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

Marie Bessec ()

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Abstract: 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.

Keywords: Factor model; GDP forecasting; Large dataset; Targeted predictors; Variable selection (search for similar items in EconPapers)
Date: 2013
Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-01515605
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Published in Journal of Forecasting, 2013, 32 (6), pp.25. ⟨10.1002/for.2262⟩

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Related works:
Journal Article: Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors (2013)
Working Paper: Short-term forecasts of French GDP: a dynamic factor model with targeted predictors (2012) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01515605

DOI: 10.1002/for.2262

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