| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w23917 |
| 来源ID | Working Paper 23917 |
| Directed Attention and Nonparametric Learning | |
| Ian Dew-Becker; Charles G. Nathanson | |
| 发表日期 | 2017-10-09 |
| 出版年 | 2017 |
| 语种 | 英语 |
| 摘要 | We study an ambiguity-averse agent with uncertainty about income dynamics who chooses what aspects of the income process to learn about. The agent chooses to learn most about income dynamics at the very lowest frequencies, which have the greatest effect on utility. Deviations of consumption from the full-information benchmark are then largest at high frequencies, so consumption responds strongly to predictable changes in income in the short-run but is closer to a random walk in the long-run. Whereas ambiguity aversion typically leads agents to act as though shocks are more persistent than the truth, endogenous learning here eliminates that effect. |
| 主题 | Econometrics ; Estimation Methods ; Microeconomics ; Economics of Information ; Macroeconomics ; Consumption and Investment |
| URL | https://www.nber.org/papers/w23917 |
| 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/581590 |
| 推荐引用方式 GB/T 7714 | Ian Dew-Becker,Charles G. Nathanson. Directed Attention and Nonparametric Learning. 2017. |
| 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 | ||
| w23917.pdf（779KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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