The Contribution of Structural Break Models to Forecasting Macroeconomic Series
AbstractThis paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. We find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling window based forecasts perform well.
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Bibliographic InfoPaper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 38_11.
Date of creation: Jul 2011
Date of revision:
Forecasting; change-points; Markov switching; Bayesian inference;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-07-21 (All new papers)
- NEP-CBA-2011-07-21 (Central Banking)
- NEP-ECM-2011-07-21 (Econometrics)
- NEP-ETS-2011-07-21 (Econometric Time Series)
- NEP-FOR-2011-07-21 (Forecasting)
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- Czinkota, Thomas, 2012.
"Das Halteproblem bei Strukturbrüchen in Finanzmarktzeitreihen
[The Halting Problem applied to Structural Breaks in Financial Time Series]," MPRA Paper 37072, University Library of Munich, Germany.
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