Working Paper: CEPR ID: DP15356
Authors: Mariagiovanna Baccara; Sangmok Lee; Leeat Yariv
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.
Keywords: dynamic matching; training by doing; market design
JEL Codes: C02; C61; C78; D02; J22; L23
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| optimal assignment protocols for task allocation (C78) | significant welfare gains (D69) |
| centralization of task allocation (H77) | increase overall welfare (D69) |
| higher client arrival rates (J69) | increased congestion (L91) |
| higher client arrival rates (J69) | more training opportunities (M53) |
| improvements in training technology (M53) | service quality (L15) |
| improvements in training technology (M53) | longer wait times (C41) |
| senior's backlog of clients (J14) | increase welfare (I38) |
| senior's backlog of clients (J14) | decrease training opportunities for junior employees (M53) |
| increased client arrivals (R23) | higher service quality (L15) |
| increased client arrivals (R23) | longer wait times (C41) |
| monitoring queue length (C69) | higher average service quality (L15) |
| monitoring queue length (C69) | reduced wait times (C41) |
| improved monitoring (E01) | better allocation of clients to service providers (L84) |
| better allocation of clients to service providers (L84) | enhanced overall welfare (I31) |