| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w25456 |
| 来源ID | Working Paper 25456 |
| Inference on Winners | |
| Isaiah Andrews; Toru Kitagawa; Adam McCloskey | |
| 发表日期 | 2019-01-21 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | Many empirical questions concern target parameters selected through optimization. For example, researchers may be interested in the effectiveness of the best policy found in a randomized trial, or the best-performing investment strategy based on historical data. Such settings give rise to a winner’s curse, where conventional estimates are biased and conventional confidence intervals are unreliable. This paper develops optimal confidence intervals and median-unbiased estimators that are valid conditional on the target selected and so overcome this winner’s curse. If one requires validity only on average over targets that might have been selected, we develop hybrid procedures that combine conditional and projection confidence intervals to offer further performance gains relative to existing alternatives. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/w25456 |
| 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/583130 |
| 推荐引用方式 GB/T 7714 | Isaiah Andrews,Toru Kitagawa,Adam McCloskey. Inference on Winners. 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 | ||
| w25456.pdf（1600KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
