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Determinants of solar photovoltaic deployment in the electricity mix : Do oil prices really matter?

Author

Listed:
  • Margaux Escoffier

    (IFPEN - IFP Energies nouvelles, EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Emmanuel Hache

    (IFPEN - IFP Energies nouvelles, EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique, IRIS - Institut de Relations Internationales et Stratégiques)

  • Valérie Mignon

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique, CEPII - Centre d'Etudes Prospectives et d'Informations Internationales - Centre d'analyse stratégique)

  • Anthony Paris

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique, LEO - Laboratoire d'Économie d'Orleans [2021-2022] - UO - Université d'Orléans - UT - Université de Tours)

Abstract

This paper investigates the determinants of solar photovoltaic (PV) deployment in the electricity mix for a panelof OECD and BRICS countries from 1997 to 2016 by paying particular attention to the impact of oil market con-ditions. Relying on a nonlinear, regime-switching specification, we show that rising oil prices stimulate PV de-ployment only if their growth rate exceeds 6.7% per annum. Although wefind that various other determinantsmatter—with the influence of some of them depending on the situation on the oil market—public policies playa crucial role.

Suggested Citation

  • Margaux Escoffier & Emmanuel Hache & Valérie Mignon & Anthony Paris, 2021. "Determinants of solar photovoltaic deployment in the electricity mix : Do oil prices really matter?," Post-Print hal-03339134, HAL.
    • Handle: RePEc:hal:journl:hal-03339134
    DOI: 10.1016/j.eneco.2020.105024
    Note: View the original document on HAL open archive server: https://ifp.hal.science/hal-03339134v1
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    Cited by:

    1. Błaszczyk, Alfred & Matuszak-Flejszman, Alina & Nawrocki, Kamil, 2024. "Determinants of the development of photovoltaics in Poland," Renewable Energy, Elsevier, vol. 233(C).
    2. Jinghong Zhou & Ke Chen & Weidong Wang, 2023. "A Power Evolution Game Model and Its Application Contained in Virtual Power Plants," Energies, MDPI, vol. 16(11), pages 1-22, May.
    3. Ishaya Jonah Tegina Tambari & Pierre Failler & Shabbar Jaffry, 2023. "The Differential Effects of Oil Prices on the Development of Renewable Energy in Oil-Importing and Oil-Exporting Countries in Africa," Energies, MDPI, vol. 16(9), pages 1-20, April.
    4. C. M. Quintella & P. D. Rodrigues & J. L. Nicoleti & E. Ramos-de-Souza & E. B. Carvalho & S. A. Hanna, 2024. "EOR Technology (Patents) and Science (Articles) Assessment of BRICS and nonBRICS with Growth Rates and Specializations within Responsible Global Energy Transition: A Critical Review," Energies, MDPI, vol. 17(13), pages 1-17, June.
    5. Hille, Erik & Oelker, Thomas J., 2023. "International expansion of renewable energy capacities: The role of innovation and choice of policy instruments," Ecological Economics, Elsevier, vol. 204(PA).
    6. Best, Rohan & Chareunsy, Andrea, 2022. "The impact of income on household solar panel uptake: Exploring diverse results using Australian data," Energy Economics, Elsevier, vol. 112(C).
    7. Kim, Moon Joon, 2024. "Air Pollution and Solar Photovoltaic Power Generation: Evidence from South Korea," Energy Economics, Elsevier, vol. 139(C).
    8. Hille, Erik, 2023. "Europe's energy crisis: Are geopolitical risks in source countries of fossil fuels accelerating the transition to renewable energy?," Energy Economics, Elsevier, vol. 127(PA).

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    Keywords

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    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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