Arbeitspapier
Adaptive forecasting in the presence of recent and ongoing structural change
We consider time series forecasting in the presence of ongoing structural change where both the time series dependence and the nature of the structural change are unknown. Methods that downweight older data, such as rolling regressions, forecast averaging over different windows and exponentially weighted moving averages, known to be robust to historical structural change, are found to be also useful in the presence of ongoing structural change in the forecast period. A crucial issue is how to select the degree of downweighting, usually defined by an arbitrary tuning parameter. We make this choice data dependent by minimizing forecast mean square error, and provide a detailed theoretical analysis of our proposal. Monte Carlo results illustrate the methods. We examine their performance on 191 UK and US macro series. Forecasts using data-based tuning of the data discount rate are shown to perform well.
- Language
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Englisch
- Bibliographic citation
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Series: Working Paper ; No. 691
- Classification
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Wirtschaft
Econometric and Statistical Methods and Methodology: General
Econometric Modeling: Other
- Subject
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Recent and ongoing structural change
Forecast combination
Robust forecasts
- Event
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Geistige Schöpfung
- (who)
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Giraitis, Liudas
Kapetanios, George
Price, Simon
- Event
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Veröffentlichung
- (who)
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Queen Mary University of London, School of Economics and Finance
- (where)
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London
- (when)
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2012
- Handle
- Last update
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10.03.2025, 11:43 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Giraitis, Liudas
- Kapetanios, George
- Price, Simon
- Queen Mary University of London, School of Economics and Finance
Time of origin
- 2012