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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
