Semiparametric instrumental variable estimation of treatment response models
Semiparametric instrumental variable estimation of treatment response models
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DOI：
10.1016/s0304-4076(02)00201-4
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发表时间：
2003-04-01
影响因子：
6.3
通讯作者：
Abadie, A
中科院分区：
文献类型：
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作者：
Abadie, A
本文介绍了一类新的工具变量 (IV) 估计器，用于具有协变量的线性和非线性治疗响应模型。关注非线性模型的基本原理是，如果因变量是二元变量或有限变量，或者如果处理效果随协变量而变化，则非线性模型是合适的。本着 Roehrig (Econometrica 56 (1988) 433) 的精神，识别是通过非参数方式实现的，并且不依赖于感兴趣的响应函数的参数规范的选择。这种方法的一个优点是，它允许研究人员构建估计量，这些估计量可以解释为函数形式错误指定下治疗反应函数的明确定义的近似值的参数。与一些常见的 IV 模型相反，治疗效果的异质性不受识别条件的限制。本文中的想法和估计器使用 IV 来说明，以估计 401(k) 退休计划对储蓄的影响。 (C) 2002 Elsevier Science B.V. 保留所有权利。
This article introduces a new class of instrumental variable (IV) estimators for linear and nonlinear treatment response models with covariates. The rationale for focusing on nonlinear models is that, if the dependent variable is binary or limited, or if the effect of the treatment varies with covariates, a nonlinear model is appropriate. In the spirit of Roehrig (Econometrica 56 (1988) 433), identification is attained nonparametrically and does not depend on the choice of the parametric specification for the response function of interest. One virtue of this approach is that it allows the researcher to construct estimators that can be interpreted as the parameters of a well-defined approximation to a treatment response function under functional form misspecification. In contrast to some usual IV models, heterogeneity of treatment effects is not restricted by the identification conditions. The ideas and estimators in this article are illustrated using IV to estimate the effects of 401(k) retirement programs on savings. (C) 2002 Elsevier Science B.V. All rights reserved.