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Forecasting and uncertainty in the economic and business world

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Author Info

  • Makridakis, Spyros
  • Hogarth, Robin M.
  • Gaba, Anil

Abstract

Forecasts are crucial for practically all economic and business decisions. However, there is a mounting body of empirical evidence showing that accurate forecasting in the economic and business world is usually not possible. In addition, there is huge uncertainty, as practically all economic and business activities are subject to events we are unable to predict. The fact that forecasts can be inaccurate creates a serious dilemma for decision and policy makers. On the one hand, accepting the limits of forecasting accuracy implies being unable to assess the correctness of decisions and the surrounding uncertainty. On the other hand, believing that accurate forecasts are possible means succumbing to the illusion of control and experiencing surprises, often with negative consequences. We believe that the time has come for a new attitude towards dealing with the future. In this article, we discuss the limited predictability in the economic and business environment. We also provide a framework that allows decision and policy makers to face the future -- despite the inherent limitations of forecasting and the uncertainty, sometimes huge, surrounding most future-oriented decisions.

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Bibliographic Info

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 25 (2009)
Issue (Month): 4 (October)
Pages: 794-812

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Handle: RePEc:eee:intfor:v:25:y:2009:i:4:p:794-812

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Web page: http://www.elsevier.com/locate/ijforecast

Related research

Keywords: Forecasting Accuracy Uncertainty Subway uncertainty Coconut uncertainty Black swans Illusion of control Dealing with uncertainty;

References

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  1. Antonio Bernardo & Ivo Welch, 2001. "On the Evolution of Overconfidence and Entrepreneurs," Yale School of Management Working Papers ysm211, Yale School of Management, revised 01 Nov 2003.
  2. Daniel Kahneman & Dan Lovallo, 1993. "Timid Choices and Bold Forecasts: A Cognitive Perspective on Risk Taking," Management Science, INFORMS, vol. 39(1), pages 17-31, January.
  3. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
  4. Robin M. Hogarth & Spyros Makridakis, 1981. "Forecasting and Planning: An Evaluation," Management Science, INFORMS, vol. 27(2), pages 115-138, February.
  5. Orrell, David & McSharry, Patrick, 2009. "System economics: Overcoming the pitfalls of forecasting models via a multidisciplinary approach," International Journal of Forecasting, Elsevier, vol. 25(4), pages 734-743, October.
  6. Johnson, Eric J, et al, 1993. " Framing, Probability Distortions, and Insurance Decisions," Journal of Risk and Uncertainty, Springer, vol. 7(1), pages 35-51, August.
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Citations

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Cited by:
  1. Knüppel, Malte, 2014. "Efficient estimation of forecast uncertainty based on recent forecast errors," International Journal of Forecasting, Elsevier, vol. 30(2), pages 257-267.
  2. Savio, Nicolas D. & Nikolopoulos, Konstantinos, 2013. "A strategic forecasting framework for governmental decision-making and planning," International Journal of Forecasting, Elsevier, vol. 29(2), pages 311-321.
  3. Makridakis, Spyros & Taleb, Nassim, 2009. "Living in a world of low levels of predictability," International Journal of Forecasting, Elsevier, vol. 25(4), pages 840-844, October.

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