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Evaluating multi-step system forecasts with relatively few forecast-error observations

David Hendry () and Andrew Martinez ()

International Journal of Forecasting, 2017, vol. 33, issue 2, 359-372

Abstract: 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.

Keywords: Invariance; Forecast evaluation; Forecast error; Moment matrices; MSFE; GFESM (search for similar items in EconPapers)
Date: 2017
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Working Paper: Evaluating Multi-Step System Forecasts with Relatively Few Forecast-Error Observations (2016) Downloads
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