Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/35376
Authors: 
Busso, Matias
DiNardo, John
McCrary, Justin
Year of Publication: 
2009
Series/Report no.: 
IZA discussion papers 3998
Abstract: 
Currently available asymptotic results in the literature suggest that matching estimators have higher variance than reweighting estimators. The extant literature comparing the finite sample properties of matching to specific reweighting estimators, however, has concluded that reweighting performs far worse than even the simplest matching estimator. We resolve this puzzle. We show that the findings from the finite sample analyses are not inconsistent with asymptotic analysis, but are very specific to particular choices regarding the implementation of reweighting, and fail to generalize to settings likely to be encountered in actual empirical practice. In the DGPs studied here, reweighting typically outperforms propensity score matching.
Subjects: 
Treatment effects
propensity score
semiparametric efficiency
JEL: 
C14
C21
C52
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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