A robust criterion for determining the number of static factors in approximate factor models
Lucia Alessi (lucia.alessi@ec.europa.eu),
Matteo Barigozzi and
Marco Capasso
No 903, Working Paper Series from European Central Bank
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 multi-plying the penalty function by a constant which tunes the penalizing power of the function itself as in the Hallin and Liška [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. Two empirical applications are carried out on a macroeconomic and a financial dataset. JEL Classification: C52
Keywords: Approximate factor models; Information criterion; Number of factors. (search for similar items in EconPapers)
Date: 2008-05
Note: 1023254
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Citations: View citations in EconPapers (20)
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Related works:
Working Paper: A Robust Criterion for Determining the Number of Static Factors in Approximate Factor Models (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:2008903
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