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Energy Pricing during the COVID-19 Pandemic: Predictive Information-Based Uncertainty Indexes with Machine Learning Algorithm

Author

Listed:
  • Olubusoye, Olusanya E
  • Akintande, Olalekan J.
  • Yaya, OlaOluwa S.
  • Ogbonna, Ahamuefula
  • Adenikinju, Adeola F.

Abstract

The study investigates the impact of uncertainties on energy pricing during the COVID-19 pandemic using five uncertainty measures that include the COVID-Induced Uncertainty (CIU), Economic Policy Uncertainty (EPU), Global Fear Index (GFI); Volatility Index (VIX), and the Misinformation Index of Uncertainty (MIU). The data, which span between 2-January, 2020 and 19-January, 2021, corresponding to the period of the COVID-19 pandemic. The study finds energy prices to respond significantly to the examined uncertainty measures, with EPU seen to affect the prices of most energy types during the pandemic. We also find predictive potentials inherent in VIX, CIU, and MIU for global energy sources.

Suggested Citation

  • Olubusoye, Olusanya E & Akintande, Olalekan J. & Yaya, OlaOluwa S. & Ogbonna, Ahamuefula & Adenikinju, Adeola F., 2021. "Energy Pricing during the COVID-19 Pandemic: Predictive Information-Based Uncertainty Indexes with Machine Learning Algorithm," MPRA Paper 109838, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:109838
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    References listed on IDEAS

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    1. Salisu, Afees A. & Akanni, Lateef & Raheem, Ibrahim, 2020. "The COVID-19 global fear index and the predictability of commodity price returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    2. Afees A. Salisu & Ahamuefula E. Ogbonna & Tirimisiyu F. Oloko & Idris A. Adediran, 2021. "A New Index for Measuring Uncertainty Due to the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    3. Dang, Hai-Anh H. & Trinh, Trong-Anh, 2021. "Does the COVID-19 lockdown improve global air quality? New cross-national evidence on its unintended consequences," Journal of Environmental Economics and Management, Elsevier, vol. 105(C).
    4. Akintande, Olalekan J. & Olubusoye, Olusanya E. & Adenikinju, Adeola F. & Olanrewaju, Busayo T., 2020. "Modeling the determinants of renewable energy consumption: Evidence from the five most populous nations in Africa," Energy, Elsevier, vol. 206(C).
    5. Salisu, Afees A. & Ogbonna, Ahamuefula E., 2019. "Another look at the energy-growth nexus: New insights from MIDAS regressions," Energy, Elsevier, vol. 174(C), pages 69-84.
    6. Olubusoye, Olusanya E & Yaya, OlaOluwa S. & Ogbonna, Ahamuefula, 2021. "An Information-Based Index of Uncertainty and the predictability of Energy Prices," MPRA Paper 109839, University Library of Munich, Germany.
    7. Honorata Nyga-Łukaszewska & Kentaka Aruga, 2020. "Energy Prices and COVID-Immunity: The Case of Crude Oil and Natural Gas Prices in the US and Japan," Energies, MDPI, vol. 13(23), pages 1-17, November.
    8. Herrera, Gabriel Paes & Constantino, Michel & Tabak, Benjamin Miranda & Pistori, Hemerson & Su, Jen-Je & Naranpanawa, Athula, 2019. "Long-term forecast of energy commodities price using machine learning," Energy, Elsevier, vol. 179(C), pages 214-221.
    9. Olanrewaju, Busayo T. & Olubusoye, Olusanya E. & Adenikinju, Adeola & Akintande, Olalekan J., 2019. "A panel data analysis of renewable energy consumption in Africa," Renewable Energy, Elsevier, vol. 140(C), pages 668-679.
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    Cited by:

    1. Yagi, Michiyuki & Managi, Shunsuke, 2023. "The spillover effects of rising energy prices following 2022 Russian invasion of Ukraine," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 680-695.
    2. Khan, Khalid & Su, Chi-Wei & Khurshid, Adnan & Umar, Muhammad, 2022. "COVID-19 impact on multifractality of energy prices: Asymmetric multifractality analysis," Energy, Elsevier, vol. 256(C).
    3. Ahmed Mohamed Habib & Umar Nawaz Kayani, 2024. "Price reaction of global economic indicators: evidence from the COVID-19 pandemic and the Russia–Ukraine conflict," SN Business & Economics, Springer, vol. 4(1), pages 1-21, January.

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    More about this item

    Keywords

    Coronavirus pandemic; Energy market; Machine Learning; Uncertainty;
    All these keywords.

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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