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

L. Alessi, M. Barigozzi*, M. Capasso

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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.

Original languageEnglish
Pages (from-to)1806-1813
Number of pages8
JournalStatistics & Probability Letters
Issue number23-24
Publication statusPublished - 1 Dec 2010


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

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