Consumers’ willingness to pay for renewable energy: A meta-regression analysis

Abstract

JEL classification: C53 D62 Q40 Q48 Q51Keywords: Meta-regression Renewable energy Green electricity Valuation Willingness to pay a b s t r a c t Using renewable energy for domestic consumption has been identified as a key strategy by the Intergovernmental Panel on Climate Change to reduce greenhouse gas emissions. Critical to the success of this strategy is to know whether consumers are willing to pay to increase the proportion of electricity generated from renewable energy in their electricity portfolio. There are a number of studies in the literature that report a wide range of willingness to pay estimates. In this study, we used a meta-regression analysis to determine how much of the variation in willingness to pay reflects true differences across the population and how much is due to study design, such as survey design and administration, and model specification. The results showed that factors that influence willingness to pay, such as renewable energy type, consumers' socio-economic profile and consumers' energy consumption patterns, explain less variation in willingness to pay estimates than the characteristics of the study design itself. Because of this effect, we recommend that policy makers exercise caution when interpreting and using willingness to pay results from primary studies. Our meta-regression analysis further shows that consumers have significantly higher (C. Ma). http://dx.doi.org/10.1016/j.reseneeco.2015.07.003 0928-7655/© 2015 Elsevier B.V. All rights reserved. 94 C. Ma et al. / Resource and Energy Economics 42 (2015) 93-109willingness to pay for electricity generated from solar, wind or generic renewable energy source (i.e. not a specific source) than hydro power or biomass.

Green Returns to Education: Does Schooling Contribute to Pro-Environmental Behaviours? Evidence from Thailand

“…While a series of literature showed that education is an important indicator of willingness to pay higher prices and higher taxes for the protection of the environment (Bigerna and Polinori, 2014;Franzen and Vogl, 2013;Ivanova and Tranter, 2008;Kotchen et al, 2013;Zhang and Wu, 2012;Zorić and Hrovatin, 2012), some studies reported no significant or negative relationships between education and willingness to pay for the environment (Dorsch, 2011;Gökşen et al, 2002;Ma et al, 2015). Indeed, Adaman et al (2011) found it rather surprising that in Turkey individuals with university degree are not significantly more willing to pay for CO2 emission reductions from power production than those with no qualification.…”

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

“…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.…”

How Do Chinese Residents Expect of Government Subsidies on Solar Photovoltaic Power Generation?—A Case of Wuhan, China

“…(2) Comparative analysis Most scholars focus on the factors that affect the WTP for renewable energy [15,30], while we focus on the factors that influence residents' expectations of government subsidies for renewable energy. Uehleke [13] argued that gender had a significant impact on WTP; in our study, however, gender was found to have little effect on the results.…”