Relational contracts with subjective peer evaluations

• 成果类型: Article
• 署名作者: Deb, Joyee; Li, Jin; Mukherjee, Arijit
• 署名单位: Yale University; Northwestern University; Michigan State University
• 刊物名称: RAND JOURNAL OF ECONOMICS
• ISSN/ISSBN: 0741-6261
• DOI: 10.1111/1756-2171.12116
• 发表日期: 2016
• 页码: 3-28
• 关键词: Repeated games; moral hazard; incentives; COMMUNICATION; appraisal; principal; collusion; DESIGN

摘要

We study optimal dynamic contracting for a firm with multiple workers where compensation is based on public performance signals and privately reported peer evaluations. We show that if evaluation and effort provision are done by different workers (e.g., consider supervisor-agent hierarchy), first-best can be achieved even in a static setting. However, if each worker both exerts effort and reports peer evaluations (e.g., consider team setting), effort incentives cannot be decoupled from truth-telling incentives. This makes the optimal static contract inefficient. Relational contracts based on public signals increase efficiency. Interestingly, the optimal contract may ignore signals that are informative about effort.