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Soziale Verteilungswirkungen der EEG-Umlage

Author

Listed:
  • Dr. Ulrike Lehr

    (GWS - Institute of Economic Structures Research)

  • Dr. Thomas Drosdowski

    (GWS - Institute of Economic Structures Research)

Abstract

Die Berechnung der EEG-Umlage für das Jahr 2013 durch die Netzbetreiber hat zu einer breiten Diskussion über die sozialen Auswirkungen steigender Strompreise geführt. In der vorliegenden Studie werden modellgestützt Verteilungswirkungen bei einem Vergleich verschiedener Entwicklungspfade der EEG-Umlage untersucht. Die Entwicklung der Umlage orientiert sich am unteren und oberen Szenario der Mittelfristprognose. Es treten leicht regressive Verteilungswirkungen auf, wie diese bei anderen umweltpolitischen Instrumenten ebenfalls zu beobachten sind. Die durchschnittliche Belastung der Haushalte ist besonders gering, wenn Verhaltensanpassungen beim Stromverbrauch aufgrund von steigenden relativen Preisen modelliert werden.

Suggested Citation

  • Dr. Ulrike Lehr & Dr. Thomas Drosdowski, 2013. "Soziale Verteilungswirkungen der EEG-Umlage," GWS Discussion Paper Series 13-3, GWS - Institute of Economic Structures Research.
    • Handle: RePEc:gws:dpaper:13-3
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    References listed on IDEAS

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    1. Peter Grösche & Carsten Schröder, 2014. "On the redistributive effects of Germany’s feed-in tariff," Empirical Economics, Springer, vol. 46(4), pages 1339-1383, June.
    2. Karsten Neuhoff & Stefan Bach & Jochen Diekmann & Martin Beznoska & Tarik El-Laboudy, 2012. "Steigende EEG-Umlage: unerwünschte Verteilungseffekte können vermindert werden," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 79(41), pages 3-12.
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    Cited by:

    1. Dr. Jochen Diekmann (DIW Berlin) & Dr. Barbara Breitschopf (Fraunhofer ISI) & Dr. Ulrike Lehr, 2015. "Politische Optionen zur Verminderung von Verteilungswirkungen der EEG-Umlage," GWS Discussion Paper Series 15-18, GWS - Institute of Economic Structures Research.
    2. Herrmann, J.K. & Savin, I., 2017. "Optimal policy identification: Insights from the German electricity market," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 71-90.
    3. Pegels, Anna & Lütkenhorst, Wilfried, 2014. "Is Germany׳s energy transition a case of successful green industrial policy? Contrasting wind and solar PV," Energy Policy, Elsevier, vol. 74(C), pages 522-534.
    4. Dr. Ulrike Lehr & Dr. Thomas Drosdowski, 2015. "Soziale Verteilungswirkungen der EEG-Umlage unter Berücksichtigung von Einkommensklassen," GWS Discussion Paper Series 15-1, GWS - Institute of Economic Structures Research.
    5. Growitsch Christian & Meier Helena & Schleich Sebastian, 2015. "Regionale Verteilungswirkungen des Erneuerbare-Energien-Gesetzes," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 16(1), pages 72-87, March.
    6. Dr. Thomas Drosdowski & Dr. Christian Lutz, 2014. "Weiterentwicklung des aktualisierten Panta Rhei Modells um sozioökonomische Aspekte," GWS Research Report Series 14-1, GWS - Institute of Economic Structures Research.
    7. Dr. Jochen Dieckmann & Dr. Barbara Breitschopf & Dr. Ulrike Lehr, 2016. "Social impacts of renewable energy in Germany – size, history and alleviation," GWS Discussion Paper Series 16-7, GWS - Institute of Economic Structures Research.

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    More about this item

    Keywords

    Q48; D31; H23;
    All these keywords.

    JEL classification:

    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies

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