Literaturnachweis - Detailanzeige
Autor/inn/en | Banerjee, Abhijit V.; Compte, Olivier |
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Institution | National Bureau of Economic Research |
Titel | Consensus and Disagreement. Information Aggregation under (not so) Naive Learning. |
Quelle | Cambridge, Mass.: National Bureau of Economic Research (2022), 62 S.
PDF als Volltext (1); PDF als Volltext (2) |
Reihe | NBER working paper series. w29897 |
Beigaben | Illustrationen |
Sprache | englisch |
Dokumenttyp | online; Monographie; Graue Literatur |
DOI | 10.3386/w29897 |
Schlagwörter | Spieltheorie; Lernen; Aggregation; Arbeitspapier; Informationsverhalten |
Abstract | We explore a model of non-Bayesian information aggregation in networks. Agents non-cooperatively 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 blows up disagreement: even with little noise, individuals place substantial weight on their own initial opinion in every period, which inflates 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. |
Erfasst von | ZBW - Leibniz-Informationszentrum Wirtschaft, Kiel |
Update | 2023/1 |