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Asymmetries in the oil market: Accounting for the growing role of China through quantile regressions

Author

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  • Valérie Mignon

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Jamel Saadaoui

Abstract

This paper investigates the role of political tensions between the US and China and global market forces in explaining oil price fluctuations. To this end, we rely on quantile regressions—quantile autoregressive distributed lag (QARDL) error-correction model—to account for possible asymmetric effects of those determinants, depending on both the level of oil prices and the period. Our results show evidence of a quantile-dependent long-term relationship between oil prices and their determinants over the 1958-2022 period, with an exacerbated effect of US-China political tensions in times of high oil prices. Furthermore, this quantile-dependent cointegrating relationship is time-varying across quantiles, highlighting the increased role played by China in the oil market since the mid-2000s.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Valérie Mignon & Jamel Saadaoui, 2023. "Asymmetries in the oil market: Accounting for the growing role of China through quantile regressions," Post-Print hal-04435774, HAL.
    • Handle: RePEc:hal:journl:hal-04435774
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    Cited by:

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    2. Saadaoui, Jamel, 2025. "Geopolitical Turning Points and Oil Price Responses: An IV-LP Approach," MPRA Paper 125586, University Library of Munich, Germany.

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    Keywords

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    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • F51 - International Economics - - International Relations, National Security, and International Political Economy - - - International Conflicts; Negotiations; Sanctions
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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