Efficiency bounds for missing data models with semiparametric restrictions

Bryan Graham

No 14376, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: This paper shows that the semiparametric efficiency bound for a parameter identified by an unconditional moment restriction with data missing at random (MAR) coincides with that of a particular augmented moment condition problem. The augmented system consists of the inverse probability weighted (IPW) original moment restriction and an additional conditional moment restriction which exhausts all other implications of the MAR assumption. The paper also investigates the value of additional semiparametric restrictions on the conditional expectation function (CEF) of the original moment function given always- observed covariates. In the program evaluation context, for example, such restrictions are implied by semiparametric models for the potential outcome CEFs given baseline covariates. The efficiency bound associated with this model is shown to also coincide with that of a particular moment condition problem. Some implications of these results for estimation are briefly discussed.

JEL-codes: C1 C14 C21 (search for similar items in EconPapers)
Date: 2008-10
New Economics Papers: this item is included in nep-ecm
Note: TWP
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Published as Bryan S. Graham, 2011. "Efficiency Bounds for Missing Data Models With Semiparametric Restrictions," Econometrica, Econometric Society, vol. 79(2), pages 437-452, 03.

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Journal Article: Efficiency Bounds for Missing Data Models With Semiparametric Restrictions (2011)
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