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A Markov regime-switching model of crude oil market integration

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  • 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
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    6. Stavros Stavroyiannis, 2022. "Cointegration and ARDL specification between the Dubai crude oil and the US natural gas market," Papers 2206.03278, arXiv.org.
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    8. 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).
    9. Harrison, Andre & Liu, Xiaochun & Stewart, Shamar L., 2023. "Structural sources of oil market volatility and correlation dynamics," Energy Economics, Elsevier, vol. 121(C).
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    16. 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.
    17. 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).
    18. Shi, Wenming & Gong, Yuting & Yin, Jingbo & Nguyen, Son & Liu, Qian, 2022. "Determinants of dynamic dependence between the crude oil and tanker freight markets: A mixed-frequency data sampling copula model," Energy, Elsevier, vol. 254(PB).
    19. 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).
    20. 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.
    21. 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).

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    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

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