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Way Off: The Effect of Minimum Distance Regulation on the Deployment of Wind Power

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  • Jan Stede
  • Nils May

Abstract

Several countries and regions have introduced mandatory minimum distances of wind turbines to nearby residential areas, in order to increase public acceptance of wind power. Germany’s largest federal state Bavaria introduced such separation distances of ten times the height of new wind turbines in 2014. Here, we provide a novel monthly district-level dataset of construction permits for wind turbines constructed in Germany between 2010 and 2018. We use this dataset to evaluate the causal effect of introducing the Bavarian minimum distance regulation on the issuance of construction permits for wind turbines. We find that permits decreased by up to 90 percent. This decrease is in the same order of magnitude as the reduction of land area available for wind turbines. The results are in line with findings indicating that minimum distances do not increase the public acceptance of wind power, but harm the expansion of onshore wind power.

Suggested Citation

  • Jan Stede & Nils May, 2020. "Way Off: The Effect of Minimum Distance Regulation on the Deployment of Wind Power," Discussion Papers of DIW Berlin 1867, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp1867
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    1. Florian Egli & Bjarne Steffen & Tobias S. Schmidt, 2018. "A dynamic analysis of financing conditions for renewable energy technologies," Nature Energy, Nature, vol. 3(12), pages 1084-1092, December.
    2. Zerrahn, Alexander, 2017. "Wind Power and Externalities," Ecological Economics, Elsevier, vol. 141(C), pages 245-260.
    3. James G. MacKinnon & Matthew D. Webb, 2018. "The wild bootstrap for few (treated) clusters," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 114-135, June.
    4. Hoen, Ben & Firestone, Jeremy & Rand, Joseph & Elliot, Debi & Hübner, Gundula & Pohl, Johannes & Wiser, Ryan & Lantz, Eric & Haac, T. Ryan & Kaliski, Ken, 2019. "Attitudes of U.S. Wind Turbine Neighbors: Analysis of a Nationwide Survey," Energy Policy, Elsevier, vol. 134(C).
    5. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    6. Ladenburg, Jacob & Dahlgaard, Jens-Olav, 2012. "Attitudes, threshold levels and cumulative effects of the daily wind-turbine encounters," Applied Energy, Elsevier, vol. 98(C), pages 40-46.
    7. Wustenhagen, Rolf & Wolsink, Maarten & Burer, Mary Jean, 2007. "Social acceptance of renewable energy innovation: An introduction to the concept," Energy Policy, Elsevier, vol. 35(5), pages 2683-2691, May.
    8. James G. MacKinnon & Matthew D. Webb, 2019. "Wild Bootstrap Randomization Inference for Few Treated Clusters," Advances in Econometrics, in: The Econometrics of Complex Survey Data, volume 39, pages 61-85, Emerald Group Publishing Limited.
    9. Masurowski, Frank & Drechsler, Martin & Frank, Karin, 2016. "A spatially explicit assessment of the wind energy potential in response to an increased distance between wind turbines and settlements in Germany," Energy Policy, Elsevier, vol. 97(C), pages 343-350.
    10. Steven Chu & Arun Majumdar, 2012. "Opportunities and challenges for a sustainable energy future," Nature, Nature, vol. 488(7411), pages 294-303, August.
    11. Nils May & Øivind A. Nilsen, 2019. "The Local Economic Impact of Wind Power Deployment," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 75(1), pages 56-92.
    12. Wolsink, Maarten, 2012. "Undesired reinforcement of harmful ‘self-evident truths’ concerning the implementation of wind power," Energy Policy, Elsevier, vol. 48(C), pages 83-87.
    13. Langer, Katharina & Decker, Thomas & Roosen, Jutta & Menrad, Klaus, 2016. "A qualitative analysis to understand the acceptance of wind energy in Bavaria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 248-259.
    14. James G. MacKinnon & Matthew D. Webb, 2018. "The wild bootstrap for few (treated) clusters," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 114-135, June.
    15. Matthew Cashmore & David Rudolph & Sanne Vammen Larsen & Helle Nielsen, 2019. "International experiences with opposition to wind energy siting decisions: lessons for environmental and social appraisal," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 62(7), pages 1109-1132, June.
    16. James G. MacKinnon & Matthew D. Webb, 2017. "Wild Bootstrap Inference for Wildly Different Cluster Sizes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 233-254, March.
    17. Martin Drechsler & Jonas Egerer & Martin Lange & Frank Masurowski & Jürgen Meyerhoff & Malte Oehlmann, 2017. "Efficient and equitable spatial allocation of renewable power plants at the country scale," Nature Energy, Nature, vol. 2(9), pages 1-9, September.
    18. Krekel, Christian & Zerrahn, Alexander, 2017. "Does the presence of wind turbines have negative externalities for people in their surroundings? Evidence from well-being data," Journal of Environmental Economics and Management, Elsevier, vol. 82(C), pages 221-238.
    19. Leer Jørgensen, Marie & Anker, Helle Tegner & Lassen, Jesper, 2020. "Distributive fairness and local acceptance of wind turbines: The role of compensation schemes," Energy Policy, Elsevier, vol. 138(C).
    20. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    21. Catherine Mitchell, 2016. "Momentum is increasing towards a flexible electricity system based on renewables," Nature Energy, Nature, vol. 1(2), pages 1-6, February.
    22. Ladenburg, Jacob & Termansen, Mette & Hasler, Berit, 2013. "Assessing acceptability of two onshore wind power development schemes: A test of viewshed effects and the cumulative effects of wind turbines," Energy, Elsevier, vol. 54(C), pages 45-54.
    23. Jan Stede & Nils May, 2019. "Strikte Mindestabstände bremsen den Ausbau der Windenergie," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 86(48), pages 895-903.
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    2. Peri, Erez & Tal, Alon, 2021. "Is setback distance the best criteria for siting wind turbines under crowded conditions? An empirical analysis," Energy Policy, Elsevier, vol. 155(C).
    3. Dehler-Holland, Joris & Okoh, Marvin & Keles, Dogan, 2022. "Assessing technology legitimacy with topic models and sentiment analysis – The case of wind power in Germany," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    4. Stetter, Chris & Wielert, Henrik & Breitner, Michael H., 2022. "Hidden repowering potential of non-repowerable onshore wind sites in Germany," Energy Policy, Elsevier, vol. 168(C).
    5. Croonenbroeck, Carsten & Hennecke, David, 2021. "A comparison of optimizers in a unified standard for optimization on wind farm layout optimization," Energy, Elsevier, vol. 216(C).
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    7. Jan-Niklas Meier & Paul Lehmann & Bernd Süssmuth & Stephan Wedekind, 2024. "Wind power deployment and the impact of spatial planning policies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(2), pages 491-550, February.

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    More about this item

    Keywords

    Onshore wind power; minimum distance; separation distance; energy transition; acceptance; panel data; difference-in-differences; causal inference; event study;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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