G2TT
来源类型Working Paper
规范类型报告
DOI10.3386/w23568
来源IDWorking Paper 23568
Using Instrumental Variables for Inference about Policy Relevant Treatment Effects
Magne Mogstad; Andres Santos; Alexander Torgovitsky
发表日期2017-07-17
出版年2017
语种英语
摘要We propose a method for using instrumental variables (IV) to draw inference about causal effects for individuals other than those affected by the instrument at hand. Policy relevance and external validity turns on the ability to do this reliably. Our method exploits the insight that both the IV estimand and many treatment parameters can be expressed as weighted averages of the same underlying marginal treatment effects. Since the weights are known or identified, knowledge of the IV estimand generally places some restrictions on the unknown marginal treatment effects, and hence on the values of the treatment parameters of interest. We show how to extract information about the average effect of interest from the IV estimand, and, more generally, from a class of IV-like estimands that includes the two stage least squares and ordinary least squares estimands, among many others. Our method has several applications. First, it can be used to construct nonparametric bounds on the average causal effect of a hypothetical policy change. Second, our method allows the researcher to flexibly incorporate shape restrictions and parametric assumptions, thereby enabling extrapolation of the average effects for compliers to the average effects for different or larger populations. Third, our method can be used to test model specification and hypotheses about behavior, such as no selection bias and/or no selection on gain. To accommodate these diverse applications, we devise a novel inference procedure that is designed to exploit the convexity of our setting. We develop uniformly valid tests that allow for an infinite number of IV--like estimands and a general convex parameter space. We apply our method to analyze the effects of price subsidies on the adoption and usage of an antimalarial bed net in Kenya.
主题Econometrics ; Estimation Methods
URLhttps://www.nber.org/papers/w23568
来源智库National Bureau of Economic Research (United States)
引用统计
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/581242
推荐引用方式
GB/T 7714
Magne Mogstad,Andres Santos,Alexander Torgovitsky. Using Instrumental Variables for Inference about Policy Relevant Treatment Effects. 2017.
条目包含的文件
文件名称/大小 资源类型 版本类型 开放类型 使用许可
w23568.pdf(1203KB)智库出版物 限制开放CC BY-NC-SA浏览
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Magne Mogstad]的文章
[Andres Santos]的文章
[Alexander Torgovitsky]的文章
百度学术
百度学术中相似的文章
[Magne Mogstad]的文章
[Andres Santos]的文章
[Alexander Torgovitsky]的文章
必应学术
必应学术中相似的文章
[Magne Mogstad]的文章
[Andres Santos]的文章
[Alexander Torgovitsky]的文章
相关权益政策
暂无数据
收藏/分享
文件名: w23568.pdf
格式: Adobe PDF
此文件暂不支持浏览

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。