Conditional moment models with data missing at random

M. Hristache and V. Patilea

Biometrika, 2017, vol. 104, issue 3, 735-742

Abstract: SummaryWe consider a general statistical model defined by moment restrictions when data are missing at random. Using inverse probability weighting, we show that such a model is equivalent to a model for the observed variables only, augmented by a moment condition defined by the missingness mechanism. Our framework covers parametric and semiparametric mean regressions and quantile regressions. We allow for missing responses, missing covariates and any combination of them. The equivalence result sheds new light on various aspects of missing data, and provides guidelines for building efficient estimators.

Keywords: Efficiency bound; Inverse probability weighting; Missing at random; Semiparametric regression (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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