Identification of Binary Response Models
Identification of Binary Response Models
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DOI：
10.1080/01621459.1988.10478655
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发表时间：
1988-09
影响因子：
3.7
通讯作者：
C. Manski
中科院分区：
文献类型：
--
作者：
C. Manski
摘要本文研究二元响应阈值交叉模型的辨识。大多数关于二元响应的研究都考虑了特定的估计器和测试。识别的研究通过明确证明不同方法所需的假设，暴露了二元响应分析的基础。阐明了二元响应数据的简化分析与结构分析之间的联系。假设二元结果z由一个可观察的随机向量x和一个不可观察的标量u通过模型z = 1[xβ + u≤0]决定。同时假设u在x条件下的概率分布Fu|x是连续且严格递增的。在这些维持的假设下，我们研究了给定分布（Fu|x, x∈x）的下列限制条件下β的可辨识性：平均独立性、分位数独立性、指数充分性、统计独立性和已知分布的统计独立性。我们发现平均独立性有n。
Abstract This article studies identification of the threshold-crossing model of binary response. Most research on binary response has considered specific estimators and tests. The study of identification exposes the foundations of binary response analysis by making explicit the assumptions needed to justify different methods. It also clarifies the connections between reduced-form and structural analyses of binary response data. Assume that the binary outcome z is determined by an observable random vector x and by an unobservable scalar u through a model z = 1[xβ + u ≤ 0]. Also assume that Fu|x , the probability distribution of u conditional on x, is continuous and strictly increasing. Given these maintained assumptions, we investigate the identifiability of β given the following restrictions on the distributions (Fu|x, x ∈ X): mean independence, quantile independence, index sufficiency, statistical independence, and statistical independence with the distribution known. We find that mean independence has n...