What is the Value of Knowing the Propensity Score for Estimating Average Treatment Effects?
AbstractPropensity score matching is widely used in treatment evaluation to estimate average treatment effects. Nevertheless, the role of the propensity score is still controversial. Since the propensity score is usually unknown and has to be estimated, the efficiency loss arising from not knowing the true propensity score is examined. Hahn (1998) derived the asymptotic variance bounds for known and unknown propensity scores. Whereas the variance of the average treatment effect is unaffected by knowledge of the propensity score, the bound for the treatment effect on the treated changes if the propensity score is known. However, the reasons for this remain unclear. In this paper it is shown that knowledge of the propensity score does not lead to a “dimension reduction”. Instead it enables a more efficient estimation of the distribution of the confounding variables. c efficiency bound
Download InfoIf 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.
Bibliographic InfoPaper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 548.
Length: 22 pages
Date of creation: Aug 2002
Date of revision:
Publication status: published in: Econometric Reviews, 2004, 23 (2), 167-174
Contact details of provider:
Postal: IZA, P.O. Box 7240, D-53072 Bonn, Germany
Phone: +49 228 3894 223
Fax: +49 228 3894 180
Web page: http://www.iza.org
Postal: IZA, Margard Ody, P.O. Box 7240, D-53072 Bonn, Germany
Other versions of this item:
- Markus Froelich, 2002. "What is the value of knowing the propensity score for estimating average treatment effects?," University of St. Gallen Department of Economics working paper series 2002 2002-06, Department of Economics, University of St. Gallen.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2002-09-11 (All new papers)
- NEP-ECM-2002-09-11 (Econometrics)
- NEP-GEO-2002-09-11 (Economic Geography)
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral 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: (Mark Fallak).
If references are entirely missing, you can add them using this form.