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Citizens’ Versus Consumers’ Attitudes Toward Renewable Electricity: What the Literature Tells Us in a Contingent Valuation Framework

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The Economic Valuation of Green Electricity

Part of the book series: SpringerBriefs in Environmental Science ((BRIEFSENVIRONMENTAL))

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Abstract

In dealing with renewable electricity (RE), individuals are involved both as end consumers on the demand side and as stakeholders (citizens) in the local production process on the supply side. Empirical evidence shows that in many countries, consumers are willing to pay a significant amount to facilitate adoption of RE. In contrast, environmental externalities are often the cause of strong opposition to RE adoption if local communities are involved as stakeholders in wind, solar, or biomass investment projects. Looking at the literature on willingness to pay and on willingness to accept, we have investigated RE acceptance mechanisms. In this chapter, we use a meta-analysis to assess the major determinants of RE acceptance on both the demand and supply sides. This meta-analysis has provided some insights that are useful for managing field research on an onshore wind farm enlargement project located in the Umbria region of Italy. The meta-analysis and survey results confirm that the local community plays a central role in local RE acceptance. Furthermore, people who have previous experience of windmills require less compensation, or are willing to pay more, for RE development. The results suggest that these attributes should be included in future research to improve understanding of determinants of RE acceptance.

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Notes

  1. 1.

    For a recent review see Herbse and Frienge (2017).

  2. 2.

    The new European Union (EU) targets involve (1) a reduction of 40% in greenhouse gas emissions, with binding targets for Member States for non–Emissions Trading System (non-ETS) sectors; (2) increasing the share of renewable energy sources (REnS) by 27% of final consumption of energy without binding targets at the Member State level; and (3) a 27% increase in energy efficiency, which could be revised with a rise to 30%.

  3. 3.

    This new scenario points out the relevance of knowledge of the determinants of RE acceptance/opposition, on both the demand and supply sides, in designing new energy policy agenda. The relevance is strengthened by the fact that consumers perceive RE as a clean and environmentally friendly good even if establishment of REnS infrastructure meets strong local opposition regarding siting processes, such as in wind energy, biomass, and large photovoltaic plant projects (Wüstenhagen et al. 2007; Kaldellis et al. 2013).

  4. 4.

    This last topic is related to the impact of existing wind farms on the attitudes and preferences of respondents.

  5. 5.

    In the meta-analysis, controlling for heterogeneity, we have also tried to take into account these aspects whenever possible.

  6. 6.

    In the literature, these reference levels are usually calculated as the average level of production of RE and the purchase price used in the survey. Reference levels can vary considerably between primary studies, so comparison of WTP/WTA values obtained using different utility function specifications can be difficult and puzzling.

  7. 7.

    For each study, we take into account, as far as possible, the initial and the final value of rationed good, RG0 and RG1 respectively. The change in rationed good (ΔRG) objective of the environmental policy.

  8. 8.

    This survey is included in more wide CV studies in which the monetary evaluation is obtained through the development of a hypothetical market. We use the results of the preliminary survey to test the questionnaire.

  9. 9.

    The project involves the installation of 16 towers for wind generation of electricity. Precisely, the plan should provide for the installation of four towers reaching 40–60 m in Pian di Spilli (in the municipality of Costacciaro) and in Val di Ronco (in the municipality of Sigillo), and eight similar towers in the municipalities of Scheggia Pascelupo and Fossato di Vico. Each tower will have a maximum power of 1 MW.

  10. 10.

    Initially, respondents are asked if they perceive the project as positive and consequently if they want to support the project (i.e., WTP). Otherwise respondents can declare their opposition to the project, due to their negative perception, and consequently they are asked if they are willing to accept monetary compensation for the project (WTA).

  11. 11.

    Both equations are estimated using unweighted and weighted least squares estimators. In particular, the weighted ordinary least squares (wOLS) estimator is superior to the conventional random effects estimator when the meta-analysis refers to a small sample (Stanley and Doucouliagos 2013), such as in this chapter. We have reduced selection distortion, using, as far as possible, published papers and working papers, by correcting for heteroscedasticity. Finally, we want to underline that in both models we have used a log-linear specification because transformed data are less sensitive to the problem of heteroscedasticity.

  12. 12.

    In other words, both WTP for RE households’ consumption and WTP/WTA for wind farm production refer to kilowatt hours.

  13. 13.

    Consumption data are available from the World Energy Council website (http://www.wec-indicators.enerdata.eu/thermal-electricity-use.html). For the UK, additional information is available from the Department of Energy and Climate Change website (https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/65940/7341-quarterly-energy-prices-december-2012.pdf). For Italy, additional information is available from the Terna (http://www.terna.it/) and Gestore dei Servizi Energetici (GSE) (http://www.gse.it) websites. Information on capacity factors is gathered by the websites https://www.eia.gov and https://community.ieawind.org. Finally, information on exchange rates and deflators is gathered by the websites https://www.bloomberg.com and https://www.oanda.com.

  14. 14.

    RE consumption is expressed in logarithm.

  15. 15.

    A possible explanation is that current environmental policy uses too many strategies and consequently environmental targets are not clear to the citizens who perceive a lack of policy efficacy (European Environmental Bureau 2010).

  16. 16.

    The type of resistance is dichotomized into a variable, which takes the value one if it is NIMBY syndrome and zero otherwise.

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Authors and Affiliations

  1. Università di Perugia, Perugia, Italy

    Simona Bigerna & Paolo Polinori

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  1. Simona Bigerna
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Bigerna, S., Polinori, P. (2019). Citizens’ Versus Consumers’ Attitudes Toward Renewable Electricity: What the Literature Tells Us in a Contingent Valuation Framework. In: The Economic Valuation of Green Electricity. SpringerBriefs in Environmental Science. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-1574-2_1

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