Instrumental Variable Models for Discrete Outcomes
证明离散结果的单方程工具变量模型只能识别结构函数的集合而非点，推导了非参数模型的边界，并扩展了结构分位数函数分析至离散结果情形。
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.