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.

Alessi L, Barigozzi M, Capasso M (2010). Improved Penalization when Determining the Number of Factors in Approximate Static Factor Models. STATISTICS & PROBABILITY LETTERS, 80, 1806-1813 [10.1016/j.spl.2010.08.005].

Improved Penalization when Determining the Number of Factors in Approximate Static Factor Models

Barigozzi M
;
2010

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.
2010
Alessi L, Barigozzi M, Capasso M (2010). Improved Penalization when Determining the Number of Factors in Approximate Static Factor Models. STATISTICS & PROBABILITY LETTERS, 80, 1806-1813 [10.1016/j.spl.2010.08.005].
Alessi L; Barigozzi M; Capasso M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/722355
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