Dynamic Delegation with Reputation Feedback
Fuente:
arXiv
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866912558625062912 |
|---|---|
| author | Lukyanov, Georgy Vlasova, Anna |
| author_facet | Lukyanov, Georgy Vlasova, Anna |
| contents | We study dynamic delegation with reputation feedback: a long-lived expert advises a sequence of implementers whose effort responds to current reputation, altering outcome informativeness and belief updates. We solve for a recursive, belief-based equilibrium and show that advice is a reputation-dependent cutoff in the expert's signal. A diagnosticity condition - failures at least as informative as successes - implies reputational conservatism: the cutoff (weakly) rises with reputation. Comparative statics are transparent: greater private precision or a higher good-state prior lowers the cutoff, whereas patience (value curvature) raises it. Reputation is a submartingale under competent types and a supermartingale under less competent types; we separate boundary hitting into learning (news generated infinitely often) versus no-news absorption. A success-contingent bonus implements any target experimentation rate with a plug-in calibration in a Gaussian benchmark. The framework yields testable predictions and a measurement map for surgery (operate vs. conservative care). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_19676 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Dynamic Delegation with Reputation Feedback Lukyanov, Georgy Vlasova, Anna Theoretical Economics We study dynamic delegation with reputation feedback: a long-lived expert advises a sequence of implementers whose effort responds to current reputation, altering outcome informativeness and belief updates. We solve for a recursive, belief-based equilibrium and show that advice is a reputation-dependent cutoff in the expert's signal. A diagnosticity condition - failures at least as informative as successes - implies reputational conservatism: the cutoff (weakly) rises with reputation. Comparative statics are transparent: greater private precision or a higher good-state prior lowers the cutoff, whereas patience (value curvature) raises it. Reputation is a submartingale under competent types and a supermartingale under less competent types; we separate boundary hitting into learning (news generated infinitely often) versus no-news absorption. A success-contingent bonus implements any target experimentation rate with a plug-in calibration in a Gaussian benchmark. The framework yields testable predictions and a measurement map for surgery (operate vs. conservative care). |
| title | Dynamic Delegation with Reputation Feedback |
| topic | Theoretical Economics |
| url | https://arxiv.org/abs/2508.19676 |