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首页> 外文期刊>Ecological Economics >Public Support For Reducing Us Reliance On Fossil Fuels: Investigating Household Willingness-to-pay For Energy Research And Development
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Public Support For Reducing Us Reliance On Fossil Fuels: Investigating Household Willingness-to-pay For Energy Research And Development

机译:减少我们对化石燃料的依赖的公共支持:调查家庭为能源研究与开发支付的意愿

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摘要

In order to reduce future dependence on foreign oil and emissions of CO_2, how much would US households be willing to pay annually to support increased energy research and development (R&D) activities designed to replace fossil fuels? Does it matter whether the R&D includes nuclear energy options? We explore these questions using data from a unique set of national telephone and Internet surveys. Using a national advisory referendum format, the contingent valuation method is applied to estimate annual household willingness-to-pay (WTP) for US household support of a national Energy Research and Development Fund (ERDF) for investments in energy sources not reliant on fossil fuels. While accounting for the level of (un)certainty in voting responses, the WTP modeling includes a comparison of both classic maximum likelihood estimation (MLE) and Bayesian analysis. Evidence indicates that MLE and Bayesian analysis achieve similar statistical inference, while the Bayesian analysis provides a narrower confidence interval around estimated WTP.
机译:为了减少将来对外国石油和CO_2排放的依赖,美国家庭愿意每年支付多少钱来支持旨在替代化石燃料的能源研究与开发(R&D)活动?研发是否包括核能选择是否重要?我们使用来自一组独特的国家电话和互联网调查的数据来探讨这些问题。使用国家咨询公投格式,采用或有估值法,以估算美国家庭每年对国家能源研究与发展基金(ERDF)的家庭支持的支付意愿(WTP),以用于不依赖化石燃料的能源投资。在考虑投票响应中(不确定)水平的同时,WTP建模包括经典最大似然估计(MLE)和贝叶斯分析的比较。证据表明,MLE和贝叶斯分析获得了相似的统计推断,而贝叶斯分析在估计的WTP周围提供了更窄的置信区间。

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