Advanced Search
MyIDEAS: Login

Propensity Score Matching Method in Quasi-Experimental Designs: An Approach to Program Evaluation of INHP-III

Contents:

Author Info

  • Kaushal Deep Gakhar
  • Vidhu Kapur
  • Navneet Kaur
Registered author(s):

    Abstract

    The experimental designs are generally considered as the robust evaluation methodologies as there is random assignment. These are possible in clinical trials or in pilot phase of the project but during the development phase due to ethical issues and resource constraints; use of true experimental designs are not feasible in majority of development interventions as use of experimental design entails creation of treatment and comparison group thereby providing benefits to some and excluding others. It is unethical at program-level to provide the benefits to few and leave others and thus, there is difficulty in construction of both treatment and comparison at baseline. This makes attribution of observed outcomes and impacts to program intervention very difficult. The task gets more difficult when there are no baseline studies available. PSM offers one such alternative for addressing the concerns comparison and attribution. This paper is based on the case of Endline Evaluation of INHP- III where the Quasi-Experimental Design was employed using the PSM technique to construct the ideal comparison match for the treatment groups. [Discussion Paper 3]

    Download Info

    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: http://www.esocialsciences.org/Download/repecDownload.aspx?fname=Document12382010134.212588E-02.pdf&fcategory=Articles&AId=2782&fref=repec
    Our checks indicate that this address may not be valid because: 403 Forbidden. If this is indeed the case, please notify (Padma Prakash)
    Download Restriction: no

    Bibliographic Info

    Paper provided by eSocialSciences in its series Working Papers with number id:2782.

    as in new window
    Length:
    Date of creation: Aug 2010
    Date of revision:
    Handle: RePEc:ess:wpaper:id:2782

    Note: Institutional Papers
    Contact details of provider:
    Web page: http://www.esocialsciences.org

    Related research

    Keywords: PSM; Counterfactual; Treatment; Comparison; Quasi-experimental; Matching Groups;

    This paper has been announced in the following NEP Reports:

    References

    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. 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.
    2. Juan José Díaz & Sudhanshu Handa, 2005. "An Assessment of Propensity Score Matching as a Non Experimental Impact Estimator: Evidence from Mexico's PROGRESA Program," IDB Publications 25418, Inter-American Development Bank.
    3. Marco Caliendo & Sabine Kopeinig, 2005. "Some Practical Guidance for the Implementation of Propensity Score Matching," Discussion Papers of DIW Berlin 485, DIW Berlin, German Institute for Economic Research.
    4. Rajeev H. Dehejia & Sadek Wahba, 1998. "Propensity Score Matching Methods for Non-experimental Causal Studies," NBER Working Papers 6829, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

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

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:ess:wpaper:id:2782. 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: (Padma Prakash).

    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.