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• W1575069184 abstract "This paper considers forecast averaging when the same model is used but estimation is carried out over different estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or more structural breaks. It is shown that compared to using forecasts based on a single estimation window, averaging over estimation windows leads to a lower bias and to a lower root mean square forecast error for all but the smallest of breaks. Similar results are also obtained when observations are exponentially down-weighted, although in this case the performance of forecasts based on exponential down-weighting critically depends on the choice of the weighting coefficient. The forecasting techniques are applied to monthly inflation series of 21 OECD countries and it is found that average forecasting methods in general perform better than using forecasts based on a single estimation window." @default.
• W1575069184 created "2016-06-24" @default.
• W1575069184 creator A5004307122 @default.
• W1575069184 creator A5035852116 @default.
• W1575069184 date "2008-03-01" @default.
• W1575069184 modified "2023-09-25" @default.
• W1575069184 title "Forecasting random walks under drift instability" @default.
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• W1575069184 doi "https://doi.org/10.17863/cam.5322" @default.
• W1575069184 hasPublicationYear "2008" @default.
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