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Dynamic caliper matching

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  • Paweł Strawiński

    ()
    (Faculty of Economic Sciences, University of Warsaw)

Abstract

Matched sampling is a methodology used to estimate treatment effects. A caliper mechanism is used to achieve better similarity among matched pairs. We investigate finite sample properties of matching with calipers and propose a slight modification to the existing mechanism. The simulation study compares the performance of both methods and shows that a standard caliper performs well only in case of constant treatment or uniform propensity score distribution. Secondly, in a case of non-uniform distribution or non-uniform treatment the dynamic caliper method outperforms standard caliper matching.

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File URL: http://www.wne.uw.edu.pl/inf/wyd/WP/WNE_WP65.pdf
File Function: First version, 2011
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Bibliographic Info

Paper provided by Faculty of Economic Sciences, University of Warsaw in its series Working Papers with number 2011-25.

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Length: 13 pages
Date of creation: 2011
Date of revision:
Handle: RePEc:war:wpaper:2011-25

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Keywords: propensity score matching; caliper; efficiency; Monte Carlo study; finite sample properties;

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  1. Blundell, Richard & Costa Dias, Monica, 2008. "Alternative Approaches to Evaluation in Empirical Microeconomics," IZA Discussion Papers 3800, Institute for the Study of Labor (IZA).
  2. Heckman, James J & Ichimura, Hidehiko & Todd, Petra E, 1997. "Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 64(4), pages 605-54, October.
  3. Markus Frölich, 2004. "Finite-Sample Properties of Propensity-Score Matching and Weighting Estimators," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 77-90, February.
  4. Lee, Myoung-jae, 2005. "Micro-Econometrics for Policy, Program and Treatment Effects," OUP Catalogue, Oxford University Press, Oxford University Press, number 9780199267699, October.
  5. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, Elsevier, vol. 125(1-2), pages 305-353.
  6. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
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