Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/154206
Authors: 
Camba-Méndez, Gonzalo
Kapetanios, George
Papailias, Fotis
Weale, Martin R.
Year of Publication: 
2015
Series/Report no.: 
ECB Working Paper 1773
Abstract: 
This paper assesses the forecasting performance of various variable reduction and variable selection methods. A small and a large set of wisely chosen variables are used in forecasting the industrial production growth for four Euro Area economies. The results indicate that the Automatic Leading Indicator (ALI) model performs well compared to other variable reduction methods in small datasets. However, Partial Least Squares and variable selection using heuristic optimisations of information criteria along with the ALI could be used in model averaging methodologies.
Subjects: 
Bayesian shrinkage regression
dynamic factor model
euro area
forecasting
Kalman filter
partial least squares
JEL: 
C11
C32
C52
ISBN: 
978-92-899-1586-1
Document Type: 
Working Paper

Files in This Item:
File
Size
514.24 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.