Efficient GMM estimation with incomplete data

Chris Muris

doi:10.1162/rest_a_00836

Efficient GMM estimation with incomplete data

Chris Muris^*

^*Corresponding author for this work

School of Economics

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4 Citations (Scopus)

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Abstract

In the standard missing data model, data are either complete or completely missing. However, applied researchers face situations with an arbitrary number of strata of incompleteness. Examples include unbalanced panels and instrumental variables settings where some observations are missing some instruments. I propose a model for settings where observations may be incomplete, with an arbitrary number of strata of incompleteness. I derive a set of moment conditions that generalizes those in Graham’s (2011) standard missing data setup. I derive the associated efficiency bound and propose efficient estimators. Identification can be achieved even if it
fails in each stratum of incompleteness.

Original language	English
Pages (from-to)	518-530
Number of pages	14
Journal	Review of Economics and Statistics
Volume	102
Issue number	3
DOIs	https://doi.org/10.1162/rest_a_00836
Publication status	Published - 2 Jul 2020

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ECON Econometrics
ECON CEPS Data

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10.1162/rest_a_00836

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Replication data for: "Efficient GMM Estimation with Incomplete Data"
Muris, C. (Contributor), Harvard University, 29 Mar 2019
DOI: 10.7910/dvn/zkqpk7, https://doi.org/10.7910%2Fdvn%2Fzkqpk7
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Cite this

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Efficient GMM estimation with incomplete data

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