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Identification and Estimation of Causal Mechanisms and Net Effects of a Treatment∗ (2007)
BibTeX
@MISC{07identificationand,
author = {},
title = {Identification and Estimation of Causal Mechanisms and Net Effects of a Treatment∗},
year = {2007}
}
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Abstract
An important goal in the analysis of the causal effect of a treatment on an outcome is to understand the mechanisms through which the treatment causally works. In the economics literature, however, there seems to be no available framework to estimate the relative impor-tance of different causal mechanisms of a treatment. We fill this void by precisely defining a causal mechanism effect of a treatment and the causal effect of a treatment net of that mechanism using the potential outcomes framework, and by considering their identification and estimation. The definition of our parameters results in an intuitive decomposition of the total effect of a treatment that is useful for policy purposes. We offer conditions under which these causal effects can be estimated for the case of a randomly assigned treatment and when selection into the treatment is random conditional on a set of covariates. We close with two empirical applications that illustrate the concepts and methods introduced in this paper. Key words and phrases: causal inference, post-treatment variables, principal stratifica-tion.
Keyphrases
causal mechanism causal effect net effect treatment net causal mechanism effect potential outcome framework economics literature total effect different causal mechanism policy purpose relative impor-tance intuitive decomposition causal inference post-treatment variable available framework important goal parameter result key word principal stratifica-tion empirical application
