Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/89327
Authors: 
Alessi, Lucia
Barigozzi, Matteo
Capasso, Marco
Year of Publication: 
2007
Series/Report no.: 
LEM Working Paper Series 2007/19
Abstract: 
We propose a refinement of the criterion by Bai and Ng [2002] for determining the number of static factors in factor models with large datasets. It consists in multiplying the penalty function times a constant which tunes the penalizing power of the function itself as in the Hallin and Lika [2007] criterion for the number of dynamic factors. By iteratively evaluating the criterion for different values of this constant, we achieve more robust results than in the case of fixed penalty function. This is shown by means of Monte Carlo simulations on seven data generating processes, including heteroskedastic processes, on samples of different size.
Subjects: 
Approximate factor models
Information criterion
Number of factors
JEL: 
C52
Document Type: 
Working Paper

Files in This Item:
File
Size
531.98 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.