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Dynamic Factors in the Presence of Block Structure

Marc Hallin () and Roman Liska ()

No 2008_012, Working Papers ECARES from ULB -- Universite Libre de Bruxelles

Abstract: Macroeconometric data often come under the form of large panels of time series, themselves decomposing into smaller but still quite large subpanels or blocks. We show how the dynamic factor analysis method proposed in Forni et al (2000), combined with the identification method of Hallin and Liska (2007), allows for identifying and estimating joint and block-specific common factors. This leads to a more sophisticated analysis of the structures of dynamic interrelations within and between the blocks in such datasets, along with an informative decomposition of explained variances. The method is illustrated with an analysis of the Industrial Production Index data for France, Germany, and Italy.

Keywords: Panel data; Time series; High dimensional data; Dynamic factor model; Business cycle; Block specific factors; Dynamic principal components; Information criterion (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2008
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