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Growth and competition in renewable energy industries: Insights from an integrated assessment model with strategic firms

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  • Leibowicz, Benjamin D.

Abstract

This article describes the development, implementation, and application of an integrated assessment modeling framework featuring renewable technology markets with producers engaged in Cournot competition. Scenario results reveal how climate policy and inter-firm learning spillovers interact with market structure to affect wind and solar PV prices, adoption, producer profits, and carbon emissions. Competitive markets yield consistently lower markups than concentrated markets, leading to significantly more adoption and lower emissions. Widespread solar PV adoption is a key component of the largest emissions reductions, but this requires substantial price reductions that only occur if the solar PV market is competitive and learning spills over across producers. Whether a leading firm has a profit incentive to facilitate or obstruct learning spillovers depends on the availability of cost-competitive substitute technologies. If such a substitute exists, the firm prefers strong spillovers that help its industry compete against the substitute; if not, the firm prefers weak spillovers that prevent competitors in its industry from seizing market share. The relationship between price and cumulative capacity is endogenous in the modeling framework. Regression analysis of scenario results yields price learning rates which are similar to unit production cost learning rates in competitive markets, but substantially lower – even negative – in concentrated markets.

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  • Leibowicz, Benjamin D., 2015. "Growth and competition in renewable energy industries: Insights from an integrated assessment model with strategic firms," Energy Economics, Elsevier, vol. 52(PA), pages 13-25.
  • Handle: RePEc:eee:eneeco:v:52:y:2015:i:pa:p:13-25
    DOI: 10.1016/j.eneco.2015.09.010
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    Cited by:

    1. Strupeit, Lars, 2017. "An innovation system perspective on the drivers of soft cost reduction for photovoltaic deployment: The case of Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 273-286.
    2. de Frutos Cachorro, J. & Willeghems, G. & Buysse, J., 2019. "Strategic investment decisions under the nuclear power debate in Belgium," Resource and Energy Economics, Elsevier, vol. 57(C), pages 156-184.
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    4. Thomassen, Gwenny & Van Passel, Steven & Dewulf, Jo, 2020. "A review on learning effects in prospective technology assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    5. Sansi Yang & C. Richard Shumway, 2020. "Knowledge accumulation in US agriculture: research and learning by doing," Journal of Productivity Analysis, Springer, vol. 54(2), pages 87-105, December.

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    More about this item

    Keywords

    Technological change; Market structure; Integrated assessment; Renewable energy; Learning by doing;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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