Combination schemes for turning point predictions

M Billio, R Casarin, F Ravazzolo, Herman van Dijk

Research output: Contribution to journalArticleAcademicpeer-review

17 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)402-412
Number of pages11
JournalQuarterly Review of Economics and Finance
Issue number4
Publication statusPublished - 2012


Dive into the research topics of 'Combination schemes for turning point predictions'. Together they form a unique fingerprint.

Cite this