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

Sheik Meeran, Paul Goodwin and Baris Yalabik

International Journal of Forecasting, 2016, vol. 32, issue 1, 112-120

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.

Keywords: Judgmental forecasting; Metacognitive skills; Regression effects; Self-performance forecasting; Anchoring and adjustment (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:32:y:2016:i:1:p:112-120

DOI: 10.1016/j.ijforecast.2015.05.001

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