| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP15534 |
| DP15534 Retrospective Search: Exploration and Ambition on Uncharted Terrain | |
| Can Urgun; Leeat Yariv | |
| 发表日期 | 2020-12-08 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | We study a model of retrospective search in which an agent—a researcher, an online shopper, or a politician—tracks the value of a product. Discoveries beget discoveries and their observations are correlated over time, which we model using a Brownian motion. The agent decides both how ambitiously, or broadly, to search, and for how long. We fully characterize the optimal search policy and show that it entails constant scope of search and a simple stopping boundary. We also show the special features that emerge from contracting with a retrospective searcher. |
| 主题 | Industrial Organization |
| 关键词 | Retrospective search Drawdown stopping boundary Contracting |
| URL | https://cepr.org/publications/dp15534 |
| 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/544536 |
| 推荐引用方式 GB/T 7714 | Can Urgun,Leeat Yariv. DP15534 Retrospective Search: Exploration and Ambition on Uncharted Terrain. 2020. |
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