Forecasting time series subject to multiple structural breaks
By: by Hashem Pesaran, Davide Pettenuzzo, Allan Timmermann.
Contributors: Pettenuzzo, Davide.; Timmermann, Allan.
Series: Discussion paper ;; no. 1196; Discussion paper (Forschungsinstitut zur Zukunft der Arbeit : Online) ;; no. 1196
Publisher: IZA
Published: 2004
Place of publication: Bonn, Germany
Language: eng
Format: Electronic resource
Subjects: Treasury bills -- Prices -- United States -- Forecasting
Description: "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"--Forschungsinstitut zur Zukunft der Arbeit web site.
Notes: Also available in print.
Includes bibliographical references.
Title from PDF file as viewed on 5/9/2005.
System requirements: Adobe Acrobat Reader.
Mode of access: World Wide Web.