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Are disaggregate data useful for factor analysis in forecasting French GDP?

  • Karim Barhoumi

    (Banque de France, DGEI-DCPM, Paris, France)

  • Olivier Darné
  • Laurent Ferrara

    (Banque de France, DGEI-DCPM, Paris, France)

This paper compares the GDP forecasting performance of alternative factor models based on monthly time series for the French economy. These models are based on static and dynamic principal components obtained using time and frequency domain methods. We question whether it is more appropriate to use aggregate or disaggregate data to extract the factors used in forecasting equations. The forecasting accuracy is evaluated for various forecast horizons considering both rolling and recursive schemes. We empirically show that static factors, estimated from a small database, lead to competitive results, especially for nowcasting. Copyright © 2009 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1162
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 29 (2010)
Issue (Month): 1-2 ()
Pages: 132-144

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Handle: RePEc:jof:jforec:v:29:y:2010:i:1-2:p:132-144
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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