Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models

Anders Kock

Journal of Econometrics, 2016, vol. 195, issue 1, 71-85

Abstract: In this paper we study high-dimensional correlated random effects panel data models. Our setting is useful as it allows including time invariant covariates as under random effects yet allows for correlation between covariates and unobserved heterogeneity as under fixed effects. We use the Mundlak–Chamberlain device to model this correlation. Allowing for a flexible correlation structure naturally leads to a high-dimensional model in which least squares estimation easily becomes infeasible with even a moderate number of explanatory variables.

Keywords: Panel data; Lasso; Oracle inequality; Sup-norm bounds; High-dimensional models; Weak sparsity; Correlated random effects; Mundlak–Chamberlain; Variable selection; Uniform inference (search for similar items in EconPapers)
JEL-codes: C01 C10 C23 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:195:y:2016:i:1:p:71-85

DOI: 10.1016/j.jeconom.2016.06.001

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