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Optimal Rating Design under Moral Hazard
We study optimal rating design under moral hazard and strategic manipulation. An intermediary observes a noisy indicator of effort and commits to a rating policy that shapes market beliefs and pay. We characterize optimal ratings via concavification of a gain function. Optimal ratings depends on interaction of effort and risk: for activities that raise tail risk, optimal ratings exhibit lower censorship, pooling poor outcomes to insure and encourage risk-taking; for activities that reduce tail risk, upper censorship increases penalties for negligence. In multi-task environments with window dressing, less informative ratings deter manipulation. In redistributive test design, optimal tests exhibit mid censorship.
Date:
19 May 2026, 12:45
Venue:
Nuffield College, New Road OX1 1NF
Venue Details:
Butler Room
Speaker:
Maryam Saaedi (Carnegie Mellon University)
Organising department:
Department of Economics
Part of:
Economic Theory Workshop
Booking required?:
Not required
Audience:
Members of the University only
Editor:
Edward Valenzano
