Task Allocation and On-the-job Training

Mariagiovanna Baccara, SangMok Lee and Leeat Yariv

No 29312, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: C02 C61 C78 D02 J22 L23 (search for similar items in EconPapers)
Date: 2021-09
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Published as Mariagiovanna Baccara & SangMok Lee & Leeat Yariv, 2022. "Task Allocation and On-the-job Training," Journal of Economic Theory, .

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Journal Article: Task allocation and on-the-job training (2023)
Working Paper: Task Allocation and On-the-job Training (2021)
Working Paper: Task Allocation and On-the-job Training (2020)
Working Paper: Task Allocation and On-the-job Training (2020)
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