IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v151y2009i1p33-46.html
   My bibliography  Save this article

A specification test for the propensity score using its distribution conditional on participation

Author

Listed:
  • Shaikh, Azeem M.
  • Simonsen, Marianne
  • Vytlacil, Edward J.
  • Yildiz, Nese

Abstract

Propensity score matching has become a popular method for the estimation of average treatment effects. In empirical applications, researchers almost always impose a parametric model for the propensity score. This practice raises the possibility that the model for the propensity score is misspecified and therefore the propensity score matching estimator of the average treatment effect may be inconsistent. We show that the common practice of calculating estimates of the densities of the propensity score conditional on the participation decision provides a means for examining whether the propensity score is misspecified. In particular, we derive a restriction between the density of the propensity score among participants and the density among nonparticipants. We show that this restriction between the two conditional densities is equivalent to a particular orthogonality restriction and derive a formal test based upon it. The resulting test is shown via a simulation study to have dramatically greater power than competing tests for many alternatives. The principal disadvantage of this approach is loss of power against some alternatives.

Suggested Citation

  • Shaikh, Azeem M. & Simonsen, Marianne & Vytlacil, Edward J. & Yildiz, Nese, 2009. "A specification test for the propensity score using its distribution conditional on participation," Journal of Econometrics, Elsevier, vol. 151(1), pages 33-46, July.
  • Handle: RePEc:eee:econom:v:151:y:2009:i:1:p:33-46
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4076(09)00049-9
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Michael Lechner, 2002. "Program Heterogeneity And Propensity Score Matching: An Application To The Evaluation Of Active Labor Market Policies," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 205-220, May.
    2. Michael Lechner, 2000. "An Evaluation of Public-Sector-Sponsored Continuous Vocational Training Programs in East Germany," Journal of Human Resources, University of Wisconsin Press, vol. 35(2), pages 347-375.
    3. Smith, Jeffrey & Todd, Petra, 2005. "Rejoinder," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 365-375.
    4. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-1430, November.
    5. Lechner, Michael, 1999. "Earnings and Employment Effects of Continuous Off-the-Job Training in East Germany after Unification," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 74-90, January.
    6. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    7. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    8. Barbara Sianesi, 2004. "An Evaluation of the Swedish System of Active Labor Market Programs in the 1990s," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 133-155, February.
    9. John Xu Zheng, 1996. "A consistent test of functional form via nonparametric estimation techniques," Journal of Econometrics, Elsevier, vol. 75(2), pages 263-289, December.
    10. Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics,in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097 Elsevier.
    11. Horowitz, Joel L & Spokoiny, Vladimir G, 2001. "An Adaptive, Rate-Optimal Test of a Parametric Mean-Regression Model against a Nonparametric Alternative," Econometrica, Econometric Society, vol. 69(3), pages 599-631, May.
    12. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
    13. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," Review of Economic Studies, Oxford University Press, vol. 65(2), pages 261-294.
    14. Hong, Yongmiao & White, Halbert, 1995. "Consistent Specification Testing via Nonparametric Series Regression," Econometrica, Econometric Society, vol. 63(5), pages 1133-1159, September.
    15. Lars Skipper & Marianne Simonsen, 2006. "The costs of motherhood: an analysis using matching estimators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 919-934.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. 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.
    3. von Eije, Henk & Goyal, Abhinav & Muckley, Cal B., 2014. "Does the information content of payout initiations and omissions influence firm risks?," Journal of Econometrics, Elsevier, vol. 183(2), pages 222-229.
    4. Steven Lehrer & Gregory Kordas, 2013. "Matching using semiparametric propensity scores," Empirical Economics, Springer, vol. 44(1), pages 13-45, February.
    5. Pedro H. C. Sant'Anna & Xiaojung Song, 2016. "Specification Tests for the Propensity Score," Papers 1611.06217, arXiv.org.
    6. Caliendo, Marco & Mahlstedt, Robert & Mitnik, Oscar A., 2017. "Unobservable, but unimportant? The relevance of usually unobserved variables for the evaluation of labor market policies," Labour Economics, Elsevier, vol. 46(C), pages 14-25.
    7. Wang-Sheng Lee, 2013. "Propensity score matching and variations on the balancing test," Empirical Economics, Springer, vol. 44(1), pages 47-80, February.
    8. Li Liang & Greene Tom, 2013. "A Weighting Analogue to Pair Matching in Propensity Score Analysis," The International Journal of Biostatistics, De Gruyter, vol. 9(2), pages 215-234, July.
    9. Huber, Martin, 2012. "Identifying causal mechanisms in experiments (primarily) based on inverse probability weighting," Economics Working Paper Series 1213, University of St. Gallen, School of Economics and Political Science, revised May 2013.

    Corrections

    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:eee:econom:v:151:y:2009:i:1:p:33-46. 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: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.