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Golden rule of forecasting: Be conservative

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  • Armstrong, J. Scott
  • Green, Kesten C.
  • Graefe, Andreas

Abstract

This article proposes a unifying theory, or the Golden Rule, of forecasting. The Golden Rule of Forecasting is to be conservative. A conservative forecast is consistent with cumulative knowledge about the present and the past. To be conservative, forecasters must seek out and use all knowledge relevant to the problem, including knowledge of methods validated for the situation.

Suggested Citation

  • Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
  • Handle: RePEc:eee:jbrese:v:68:y:2015:i:8:p:1717-1731
    DOI: 10.1016/j.jbusres.2015.03.031
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    More about this item

    Keywords

    Analytics; Bias; Big data; Checklists; Combining; Uncertainty;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • K2 - Law and Economics - - Regulation and Business Law

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