A hybrid forecasting approach for piece-wise stationary time series

Ronald Bewley and Minxian Yang
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Ronald Bewley: School of Economics, University of New South Wales, Sydney, Australia, Postal: School of Economics, University of New South Wales, Sydney, Australia

Journal of Forecasting, 2006, vol. 25, issue 7, 513-527

Abstract: We consider the problem of forecasting a stationary time series when there is an unknown mean break close to the forecast origin. Based on the intercept-correction methods suggested by Clements and Hendry (1998) and Bewley (2003), a hybrid approach is introduced, where the break and break point are treated in a Bayesian fashion. The hyperparameters of the priors are determined by maximizing the marginal density of the data. The distributions of the proposed forecasts are derived. Different intercept-correction methods are compared using simulation experiments. Our hybrid approach compares favorably with both the uncorrected and the intercept-corrected forecasts. Copyright © 2006 John Wiley & Sons, Ltd.

Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:jof:jforec:v:25:y:2006:i:7:p:513-527

DOI: 10.1002/for.1003

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