One-and-One-Half-Bound Dichotomous Choice Contingent Valuation
提出一种新的二分选择条件估值格式（单半界法），在减少后续回答偏差的同时保持较高效率，并通过实验室数据和半参数估计验证其优于传统双界法。
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. © 2002 President and Fellows of Harvard College and the Massachusetts Institute of Technology.