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Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models

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  • Anders Bredahl Kock

    ()
    (CREATES, Aarhus University)

Abstract

This paper generalizes the results for the Bridge estimator of Huang et al. (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 is oracle ecient. It can correctly distinguish between relevant and irrelevant variables and the asymptotic distribution of the estimators of the coecients 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. We do this without assuming sub-Gaussianity of the error terms. However, a partial orthogonality condition of the same type as in Huang et al. (2008) is needed.

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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2010-56.

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Length: 29
Date of creation: 01 Sep 2010
Date of revision:
Handle: RePEc:aah:create:2010-56

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: Panel data; high dimensional modeling; variable selection; Bridge estimators; oracle property;

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Cited by:
  1. Anders Bredahl Kock & Laurent A.F. Callot, 2012. "Oracle Inequalities for High Dimensional Vector Autoregressions," CREATES Research Papers 2012-16, School of Economics and Management, University of Aarhus.
  2. Mehmet Caner & Anders Bredahl Kock, 2013. "Oracle Inequalities for Convex Loss Functions with Non-Linear Targets," CREATES Research Papers 2013-51, School of Economics and Management, University of Aarhus.
  3. Jia Chen & Jiti Gao, 2014. "Semiparametric Model Selection in Panel Data Models with Deterministic Trends and Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/14, Monash University, Department of Econometrics and Business Statistics.
  4. Anders Bredahl Kock, 2012. "On the Oracle Property of the Adaptive Lasso in Stationary and Nonstationary Autoregressions," CREATES Research Papers 2012-05, School of Economics and Management, University of Aarhus.

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