IDEAS home Printed from https://ideas.repec.org/p/boc/usug01/12.html
   My bibliography  Save this paper

Propensity score matching

Author

Listed:
  • Barbara Sianesi

    () (Institute for Fiscal Studies)

Abstract

The typical evaluation problem aims at quantifying the impact of a ÔtreatmentÕ (e.g. a training programme, a reform, or a medicine) on an outcome of interest (such as earnings, school attendance or illness indicators), where a group of units, the ÔtreatedÕ, receive the ÔtreatmentÕ, while a second group remains untreated. Statistical matching involves pairing to each treated unit a non-treated unit with the ÔsameÕ observable characteristics, so that (under some assumptions) the outcome experienced by the matched pool of non-treated may be taken as the outcome the treated units would have experienced had they not been treated. Alternatively, one can associate to each treated unit a matched outcome given by the average of the outcome of all the untreated units, where each of their contributions can be weighted according to their 'distance' to the treated unit under consideration. An interesting quantity which avoids the dimensionality problem is the Ôpropensity scoreÕ, the conditional probability of being treated. psmatch implements various types of propensity score matching estimators: from one-to-one matching with replacement (optionally within a caliper) to a number of smoothed versions (including nearest neighbours, kernel, local linear regression). Additionally, it allows to implement Mahalanobis metric matching on two or three variables. Other options include estimation of the propensity score, bootstrapping of the treatment effect, the creation of matching quality indicators for a set of specified variables and producing a smoothed outcome for the treated as well. The software (version 2.0) was revised in August 2001. The current version is psmatch2 of Leuven and Sianesi.

Suggested Citation

  • Barbara Sianesi, 2001. "Propensity score matching," United Kingdom Stata Users' Group Meetings 2001 12, Stata Users Group, revised 23 Aug 2001.
  • Handle: RePEc:boc:usug01:12
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/RePEc/usug2001/psmatch.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 605-654.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Statistics

    Access and download statistics

    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:boc:usug01:12. 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: (Christopher F Baum). General contact details of provider: http://edirc.repec.org/data/stataea.html .

    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.