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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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    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. Bertrand Candelon & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2011. "Backtesting Value-at-Risk: A GMM Duration-Based Test," Journal of Financial Econometrics, Oxford University Press, vol. 9(2), pages 314-343, Spring.
    3. Jondeau, Eric & Rockinger, Michael, 2003. "Testing for differences in the tails of stock-market returns," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 559-581, December.
    4. 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.
    5. A. Lanza & M. Manera & M. Giovannini, 2003. "Oil and price dynamics in international petroleum markets," Working Paper CRENoS 200306, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    6. Andrew N. Kleit, 2001. "Are Regional Oil Markets Growing Closer Together?: An Arbitrage Cost Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-15.
    7. Dumitrescu, Elena-Ivona & Hurlin, Christophe, 2012. "Testing for Granger non-causality in heterogeneous panels," Economic Modelling, Elsevier, vol. 29(4), pages 1450-1460.
    8. Brémond, Vincent & Hache, Emmanuel & Mignon, Valérie, 2012. "Does OPEC still exist as a cartel? An empirical investigation," Energy Economics, Elsevier, vol. 34(1), pages 125-131.
    9. Gelper, Sarah & Croux, Christophe, 2007. "Multivariate out-of-sample tests for Granger causality," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3319-3329, April.
    10. Dufour, Jean-Marie, 2006. "Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics," Journal of Econometrics, Elsevier, vol. 133(2), pages 443-477, August.
    11. Fattouh, Bassam, 2010. "The dynamics of crude oil price differentials," Energy Economics, Elsevier, vol. 32(2), pages 334-342, March.
    12. Szymon Wlazlowski & Bjorn Hagstromer & Monica Giulietti, 2011. "Causality in crude oil prices," Applied Economics, Taylor & Francis Journals, vol. 43(24), pages 3337-3347.
    13. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    14. Jeremy Berkowitz & Peter Christoffersen & Denis Pelletier, 2011. "Evaluating Value-at-Risk Models with Desk-Level Data," Management Science, INFORMS, vol. 57(12), pages 2213-2227, December.
    15. Harvey, Campbell R. & Siddique, Akhtar, 1999. "Autoregressive Conditional Skewness," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(4), pages 465-487, December.
    16. Hong, Yongmiao & Liu, Yanhui & Wang, Shouyang, 2009. "Granger causality in risk and detection of extreme risk spillover between financial markets," Journal of Econometrics, Elsevier, vol. 150(2), pages 271-287, June.
    17. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    18. Hamilton, James D., 2003. "What is an oil shock?," Journal of Econometrics, Elsevier, vol. 113(2), pages 363-398, April.
    19. Lutz Kilian, 2008. "A Comparison of the Effects of Exogenous Oil Supply Shocks on Output and Inflation in the G7 Countries," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 78-121, March.
    20. Sadorsky, Perry, 1999. "Oil price shocks and stock market activity," Energy Economics, Elsevier, vol. 21(5), pages 449-469, October.
    21. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    22. Alessandro Lanza & Matteo Manera & Massimo Giovannini, 2003. "Oil and Product Price Dynamics in International Petroleum Markets," Working Papers 2003.81, Fondazione Eni Enrico Mattei.
    23. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    24. M. A. Adelman, 1984. "International Oil Agreements," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-10.
    25. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    26. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    27. Boudoukh, Jacob & Richardson, Matthew P & Whitelaw, Robert F, 1994. "A Tale of Three Schools: Insights on Autocorrelations of Short-Horizon Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 7(3), pages 539-573.
    28. 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.
    29. Clive, W.J. & Lin, Jin-Lung, 1995. "Causality in the Long Run," Econometric Theory, Cambridge University Press, vol. 11(3), pages 530-536, June.
    30. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
    31. Granger, C. W. J., 1980. "Testing for causality : A personal viewpoint," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 329-352, May.
    32. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    33. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
    34. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    35. Dong-Hyun Ahn & Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 2002. "Partial Adjustment or Stale Prices? Implications from Stock Index and Futures Return Autocorrelations," The Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 655-689, March.
    36. Breitung, Jorg & Candelon, Bertrand, 2006. "Testing for short- and long-run causality: A frequency-domain approach," Journal of Econometrics, Elsevier, vol. 132(2), pages 363-378, June.
    37. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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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.
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    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).
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    17. 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.
    18. 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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