跳跃式监视
工具变量
估计
鉴定(生物学)
点估计
计算机科学
推论
计量经济学
点(几何)
平均处理效果
退休金
治疗效果
精算学
统计
业务
数学
经济
财务
医学
人工智能
倾向得分匹配
植物
几何学
管理
生物
传统医学
作者
Andy Lin,Denni Tommasi,Lina Zhang
标识
DOI:10.1177/1536867x241257347
摘要
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.
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