Information Acquisition and Dissemination in Groups

Abstract

This dissertation focuses on group information acquisition and how this information disseminates within the group. Across the three chapters we derive theoretical predictions and experimentally test these predictions. In Chapter I, we analyze whether the sequencing of information affect beliefs formed within a group. We extend the DeGroot model to allow for sequential information arrival. We find that the final beliefs can be altered by varying the sequencing of information, keeping the information content unchanged. We identify the sequences that yield the highest and lowest attainable consensus, thus bounding the variation in final beliefs that can be attributed to information sequencing. With regard to information aggregation, as the number of group members grows, the sequential arrival of information compromises the group's beliefs: in all but particular cases, beliefs converge away from the truth. In Chapter II, motivated by the findings in the previous chapter, we test whether information sequencing affects beliefs formed in groups. In a lab experiment, participants estimate a parameter of interest using a common and a private signal, as well as past guesses of group members. At odds with the Bayesian model, we find that the order and timing of information affect final beliefs, even when the information content is unchanged. Although behavior is non-Bayesian, it is robustly predictable by a model relying on simple heuristics. We explore ways in which the network structure and the timing of information help alleviate correlation neglect. We highlight that the influence of private information on participants' actions is time-independent—a novel documented behavioral heuristic. Finally, in Chapter III, co-authored with Alessandro Lizzeri, Leeat Yariv, Jimmy Chan, and Wing Suen, we report results from lab experiments on information acquisition. We consider decisions governed by individuals and groups and compare how different voting rules affect outcomes. We contrast static with dynamic information collection. Generally, outcomes approximate theoretical benchmarks, and sequential information collection is welfare enhancing. Nonetheless, several important departures emerge. Static information collection is excessive, and sequential information collection is non-stationary, producing declining decision accuracies over time. Furthermore, groups using majority rule often reach hasty and inaccurate decisions.