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When the principal knows better than the agent: Subjective evaluations as an optimal disclosure mechanism
Author(s) -
Zhang Mengxi
Publication year - 2018
Publication title -
journal of economics and management strategy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.672
H-Index - 68
eISSN - 1530-9134
pISSN - 1058-6407
DOI - 10.1111/jems.12297
Subject(s) - moral hazard , mechanism design , payment , private information retrieval , function (biology) , principal (computer security) , mechanism (biology) , microeconomics , key (lock) , distribution (mathematics) , business , actuarial science , economics , computer science , incentive , computer security , mathematics , finance , mathematical analysis , philosophy , epistemology , evolutionary biology , biology
When the firm has some private and unverifiable information about an employee’s ability, it can design a subjective evaluation mechanism, whereby payments are tied to evaluations, to communicate such information. In this paper, I investigate how to design an optimal disclosure mechanism for the firm. I characterize the firm’s optimal disclosure policy as a function of the worker’s ability distribution, with the hazard rate function playing a key role. I also demonstrate that with some reasonable restrictions on the ability distribution, the firm’s optimal strategy exhibits a particular pattern: it will reward the best workers aggressively, fire the worst ones, and assign one central rating to the rest. The predictions are consistent with the way firms utilize subjective evaluations in reality.