Bounding program benefits when participation is misreported: Estimation and inference with Stata

Andy Lin, Denni Tommasi, Lina Zhang
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Abstract

Instrumental-variables estimation is an approach commonly used to evaluate the effect of a program in case of noncompliance. However, when the binary treatment status is misreported, standard techniques are not sufficient to point identify and consistently estimate the effect of interest. We present a new command, ivbounds, that implements three partial identification strategies developed by Tommasi and Zhang (2024, Journal of Econometrics 238: 105556) to bound the heterogeneous treatment effect when both noncompliance and misreporting of treatment status are present. We illustrate the use of the command by reassessing the benefits of participating in the 401(k) pension plan on savings in the United States.
误报参与情况时的项目收益边界:使用 Stata 进行估计和推论
工具变量估算是一种常用的方法,用于评估不遵守计划情况下的计划效果。然而,当二元治疗状态被误报时,标准技术不足以对相关效应进行点识别和一致估计。我们提出了一个新的命令 ivbounds,它实现了 Tommasi 和 Zhang(2024 年,《计量经济学杂志》238: 105556)提出的三种部分识别策略,以约束同时存在不遵守和误报治疗状态时的异质性治疗效果。我们通过重新评估参与美国 401(k) 养老金计划对储蓄的益处来说明该命令的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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