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Short-term forecasts of French GDP: A dynamic factor model with targeted predictors

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Date
2013
Submitted
oui
Dewey
Macroéconomie
Sujet
Factor model; GDP forecasting; Large dataset; Targeted predictors; Variable selection
JEL code
C.C2.C22; E.E3.E32; E.E3.E37
Journal issue
Journal of Forecasting
Volume
32
Number
6
Publication date
09-2013
Article pages
500-511
DOI
http://dx.doi.org/10.1002/for.2262
URI
https://basepub.dauphine.fr/handle/123456789/10079
Collections
  • LEDa : Publications
Metadata
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Author
Bessec, Marie
status unknown
Type
Article accepté pour publication ou publié
Item number of pages
25
Abstract (EN)
In recent years, factor models have received increasing attention from both econometricians and practitioners in the forecasting of macroeconomic variables. In this context, Bai and Ng (2008) find an improvement in selecting indicators according to the forecast variable prior to factor estimation (targeted predictors). In particular, they propose using the LARS-EN algorithm to remove irrelevant predictors. In this paper, we adapt the Bai and Ng procedure to a setup in which data releases are delayed and staggered. In the pre-selection step, we replace actual data with estimates obtained on the basis of past information, where the structure of the available information replicates the one a forecaster would face in real time. We estimate on the reduced dataset the dynamic factor model of Giannone, Reichlin and Small (2008) and Doz, Giannone and Reichlin (2011), which is particularly suitable for the very short-term forecast of GDP. A pseudo real-time evaluation on French data shows the potential of our approach.

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