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The Finite Sample Performance of Semi- and Nonparametric Estimators for Treatment Effects and Policy Evaluation

58 Pages Posted: 24 Jan 2015  

Markus Frölich

Universität Mannheim, Chair of Econometrics

Martin Huber

University of Fribourg

Manuel Wiesenfarth

German Cancer Research Center

Abstract

This paper investigates the finite sample performance of a comprehensive set of semi- and nonparametric estimators for treatment and policy evaluation. In contrast to previous simulation studies which mostly considered semiparametric approaches relying on parametric propensity score estimation, we also consider more flexible approaches based on semi- or nonparametric propensity scores, nonparametric regression, and direct covariate matching. In addition to (pair, radius, and kernel) matching, inverse probability weighting, regression, and doubly robust estimation, our studies also cover recently proposed estimators such as genetic matching, entropy balancing, and empirical likelihood estimation.We vary a range of features (sample size, selection into treatment, effect heterogeneity, and correct/misspecification) in our simulations and find that several nonparametric estimators by and large outperform commonly used treatment estimators using a parametric propensity score. Nonparametric regression, nonparametric doubly robust estimation, nonparametric IPW, and one-to-many covariate matching perform best.

Keywords: treatment effects, policy evaluation, simulation, empirical Monte Carlo study, propensity score, semi- and nonparametric estimation

JEL Classification: C21

Suggested Citation

Frölich, Markus and Huber, Martin and Wiesenfarth, Manuel, The Finite Sample Performance of Semi- and Nonparametric Estimators for Treatment Effects and Policy Evaluation. IZA Discussion Paper No. 8756. Available at SSRN: https://ssrn.com/abstract=2554884

Markus Frölich (Contact Author)

Universität Mannheim, Chair of Econometrics ( email )

L7, 3-5
68131 Mannheim
D-Mannheim, 68131
Germany

HOME PAGE: http://froelich.vwl.uni-mannheim.de

Martin Huber

University of Fribourg ( email )

Bd de Pérolles 90
Fribourg, Fribourg CH-1700
Switzerland

Manuel Wiesenfarth

German Cancer Research Center ( email )

Germany

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