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Assessing the accuracy of business‐level forecasts

Author

Listed:
  • Pete Brodie

    (Office for National Statistics)

  • Tullio Buccellato

    (Office for National Statistics)

  • Eric Scheffel

    (Office for National Statistics)

Abstract

SummaryThis article presents original work on some aspects of forecasting at the individual business‐ or firm‐level. In particular, two ways are suggested for assessing the accuracy of these forecasts based on the calculation of average percentage errors and the construction of a 95 per cent confidence interval. It is found that the quality of forecasts tend to become increasingly unreliable after two years and that the decay in forecast quality is inversely related to the frequency of the time series ‐ that is the less often a time series is updated/published the faster the deterioration in forecast quality.

Suggested Citation

  • Pete Brodie & Tullio Buccellato & Eric Scheffel, 2011. "Assessing the accuracy of business‐level forecasts," Economic & Labour Market Review, Palgrave Macmillan;Office for National Statistics, vol. 5(4), pages 119-134, April.
    • Handle: RePEc:pal:ecolmr:v:5:y:2011:i:4:p:119-134
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    Cited by:

    1. Frank Heilig & Edward J. Lusk, 2020. "OLS-Regression Forecasting Confidence Intervals Capture Rates: Precision Profiling in the Forecasting Model Selection Process," International Business Research, Canadian Center of Science and Education, vol. 13(4), pages 1-14, April.

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