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The Impacts of Feed-in Tariffs on Innovation: Empirical Evidence from Germany

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Listed:
  • Christoph Böhringer
  • Alexander Cuntz
  • Dietmar Harhoff
  • Emmanuel Asane Otoo

Abstract

Feed-in tariffs under the Renewable Energy Sources Act, the so-called Erneuerbare-Energien-Gesetz (EEG), have triggered a massive expansion of electricity from renewable energy sources in Germany over the last decade. The increase in non-competitive renewable power generation though went hand in hand with a substantial rise in electricity prices with consumers paying for the renewable energy subsidies. The high cost burden has provoked an intense public debate on the benefits of renewable energy promotion. In this paper, we assess one popular justification for feed-in tariffs, i.e., induced innovation as a positive spillover externality. Based on regressions with a time-technology fixed effect negative binomial model, we find that innovation impacts of feed-in tariffs under the EEG are insignificant.

Suggested Citation

  • Christoph Böhringer & Alexander Cuntz & Dietmar Harhoff & Emmanuel Asane Otoo, 2014. "The Impacts of Feed-in Tariffs on Innovation: Empirical Evidence from Germany," CESifo Working Paper Series 4680, CESifo.
    • Handle: RePEc:ces:ceswps:_4680
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Arthur Korus, 2016. "Erneuerbare Energien und Leitmärkte in der EU und Deutschland," EIIW Discussion paper disbei225, Universitätsbibliothek Wuppertal, University Library.
    2. Cantner, Uwe & Graf, Holger & Herrmann, Johannes & Kalthaus, Martin, 2016. "Inventor networks in renewable energies: The influence of the policy mix in Germany," Research Policy, Elsevier, vol. 45(6), pages 1165-1184.
    3. Mark A. Andor, Manuel Frondel, and Colin Vance, 2017. "Germanys Energiewende: A Tale of Increasing Costs and Decreasing Willingness-To-Pay," The Energy Journal, International Association for Energy Economics, vol. 0(KAPSARC S).
    4. Rexhäuser, Sascha & Löschel, Andreas, 2015. "Invention in energy technologies: Comparing energy efficiency and renewable energy inventions at the firm level," Energy Policy, Elsevier, vol. 83(C), pages 206-217.
    5. Bruns, Stephan B. & Kalthaus, Martin, 2020. "Flexibility in the selection of patent counts: Implications for p-hacking and evidence-based policymaking," Research Policy, Elsevier, vol. 49(1).
    6. Guillaume Bourgeois & Sandrine Mathy & Philippe Menanteau, 2017. "The effect of climate policies on renewable energies : a review of econometric studies [L’effet des politiques climatiques sur les énergies renouvelables : une revue des études économétriques]," Post-Print hal-01585906, HAL.
    7. Consolación Quintana-Rojo & Fernando-Evaristo Callejas-Albiñana & Miguel-Ángel Tarancón & Isabel Martínez-Rodríguez, 2020. "Econometric Studies on the Development of Renewable Energy Sources to Support the European Union 2020–2030 Climate and Energy Framework: A Critical Appraisal," Sustainability, MDPI, vol. 12(12), pages 1-26, June.
    8. Samant, Shantala & Thakur-Wernz, Pooja & Hatfield, Donald E., 2020. "Does the focus of renewable energy policy impact the nature of innovation? Evidence from emerging economies," Energy Policy, Elsevier, vol. 137(C).

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    More about this item

    Keywords

    renewable energy promotion; feed-in tariffs; innovation; negative binomial regression;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

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