Arbeitspapier
Forecasting Time Series Subject to Multiple Structural Breaks
This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks over the forecast horizon, taking account of the size and duration of past breaks (if any) by means of a hierarchical hidden Markov chain model. Predictions are formed by integrating over the hyper parameters from the meta distributions that characterize the stochastic break point process. In an application to US Treasury bill rates, we find that the method leads to better out-of-sample forecasts than alternative methods that ignore breaks, particularly at long horizons.
- Sprache
-
Englisch
- Erschienen in
-
Series: IZA Discussion Papers ; No. 1196
- Klassifikation
-
Wirtschaft
Bayesian Analysis: General
Statistical Simulation Methods: General
Forecasting Models; Simulation Methods
- Thema
-
structural breaks
forecasting
hierarchical hidden Markov chain model
Bayesian model averaging
Prognoseverfahren
Zeitreihenanalyse
Strukturbruch
Theorie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Timmermann, Allan
Pettenuzzo, Davide
Pesaran, Mohammad Hashem
- Ereignis
-
Veröffentlichung
- (wer)
-
Institute for the Study of Labor (IZA)
- (wo)
-
Bonn
- (wann)
-
2004
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Timmermann, Allan
- Pettenuzzo, Davide
- Pesaran, Mohammad Hashem
- Institute for the Study of Labor (IZA)
Entstanden
- 2004
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