Combination Schemes for Turning Point Predictions - Monica Billio; Roberto Casarin; Francesco Ravazzolo; Herman K. van Dijk (Tinbergen Institute, 2011)
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.
urn:NBN:nl:ui:31-1871/38539
Keywords: C11; C15; C53; E37; 330; Turning Points; Markov-switching; Forecast Combination; Bayesian Model Averaging; Prognoseverfahren; Konjunkturprognose; Autokorrelation; Markovscher Prozess; Bayes-Statistik; Modellierung; OECD-Staaten