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

机译:消费者购买绿色电力的意愿:对文献的荟萃分析

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摘要

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%. (C) 2015 Elsevier B.V. All rights reserved.
机译:当前,使用可再生资源的发电厂产生的电力成本高于使用常规燃料的发电厂产生的电力成本。消费者通过提高可再生能源价格或税收直接或间接承担这些费用。在过去几年中,针对人们对可再生能源的偏爱而发表的研究数量稳步增长,这使得确定决定人们对可再生能源的支付意愿(WTP)的关键解释因素变得越来越困难。我们提出了对消费者偏好评估的元回归结果,这些消费者偏好在其电力结构中可再生能源的份额更大。我们的元回归结果揭示了许多重要因素,这些因素可以解释可再生能源WTP值的差异。不同的评估方法显示出截然不同的价值,选择实验产生的估算值最高。我们的结果进一步表明,消费者的绿色电力WTP因来源而异,其中水电的价值最低。初级估值研究中通常会省略的变量对于解释价值差异非常重要。这些变量描述了个人和家庭特征以及有关将由可再生能源替代的电厂类型的信息。此外,在美国进行的一项调查的边际效应很明显。我们还评估了将结果用于样本外值转移的可能性,发现中值误差为21%。 (C)2015 Elsevier B.V.保留所有权利。

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