We propose new forecast combination schemes for predicting turning points of business cycles. The proposed combination schemes are based on the forecasting performances of a given set of models with the aim to provide better turning point predictions. In particular, we consider 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 for 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 the Euro area business cycles.

Bayesian model averaging, Forecast combination, Markov-switching, Turning points
dx.doi.org/10.1016/j.qref.2012.08.002, hdl.handle.net/1765/37707
Quarterly Review of Economics and Finance
Erasmus Research Institute of Management

Billio, M, Casarin, R, Ravazzolo, F, & van Dijk, H.K. (2012). Combination schemes for turning point predictions. Quarterly Review of Economics and Finance, 52, 402–412. doi:10.1016/j.qref.2012.08.002