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Testing for Granger causality in distribution tails: An application to oil markets integration

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  • Candelon, Bertrand
  • Joëts, Marc
  • Tokpavi, Sessi

Abstract

This paper proposes an original procedure which allows for testing of Granger-causality for multiple risk levels across tail distributions, hence extending the procedure proposed by Hong et al. (2009). Asymptotic and finite sample properties of the test are considered. This new Granger-causality framework is applied for a set of regional oil markets series. It helps to tackle two main questions 1) Whether oil markets are more or less integrated during periods of extreme energetic prices movements and 2) Whether price-setter markets change during such periods. Our findings indicate that the integration level between crude oil markets tends to decrease during extreme periods and that price-setter markets also change. Such results have policy implication and stress the importance of an active energetic policy during episode of extreme movements.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ecmode:v:31:y:2013:i:c:p:276-285
    DOI: 10.1016/j.econmod.2012.11.049
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    Cited by:

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    2. Mobeen Ur Rehman, 2020. "Dynamic correlation pattern amongst alternative energy market for diversification opportunities," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-24, December.
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    4. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    5. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2017. "Can stock market investors hedge energy risk? Evidence from Asia," Energy Economics, Elsevier, vol. 66(C), pages 559-570.
    6. Soylu, Pınar Kaya & Güloğlu, Bülent, 2019. "Financial contagion and flight to quality between emerging markets and U.S. bond market," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    7. Storhas, Dominik P. & De Mello, Lurion & Singh, Abhay Kumar, 2020. "Multiscale lead-lag relationships in oil and refined product return dynamics: A symbolic wavelet transfer entropy approach," Energy Economics, Elsevier, vol. 92(C).
    8. Joëts, Marc, 2014. "Energy price transmissions during extreme movements," Economic Modelling, Elsevier, vol. 40(C), pages 392-399.
    9. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 240-253, April.
    10. Song, Yu & Chen, Bo & Hou, Na & Yang, Yi, 2022. "Terrorist attacks and oil prices: A time-varying causal relationship analysis," Energy, Elsevier, vol. 246(C).
    11. Xi, Yue & Zeng, Qing & Lu, Xinjie & Huynh, Toan L.D., 2022. "Oil and renewable energy stock markets: Unique role of extreme shocks," Energy Economics, Elsevier, vol. 109(C).
    12. 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.
    13. Marcin Faldzinski & Magdalena Osinska, 2016. "Volatility estimators in econometric analysis of risk transfer on capital markets," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 16, pages 21-35.
    14. Wang, Lu & Ma, Feng & Niu, Tianjiao & Liang, Chao, 2021. "The importance of extreme shock: Examining the effect of investor sentiment on the crude oil futures market," Energy Economics, Elsevier, vol. 99(C).
    15. Apostolakis, George N. & Floros, Christos & Gkillas, Konstantinos & Wohar, Mark, 2024. "Volatility spillovers across the spot and futures oil markets after news announcements," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    16. Wang, Lu & Ma, Feng & Niu, Tianjiao & He, Chengting, 2020. "Crude oil and BRICS stock markets under extreme shocks: New evidence," Economic Modelling, Elsevier, vol. 86(C), pages 54-68.
    17. 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.
    18. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 240-253, April.
    19. Mohamed Albaity & Hasan Mustafa, 2018. "International and Macroeconomic Determinants of Oil Price: Evidence from Gulf Cooperation Council Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 8(1), pages 69-81.
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    More about this item

    Keywords

    Extreme risk spillovers; Granger-causality in risk; Distribution tails; Value-at-Risk; Crude oil markets integration;
    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
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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