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How fit are feed-in tariff policies ? evidence from the European wind market

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  • Zhang, Fan

Abstract

Feed-in tariffs have become the most widely used policy instrument to promote renewable energy deployment around the world. This paper examines the relation between tariff setting and policy outcome based on wind capacity expansion in 35 European countries over the 1991-2010 period. Using a dynamic panel data model, it estimates the long-run elasticity of wind deployment with respect to the level of feed-in support. The analysis finds that higher subsidies do not necessarily yield greater levels of wind installation. Non-economic barriers and rent-seeking may have contributed to the weak correlation. On the other hand, the length of feed-in contract and guaranteed grid access are important determinants of policy effectiveness. A one-year extension of an original 5-year agreement on average increases wind investment by 6 percent annually, while providing an interconnection guarantee almost doubles wind investment in one year.

Suggested Citation

  • Zhang, Fan, 2013. "How fit are feed-in tariff policies ? evidence from the European wind market," Policy Research Working Paper Series 6376, The World Bank.
    • Handle: RePEc:wbk:wbrwps:6376
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    References listed on IDEAS

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    Cited by:

    1. Basher, Syed Abul & Masini, Andrea & Aflaki, Sam, 2015. "Time series properties of the renewable energy diffusion process: Implications for energy policy design and assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1680-1692.
    2. Bigerna, Simona & D'Errico, Maria Chiara & Polinori, Paolo, 2022. "Environmental variables and power firms' productivity: micro panel estimation with time-Invariant variables," MPRA Paper 114157, University Library of Munich, Germany.
    3. Quintana-Rojo, Consolación & Callejas-Albiñana, Fernando-Evaristo & Tarancón, Miguel-Ángel & del Río, Pablo, 2020. "Assessing the feasibility of deployment policies in wind energy systems. A sensitivity analysis on a multiequational econometric framework," Energy Economics, Elsevier, vol. 86(C).
    4. Sotiris Papadelis & Vasssilis Stavrakas & Alexandros Flamos, 2016. "What Do Capacity Deployment Rates Tell Us about the Efficiency of Electricity Generation from Renewable Energy Sources Support Measures in Greece?," Energies, MDPI, vol. 9(1), pages 1-16, January.
    5. 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.
    6. María-Jesús Gutiérrez-Pedrero & María J. Ruiz-Fuensanta & Miguel-Ángel Tarancón, 2020. "Regional Factors Driving the Deployment of Wind Energy in Spain," Energies, MDPI, vol. 13(14), pages 1-13, July.
    7. Kathuria, Vinish & Ray, Pradeep & Bhangaonkar, Rekha, 2015. "FDI (foreign direct investment) in wind energy sector in India: Testing the effectiveness of state policies using panel data," Energy, Elsevier, vol. 80(C), pages 190-202.

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    Keywords

    Energy Production and Transportation; Climate Change Mitigation and Green House Gases; Carbon Policy and Trading; Climate Change Economics; Markets and Market Access;
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