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Combination schemes for turning point predictions

  • Monica Billio

    (University of Venice, GRETA Assoc. and School for Advanced Studies in Venice)

  • Roberto Casarin


    (University of Venice, GRETA Assoc. and School for Advanced Studies in Venice)

  • Francesco Ravazzolo

    (Norges Bank (Central Bank of Norway) and BI Norwegian Business School)

  • Herman K. van Dijk

    (Econometric Institute, Erasmus University Rotterdam and VU University Amsterdam and Tinbergen Institute)

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.

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Paper provided by Norges Bank in its series Working Paper with number 2012/04.

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Length: 30 pages
Date of creation: 10 Apr 2012
Date of revision:
Handle: RePEc:bno:worpap:2012_04
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