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Wind power deployment and the impact of spatial planning policies

Author

Listed:
  • Jan-Niklas Meier

    (Leipzig University)

  • Paul Lehmann

    (Leipzig University)

  • Bernd Süssmuth

    (Leipzig University)

  • Stephan Wedekind

    (Leipzig University)

Abstract

Spatio-environmental externalities of renewable energy deployment are mainly managed through spatial planning policies, like regional expansion goals, zoning designated areas, or setback distances. We provide a quantitative analysis of how effectively spatial planning policies can steer RES deployment, using the example of onshore wind power expansion in Germany. Based on a novel georeferenced dataset of wind turbines and spatial planning policies, we use a dynamic panel data model to explain yearly additions in wind power capacities. Most importantly, we find a strong positive impact of zoning specific land areas for wind power deployment. An additional square kilometer of designated area leads to an increase of 4.6% of yearly capacity additions per county. Not only the amount of designated area matters, but also the size and shape of each individual designated area. Small and elongated areas are, on average, associated with more wind power expansion than large and compact areas. Moreover, we find that in states with an expansion goal, capacity additions are 2.6% higher. In contrast, increasing the setback distance between turbine sites and settlements by 100 m is associated with reductions of yearly capacity additions by about 3.1%. Our findings show that policymakers can resort to spatial planning instruments in order to effectively arrange wind power deployment with other land uses.

Suggested Citation

  • 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.
  • Handle: RePEc:kap:enreec:v:87:y:2024:i:2:d:10.1007_s10640-023-00820-3
    DOI: 10.1007/s10640-023-00820-3
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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. 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.
    3. Kiviet, Jan F., 2020. "Microeconometric dynamic panel data methods: Model specification and selection issues," Econometrics and Statistics, Elsevier, vol. 13(C), pages 16-45.
    4. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    5. 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.
    6. Andrews, Donald W. K. & Lu, Biao, 2001. "Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models," Journal of Econometrics, Elsevier, vol. 101(1), pages 123-164, March.
    7. Meyerhoff, Jürgen & Ohl, Cornelia & Hartje, Volkmar, 2010. "Landscape externalities from onshore wind power," Energy Policy, Elsevier, vol. 38(1), pages 82-92, January.
    8. Iglesias, Guillermo & del Río, Pablo & Dopico, Jesús Ángel, 2011. "Policy analysis of authorisation procedures for wind energy deployment in Spain," Energy Policy, Elsevier, vol. 39(7), pages 4067-4076, July.
    9. Justin B. Winikoff, 2022. "Learning by Regulating: The Evolution of Wind Energy Zoning Laws," Journal of Law and Economics, University of Chicago Press, vol. 65(S1), pages 223-262.
    10. Gibbons, Stephen, 2015. "Gone with the wind: Valuing the visual impacts of wind turbines through house prices," Journal of Environmental Economics and Management, Elsevier, vol. 72(C), pages 177-196.
    11. Hitaj, Claudia, 2013. "Wind power development in the United States," Journal of Environmental Economics and Management, Elsevier, vol. 65(3), pages 394-410.
    12. J. K. Lundquist & K. K. DuVivier & D. Kaffine & J. M. Tomaszewski, 2019. "Costs and consequences of wind turbine wake effects arising from uncoordinated wind energy development," Nature Energy, Nature, vol. 4(1), pages 26-34, January.
    13. Thomas Lauf & Kristina Ek & Erik Gawel & Paul Lehmann & Patrik Söderholm, 2020. "The regional heterogeneity of wind power deployment: an empirical investigation of land-use policies in Germany and Sweden," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 63(4), pages 751-778, March.
    14. Lerner, Michael, 2022. "Local power: understanding the adoption and design of county wind energy regulation," LSE Research Online Documents on Economics 112757, London School of Economics and Political Science, LSE Library.
    15. Zerrahn, Alexander, 2017. "Wind Power and Externalities," Ecological Economics, Elsevier, vol. 141(C), pages 245-260.
    16. J. K. Lundquist & K. K. DuVivier & D. Kaffine & J. M. Tomaszewski, 2019. "Publisher Correction: Costs and consequences of wind turbine wake effects arising from uncoordinated wind energy development," Nature Energy, Nature, vol. 4(3), pages 251-251, March.
    17. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    18. David Manske & Lukas Grosch & Julius Schmiedt & Nora Mittelstädt & Daniela Thrän, 2022. "Geo-Locations and System Data of Renewable Energy Installations in Germany," Data, MDPI, vol. 7(9), pages 1-15, September.
    19. 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.
    20. Michael Lerner, 2022. "Local power: Understanding the adoption and design of county wind energy regulation," Review of Policy Research, Policy Studies Organization, vol. 39(2), pages 120-142, March.
    21. Drechsler, Martin & Ohl, Cornelia & Meyerhoff, Jürgen & Eichhorn, Marcus & Monsees, Jan, 2011. "Combining spatial modeling and choice experiments for the optimal spatial allocation of wind turbines," Energy Policy, Elsevier, vol. 39(6), pages 3845-3854, June.
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    More about this item

    Keywords

    Environmental regulation; Multi-level governance; Panel data; Wind power; Spatial planning;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • H77 - Public Economics - - State and Local Government; Intergovernmental Relations - - - Intergovernmental Relations; Federalism
    • R52 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Land Use and Other Regulations
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy

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