Model averaging with covariates that are missing completely at random

Missing data is a common problem in economics studies. We propose using Mallows model averaging (MMA) to deal with this problem, which has an important advantage over its competitors in that it asymptotically achieves the lowest possible squared error. A simulation study in comparison with existing methods strongly favors the MMA estimator.

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Year of publication:	2013
Authors:	Zhang, Xinyu
Published in:	Economics Letters. - Elsevier, ISSN 0165-1765. - Vol. 121.2013, 3, p. 360-363
Publisher:	Elsevier
Subject:	Asymptotic optimality \| Mallows model averaging \| Missing data

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Type of publication:	Article
Classification:	C5 - Econometric Modeling ; C13 - Estimation
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010729466