IDEAS home Printed from
   My bibliography  Save this paper

Latent Variables and Propensity Score Matching


  • Maciej Jakubowski

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


This paper examines how including latent variables can benefit propensity score matching. A researcher can estimate, based on theoretical presumptions, the latent variable from the observed manifest variables and can use this estimate in propensity score matching. This paper demonstrates the benefits of such an approach and compares it with a method more common in econometrics, where the manifest variables are directly used in matching. We intuit that estimating the propensity score on the manifest variables introduces a measurement error that can be limited when estimating the propensity score on the estimated latent variable. We use Monte Carlo simulations to test how various matching methods behave under distinct circumstances found in practice. Also, we apply this approach to real data. Using the estimated latent variable in the propensity score matching increases the efficiency of treatment effect estimators. The benefits are larger for small samples, for non-linear processes, and for a large number of the manifest variables available, especially if they are highly correlated with the latent variable.

Suggested Citation

  • Maciej Jakubowski, 2010. "Latent Variables and Propensity Score Matching," Working Papers 2010-06, Faculty of Economic Sciences, University of Warsaw.
  • Handle: RePEc:war:wpaper:2010-06

    Download full text from publisher

    File URL:
    File Function: First version, 2010
    Download Restriction: no

    References listed on IDEAS

    1. David M. Blau, 2008. "Retirement and Consumption in a Life Cycle Model," Journal of Labor Economics, University of Chicago Press, vol. 26, pages 35-71.
    2. Fang Yang, 2009. "Consumption over the Life Cycle: How Different is Housing?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 12(3), pages 423-443, July.
    3. Storesletten, Kjetil & Telmer, Christopher I. & Yaron, Amir, 2004. "Consumption and risk sharing over the life cycle," Journal of Monetary Economics, Elsevier, vol. 51(3), pages 609-633, April.
    4. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    5. Aaberge, Rolf, et al, 2002. "Income Inequality and Income Mobility in the Scandinavian Countries Compared to the United States," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 48(4), pages 443-469, December.
    6. repec:nbp:nbpbik:v:43:y:2012:i:5:p:5-20 is not listed on IDEAS
    7. Cagetti, Marco, 2003. "Wealth Accumulation over the Life Cycle and Precautionary Savings," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 339-353, July.
    8. Javier Díaz-Giménez & Andrew Glover & José-Víctor Ríos-Rull, 2011. "Facts on the distributions of earnings, income, and wealth in the United States: 2007 update," Quarterly Review, Federal Reserve Bank of Minneapolis.
    9. Lukiyanova, Anna & Oshchepkov, Aleksey, 2012. "Income mobility in Russia (2000–2005)," Economic Systems, Elsevier, vol. 36(1), pages 46-64.
    10. Abe, Naohito & Yamada, Tomoaki, 2009. "Nonlinear income variance profiles and consumption inequality over the life cycle," Journal of the Japanese and International Economies, Elsevier, vol. 23(3), pages 344-366, September.
    Full references (including those not matched with items on IDEAS)

    More about this item


    factor analysis; latent variables; propensity score matching;

    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
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:war:wpaper:2010-06. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marcin Bąba). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.