Laurent Ferrara () (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, Banque de France - Business Conditions and Macroeconomic Forecasting Directorate) Dominique Guegan () (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris) Patrick Rakotomarolahy () (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I)
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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.
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Length: Date of creation: Nov 2008 Date of revision: Handle: RePEc:hal:cesptp:halshs-00344839_v1
Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00344839/en/ Contact details of provider: Web page: http://hal.archives-ouvertes.fr/
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