Instrumental Variable Models for Discrete Outcomes
Instrumental Variable Models for Discrete Outcomes
复制标题
离散结果的工具变量模型
DOI：
10.1920/wp.cem.2008.3008
复制
发表时间：
2008
期刊：
影响因子：
6.1
通讯作者：
A. Chesher
中科院分区：
文献类型：
--
作者：
A. Chesher
离散结果的单方程工具变量模型显示为提供离散结果值的结构函数的集合识别，而不是点识别。对于一般的非参数模型，导出了识别集的界，并证明了在二元结果情况下的尖锐集识别。点识别通常不能通过施加参数限制来实现。已识别集合的范围随工具的强度和支持而变化，并且通常随着离散结果支持的增加而缩小。本文将具有内生参数的结构分位数函数的分析扩展到存在离散结果的情况。经济计量学会版权所有。
Single equation instrumental variable models for discrete outcomes are shown to be set identifying, not point identifying, for the structural functions that deliver the values of the discrete outcome. Bounds on identified sets are derived for a general nonparametric model and sharp set identification is demonstrated in the binary outcome case. Point identification is typically not achieved by imposing parametric restrictions. The extent of an identified set varies with the strength and support of instruments, and typically shrinks as the support of a discrete outcome grows. The paper extends the analysis of structural quantile functions with endogenous arguments to cases in which there are discrete outcomes. Copyright 2010 The Econometric Society.