| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP16377 |
| DP16377 Bayesian Learning | |
| Isaac Baley; Laura Veldkamp | |
| 发表日期 | 2021-07-20 |
| 出版年 | 2021 |
| 语种 | 英语 |
| 摘要 | We survey work using Bayesian learning in macroeconomics, highlighting common themes and new directions. First, we present many of the common types of learning problems agents face -- signal extraction problems -- and trace out their effects on macro aggregates, in different strategic settings. Then we review different perspectives on how agents get their information. Models differ in their motives for information acquisition and the cost of information, or learning technology. Finally, we survey the growing literature on the data economy, where economic activity generates data and the information in data feeds back to affect economic activity. |
| 主题 | Financial Economics ; Macroeconomics and Growth ; Monetary Economics and Fluctuations |
| 关键词 | Bayes' law Passive learning Active learning Signal extraction Information choice Sticky information Rational inattention Experimentation Data economy Coordination games |
| URL | https://cepr.org/publications/dp16377 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/545341 |
| 推荐引用方式 GB/T 7714 | Isaac Baley,Laura Veldkamp. DP16377 Bayesian Learning. 2021. |
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