Judgmental aggregation strategies depend on whether the self is involved

Abstract

Abstract We report the results of a novel experiment that addresses two unresolved questions in the judgmental forecasting literature. First, how does combining the estimates of others differ from revising one’s own estimate based on the judgment of another? The experiment found that participants often ignored advice when revising an estimate but averaged estimates when combining. This was true despite receiving identical feedback about the accuracy of past judgments. Second, why do people consistently tend to overweight their own opinions at the expense of profitable advice? We compared two prominent explanations for this, differential access to reasons and egocentric beliefs, and found that neither adequately accounts for the overweighting of the self. Finally, echoing past research, we find that averaging opinions is often advantageous, but that choosing a single judge can perform well in certain predictable situations.