We explore a model of non-Bayesian information aggregation in networks. Agents noncooperatively choose among Friedkin-Johnsen-type aggregation rules to maximize payoffs. The DeGroot rule is chosen in equilibrium if and only if there is noiseless information transmission, leading to consensus. With noisy transmission, while some disagreement is inevitable, the optimal choice of rule amplifies the disagreement: even with little noise, individuals place substantial weight on their own initial opinion in every period, exacerbating the disagreement. We use this framework to think about equilibrium versus socially efficient choice of rules and its connection to polarization of opinions across groups.
This paper theoretically and empirically studies the interaction of search and application approval in credit markets. Risky borrowers internalize the probability that their application is rejected and behave as if they had high search costs. Thus, “overpayment” may be a poor proxy for consumer sophistication since it partly represents rational search in response to rejections. Contrary to standard search models, our model implies (1) endogenous adverse selection through the search and application approval process, (2) a possibly non‐monotone or non‐decreasing relationship between search and realized interest, default, and application approval rates, and (3) search costs estimated from transaction prices alone are biased. We find support for the model's predictions using a unique data set detailing search behavior of mortgage borrowers. Estimating the model, we find that screening is informative and search is costly. Counterfactual analyses reveal that tightening lending standards and discrimination through application rejection both increase equilibrium interest rates. This increase in realized interest rates is in part due to strategic complementarity in bank rate setting.