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Decision making and planning under low levels of predictability

Author

Listed:
  • Makridakis, Spyros
  • Taleb, Nassim

Abstract

This special section aims to demonstrate the limited predictability and high level of uncertainty in practically all important areas of our lives, and the implications of this. It summarizes the huge body of solid empirical evidence accumulated over the past several decades that proves the disastrous consequences of inaccurate forecasts in areas ranging from the economy and business to floods and medicine. The big problem is, however, that the great majority of people, decision and policy makers alike, still believe not only that accurate forecasting is possible, but also that uncertainty can be reliably assessed. Reality, however, shows otherwise, as this special section proves. This paper discusses forecasting accuracy and uncertainty, and distinguishes three distinct types of predictions: those relying on patterns for forecasting, those utilizing relationships as their basis, and those for which human judgment is the major determinant of the forecast. In addition, the major problems and challenges facing forecasters and the reasons why uncertainty cannot be assessed reliably are discussed using four large data sets. There is also a summary of the eleven papers included in this special section, as well as some concluding remarks emphasizing the need to be rational and realistic about our expectations and avoid the common delusions related to forecasting.

Suggested Citation

  • Makridakis, Spyros & Taleb, Nassim, 2009. "Decision making and planning under low levels of predictability," International Journal of Forecasting, Elsevier, vol. 25(4), pages 716-733, October.
  • Handle: RePEc:eee:intfor:v:25:y:2009:i:4:p:716-733
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    References listed on IDEAS

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    1. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, pages 451-476.
    2. Goldstein, Daniel G. & Gigerenzer, Gerd, 2009. "Fast and frugal forecasting," International Journal of Forecasting, Elsevier, pages 760-772.
    3. Orrell, David & McSharry, Patrick, 2009. "System economics: Overcoming the pitfalls of forecasting models via a multidisciplinary approach," International Journal of Forecasting, Elsevier, pages 734-743.
    4. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters,in: THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78 World Scientific Publishing Co. Pte. Ltd..
    5. Wright, George & Goodwin, Paul, 2009. "Decision making and planning under low levels of predictability: Enhancing the scenario method," International Journal of Forecasting, Elsevier, pages 813-825.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Derbyshire, James & Wright, George, 2017. "Augmenting the intuitive logics scenario planning method for a more comprehensive analysis of causation," International Journal of Forecasting, Elsevier, pages 254-266.
    2. repec:spr:reaccs:v:22:y:2017:i:3:d:10.1007_s11142-017-9396-0 is not listed on IDEAS
    3. Estrada, Fernando, 2011. "Theory of financial risk," MPRA Paper 29665, University Library of Munich, Germany.
    4. repec:eee:reensy:v:137:y:2015:i:c:p:18-28 is not listed on IDEAS
    5. Estrada, Fernando, 2009. "Tamaño y Riesgo en los Mercados Financieros
      [Size and Risk in the Finanzal Markets]
      ," MPRA Paper 19267, University Library of Munich, Germany.
    6. Jan Anne Annema & Hugo Priemus, 2013. "Mega-projects: new challenges to cope with climate change and energy transition," Chapters,in: International Handbook on Mega-Projects, chapter 18, pages 398-417 Edward Elgar Publishing.
    7. Miller, Craig & Newell, Barry, 2013. "Framing integrated research to address a dynamically complex issue: The red headed cockchafer challenge," Agricultural Systems, Elsevier, pages 13-18.
    8. Schumacher Christian, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, pages 28-49.
    9. Ludovic Gaudard & Franco Romerio, 2015. "Natural hazard risk in the case of an emergency: the real options’ approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, pages 473-488.

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