| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w29312 |
| 来源ID | Working Paper 29312 |
| Task Allocation and On-the-job Training | |
| Mariagiovanna Baccara; SangMok Lee; Leeat Yariv | |
| 发表日期 | 2021-09-27 |
| 出版年 | 2021 |
| 语种 | 英语 |
| 摘要 | We study dynamic task allocation when providers' expertise evolves endogenously through training. We characterize optimal assignment protocols and compare them to discretionary procedures, where it is the clients who select their service providers. Our results indicate that welfare gains from centralization are greater when tasks arrive more rapidly, and when training technologies improve. Monitoring seniors' backlog of clients always increases welfare but may decrease training. Methodologically, we explore a matching setting with endogenous types, and illustrate useful adaptations of queueing theory techniques for such environments. |
| 主题 | Econometrics ; Microeconomics ; Mathematical Tools ; Game Theory ; Labor Economics ; Labor Supply and Demand ; Industrial Organization ; Firm Behavior |
| URL | https://www.nber.org/papers/w29312 |
| 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/586985 |
| 推荐引用方式 GB/T 7714 | Mariagiovanna Baccara,SangMok Lee,Leeat Yariv. Task Allocation and On-the-job Training. 2021. |
| 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 | ||
| w29312.pdf（469KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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