Abstract:
At present, electricity generated from power plants using renewable sources costs more than electricity generated from power plants using conventional fuels. Consumers bear these expenses directly or indirectly through higher prices for renewable energy or taxes. The number of studies published over the last few years focusing on people's preferences for renewables has increased steadily, making it more and more difficult to identify key explanatory factors that determine people's willingness-to-pay (WTP) for renewables. We present results of a meta-regression on valuation of consumer preferences for a larger share of renewable energy in their electricity mix. Our meta-regression results reveal a number of important factors that explain the differences in WTP values for renewable energy. Different valuation methods show widely different values, with choice experiments producing the highest estimates. Our results further indicate that consumers' WTP for green electricity differs by source, with hydropower being the least valued. Variables that are often omitted from primary valuation studies are important in explaining differences in values. These variables describe individual and household characteristics as well as information on the type of power plant that will be replaced by renewables. Further, the marginal effect of a survey conducted in the US is pronounced. We also assess the potential for using the results for out-of-sample value transfer and find a median error of 21%.
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An extensive search for publish and unpublished ... studies relating to WTP for renewable energy was conducted on Web of Science, EconBiz, and Google Scholar and following references of relevant studies.... Overall, we count 23 studies for Europe, twelve for the Americas and six for Asia. At the country level, most of the surveys were conducted in the US (twelve publications ...). Among the 43 studies, we exclude 25 from the meta-regression because of sample selection bias (e.g., Gossling et al., 2005) or unsuitable units of WTP estimates; that is, inconvertible.... Our final meta-regression consists of 85 WTP values that are ascertained from 18 studies.... To ensure comparability, we convert WTP values in US$ per household per month and adjust them to 2010 prices using purchasing power parity exchange rates.
In our sample, the mean WTP for a higher renewable energy share in the electricity mix is US$13.13 per household per month and the median WTP is US$11.67. The lowest WTP (US$1.00) is found by Borchers et al. (2007) for an increase in biomass in the US. Hanemann et al. (2011) report the highest WTP (US$43.01) for an increase in renewables in Spain. Overall, the distribution of WTP values is positive skewed. When WTP is measured in kilowatt-hours, the mean WTP is US-Cents 3.18/kilowatt-hour and the median WTP is US-Cents 1.95/kilowatt-hour.
At the country level (see Fig. 2), the highest mean WTP per household (US$21.39), which corresponds to a mean WTP per kilowatthour of US-Cents 3.07, is observed for Finland. However, we observe the opposite for Chile, the country with the second lowest residential energy consumption per capita. Here, the WTP per household (US$10.98) is below average while the WTP per kilowatt-hour (US-Cents 6.82) is ranked highest. Furthermore, China and South Korea have the lowest WTP per household and per kilowatt-hour. Although Japan demonstrates an above average WTP per household, the average WTP for Asia (see Fig. 3) is half that of European countries and countries in the Americas, which are quite similar. With respect to the average WTP per kilowatt-hour, the WTP for Asia is the lowest. However, in contrast to the WTP per household, there exists a significant difference between the mean WTP for the Americas (US-Cents 2.49) and for Europe (US-Cents 4.43)
At present, electricity generated from power plants using renewable sources costs more than electricity generated from power plants using conventional fuels. Consumers bear these expenses directly or indirectly through higher prices for renewable energy or taxes. The number of studies published over the last few years focusing on people's preferences for renewables has increased steadily, making it more and more difficult to identify key explanatory factors that determine people's willingness-to-pay (WTP) for renewables. We present results of a meta-regression on valuation of consumer preferences for a larger share of renewable energy in their electricity mix. Our meta-regression results reveal a number of important factors that explain the differences in WTP values for renewable energy. Different valuation methods show widely different values, with choice experiments producing the highest estimates. Our results further indicate that consumers' WTP for green electricity differs by source, with hydropower being the least valued. Variables that are often omitted from primary valuation studies are important in explaining differences in values. These variables describe individual and household characteristics as well as information on the type of power plant that will be replaced by renewables. Further, the marginal effect of a survey conducted in the US is pronounced. We also assess the potential for using the results for out-of-sample value transfer and find a median error of 21%.
...
An extensive search for publish and unpublished ... studies relating to WTP for renewable energy was conducted on Web of Science, EconBiz, and Google Scholar and following references of relevant studies.... Overall, we count 23 studies for Europe, twelve for the Americas and six for Asia. At the country level, most of the surveys were conducted in the US (twelve publications ...). Among the 43 studies, we exclude 25 from the meta-regression because of sample selection bias (e.g., Gossling et al., 2005) or unsuitable units of WTP estimates; that is, inconvertible.... Our final meta-regression consists of 85 WTP values that are ascertained from 18 studies.... To ensure comparability, we convert WTP values in US$ per household per month and adjust them to 2010 prices using purchasing power parity exchange rates.
At the country level (see Fig. 2), the highest mean WTP per household (US$21.39), which corresponds to a mean WTP per kilowatthour of US-Cents 3.07, is observed for Finland. However, we observe the opposite for Chile, the country with the second lowest residential energy consumption per capita. Here, the WTP per household (US$10.98) is below average while the WTP per kilowatt-hour (US-Cents 6.82) is ranked highest. Furthermore, China and South Korea have the lowest WTP per household and per kilowatt-hour. Although Japan demonstrates an above average WTP per household, the average WTP for Asia (see Fig. 3) is half that of European countries and countries in the Americas, which are quite similar. With respect to the average WTP per kilowatt-hour, the WTP for Asia is the lowest. However, in contrast to the WTP per household, there exists a significant difference between the mean WTP for the Americas (US-Cents 2.49) and for Europe (US-Cents 4.43)
The full paper is currently available free of charge via www.ResearchGate.net at http://tinyurl.com/jy8rhxt.
http://www.sciencedirect.com/science/article/pii/S0140988315001784
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http://www.sciencedirect.com/science/article/pii/S0140988315001784
Energy Economics via Elsevier Science Direct www.ScienceDirect.Com
Volume 51; September, 2015; Pages 1–8
by Swantje Sundt 1 and Katrin Rehdanza 2
1. Kiel Institute for the World Economy, Kiellinie 66, 24105 Kiel, Germany
2. University of Kiel, Department of Economics, 24098 Kiel, Germany
Tel.: + 49 431 8814 408
Volume 51; September, 2015; Pages 1–8
by Swantje Sundt 1 and Katrin Rehdanza 2
1. Kiel Institute for the World Economy, Kiellinie 66, 24105 Kiel, Germany
2. University of Kiel, Department of Economics, 24098 Kiel, Germany
Tel.: + 49 431 8814 408
Keywords: Meta-analysis; Renewable energy; Valuation; Value transfer; Willingness to pay
Highlights
• A large WTP per household is not necessarily accompanied by a large WTP per kWh.
• WTP for green electricity differs by source, hydropower being the least valued.
• WTP for renewables increases if they substitute conventional energy sources.
• WTPs differ when a respondent's personal characteristics are accounted for.
• The out-of-sample value transfer leads to a median error of around 21%.
• A large WTP per household is not necessarily accompanied by a large WTP per kWh.
• WTP for green electricity differs by source, hydropower being the least valued.
• WTP for renewables increases if they substitute conventional energy sources.
• WTPs differ when a respondent's personal characteristics are accounted for.
• The out-of-sample value transfer leads to a median error of around 21%.
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