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Dynamic Factors in the Presence of Block Structure Author info | Abstract | Publisher info | Download info | Related research | Statistics Marc Hallin
Roman Liska
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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.
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Paper provided by Université Libre de Bruxelles, Ecares in its series ECARES Working Papers with number
2008_012.
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Length: 34 pages
Date of creation: 2008Date of revision:
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Keywords: Panel data ; Time series ; High dimensional data ; Dynamic factor model ; Business cycle ; Block specific factors ; Dynamic principal components ; Information criterion ; Other versions of this item:
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
Marc Hallin & Charles Mathias & Hugues Pirotte & David Veredas, 2009.
"Market Liquidity as Dynamic Factors ,"
ECARES Working Papers
2009_004, Université Libre de Bruxelles, Ecares.
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