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Evaluating multi-step system forecasts with relatively few forecast-error observations
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DOI：10.1016/j.ijforecast.2016.08.007.png)
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Abstract
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This paper develops a new approach for evaluating multi-step system forecasts with relatively few forecast-error observations. It extends the work of Clements and Hendry (1993) by using that of Abadir et al. (2014) to generate design-free estimates of the general matrix of the forecast-error second-moment when there are relatively few forecast-error observations. Simulations show that the usefulness of alternative methods deteriorates when their assumptions are violated. The new approach compares well with these methods and provides correct forecast rankings. (C) 2016 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Keywords:
Invariance
Forecast evaluation
Forecast error
Moment matrices
MSFE
GFESM
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