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The Influence of Policy Regime Risks on Investments in Innovative Energy Technology

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  • Garnier, Ernesto

    (RWTH Aachen University)

  • Madlener, Reinhard

    (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN))

Abstract

This paper dissects the ways in which policy regime risks influence decisions over innovative energy technology investments. We apply compound real options methodology to evaluate the investment in a virtual power plant platform and distributed energy resource (DER) assets in view of volatile electricity market prices and an uncertain future electricity market design. The analysis reveals two aspects of policy regime risks: a policy content effect relating to actual market dynamics resulting from a (new) policy regime, and a policy process effect relating to (uncertainty about) the speed and probability of a regime change. The paper underlines the importance of predictable policymaking to stimulate risky investment. It further details the need to account for technology-specific investment responses to different policy regimes and risks, caused by different degrees of market versus subsidy exposure and differences between platform versus non-platform technologies.

Suggested Citation

  • Garnier, Ernesto & Madlener, Reinhard, 2015. "The Influence of Policy Regime Risks on Investments in Innovative Energy Technology," FCN Working Papers 2/2015, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Oct 2015.
    • Handle: RePEc:ris:fcnwpa:2015_002
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    Cited by:

    1. Frank A. Wolak, 2016. "Level versus Variability Trade-offs in Wind and Solar Generation Investments: The Case of California," The Energy Journal, International Association for Energy Economics, vol. 0(Bollino-M).
    2. Frank A. Wolak, 2016. "Level versus Variability Trade-offs in Wind and Solar Generation Investments: The Case of California," NBER Working Papers 22494, National Bureau of Economic Research, Inc.
    3. Romano, Teresa & Fumagalli, Elena, 2018. "Greening the power generation sector: Understanding the role of uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 272-286.
    4. Amedeo Argentiero, Tarek Atalla, Simona Bigerna, Silvia Micheli, and Paolo Polinori, 2017. "Comparing Renewable Energy Policies in EU-15, U.S. and China: A Bayesian DSGE Model," The Energy Journal, International Association for Energy Economics, vol. 0(KAPSARC S).
    5. Amedeo Argentiero & Tarek Atalla & Simona Bigerna & Silvia Micheli & Paolo Polinori, 2017. "Comparing Renewable Energy Policies in E.U.15, U.S. and China: A Bayesian DSGE Model," The Energy Journal, , vol. 38(1_suppl), pages 77-96, June.
    6. Oguzhan Cepni, Duc Khuong Nguyen, and Ahmet Sensoy, 2022. "News Media and Attention Spillover across Energy Markets: A Powerful Predictor of Crude Oil Futures Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    7. Florian Habermacher & Paul Lehmann, 2020. "Commitment Versus Discretion in Climate and Energy Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(1), pages 39-67, May.
    8. Specht, Jan Martin & Madlener, Reinhard, 2019. "Energy Supplier 2.0: A conceptual business model for energy suppliers aggregating flexible distributed assets and policy issues raised," Energy Policy, Elsevier, vol. 135(C).

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    More about this item

    Keywords

    Policy uncertainty; Virtual power plant; Distributed energy; Real option;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • 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

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