{"title":"共识与分歧:(并非如此)朴素学习下的信息聚合","authors":"Abhijit Banerjee, Olivier Compte","doi":"arxiv-2311.08256","DOIUrl":null,"url":null,"abstract":"We explore a model of non-Bayesian information aggregation in networks.\nAgents non-cooperatively choose among Friedkin-Johnsen type aggregation rules\nto maximize payoffs. The DeGroot rule is chosen in equilibrium if and only if\nthere is noiseless information transmission, leading to consensus. With noisy\ntransmission, while some disagreement is inevitable, the optimal choice of rule\namplifies the disagreement: even with little noise, individuals place\nsubstantial weight on their own initial opinion in every period, exacerbating\nthe disagreement. We use this framework to think about equilibrium versus\nsocially efficient choice of rules and its connection to polarization of\nopinions across groups.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Consensus and Disagreement: Information Aggregation under (not so) Naive Learning\",\"authors\":\"Abhijit Banerjee, Olivier Compte\",\"doi\":\"arxiv-2311.08256\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We explore a model of non-Bayesian information aggregation in networks.\\nAgents non-cooperatively choose among Friedkin-Johnsen type aggregation rules\\nto maximize payoffs. The DeGroot rule is chosen in equilibrium if and only if\\nthere is noiseless information transmission, leading to consensus. With noisy\\ntransmission, while some disagreement is inevitable, the optimal choice of rule\\namplifies the disagreement: even with little noise, individuals place\\nsubstantial weight on their own initial opinion in every period, exacerbating\\nthe disagreement. We use this framework to think about equilibrium versus\\nsocially efficient choice of rules and its connection to polarization of\\nopinions across groups.\",\"PeriodicalId\":501487,\"journal\":{\"name\":\"arXiv - QuantFin - Economics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2311.08256\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2311.08256","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Consensus and Disagreement: Information Aggregation under (not so) Naive Learning
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
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.