What is the value of knowing the propensity score for estimating average treatment effects?

Markus Froelich ()
Authors registered in the RePEc Author Service: Markus Frölich ()

University of St. Gallen Department of Economics working paper series 2002 from Department of Economics, University of St. Gallen

Abstract: Propensity 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.

Keywords: Evaluation; matching; causal effect; semiparametric efficiency bound (search for similar items in EconPapers)
JEL-codes: C13 C14 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2002-04
New Economics Papers: this item is included in nep-ecm and nep-hea
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Working Paper: What is the Value of Knowing the Propensity Score for Estimating Average Treatment Effects? (2002)
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