English, Article, Journal or magazine article edition: Are disaggregate data useful for factor analysis in forecasting French GDP? Barhoumi, K.; Darné, O.; Ferrara, L.

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Bookmark: http://trove.nla.gov.au/version/66379
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Are disaggregate data useful for factor analysis in forecasting French GDP?
Author
  • Barhoumi, K.
  • Darné, O.
  • Ferrara, L.
Physical Description
  • preprint
Notes
  • 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.
  • GDP forecasting ; Factor models ; Data aggregation.
  • RePEc:bfr:banfra:232
Language
  • English
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