IDEAS home Printed from
MyIDEAS: Login to save this paper or follow this series

Kausalanalyse durch Matchingverfahren

  • Markus Gangl
  • Thomas A. DiPrete
Registered author(s):

    Having close linkages with the counterfactual concept of causality, nonparametric matching estimators have recently gained in popularity in the statistical and econometric literature on causal analysis. Introducing key concepts of the Rubin causal model (RCM), the paper discusses the implementation of counterfactual analyses by propensity score matching methods. We emphasize the suitability of the counterfactual framework for sociological questions as well as the assumptions underlying matching methods relative to standard regression analysis. We then illustrate the application of matching estimators in an analysis of the causal effect of unemployment on workers' subsequent careers.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: no

    Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 401.

    in new window

    Length: 30 p.
    Date of creation: 2004
    Date of revision:
    Handle: RePEc:diw:diwwpp:dp401
    Contact details of provider: Postal: Mohrenstra├če 58, D-10117 Berlin
    Phone: xx49-30-89789-0
    Fax: xx49-30-89789-200
    Web page:

    More information through EDIRC

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as in new window
    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. Charles F. Manski, 1989. "Anatomy of the Selection Problem," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 343-360.
    3. Heckman, James, 2001. "Accounting for Heterogeneity, Diversity and General Equilibrium in Evaluating Social Programmes," Economic Journal, Royal Economic Society, vol. 111(475), pages F654-99, November.
    4. Jeffrey Smith & Petra Todd, 2003. "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20035, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
    5. Simon Gachter & Ernst Fehr, 2000. "Cooperation and Punishment in Public Goods Experiments," American Economic Review, American Economic Association, vol. 90(4), pages 980-994, September.
    6. Heckman, James J. & Navarro, Salvador, 2003. "Using Matching, Instrumental Variables and Control Functions to Estimate Economic Choice Models," IZA Discussion Papers 768, Institute for the Study of Labor (IZA).
    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. Falk, Armin & Fehr, Ernst, 2003. "Why labour market experiments?," Labour Economics, Elsevier, vol. 10(4), pages 399-406, August.
    9. Pratt, John W. & Schlaifer, Robert, 1988. "On the interpretation and observation of laws," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 23-52.
    10. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
    11. 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.
    12. 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.
    13. Petra E. Todd & Jeffrey A. Smith, 2001. "Reconciling Conflicting Evidence on the Performance of Propensity-Score Matching Methods," American Economic Review, American Economic Association, vol. 91(2), pages 112-118, May.
    14. James Heckman & Justin L. Tobias & Edward Vytlacil, 2003. "Simple Estimators for Treatment Parameters in a Latent-Variable Framework," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 748-755, August.
    15. DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, Social Science Research Center Berlin (WZB).
    16. repec:att:wimass:9217 is not listed on IDEAS
    17. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Wiley Blackwell, vol. 65(2), pages 261-94, April.
    18. Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
    19. James J. Heckman, 1991. "Randomization and Social Policy Evaluation," NBER Technical Working Papers 0107, National Bureau of Economic Research, Inc.
    20. Manski, C.F., 1990. "The Selection Problem," Working papers 90-12, Wisconsin Madison - Social Systems.
    21. Rajeev H. Dehejia & Sadek Wahba, 1998. "Causal Effects in Non-Experimental Studies: Re-Evaluating the Evaluation of Training Programs," NBER Working Papers 6586, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:diw:diwwpp:dp401. 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: (Bibliothek)

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.