4.2 Article

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

期刊

STATISTICS & PROBABILITY LETTERS
卷 80, 期 23-24, 页码 1806-1813

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ELSEVIER SCIENCE BV
DOI: 10.1016/j.spl.2010.08.005

关键词

Number of factors; Approximate factor models; Information criterion; Model selection

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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 Liska (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. (c) 2010 Elsevier B.V. All rights reserved.

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