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Sowing the Wind and Reaping the Whirlwind? The Effect of Wind Turbines on Residential Well-Being

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  • Zerrahn, Alexander
  • Krekel, Christian

Abstract

This paper investigates the effect of wind turbines on residential well-being in Germany, using panel data from the German Socio-Economic Panel (SOEP) and a unique, novel data set on wind turbines for the time period between 2000 and 2012. Using a Geographical Information System (GIS), it calculates the distance from households to the nearest wind turbines to determine whether an individual is affected by disamenities, e.g. through visual pollution. The depth of our unique, novel data set on wind turbines, which has been collected at the regional level and which includes, besides their exact geographical coordinates, their construction dates, allows estimating the causal effect of wind turbines on residential well-being, using difference-in-difference propensity-score and spatial matching techniques. We demonstrate that the construction of a new wind turbine in a treatment area of 4000 metres around households has a significantly negative impact on life satisfaction. Moreover, this effect is found to be of transitory nature. Contrasting the implicit monetary valuation with the damage through CO2 emissions avoided by wind turbines, wind power turns out to be a favorable technology despite robust evidence for negative externalities.

Suggested Citation

  • Zerrahn, Alexander & Krekel, Christian, 2015. "Sowing the Wind and Reaping the Whirlwind? The Effect of Wind Turbines on Residential Well-Being," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112956, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc15:112956
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    Cited by:

    1. Krekel, Christian & Kolbe, Jens & Wüstemann, Henry, 2016. "The greener, the happier? The effect of urban land use on residential well-being," Ecological Economics, Elsevier, vol. 121(C), pages 117-127.
    2. Welsch, Heinz, 2016. "Electricity Externalities, Siting, and the Energy Mix: A Survey," International Review of Environmental and Resource Economics, now publishers, vol. 10(1), pages 57-94, November.
    3. Charlotte von Möllendorff & Heinz Welsch, 2017. "Measuring Renewable Energy Externalities: Evidence from Subjective Well-being Data," Land Economics, University of Wisconsin Press, vol. 93(1), pages 109-126.

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • R20 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - General

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