 Short-term forecasts of French GDP: A dynamic factor model with targeted predictorsPost-Print from HAL 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) Published in Journal of Forecasting, 2013, 32 (6), pp.25. ⟨10.1002/for.2262⟩ Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01515605 DOI: 10.1002/for.2262 Access Statistics for this paper More papers in Post-Print from HAL |
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