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Testing persistence of WTI and Brent long-run relationship after the shale oil supply shock

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  • Caporin, Massimiliano
  • Fontini, Fulvio
  • Talebbeydokhti, Elham

Abstract

In the paper, we study the long-run relationship in the WTI-Brent oil time series, taking into account the occurrence of two relevant events: the rise of shale oil production, in early 2011, and the widening and closing of the WTI-Brent price spread, from 2011 to 2014. Monthly data of WTI and Brent crude oil prices, as well as US shale oil quantities from January 2000 to December 2017 is used for the analyses. The empirical results of the cointegration tests with structural breaks show that two structural break occurs, in February 2011 and in October 2014. We then estimate a Vector Error Correction Model (VECM), considering the structural break suggested by the cointegration test results, the timing of the rise in shale oil production and the dynamics of the WTI-Brent price spread. Our analysis reveals that WTI and Brent crude oil prices have had a long-run relationship up to 2011; no cointegration existed during the period of widening of the spread; again, a new long-run relationship arises after the closing of the gap, which includes the shale oil production. In the last period, the cross price elasticity of Brent on WTI slightly reduces compared to the pre-2011 era, whilst the shale oil production increases its importance in explaining the long-run relationship between WTI and Brent fivefold. Using the Generalized Impulse Response Functions (GIRFs) we finally study the impact of exogenous shocks on the variables, showing that in the first period, with limited shale oil production, oil prices reacted to shale oil and not vice versa. After October 2014, the opposite becomes true and shale oil production follows changes in both WTI and Brent prices.

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  • 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.
  • Handle: RePEc:eee:eneeco:v:79:y:2019:i:c:p:21-31
    DOI: 10.1016/j.eneco.2018.08.022
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    16. Jerome Geyer‐Klingeberg & Andreas W. Rathgeber, 2021. "Determinants of the WTI‐Brent price spread revisited," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 736-757, May.
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    More about this item

    Keywords

    WTI; Brent; Shale oil; Cointegration; Vector Error Correction Model; Generalized Impulse Response Function;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • 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
    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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