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Abstract

The contention advanced in this paper is that forecast performance could be improved if short-term commodity forecasters were to consider formally the use of a variety of forecasting methods, rather than seeking to improve one selected method. Many researchers have demonstrated that a linear combination of forecasts can produce a composite superior to the individual component forecasts. Using a case study of two Bureau of Agricultural Economics' forecast series and alternative, time series model forecasts of the same series, four methods of deriving composite forecasts are applied on an ex ante basis and are thus evaluated as a means of improving the Bureau's forecast performance. Despite the fact that the authors could not, by combining the available forecasts, form a superior composite forecast, the application highlights the suitability of this approach for reviewing the performance of forecasting methods on a formal basis, and did prove useful in exposing weaknesses and strengths in BAE market information forecasts which otherwise would not have come to light.

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