What is the Value of Knowing the Propensity Score for Estimating Average Treatment Effects?

Markus Frölich

No 548, IZA Discussion Papers from IZA Network @ LISER

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. c efficiency bound

Keywords: semiparametric efficiency bound; evaluation; matching; causal effect (search for similar items in EconPapers)
JEL-codes: C13 C14 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2002-08
New Economics Papers: this item is included in nep-ecm and nep-geo
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Published - published in: Econometric Reviews, 2004, 23 (2), 167-174

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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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