A short note on the nowcasting and the forecasting of Euro-area GDP using non-parametric techniques
AbstractThe 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00461711.
Date of creation: Jan 2010
Date of revision:
Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00461711
Contact details of provider:
Web page: http://hal.archives-ouvertes.fr/
k-nearest neighbors method; radial basis function method; non-parametric; forecasts; GDP; Euro-area.;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-03-20 (All new papers)
- NEP-CBA-2010-03-20 (Central Banking)
- NEP-FOR-2010-03-20 (Forecasting)
- NEP-MAC-2010-03-20 (Macroeconomics)
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- repec:hal:journl:halshs-00511979 is not listed on IDEAS
- repec:hal:journl:halshs-00505165 is not listed on IDEAS
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (CCSD).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.