How to Control for Many Covariates? Reliable Estimators Based on the Propensity Score

65 Pages Posted: 25 Oct 2010

See all articles by Martin Huber

Martin Huber

University of Fribourg

Michael Lechner

University of St. Gallen - Swiss Institute for Empirical Economic Research

Conny Wunsch

University of Basel; IZA Institute of Labor Economics; CESifo (Center for Economic Studies and Ifo Institute); University of St. Gallen

Abstract

We investigate the finite sample properties of a large number of estimators for the average treatment effect on the treated that are suitable when adjustment for observable covariates is required, like inverse probability weighting, kernel and other variants of matching, as well as different parametric models. The simulation design used is based on real data usually employed for the evaluation of labour market programmes in Germany. We vary several dimensions of the design that are of practical importance, like sample size, the type of the outcome variable, and aspects of the selection process. We find that trimming individual observations with too much weight as well as the choice of tuning parameters is important for all estimators. The key conclusion from our simulations is that a particular radius matching estimator combined with regression performs best overall, in particular when robustness to misspecifications of the propensity score is considered an important property.

Keywords: propensity score matching, kernel matching, inverse probability weighting, selection on observables, empirical Monte Carlo study, finite sample properties

JEL Classification: C21

Suggested Citation

Huber, Martin and Lechner, Michael and Wunsch, Conny, How to Control for Many Covariates? Reliable Estimators Based on the Propensity Score. IZA Discussion Paper No. 5268, Available at SSRN: https://ssrn.com/abstract=1696892

Martin Huber (Contact Author)

University of Fribourg ( email )

Bd de PĂ©rolles 90
Fribourg, Fribourg CH-1700
Switzerland

Michael Lechner

University of St. Gallen - Swiss Institute for Empirical Economic Research ( email )

Varnbuelstrasse 14
St. Gallen, 9000
Switzerland
+41 71 224 2320 (Phone)

Conny Wunsch

University of Basel ( email )

Petersplatz 1
Basel, CH-4003
Switzerland

IZA Institute of Labor Economics ( email )

P.O. Box 7240
Bonn, D-53072
Germany

CESifo (Center for Economic Studies and Ifo Institute) ( email )

Poschinger Str. 5
Munich, DE-81679
Germany

University of St. Gallen ( email )

Dufourstrasse 50
St. Gallen, 9000
Switzerland

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