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A Comparison of the Finite Sample Properties of Selection Rules of Factor Numbers in Large Datasets

GUO-FITOUSSI, Liang (2013): A Comparison of the Finite Sample Properties of Selection Rules of Factor Numbers in Large Datasets.

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Abstract

Abstract In this paper, we compare the properties of the main criteria proposed for selecting the number of factors in dynamic factor model in a small sample. Both static and dynamic factor numbers' selection rules are studied. Simulations show that the GR ratio proposed by Ahn and Horenstein (2013) and the criterion proposed by Onatski (2010) outperform the others. Furthermore, the two criteria can select accurately the number of static factors in a dynamic factors design. Also, the criteria proposed by Hallin and Liska (2007) and Breitung and Pigorsch (2009) correctly select the number of dynamic factors in most cases. However, empirical application show most criteria select only one factor in presence of one strong factor.

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