| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w18351 |
| 来源ID | Working Paper 18351 |
| Network Structure and the Aggregation of Information: Theory and Evidence from Indonesia | |
| Vivi Alatas; Abhijit Banerjee; Arun G. Chandrasekhar; Rema Hanna; Benjamin A. Olken | |
| 发表日期 | 2012-08-31 |
| 出版年 | 2012 |
| 语种 | 英语 |
| 摘要 | We use unique data from 600 Indonesian communities on what individuals know about the poverty status of others to study how network structure influences information aggregation. We develop a model of semi-Bayesian learning on networks, which we structurally estimate using within-village data. The model generates qualitative predictions about how cross-village patterns of learning relate to different network structures, which we show are borne out in the data. We apply our findings to a community-based targeting program, where villagers chose which households should receive aid, and show that networks the model predicts to be more diffusive differentially benefit from community targeting. |
| 主题 | Microeconomics ; Economics of Information ; Public Economics ; Taxation ; Development and Growth ; Development |
| URL | https://www.nber.org/papers/w18351 |
| 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/576027 |
| 推荐引用方式 GB/T 7714 | Vivi Alatas,Abhijit Banerjee,Arun G. Chandrasekhar,et al. Network Structure and the Aggregation of Information: Theory and Evidence from Indonesia. 2012. |
| 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 | ||
| w18351.pdf（699KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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