GDP nowcasting with ragged-edge data: A semi-parametric modelling

Laurent Ferrara, Dominique Guegan () and Patrick Rakotomarolahy ()
Additional contact information
Dominique Guegan: Paris School of Economics - Centre d'Economie de la Sorbonne, https://centredeconomiesorbonne.univ-paris1.fr
Patrick Rakotomarolahy: Centre d'Economie de la Sorbonne, https://centredeconomiesorbonne.univ-paris1.fr

Documents de travail du Centre d'Economie de la Sorbonne from Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne

Abstract: This papier formalizes the process of forecasting unbalanced monthly data sets in order to obtain robust nowcasts and forecasts of quarterly GDP growth rate through a semi-parametric modelling. This innovative approach lies on the use on non-parametric methods, based on nearest neighbors and on radial basis function approaches, ti forecast the monthly variables involved in the parametric modelling of GDP using bridge equations. A real-time experience is carried out on Euro area vintage data in order to anticipate, with an advance ranging from six to one months, the GDP flash estimate for the whole zone

Keywords: Euro area GDP; real-time nowcasting; forescasting; non-parametric methods (search for similar items in EconPapers)
JEL-codes: C22 C53 E32 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2008-11, Revised 2009-11
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-for and nep-mac
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Downloads: (external link)
ftp://mse.univ-paris1.fr/pub/mse/CES2008/B08082.pdf (application/pdf)

Related works:
Journal Article: GDP nowcasting with ragged-edge data: a semi-parametric modeling (2010)
Working Paper: GDP nowcasting with ragged-edge data: a semi-parametric modeling (2010)
Working Paper: GDP nowcasting with ragged-edge data: a semi-parametric modeling (2010)
Working Paper: GDP nowcasting with ragged-edge data: A semi-parametric modelling (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:b08082

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