Giraitis, L., Kapetanios, G. & Price, S. (2012). Adaptive forecasting in the presence of recent and ongoing structural change (Report No. 12/02). London, UK: Department of Economics, City University London.
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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.
|Item Type:||Monograph (Discussion Paper)|
|Additional Information:||© 2012 The authors.|
|Subjects:||H Social Sciences > HB Economic Theory|
|Divisions:||School of Social Sciences > Department of Economics > Department of Economics Discussion Paper Series|
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- Adaptive forecasting in the presence of recent and ongoing structural change. (deposited 30 Aug 2012 13:45) [Currently Displayed]
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