G2TT
来源类型Discussion paper
规范类型论文
来源IDDP15356
DP15356 Task Allocation and On-the-job Training
Mariagiovanna Baccara; SangMok Lee; Leeat Yariv
发表日期2020-10-11
出版年2020
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Industrial Organization
关键词Dynamic matching Training by doing Market design
URLhttps://cepr.org/publications/dp15356-0
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/544337
推荐引用方式
GB/T 7714
Mariagiovanna Baccara,SangMok Lee,Leeat Yariv. DP15356 Task Allocation and On-the-job Training. 2020.
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