Aggregation of Opinions Based on Correlated Cues and Advisors
Psychology | Social and Behavioral Sciences
We study the process by which decision makers (DMs) aggregate probabilistic opinions from multiple, correlated sources with a special emphasis on the determinants of the DM’s confidence, which is a predictor of the DM’s willingness to accept the implications of the aggregation process. Our model assumes that (a) DM combines the advisors’ opinions by weighting them according to the amount of information underlying them, and (b) the DM’s confidence increases as a function of a variety of factors that reduce the variance of the aggregate. We report results of three studies that manipulate the predictive validity of the cues and their inter-correlations. Most of the models’ predictions are supported but, contrary to the model’s prediction, the DMs’ confidence is not sensitive to the inter-cue correlation. The best predictors of the DMs’ confidence are the perceived predictability of the event, the level of agreement among the advisors, and the advisors’ self-reports of confidence. This pattern of results is explained by the ‘system neglect’ hypothesis.
Budescu, David V. and Yu, Hsiu-Ting, "Aggregation of Opinions Based on Correlated Cues and Advisors" (2007). Psychology Faculty Publications. Paper 36.