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.
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- Marcellino, Massimiliano & Schumacher, Christian, 2007.
"Factor-MIDAS for now- and forecasting with ragged-edge data: a model comparison for German GDP,"
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Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers)
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- repec:ebl:ecbull:v:3:y:2008:i:32:p:1-8 is not listed on IDEAS
- Diron, Marie, 2006.
"Short-term forecasts of euro area real GDP growth: an assessment of real-time performance based on vintage data,"
Working Paper Series
0622, European Central Bank.
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- Adonis Yatchew, 1998. "Nonparametric Regression Techniques in Economics," Journal of Economic Literature, American Economic Association, vol. 36(2), pages 669-721, June.
- Olivier Darne, 2008. "Using business survey in industrial and services sector to nowcast GDP growth:The French case," Economics Bulletin, AccessEcon, vol. 3(32), pages 1-8.
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