IDEAS home Printed from https://ideas.repec.org/p/wbk/wbrwps/6376.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www-wds.worldbank.org/external/default/WDSContentServer/WDSP/IB/2013/02/27/000158349_20130227084149/Rendered/PDF/wps6376.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    2. Patrik Söderholm & Ger Klaassen, 2007. "Wind Power in Europe: A Simultaneous Innovation–Diffusion Model," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 36(2), pages 163-190, February.
    3. Stephen Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. del Rio, Pablo & Gual, Miguel A., 2007. "An integrated assessment of the feed-in tariff system in Spain," Energy Policy, Elsevier, vol. 35(2), pages 994-1012, February.
    5. Mulder, Arjen, 2008. "Do economic instruments matter? Wind turbine investments in the EU(15)," Energy Economics, Elsevier, vol. 30(6), pages 2980-2991, November.
    6. Heiman, M.K., 2006. "Expectations for renewable energy under market restructuring: the U.S. experience," Energy, Elsevier, vol. 31(6), pages 1052-1066.
    7. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    8. Stephen R. Bond, 2002. "Dynamic panel data models: a guide to micro data methods and practice," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 141-162, August.
    9. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    10. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.
    8. Bouraima, Mouhamed Bayane & Ayyildiz, Ertugrul & Badi, Ibrahim & Murat, Mirac & Es, Huseyin Avni & Pamucar, Dragan, 2024. "A decision support system for assessing the barriers and policies for wind energy deployment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 200(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Meschi, Elena & Taymaz, Erol & Vivarelli, Marco, 2011. "Trade, technology and skills: Evidence from Turkish microdata," Labour Economics, Elsevier, vol. 18(S1), pages 60-70.
    2. Abonazel, Mohamed R., 2016. "Bias Correction Methods for Dynamic Panel Data Models with Fixed Effects," MPRA Paper 70628, University Library of Munich, Germany.
    3. Caggese, Andrea, 2007. "Testing financing constraints on firm investment using variable capital," Journal of Financial Economics, Elsevier, vol. 86(3), pages 683-723, December.
    4. Davide Consoli & Francesco Vona & Francesco Rentocchini, 2016. "That was then, this is now: skills and routinization in the 2000s," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 25(5), pages 847-866.
    5. Mitsuru Sunada, 2008. "Network effects with quality change: an empirical analysis of the Japanese mobile telecommunications market, 1995-2001," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 29(8), pages 657-674.
    6. Antonio Ruiz Porras, 2016. "La investigación econométrica mediante paneles de datos:historia, modelos y usos en México," Archivos Revista Economía y Política., Facultad de Ciencias Económicas y Administrativas, Universidad de Cuenca., vol. 24, pages 11-32, Julio.
    7. Zhaoxia Xu, 2007. "Do Firms Adjust Toward a Target Leverage Level?," Staff Working Papers 07-50, Bank of Canada.
    8. Christian Merkl & Stephanie Stolz, 2009. "Banks' regulatory buffers, liquidity networks and monetary policy transmission," Applied Economics, Taylor & Francis Journals, vol. 41(16), pages 2013-2024.
    9. Juan Federico & Joan-Lluis Capelleras, 2015. "The heterogeneous dynamics between growth and profits: the case of young firms," Small Business Economics, Springer, vol. 44(2), pages 231-253, February.
    10. Tsun Se Cheong & Yanrui Wu, 2013. "Globalization and Regional Inequality," Economics Discussion / Working Papers 13-10, The University of Western Australia, Department of Economics.
    11. repec:spo:wpmain:info:hdl:2441/2ajduu0gqt9ho8h2tavbin6ops is not listed on IDEAS
    12. Cerina, Fabio & Manca, Fabio, 2018. "Catch Me If You Learn: Development-Specific Education And Economic Growth," Macroeconomic Dynamics, Cambridge University Press, vol. 22(6), pages 1652-1694, September.
    13. Borsato, Andrea & Lorentz, André, 2023. "The Kaldor–Verdoorn law at the age of robots and AI," Research Policy, Elsevier, vol. 52(10).
    14. Derek Jones & Panu Kalmi & Mikko Mäkinen, 2010. "The productivity effects of stock option schemes: evidence from Finnish panel data," Journal of Productivity Analysis, Springer, vol. 33(1), pages 67-80, February.
    15. Yongfu Huang, 2011. "Private investment and financial development in a globalized world," Empirical Economics, Springer, vol. 41(1), pages 43-56, August.
    16. Walther, Herbert & Stiassny, Alfred, 2013. "International Comparisons of Household Saving Rates and Hidden Income," Department of Economics Working Paper Series 148, WU Vienna University of Economics and Business.
    17. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    18. Joaquim Ramalho, 2005. "Feasible bias-corrected OLS, within-groups, and first-differences estimators for typical micro and macro AR(1) panel data models," Empirical Economics, Springer, vol. 30(3), pages 735-748, October.
    19. Sèna Kimm Gnangnon & Michael Roberts, 2017. "Aid for Trade, Foreign Direct Investment and Export Upgrading in Recipient Countries," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 1-36, June.
    20. Li, Hongbin & Yang, Zheyu & Yao, Xianguo & Zhang, Haifeng & Zhang, Junsen, 2012. "Entrepreneurship, private economy and growth: Evidence from China," China Economic Review, Elsevier, vol. 23(4), pages 948-961.
    21. Jung, Sven, 2013. "Employment Adjustment in German Firms," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79696, Verein für Socialpolitik / German Economic Association.

    More about this item

    Keywords

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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wbk:wbrwps:6376. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Roula I. Yazigi (email available below). General contact details of provider: https://edirc.repec.org/data/dvewbus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.