| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w25497 |
| 来源ID | Working Paper 25497 |
| Naive Learning with Uninformed Agents | |
| Abhijit Banerjee; Emily Breza; Arun G. Chandrasekhar; Markus Mobius | |
| 发表日期 | 2019-02-04 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | The DeGroot model has emerged as a credible alternative to the standard Bayesian model for studying learning on networks, offering a natural way to model naive learning in a complex setting. One unattractive aspect of this model is the assumption that the process starts with every node in the network having a signal. We study a natural extension of the DeGroot model that can deal with sparse initial signals. We show that an agent's social influence in this generalized DeGroot model is essentially proportional to the number of uninformed nodes who will hear about an event for the first time via this agent. This characterization result then allows us to relate network geometry to information aggregation. We identify an example of a network structure where essentially only the signal of a single agent is aggregated, which helps us pinpoint a condition on the network structure necessary for almost full aggregation. We then simulate the modeled learning process on a set of real world networks; for these networks there is on average 21.6% information loss. We also explore how correlation in the location of seeds can exacerbate aggregation failure. Simulations with real world network data show that with clustered seeding, information loss climbs to 35%. |
| 主题 | Microeconomics ; Economics of Information ; Development and Growth ; Development ; Other ; Culture |
| URL | https://www.nber.org/papers/w25497 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/583171 |
| 推荐引用方式 GB/T 7714 | Abhijit Banerjee,Emily Breza,Arun G. Chandrasekhar,et al. Naive Learning with Uninformed Agents. 2019. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w25497.pdf（840KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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