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

  • Barhoumi, K.
  • Darné, O.
  • Ferrara, L.

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. The dynamic principal components are obtained using time and frequency domain methods. The forecasting accuracy is evaluated in two ways for GDP growth. First, we question whether it is more appropriate to use aggregate or disaggregate data (with three disaggregating levels) to extract the factors. Second, we focus on the determination of the number of factors obtained either from various criteria or from a fixed choice.

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Paper provided by Banque de France in its series Working papers with number 232.

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Length: 27 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:bfr:banfra:232
Contact details of provider: Postal: Banque de France 31 Rue Croix des Petits Champs LABOLOG - 49-1404 75049 PARIS
Web page: http://www.banque-france.fr/

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