Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/96693
Authors: 
Imbens, Guido W.
Year of Publication: 
2014
Series/Report no.: 
IZA Discussion Paper 8049
Abstract: 
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.
Subjects: 
matching methods
propensity score methods
causality
unconfoundedness
potential outcomes
selection on observables
JEL: 
C01
C14
C21
C52
Document Type: 
Working Paper

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