期刊
REVIEW OF ECONOMICS AND STATISTICS
卷 93, 期 4, 页码 1453-1459出版社
MIT PRESS
DOI: 10.1162/REST_a_00153
关键词
-
Careful examination of the structure determining treatment choice and outcomes, as advocated by Heckman (2008), is central to the design of treatment effect estimators and, in particular, proper choice of covariates. Here, we demonstrate how causal diagrams developed in the machine learning literature by Judea Pearl and his colleagues, but not so well known to economists, can play a key role in this examination by using these methods to give a detailed analysis of the choice of efficient covariates identified by Hahn (2004).
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据