & Galperin, Diana & Shelby, Michael & Gonzalez, Manuel, 2022. "World oil price impacts on country-specific fuel markets: Evidence of a muted global rebound effect," Energy Economics, Elsevier, vol. 111(C).
    11. Georgios Bampinas & Theodore Panagiotidis & Georgios Papapanagiotou, 2022. "Oil shocks and investor attention," Working Paper series 22-13, Rimini Centre for Economic Analysis.
    12. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
    13. 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.
    14. Zhu, Bo & Lin, Renda & Liu, Jiahao, 2020. "Magnitude and persistence of extreme risk spillovers in the global energy market: A high-dimensional left-tail interdependence perspective," Energy Economics, Elsevier, vol. 89(C).
    15. 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).
    16. Xinjie Lu & Feng Ma & Jiqian Wang & Jing Liu, 2022. "Forecasting oil futures realized range‐based volatility with jumps, leverage effect, and regime switching: New evidence from MIDAS models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 853-868, July.

    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. 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.
    2. 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.
    3. 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).
    4. Jia, Xiaoliang & An, Haizhong & Sun, Xiaoqi & Huang, Xuan & Wang, Lijun, 2017. "Evolution of world crude oil market integration and diversification: A wavelet-based complex network perspective," Applied Energy, Elsevier, vol. 185(P2), pages 1788-1798.
    5. 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.
    6. 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.
    7. Samih Antoine Azar & Angelic Salha, 2017. "The Bias in the Long Run Relation between the Prices of BRENT and West Texas Intermediate Crude Oils," International Journal of Energy Economics and Policy, Econjournals, vol. 7(1), pages 44-54.
    8. 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.
    9. Giulietti, Monica & Iregui, Ana María & Otero, Jesús, 2014. "Crude oil price differentials, product heterogeneity and institutional arrangements," Energy Economics, Elsevier, vol. 46(S1), pages 28-32.
    10. 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).
    11. Stavros Stavroyiannis, 2022. "Cointegration and ARDL specification between the Dubai crude oil and the US natural gas market," Papers 2206.03278, arXiv.org.
    12. 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.
    13. Liu, Li & Chen, Ching-Cheng & Wan, Jieqiu, 2013. "Is world oil market “one great pool”?: An example from China's and international oil markets," Economic Modelling, Elsevier, vol. 35(C), pages 364-373.
    14. 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.
    15. 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.
    16. Gregory Galay & Henry Thille, 2021. "Pipeline capacity and the dynamics of Alberta crude oil price spreads," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(3), pages 1072-1102, November.
    17. 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.
    18. 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.
    19. Bravo Caro, José Manuel & Golpe, Antonio A. & Iglesias, Jesús & Vides, José Carlos, 2020. "A new way of measuring the WTI – Brent spread. Globalization, shock persistence and common trends," Energy Economics, Elsevier, vol. 85(C).
    20. Yue-Hua Dai & Wen-Jie Xie & Zhi-Qiang Jiang & George J. Jiang & Wei-Xing Zhou, 2016. "Correlation structure and principal components in the global crude oil market," Empirical Economics, Springer, vol. 51(4), pages 1501-1519, December.

    More about this item

    Keywords

    Crude oil; Market integration; Cointegration; Markov-switching vector error correction model;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

    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:jocoma:v:6:y:2017:i:c:p:16-31. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.elsevier.com/locate/jcomm .

    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.elsevier.com/locate/jcomm .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.