A Short Note on the Nowcasting and the Forecasting of Euro-area GDP Using Non-Parametric Techniques
The aim of this paper is to introduce a new methodology to forecast the monthly economic indicators used in the Gross Domestic Product (GDP) modelling in order to improve the forecasting accuracy. Our approach is based on multivariate k-nearest neighbors method and radial basis function method for which we provide new theoretical results. We apply these two methods to compute the quarter GDP on the Euro-zone, comparing our approach, with GDP obtained when we estimate the monthly indicators with a linear model, which is often used as a benchmark.
|Date of creation:||2010|
|Publication status:||Published in Economics Bulletin, Economics Bulletin, 2010, 30 (1), pp.508-518|
|Note:||View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00460472|
|Contact details of provider:|| Web page: https://hal.archives-ouvertes.fr/|
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Documents de travail du Centre d'Economie de la Sorbonne
09050, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Dec 2009.
- Dominique Guegan & Patrick Rakotomarolahy, 2009. "The Multivariate k-Nearest Neighbor Model for Dependent Variables : One-Sided Estimation and Forecasting," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00423871, HAL.
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