Semiparametric Approaches to Welfare Evaluations in Binary Response Models
比较了不同半参数方法在二元响应模型中恢复福利收益条件分布的效果，发现这些方法能捕捉到被Logit模型忽略的异质性结构，若忽视该结构可能导致基于Kaldor-Hicks准则的项目误判。
Applied welfare analysis is commonly based on mean or median benefit estimates. However, the whole conditional distribution of benefits is often of interest for policy makers. This article compares the distributional information recovered by competing semiparametric methods. Results obtained using a valuation study for the improvement of water resources in Brazil suggest that the semiparametric approaches are in line with each other, capturing a rich heterogeneity structure that is ignored by the logit approach. Failure to take this structure into account may lead to the undue rejection of the project according to the Kaldor–Hicks criterion.