ESTIMATION IN AN INSTRUMENTAL VARIABLES MODEL WITH TREATMENT EFFECT HETEROGENEITY
ESTIMATION IN AN INSTRUMENTAL VARIABLES MODEL WITH TREATMENT EFFECT HETEROGENEITY
复制标题
具有治疗效果异质性的工具变量模型中的估计
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
M. Kolesár
中科院分区：
文献类型：
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作者：
M. Kolesár
本文分析了基于经典线性工具变量模型的估计量，当治疗效果实际上是异质的，如Imbens和Angrist（1994）。我把这些估计分为两类：两步工具变量（tsiv）估计，包括两阶段最小二乘（tsls）估计;和最小距离估计，包括有限信息最大似然（liml）估计。我表明，如果局部平均治疗效果不同，则tsiv类中的估计量通常都会估计它们的相同凸组合。相反，最小距离估计量的被估量可能在局部平均治疗效应的凸船体之外，因此可能不对应于因果效应。这一结果质疑了当仪器数量很大时使用liml作为解决这些设置中tsls所表现出的偏倚的方法的标准建议。相反，我提出了一个新的tsiv估计，一个版本的刀切工具变量估计（ujive）。与tsls或liml不同，ujive在许多工具渐近下对于局部平均处理效应的凸组合是一致的，这些工具渐近也允许许多协变量和异方差。因此，我建议研究人员在使用多种仪器的情况下使用ujive，而不是tsls或liml。
This paper analyzes estimators based on the classic linear instrumental variables model when the treatment effects are in fact heterogeneous, as in Imbens and Angrist (1994). I divide these estimators into two classes: two-step instrumental variables (tsiv) estimators that include the two-stage least squares (tsls) estimator; and minimum distance estimators that include the limited information maximum likelihood (liml) estimator. I show that if the local average treatment effects vary, estimators in the tsiv class typically all estimate the same convex combination of them. In contrast, estimands of minimum distance estimators may be outside of the convex hull of the local average treatment effects, and may therefore not correspond to a causal effect. This result questions the standard recommendation to use liml when the number of instruments is large as a way of addressing the bias exhibited by tsls in these settings. Instead, I propose a new tsiv estimator, a version of the jackknife instrumental variables estimator (ujive). Unlike tsls or liml, ujive is consistent for a convex combination of local average treatment effects under many instrument asymptotics that also allow for many covariates and heteroscedasticity. I therefore recommend that in settings with many instruments researchers use ujive, instead of tsls or liml.
DOI：
10.1073/pnas.96.8.4730
发表时间：
1999-04-13
影响因子：
11.1
作者：
Heckman, JJ;Vytlacil, EJ
通讯作者：
Vytlacil, EJ