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Time-varying Granger causality tests for applications in global crude oil markets

  • Lu, Feng-bin
  • Hong, Yong-miao
  • Wang, Shou-yang
  • Lai, Kin-keung
  • Liu, John
Registered author(s):

    This paper proposes time-varying Granger causality tests based on the tests developed by Hong (2001) and two dynamic correlation estimators (i.e., rolling correlation and dynamic conditional correlation multivariate GARCH), here called the rolling Hong and DCC-MGARCH Hong tests, respectively. The proposed tests are used to examine time-varying information spillover among global crude oil markets. The results provide empirical evidence of time-varying information spillover. In particular, the instantaneous causal effects of Dubai and Tapis crudes on Brent and WTI become stronger when a major event or events occur in major oil-producing countries. Such events include the Iraq War in March 2003, OPEC's announcement of a record production cut in December 2008, and the Libyan civil war in early 2011. And consistent with previous studies, WTI and Brent play dominant roles in global crude markets. Impulse response analysis shows that market information has a positive influence on the spillover effect in global crude oil markets. Moreover, the DCC-MGARCH Hong test consistently leads the rolling Hong test, which indicates that the former performs better.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0140988314000048
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    Article provided by Elsevier in its journal Energy Economics.

    Volume (Year): 42 (2014)
    Issue (Month): C ()
    Pages: 289-298

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    Handle: RePEc:eee:eneeco:v:42:y:2014:i:c:p:289-298
    Contact details of provider: Web page: http://www.elsevier.com/locate/eneco

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    1. Cheung, Yin-Wong & Ng, Lilian K., 1996. "A causality-in-variance test and its application to financial market prices," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 33-48.
    2. Lin, Sharon Xiaowen & Tamvakis, Michael N., 2004. "Effects of NYMEX trading on IPE Brent Crude futures markets: a duration analysis," Energy Policy, Elsevier, vol. 32(1), pages 77-82, January.
    3. Hammoudeh, Shawkat & Li, Huimin, 2004. "The impact of the Asian crisis on the behavior of US and international petroleum prices," Energy Economics, Elsevier, vol. 26(1), pages 135-160, January.
    4. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-52, September.
    5. Dimitris K. Christopoulos & Miguel A. León-Ledesma, 2008. "Testing for Granger (non-)causality in a time-varying coefficient VAR model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 293-303.
    6. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    7. Chai, Jian & Guo, Ju-E. & Meng, Lei & Wang, Shou-Yang, 2011. "Exploring the core factors and its dynamic effects on oil price: An application on path analysis and BVAR-TVP model," Energy Policy, Elsevier, vol. 39(12), pages 8022-8036.
    8. Brunetti, Celso & Gilbert, Christopher L., 2000. "Bivariate FIGARCH and fractional cointegration," Journal of Empirical Finance, Elsevier, vol. 7(5), pages 509-530, December.
    9. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 821-852.
    10. Bekiros, S. & Diks, C.G.H., 2007. "The Relationship between Crude Oil Spot and Futures Prices: Cointegration, Linear and Nonlinear Causality," CeNDEF Working Papers 07-11, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    11. Fan, Ying & Zhang, Yue-Jun & Tsai, Hsien-Tang & Wei, Yi-Ming, 2008. "Estimating 'Value at Risk' of crude oil price and its spillover effect using the GED-GARCH approach," Energy Economics, Elsevier, vol. 30(6), pages 3156-3171, November.
    12. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2010. "Analyzing and Forecasting Volatility Spillovers, Asymmetries and Hedging in Major Oil Markets," Working Papers in Economics 10/19, University of Canterbury, Department of Economics and Finance.
    13. Aaltonen, J. & Östermark, R., 1997. "A rolling test of granger causality between the Finnish and Japanese security markets," Omega, Elsevier, vol. 25(6), pages 635-642, December.
    14. 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.
    15. Lin, Sharon Xiaowen & Tamvakis, Michael N., 2001. "Spillover effects in energy futures markets," Energy Economics, Elsevier, vol. 23(1), pages 43-56, January.
    16. Hong, Yongmiao, 2001. "A test for volatility spillover with application to exchange rates," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 183-224, July.
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