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Forecasting accuracy and the assumption of constancy

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  • Makridakis, Spyros

Abstract

Statistical forecasting is based on the assumption of constancy, or structural ability in the data. This paper argues that such an assumption might not always be realistic in real life forecasting situations. Unfortunately, however, statisticians and forecasters tend to forget, or at least not make explicit this important assumption, thus creating false expectations which cannot be realistically fulfilled. The paper proposes a wider role for forecasting and makes specific suggestions to overcome the problems arising when the assumption of constancy does not hold.

Suggested Citation

  • Makridakis, Spyros, 1981. "Forecasting accuracy and the assumption of constancy," Omega, Elsevier, vol. 9(3), pages 307-311.
    • Handle: RePEc:eee:jomega:v:9:y:1981:i:3:p:307-311
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    Cited by:

    1. Lawrence, Michael & O'Connor, Marcus, 2005. "Judgmental forecasting in the presence of loss functions," International Journal of Forecasting, Elsevier, vol. 21(1), pages 3-14.
    2. Francis X. Diebold & Peter Pauly, 1987. "Structural change and the combination of forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 6(1), pages 21-40.

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