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Improved penalization for determining the number of factors in approximate factor models

By Lucia Alessi, Matteo Barigozzi and Marco Capasso

Abstract

The procedure proposed by Bai and Ng (2002) for identifying the number of factors in static factor models is revisited. In order to improve its performance, we introduce a tuning multiplicative constant in the penalty, an idea that was proposed by Hallin and Liška (2007) in the context of dynamic factor models. Simulations show that our method in general delivers more reliable estimates, in particular in the case of large idiosyncratic disturbances. Keywords: Number of factors; Approximate factor models; Information criterion; Model selectio

Topics: QA Mathematics
Publisher: Elsevier
Year: 2010
DOI identifier: 10.1016/j.spl.2010.08.005
OAI identifier: oai:eprints.lse.ac.uk:30981
Provided by: LSE Research Online
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