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The determinants of crude oil prices: Evidence from ARDL and nonlinear ARDL approaches

Author

Listed:
  • Leila Ben Salem

    (USO - جامعة سوسة = Université de Sousse = University of Sousse)

  • Ridha Nouira

    (USO - جامعة سوسة = Université de Sousse = University of Sousse)

  • Khaled Jeguirim

    (UM - Université de Monastir - University of Monastir - جامعة المنستير)

  • Christophe Rault

    (LEO - Laboratoire d'Économie d'Orleans [2022-...] - UO - Université d'Orléans - UT - Université de Tours - UCA - Université Clermont Auvergne)

Abstract

This paper is an innovative attempt to empirically investigate the determinants of crude oil prices. The main objective is to distinguish between short- and long-term effects of some covariates on oil prices. The autoregressive distributed lag (ARDL) approach is applied to daily series spanning the period from January 2, 2003, to May 24, 2021, to analyze long-run relationships and short-run dynamics. The paper also focuses on the asymmetric effects of covariates and a nonlinear ARDL (NARDL) approach is used to explore this asymmetry. The use of an asymmetric error correction model with asymmetric cointegration provides new insights for examining the determinants of oil prices. All investigations of underlying oil price fluctuations are examined both before and in the COVID-19 pandemic. Our results, based on different econometric specifications, have key policy implications for policymakers both with and without COVID-19 potential considerations.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Leila Ben Salem & Ridha Nouira & Khaled Jeguirim & Christophe Rault, 2022. "The determinants of crude oil prices: Evidence from ARDL and nonlinear ARDL approaches," Post-Print hal-04143946, HAL.
    • Handle: RePEc:hal:journl:hal-04143946
    DOI: 10.1016/j.resourpol.2022.103085
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    Cited by:

    1. Nour Fakhreddine & Noura Najia & Abbas Mourad & Wafaa Nasser, 2024. "Asymmetric Effect of Oil Price on Economic Activity: Evidence from Lebanon Using NARDL Model," International Journal of Energy Economics and Policy, Econjournals, vol. 14(2), pages 258-266, March.
    2. Ben Jabeur, Sami & Boubaker, Sabri & Carmona, Pedro & Stef, Nicolae, 2025. "How do environmental concerns and global economic conditions affect energy prices?," Energy Policy, Elsevier, vol. 204(C).
    3. Qin Meng & Jing-Wen Zhang & Yunxu Wang & Hsu-Ling Chang & Chi-Wei Su, 2023. "Green Household Technology and Its Impacts on Environmental Sustainability in China," Sustainability, MDPI, vol. 15(17), pages 1-13, August.
    4. Kirikkaleli, Dervis, 2023. "Resource efficiency, energy productivity, and environmental quality in Japan," Resources Policy, Elsevier, vol. 85(PB).
    5. Yu, Yue & Wang, Jianzhou & Jiang, He & Lu, Haiyan, 2025. "How to manage a multifactor-driven crude oil market more effectively? A revisit based on the multiple criteria perspective," Resources Policy, Elsevier, vol. 100(C).
    6. Simsek, Ahmed Ihsan & Bulut, Emre & Gur, Yunus Emre & Gültekin Tarla, Esma, 2024. "A novel approach to Predict WTI crude spot oil price: LSTM-based feature extraction with Xgboost Regressor," Energy, Elsevier, vol. 309(C).
    7. Tsitouras Antonis & Tsounis Nicholas, 2024. "Military Outlays and Economic Growth: A Nonlinear Disaggregated Analysis for a Developed Economy," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 30(3), pages 341-391.

    More about this item

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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