Abstract

Theoretical paper DeMarzo, Vayanos, and Zwiebel (2003) proposes a model of information aggregation in networks when individuals are subject to bias. The term persuasion refers to a particular form of boundedly rational behavior when individuals connected into a network do not account for repetition in the information they acquire. We argue that under the assumption that agents form their beliefs as a weighted average of all information available to them, the bias assumption is equivalent to a generalized version of the famous DeGroot model (DeGroot (1974)). We test the bias hypothesis against the (generalized) Bayesian updating model and find support for the bias hypothesis. We also found a positive correlation between how well a subject fits the generalized DeGroot model, compared to the alternative generalized Bayesian updating model, and their performance in the experiment. Data suggest that the generalized DeGroot model better accommodates other subjects' deviations from equilibrium, which explains the positive correlation.

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