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Testing for covariate balance using quantile regression and resampling methods

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  • Martin Huber

Abstract

Consistency of propensity score matching estimators hinges on the propensity score's ability to balance the distributions of covariates in the pools of treated and non-treated units. Conventional balance tests merely check for differences in covariates’ means, but cannot account for differences in higher moments. For this reason, this paper proposes balance tests which test for differences in the entire distributions of continuous covariates based on quantile regression (to derive Kolmogorov--Smirnov and Cramer--von-Mises--Smirnov-type test statistics) and resampling methods (for inference). Simulations suggest that these methods are very powerful and capture imbalances related to higher moments when conventional balance tests fail to do so.

Suggested Citation

  • Martin Huber, 2011. "Testing for covariate balance using quantile regression and resampling methods," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2881-2899, February.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:12:p:2881-2899
    DOI: 10.1080/02664763.2011.570323
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    Cited by:

    1. Rajeev Dehejia, 2013. "The Porous Dialectic: Experimental and Non-Experimental Methods in Development Economics," WIDER Working Paper Series wp-2013-011, World Institute for Development Economic Research (UNU-WIDER).
    2. Dehejia, Rajeev, 2013. "The Porous Dialectic: Experimental and Non-Experimental Methods in Development Economics," WIDER Working Paper Series 011, World Institute for Development Economic Research (UNU-WIDER).
    3. Magdalena Smyk & Joanna Tyrowicz & Lucas van der Velde, 2021. "A Cautionary Note on the Reliability of the Online Survey Data: The Case of Wage Indicator," Sociological Methods & Research, , vol. 50(1), pages 429-464, February.
    4. Peter H. Egger & Filip Tarlea, 2021. "Comparing Apples to Apples: Estimating Consistent Partial Effects of Preferential Economic Integration Agreements," Economica, London School of Economics and Political Science, vol. 88(350), pages 456-473, April.
    5. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
    6. Dehejia Rajeev, 2015. "Experimental and Non-Experimental Methods in Development Economics: A Porous Dialectic," Journal of Globalization and Development, De Gruyter, vol. 6(1), pages 47-69, June.
    7. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2010. "How to Control for Many Covariates? Reliable Estimators Based on the Propensity Score," IZA Discussion Papers 5268, Institute of Labor Economics (IZA).

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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