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A parsimonious explanation of observed biases when forecasting one’s own performance

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  • Meeran, Sheik
  • Goodwin, Paul
  • Yalabik, Baris

Abstract

Forecasting one’s own performance on tasks is important in a wide range of contexts. Over-forecasting can lead to an unresponsiveness to advice and feedback. In group forecasting, under-forecasting may lead individuals to discount valuable inputs that they could contribute. Research shows that those who perform relatively poorly in tasks tend to make predictions that are too high, while high performers tend to under-forecast their performances. Several explanations have been put forward for this ‘regressive forecasting’, such as a lack of metacognitive skills in poor performers and a false-consensus bias in high performers. Others claim that the bias is simply an artefact of regression. In this study, people were asked to forecast their performances on six multiple-choice tests. The results suggest that a simple explanation based on the anchoring and adjustment heuristic would account for the phenomenon, at least in part.

Suggested Citation

  • Meeran, Sheik & Goodwin, Paul & Yalabik, Baris, 2016. "A parsimonious explanation of observed biases when forecasting one’s own performance," International Journal of Forecasting, Elsevier, vol. 32(1), pages 112-120.
  • Handle: RePEc:eee:intfor:v:32:y:2016:i:1:p:112-120
    DOI: 10.1016/j.ijforecast.2015.05.001
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    References listed on IDEAS

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    1. Markus M. Möbius & Muriel Niederle & Paul Niehaus & Tanya S. Rosenblat, 2022. "Managing Self-Confidence: Theory and Experimental Evidence," Management Science, INFORMS, vol. 68(11), pages 7793-7817, November.
    2. Krajc, Marian & Ortmann, Andreas, 2008. "Are the unskilled really that unaware? An alternative explanation," Journal of Economic Psychology, Elsevier, vol. 29(5), pages 724-738, November.
    3. Ehrlinger, Joyce & Johnson, Kerri & Banner, Matthew & Dunning, David & Kruger, Justin, 2008. "Why the unskilled are unaware: Further explorations of (absent) self-insight among the incompetent," Organizational Behavior and Human Decision Processes, Elsevier, vol. 105(1), pages 98-121, January.
    4. repec:cup:judgdm:v:9:y:2014:i:5:p:445-464 is not listed on IDEAS
    5. Schlösser, Thomas & Dunning, David & Johnson, Kerri L. & Kruger, Justin, 2013. "How unaware are the unskilled? Empirical tests of the “signal extraction” counterexplanation for the Dunning–Kruger effect in self-evaluation of performance," Journal of Economic Psychology, Elsevier, vol. 39(C), pages 85-100.
    6. Bonner, Bryan L. & Baumann, Michael R. & Dalal, Reeshad S., 2002. "The effects of member expertise on group decision-making and performance," Organizational Behavior and Human Decision Processes, Elsevier, vol. 88(2), pages 719-736, July.
    7. Lawrence, Michael & O'Connor, Marcus, 1992. "Exploring judgemental forecasting," International Journal of Forecasting, Elsevier, vol. 8(1), pages 15-26, June.
    8. O'Connor, Marcus & Remus, William & Griggs, Ken, 1993. "Judgemental forecasting in times of change," International Journal of Forecasting, Elsevier, vol. 9(2), pages 163-172, August.
    9. Rowe, Gene & Wright, George, 1999. "The Delphi technique as a forecasting tool: issues and analysis," International Journal of Forecasting, Elsevier, vol. 15(4), pages 353-375, October.
    10. Marian Krajc, 2008. "Are the Unskilled Really That Unaware? Understanding Seemingly Biased Self-Assessments," CERGE-EI Working Papers wp373, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    11. Bonaccio, Silvia & Dalal, Reeshad S., 2006. "Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences," Organizational Behavior and Human Decision Processes, Elsevier, vol. 101(2), pages 127-151, November.
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