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Valuing wind farms’ environmental impacts by geographical distance: A contingent valuation study in Portugal

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Abstract

Wind energy is currently one the most important energy sources in the production of electricity. In this study, we use the CVM to elicit the monetary value attached to wind power’s environmental impacts from three different groups of individuals: local residents, residents in a nearby town, and residents outside the area of a wind farm located in Portugal, one of the top 10 countries in the world with the highest cumulative wind power capacity to date. In each case, our empirical analysis employs a novel likelihood function that is constructed to be appropriate for the type of data collected. The main results are supportive of a NYMBY effect, but also indicate that the amount needed to compensate local residents for the negative impacts caused by the wind farm can be raised by the constitution of a compensation fund paid by non-residents, thereby overcoming the inefficiency caused by the NYMBY effect.

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Paper provided by Núcleo de Investigação em Microeconomia Aplicada (NIMA), Universidade do Minho in its series NIMA Working Papers with number 52.

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Length: 17 pages
Date of creation: Jul 2013
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Handle: RePEc:nim:nimawp:52/2013

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Related research

Keywords: Contingent Valuation; uncertainty; renewable energy; Stochastic frontier models; Willingness to pay/accept; hypothetical bias;

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  6. Ladenburg, Jacob & Dubgaard, Alex, 2007. "Willingness to pay for reduced visual disamenities from offshore wind farms in Denmark," Energy Policy, Elsevier, vol. 35(8), pages 4059-4071, August.
  7. Kunreuther, Howard & Kleindorfer, Paul & Knez, Peter J. & Yaksick, Rudy, 1987. "A compensation mechanism for siting noxious facilities: Theory and experimental design," Journal of Environmental Economics and Management, Elsevier, vol. 14(4), pages 371-383, December.
  8. Bengt Kriström, 1993. "Comparing continuous and discrete contingent valuation questions," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 3(1), pages 63-71, February.
  9. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  10. Saidur, R. & Rahim, N.A. & Islam, M.R. & Solangi, K.H., 2011. "Environmental impact of wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(5), pages 2423-2430, June.
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