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Causality in Quantiles and Dynamic Relations in Energy Markets


  • Kyritsis, Evangelos
  • Andersson, Jonas


In this paper we investigate the dynamic relations between crude oil price returns and a set of energy price returns, namely diesel, gasoline, heating, and the natural gas. This is performed by means of Granger non-causality tests for US spot closing prices over the period from January 1997 to December 2017. In previous studies this has been done by testing for the added predictive value of including lagged values of one energy price return in predicting the conditional expectation of another. In this paper, we instead focus on different ranges of the full conditional distribution within the framework of a dynamic quantile regression model, and identify the quantile ranges from which causality arises. The results constitute a richer set of findings than what is possible by just considering a single moment of the conditional distribution, which can be useful for implementing better substitution investment strategies and effective policy interventions. We find several interesting one-directional dynamic relations between the employed energy prices, especially in the tail quantiles, but also a bi-directional causal relation between energy prices for which the classical Granger non-causality test suggests otherwise. Our results are robust to alternative measures of the price of oil and different data frequencies.

Suggested Citation

  • Kyritsis, Evangelos & Andersson, Jonas, 2019. "Causality in Quantiles and Dynamic Relations in Energy Markets," Working Papers 116, VATT Institute for Economic Research.
  • Handle: RePEc:fer:wpaper:116

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    References listed on IDEAS

    1. Kyritsis, Evangelos & Serletis, Apostolos, 2018. "The zero lower bound and market spillovers: Evidence from the G7 and Norway," Research in International Business and Finance, Elsevier, vol. 44(C), pages 100-123.
    2. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2017. "Wavelet-based test of co-movement and causality between oil and renewable energy stock prices," Energy Economics, Elsevier, vol. 61(C), pages 241-252.
    3. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    4. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    5. Kyritsis, Evangelos & Andersson, Jonas & Serletis, Apostolos, 2017. "Electricity prices, large-scale renewable integration, and policy implications," Energy Policy, Elsevier, vol. 101(C), pages 550-560.
    6. repec:ipg:wpaper:2014-569 is not listed on IDEAS
    7. Ding, Haoyuan & Chong, Terence Tai-leung & Park, Sung Y., 2014. "Nonlinear dependence between stock and real estate markets in China," Economics Letters, Elsevier, vol. 124(3), pages 526-529.
    8. Atil, Ahmed & Lahiani, Amine & Nguyen, Duc Khuong, 2014. "Asymmetric and nonlinear pass-through of crude oil prices to gasoline and natural gas prices," Energy Policy, Elsevier, vol. 65(C), pages 567-573.
    9. Chang, Dongfeng & Serletis, Apostolos, 2018. "Oil, Uncertainty, And Gasoline Prices," Macroeconomic Dynamics, Cambridge University Press, vol. 22(03), pages 546-561, April.
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    More about this item


    Energy price returns; Granger non-causality; Quantile regression; Tail quantiles; Environment; energy and climate policy; C22; G14; Q41;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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