One-and-one-half-bound dichotomous choice contingent valuation
One-and-one-half-bound dichotomous choice contingent valuation
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DOI：
10.1162/003465302760556549
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发表时间：
2002-11-01
影响因子：
8
通讯作者：
Signorello, G
中科院分区：
文献类型：
--
作者：
Cooper, JC;Hanemann, M;Signorello, G
虽然离散选择条件估值法（CVM）的双界（DB）格式在福利收益估计方面比单界（SB）离散选择CVM具有更高的效率，但它一直受到批评，因为有证据表明，第二次投标的一些响应可能与第一次投标的响应不一致。作为一种手段，以减少潜在的响应偏差的后续出价在多约束离散选择格式，如DB模型，同时保持多约束的方法的效率收益，我们介绍了一个半约束（OOHB）的方法，并提出了一个现实世界中的应用。在实验室环境中，尽管OOHB模型使用的信息比DB方法少，但从SB到OOHB的效率增益捕获了与从SB到DB相关的大部分增益。利用分布免费的split-survey数据集上的非参数估计技术，我们的OOHB估计表现出更高的一致性，就后续数据比DB估计，更有效。因此，OOHB可以作为一个可行的替代DB格式的情况下，随访反应偏差可能是一个问题。
Although the double-bound (DB) format for the discrete choice contingent valuation method (CVM) has the benefit of higher efficiency in welfare benefit estimates than the single-bound (SB) discrete choice CVM, it has been subject to criticism due to evidence that some of the responses to the second bid may be inconsistent with the responses to the first bid. As a means to reduce the potential for response bias on the follow-up bid in multiple-bound discrete choice formats such as the DB model while maintaining much of the efficiency gains of the multiple-bound approach, we introduce the one-and-one-half-bound (OOHB) approach and present a real-world application. In a laboratory setting, despite the fact that the OOHB model uses less information than the DB approach, the efficiency gains in moving from SB to OOHB capture a large portion of the gain associated with moving from SB to DB. Utilizing distribution-free seminonparametric estimation techniques on a split-survey data set, our OOHB estimates demonstrated higher consistency with respect to the follow-up data than the DB estimates and were more efficient as well. Hence, OOHB may serve as a viable alternative to the DB format in situations where follow-up response bias may be a concern.