Matching Methods in Practice: Three Examples

There is a large theoretical literature on methods for estimating causal effects under unconfoundedness, exogeneity, or selection-on-observables type assumptions using matching or propensity score methods. Much of this literature is highly technical and has not made inroads into empirical practice w...

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Bibliographic Details
Published in:The Journal of human resources 2015, Vol.50 (2), p.373-419
Main Author: Imbens, Guido W.
Format: Article
Language:English
Subjects:
Causality
Decision theory
Economic analysis
Empirical research
Estimating techniques
Human resources
Least squares method
Management science
Regression analysis
Studies
Symposium on Empirical Methods
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Summary:There is a large theoretical literature on methods for estimating causal effects under unconfoundedness, exogeneity, or selection-on-observables type assumptions using matching or propensity score methods. Much of this literature is highly technical and has not made inroads into empirical practice where many researchers continue to use simple methods such as ordinary least squares regression even in settings where those methods do not have attractive properties. In this paper, I discuss some of the lessons for practice from the theoretical literature and provide detailed recommendations on what to do. I illustrate the recommendations with three detailed applications.
ISSN:0022-166X
1548-8004
DOI:10.3368/jhr.50.2.373