Independence, monotonicity, and latent index models: An equivalence result
Independence, monotonicity, and latent index models: An equivalence result
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DOI：
10.1111/1468-0262.00277
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发表时间：
2002-01-01
期刊：
影响因子：
6.1
通讯作者：
Vytlacil, E
中科院分区：
文献类型：
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作者：
Vytlacil, E
经济学中的一个常见问题是当个体自我选择是否接受治疗时评估治疗的效果。当试图评估工会/非工会工资差异、职业培训对收入的影响以及学校教育的回报时，就会出现这个问题，其中加入工会或进行人力资本投资是待遇，解决这个问题的一个标准方法是使用Heckman（1976）首次提出的选择模型。在这种方法下，研究人员模型选择到程序的潜在指数跨越阈值，其中的潜在指数被解释为预期的净效用选择到治疗。然而，一些统计学家批评甚至拒绝使用选择模型来估计治疗效果，认为这种分析本质上是由分布和功能形式假设驱动的。[2]这种观点在经济学中也得到了回应。局部平均治疗效应（LATE）框架是由Imbens和Angrist（1994）开发的线性工具变量（IV）分析的一种形式。3、像
A COMMON PROBLEM IN ECONOMICS is to evaluate the effect of a treatment when individuals self-select whether to receive the treatment. This problem arises when trying to evaluate the union/nonunion wage differential, the effect of job training on earnings, and the returns to schooling, where being unionized or making a human capital investment is the treatment.One standard approach to this problem is the use of a selection model as first proposed by Heckman (1976). Under this approach, the researcher models selection into the program by a latent index crossing a threshold, where the latent index is interpreted as the expected net utility of selecting into treatment. However, some statisticians have criticized or even dismissed the use of selection models to estimate treatment effects, arguing that such analysis is inherently driven by distributional and functional form assumptions. 2 This sentiment has been echoed within economics. The local average treatment effect (LATE) framework is a form of linear instrumental variables (IV) analysis developed by Imbens and Angrist (1994). 3 However, like the