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The Propensity Score: A Means to An End


  • Augurzky, Boris

    () (RWI)

  • Schmidt, Christoph M.

    () (RWI)


Propensity score matching is a prominent strategy to reduce imbalance in observational studies. However, if imbalance is considerable and the control reservoir is small, either one has to match one control to several treated units or, alternatively, discard many treated persons. The first strategy tends to increase standard errors of the estimated treatment effects while the second might produce a matched sample that is not anymore representative of the original one. As an alternative approach, this paper argues to carefully reconsider the selection equation upon which the propensity score estimates are based. Often, all available variables that rule the selection process are included into the selection equation. Yet, it would suffice to concentrate on only those exhibiting a large impact on the outcome under scrutiny, as well. This would introduce more stochastic noise making treatment and comparison group more similar. We assess the advantages and disadvantages of the latter approach in a simulation study.

Suggested Citation

  • Augurzky, Boris & Schmidt, Christoph M., 2001. "The Propensity Score: A Means to An End," IZA Discussion Papers 271, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp271

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    References listed on IDEAS

    1. Parsons, Donald O, 1980. "The Decline in Male Labor Force Participation," Journal of Political Economy, University of Chicago Press, vol. 88(1), pages 117-134, February.
    2. Hassink, R. & van Ours, J.C. & Ridder, G., 1997. "Dismissal through disability," Other publications TiSEM b756763d-1536-4d61-84e4-9, Tilburg University, School of Economics and Management.
    3. Robert Haveman & Philip de Jong & Barbara Wolfe, 1991. "Disability Transfers and the Work Decision of Older Men," The Quarterly Journal of Economics, Oxford University Press, vol. 106(3), pages 939-949.
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    More about this item


    Estimation of the propensity score; balance of relevant covariates; simulation study;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General


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