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The Accuracy of Combining Judgemental and Statistical Forecasts

Author

Listed:
  • M. J. Lawrence

    (Department of Information Systems, University of New South Wales, Kensington N.S.W. Australia)

  • R. H. Edmundson

    (Department of Information Systems, University of New South Wales, Kensington N.S.W. Australia)

  • M. J. O'Connor

    (Department of Information Systems, University of New South Wales, Kensington N.S.W. Australia)

Abstract

Judgement based forecasts are widely used in practice either alone or in conjunction with computer prepared forecasts. This study empirically examines the improvement in accuracy which can be gained from combining judgemental forecasts, either with other judgemental or with quantitatively derived forecasts. Two judgemental forecasting approaches are used by each of two different groups in a laboratory setting to give four sets of judgemental forecasts for the 68 monthly time series of the M-competition. These are combined either with each other or with forecasts from deseasonalised single exponential smoothing. Combined forecasts are found to be more accurate than single forecasts with the greatest benefit realised at short forecast horizons and for easier (as opposed to harder) forecast series. Averaging was observed to be a far better way of combining judgemental forecasts than a judgemental, nonsystematic combination.

Suggested Citation

  • M. J. Lawrence & R. H. Edmundson & M. J. O'Connor, 1986. "The Accuracy of Combining Judgemental and Statistical Forecasts," Management Science, INFORMS, vol. 32(12), pages 1521-1532, December.
  • Handle: RePEc:inm:ormnsc:v:32:y:1986:i:12:p:1521-1532
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    File URL: http://dx.doi.org/10.1287/mnsc.32.12.1521
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    References listed on IDEAS

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    1. Ian I. Mitroff, 1972. "The Myth of Objectivity OR Why Science Needs a New Psychology of Science," Management Science, INFORMS, vol. 18(10), pages 613-618, June.
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    Citations

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    Cited by:

    1. Theocharis, Zoe & Harvey, Nigel, 2016. "Order effects in judgmental forecasting," International Journal of Forecasting, Elsevier, vol. 32(1), pages 44-60.
    2. Welch, Eric & Bretschneider, Stuart & Rohrbaugh, John, 1998. "Accuracy of judgmental extrapolation of time series data: Characteristics, causes, and remediation strategies for forecasting," International Journal of Forecasting, Elsevier, vol. 14(1), pages 95-110, March.
    3. Rustem, Berc & Becker, Robin G. & Marty, Wolfgang, 2000. "Robust min-max portfolio strategies for rival forecast and risk scenarios," Journal of Economic Dynamics and Control, Elsevier, vol. 24(11-12), pages 1591-1621, October.
    4. Gulpinar, Nalan & Rustem, Berc, 2007. "Robust optimal decisions with imprecise forecasts," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3595-3611, April.
    5. Goodwin, Paul, 2002. "Integrating management judgment and statistical methods to improve short-term forecasts," Omega, Elsevier, vol. 30(2), pages 127-135, April.
    6. Webby, Richard & O'Connor, Marcus, 1996. "Judgemental and statistical time series forecasting: a review of the literature," International Journal of Forecasting, Elsevier, vol. 12(1), pages 91-118, March.
    7. Pär Osterholm, 2009. "Incorporating Judgement in Fan Charts," Scandinavian Journal of Economics, Wiley Blackwell, vol. 111(2), pages 387-415, June.
    8. Gulpinar, Nalan & Rustem, Berc, 2007. "Worst-case robust decisions for multi-period mean-variance portfolio optimization," European Journal of Operational Research, Elsevier, vol. 183(3), pages 981-1000, December.
    9. Önkal, Dilek & Lawrence, Michael & Zeynep Sayım, K., 2011. "Influence of differentiated roles on group forecasting accuracy," International Journal of Forecasting, Elsevier, vol. 27(1), pages 50-68.
    10. repec:pal:jorsoc:v:59:y:2008:i:9:d:10.1057_palgrave.jors.2602597 is not listed on IDEAS
    11. Leitner, Johannes & Leopold-Wildburger, Ulrike, 2011. "Experiments on forecasting behavior with several sources of information - A review of the literature," European Journal of Operational Research, Elsevier, vol. 213(3), pages 459-469, September.
    12. Goodwin, P., 1996. "Statistical correction of judgmental point forecasts and decisions," Omega, Elsevier, vol. 24(5), pages 551-559, October.
    13. Seifert, Matthias & Hadida, Allègre L., 2013. "On the relative importance of linear model and human judge(s) in combined forecasting," Organizational Behavior and Human Decision Processes, Elsevier, vol. 120(1), pages 24-36.
    14. Harvey, Nigel & Harries, Clare, 2004. "Effects of judges' forecasting on their later combination of forecasts for the same outcomes," International Journal of Forecasting, Elsevier, vol. 20(3), pages 391-409.
    15. Syntetos, Aris A. & Kholidasari, Inna & Naim, Mohamed M., 2016. "The effects of integrating management judgement into OUT levels: In or out of context?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 853-863.
    16. Lau, Hon-Shiang & Hing-Ling Lau, Amy, 1996. "Estimating the demand distributions of single-period items having frequent stockouts," European Journal of Operational Research, Elsevier, vol. 92(2), pages 254-265, July.
    17. Dewispelare, Aaron R. & Herren, L. Tandy & Clemen, Robert T., 1995. "The use of probability elicitation in the high-level nuclear waste regulation program," International Journal of Forecasting, Elsevier, vol. 11(1), pages 5-24, March.
    18. Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael, 2014. "Collaborative forecasting in the food supply chain: A conceptual framework," International Journal of Production Economics, Elsevier, vol. 158(C), pages 120-135.
    19. Lim, Joa Sang & O'Connor, Marcus, 1996. "Judgmental forecasting with time series and causal information," International Journal of Forecasting, Elsevier, vol. 12(1), pages 139-153, March.
    20. Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, vol. 22(3), pages 493-518.
    21. Par Osterholm, 2008. "A structural Bayesian VAR for model-based fan charts," Applied Economics, Taylor & Francis Journals, vol. 40(12), pages 1557-1569.

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