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.
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Bibliographic InfoPaper provided by Department of Economics, University of St. Gallen in its series University of St. Gallen Department of Economics working paper series 2002 with number 2002-06.
Length: 22 pages
Date of creation: Apr 2002
Date of revision:
Evaluation; matching; causal effect; semiparametric efficiency bound;
Other versions of this item:
- Frölich, Markus, 2002. "What is the Value of Knowing the Propensity Score for Estimating Average Treatment Effects?," IZA Discussion Papers 548, Institute for the Study of Labor (IZA).
- 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-2002-06-13 (All new papers)
- NEP-ECM-2002-06-13 (Econometrics)
- NEP-HEA-2002-06-13 (Health Economics)
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