Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/87207
Authors: 
Billio, Monica
Casarin, Roberto
Ravazzolo, Francesco
van Dijk, Herman K.
Year of Publication: 
2011
Series/Report no.: 
Tinbergen Institute Discussion Paper 11-123/4
Abstract: 
We propose new forecast combination schemes for predicting turning points of business cycles. The combination schemes deal with the forecasting performance of a given set of models and possibly providing better turning point predictions. We consider turning point predictions generated by autoregressive (AR) and Markov-Switching AR models, which are commonly used for business cycle analysis. In order to account for parameter uncertainty we consider a Bayesian approach to both estimation and prediction and compare, in terms of statistical accuracy, the individual models and the combined turning point predictions for the United States and Euro area business cycles.
Subjects: 
Turning Points
Markov-switching
Forecast Combination
Bayesian Model Averaging
JEL: 
C11
C15
C53
E37
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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