Combination Schemes for Turning Point Predictions

Arbeitspapier

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Tinbergen Institute Discussion Paper ; No. 11-123/4

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Bayesian Analysis: General ; Statistical Simulation Methods: General ; Forecasting Models; Simulation Methods ; Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
• Thema: Turning Points ; Markov-switching ; Forecast Combination ; Bayesian Model Averaging ; Prognoseverfahren ; Konjunkturprognose ; Autokorrelation ; Markovscher Prozess ; Bayes-Statistik ; Modellierung ; OECD-Staaten

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Billio, Monica ; Casarin, Roberto ; Ravazzolo, Francesco ; van Dijk, Herman K.
• Ereignis: Veröffentlichung
• (wer): Tinbergen Institute
• (wo): Amsterdam and Rotterdam
• (wann): 2011

Weitere Informationen

• Handle: http://hdl.handle.net/10419/87207
• Letzte Aktualisierung: 10.03.2025, 11:41 MEZ