Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/154206 
Year of Publication: 
2015
Series/Report no.: 
ECB Working Paper No. 1773
Publisher: 
European Central Bank (ECB), Frankfurt a. M.
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

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