Consumers' willingness to pay for green electricity: A meta-analysis of the literature

Sundt, Swantje; Rehdanz, Katrin

doi:10.1016/j.eneco.2015.06.005

Cited by 190 publications

(112 citation statements)

References 42 publications

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“…The findings reported above are consistent with those found in a meta-regression analysis by Sundt and Rehdanz [76]:pp.7, who state that including "knowledge about renewables, household characteristics, income and education significantly influences WTP estimates. Ignoring these attributes in future WTP estimations might result in biased coefficients".…”

Section: Antecedents Of Wtp For Green Electricity In Contingent Valuasupporting

confidence: 81%

Willingness to pay for green electricity: A review of the contingent valuation literature and its sources of error

Oerlemans

Chan

Volschenk

2016

Renewable and Sustainable Energy Reviews

115

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Contingent valuation is widely used due to its flexibility in valuing a wide variety of nonmarket goods. Although this method has important benefits, its validity and reliability are often criticised. This paper reviews the literature on the use of contingent valuation for measuring willingness to pay (WTP) for electricity generated from renewable energy sources (green electricity). A literature review, conducted on a sample of 51 peer-reviewed studies, shows that the vast majority of contingent evaluation studies stems from developed economies. Furthermore, most frequently used WTP elicitation techniques are open-ended and dichotomous choice approaches, which tend to produce varying levels of WTP. Studies dealing with the antecedents of WTP are predominantly inspired by the theory of reasoned action or by its extension, the theory of planned behaviour. This paper identifies five common errors in contingent valuation methods and discusses a number of remedies to deal with these errors in WTP research.

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Section: Antecedents Of Wtp For Green Electricity In Contingent Valuasupporting

confidence: 81%

Willingness to pay for green electricity: A review of the contingent valuation literature and its sources of error

Oerlemans

Chan

Volschenk

2016

Renewable and Sustainable Energy Reviews

115

View full text Add to dashboard Cite

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“…14 Meta-analyses have focused on the preference for hydropower (Mattmann 2016a), wind power (Mattmann et al 2016b), preferences for renewables in general (Sundt and Rehdanz 2015), preferences for several types of renewables in comparison with each other (Ma et al 2015), and preferences for several conventional and renewable technologies in comparison with each other (Sundquist 2004). Except for the latter article, they primarily refer to stated preference primary studies.…”

Section: Meta-analysesmentioning

confidence: 99%

“…Noise effects and wind power's contribution to fuel independence could not be included in the meta-analysis because the number of pertinent studies was too small. Sundt and Rehdanz (2015) report results from a meta-regression analysis of consumers'…”

Section: Meta-analysesmentioning

confidence: 99%

Electricity Externalities, Siting, and the Energy Mix: A Survey

Welsch

2016

IRERE

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWhile early literature on electricity externalities was largely concerned with fossil fuel power generation and the associated emissions, nuclear accidents (Chernobyl, Fukushima) and the large-scale deployment of renewable energy facilities have spurred a wave of research on the externalities of nuclear power and renewable energies. The issue is important because many countries have started reconsidering their energy policies, and the externalities from electricity generation play a major role in the benefit-cost analysis of relevant options. This paper reviews the literature on electricity-related externalities. It starts by discussing their nature and the methods employed in valuing them. It finds that appraisals of electricity externalities are complicated because of heterogeneity of both the externalities themselves and the methods applied in measuring them. The paper reviews valuation studies of the externalities from fossil fuel, nuclear and renewable sources, and it discusses the relevance of their findings for the siting of plants and the electricity mix. It concludes by pointing out gaps in our knowledge about electricity externalities that deserve to be addressed in future research.

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“…The outcome could also be employed towards the internalization of externalities from electric power transmission, besides the production externalities usually considered in the literature (e.g. Longo et al, 2008;Realdon, 2013;Sundt and Rehdanz, 2015), in the price of energy commodities. Our results can be summarized as follows.…”

Section: Discussionmentioning

confidence: 99%

Valuing externalities from energy infrastructures through stated preferences: a geographically stratified sampling approach

2016

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The externalities produced by high voltage transmission lines are multi-dimensional, may strongly depend on the local context, and are thus difficult to capture through standard environmental valuation exercises. We experiment a GIS approach to design a geographically stratified contingent valuation sample of the population resident in infrastructure corridors in a whole region. We estimate, by means of a binary choice logit model, the perceived marginal damage from impacts of power lines on human health, the landscape and the environment. Specific treatment is given to qualitatively different forms of impact, namely real estate depreciation vs. diffused perception of damage, arising at different distances from the lines. The set of GIS-based variables (proximity to power lines, presence of other infrastructure, endowment of natural and built heritage and other local context variables) prove to be significant predictors in the utility function of resident households. Finally, we compute simulated values that combine information on individual willingness to pay, population density and the dimension of the considered corridor around the infrastructure, so as to generalize the outcomes of case-specific studies for use in policy choices such as infrastructure localization, undergrounding and negotiation of compensations.

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Consumers' willingness to pay for green electricity: A meta-analysis of the literature

Cited by 190 publications

References 42 publications

Willingness to pay for green electricity: A review of the contingent valuation literature and its sources of error

Willingness to pay for green electricity: A review of the contingent valuation literature and its sources of error

Electricity Externalities, Siting, and the Energy Mix: A Survey

Valuing externalities from energy infrastructures through stated preferences: a geographically stratified sampling approach

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