Christian Dahl (),
Henrik Hansen () and
John Smidt ()
Additional contact information John Smidt: School of Economics and Management, University of Aarhus, Denmark and CREATES, Postal: 8000 Aarhus C, Denmark
Abstract:
Forecasting using factor models based on large data sets have received ample attention due to the models’ ability to increase forecast accuracy with respect to a range of key macroeconomic variables in the US and the UK. However, forecasts based on such factor models do not uniformly outperform the simple autoregressive model when using data from other countries. In this paper we propose to estimate the factors based on the pure cyclical components of the series entering the large data set. Monte Carlo evidence and an empirical illustration using Danish data shows that this procedure can indeed improve on pseudo real time forecast accuracy.
Related works: Journal Article: The cyclical component factor model (2009) This item may be available elsewhere in EconPapers: Search for items with the same title.