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ORACLE EFFICIENT VARIABLE SELECTION IN RANDOM AND FIXED EFFECTS PANEL DATA MODELS

Published online by Cambridge University Press:  06 July 2012

Anders Bredahl Kock*
Affiliation:
Aarhus University and CREATES
*
*Address correspondence to: Anders Bredahl Kock, Department of Economics and Business, Aarhus University Fuglesangs Alle 4, 8210 Aarhus V, Denmark; e-mail:akock@creates.au.dk

Abstract

This paper generalizes the results for the Bridge estimator of Huang, Horowitz, and Ma (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular, we show that the Bridge estimator isoracle efficient. It can correctly distinguish between relevant and irrelevant variables and the asymptotic distribution of the estimators of the coefficients of the relevant variables is the same as if only these had been included in the model, i.e. as if an oracle had revealed the true model prior to estimation.

In the case of more explanatory variables than observations we prove that the Marginal Bridge estimator can asymptotically correctly distinguish between relevant and irrelevant explanatory variables if the error terms are Gaussian. Furthermore, a partial orthogonality condition of the same type as in Huang et al. (2008) is needed to restrict the dependence between relevant and irrelevant variables.

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Type
ARTICLES
Copyright
Copyright © Cambridge University Press 2012 

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