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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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  • Anabela Botelho & Lígia Costa Pinto & Patricia Sousa, 2013. "Valuing wind farms’ environmental impacts by geographical distance: A contingent valuation study in Portugal," NIMA Working Papers 52, Núcleo de Investigação em Microeconomia Aplicada (NIMA), Universidade do Minho.
    • Handle: RePEc:nim:nimawp:52/2013
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    Cited by:

    1. Anabela Botelho & Lina Lourenço-Gomes & Lígia Pinto & Sara Sousa & Marieta Valente, 2016. "Using stated preference methods to assess environmental impacts of forest biomass power plants in Portugal," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 18(5), pages 1323-1337, October.
    2. Mattmann, Matteo & Logar, Ivana & Brouwer, Roy, 2016. "Wind power externalities: A meta-analysis," Ecological Economics, Elsevier, vol. 127(C), pages 23-36.

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    More about this item

    Keywords

    Contingent Valuation; uncertainty; renewable energy; Stochastic frontier models; Willingness to pay/accept; hypothetical bias;
    All these keywords.

    JEL classification:

    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • C29 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Other
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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