G2TT
来源类型FEEM working papers "Note di lavoro" series
规范类型论文
Does a Third Bound Help? Parametric and Nonparametric Welfare Measures from a CV Interval Data Study
Riccardo Scarpa; Ian Bateman
发表日期1998
出处Climate Change and Sustainable Development
出版年1998
语种英语
摘要Positive response density estimation from CV interval data affords efficiency gains which must be weighed against the risk of introducing potential bias during questions iteration. This study examines the effect of eliciting a third response on a set of often-used welfare measures derived in a conventional parametric setting. It then compares these with distribution-free nonparametric estimates. A third bound increases censoring probability, introduces welfare estimates sensitivity to inclusion of a theoretically relevant covariate such as wealth which also affects efficiency gains. This might well introduce complications that outweigh the expected efficiency gain. This empirical finding supports and complements previous results obtained via simulation.
特色分类C14,C42,H41
关键词Parametric,Nonparametric Welfare measures,Contingent valuation (CV),Willingness to pay (WTP)
URLhttps://www.feem.it/en/publications/feem-working-papers-note-di-lavoro-series/does-a-third-bound-help-parametric-and-nonparametric-welfare-measures-from-a-cv-interval-data-study/
来源智库Fondazione Eni Enrico Mattei (Italy)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/116347
推荐引用方式
GB/T 7714
Riccardo Scarpa,Ian Bateman. Does a Third Bound Help? Parametric and Nonparametric Welfare Measures from a CV Interval Data Study. 1998.
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NDL1998-051.pdf(294KB)智库出版物 限制开放CC BY-NC-SA浏览
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