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激励性评级

Motivational Ratings
Review of Economic Studies · 2020 · Johannes Hörner、Nicolas S. Lambert

中文摘要

绩效评估(“评级”)系统不仅向用户提供信息,而且激励被评级的员工。本文在标准声誉关切框架内求解最优(努力最大化)评级。我们证明该评级是过去观测值的线性函数。然而,该评级并非马尔可夫过程,而是两个马尔可夫过程之和。我们展示了它如何结合不同类型和时期的资讯。努力的增加可能会对某些(但非全部)未来评级产生不利影响。

Abstract

Abstract Performance evaluation (“rating”) systems not only provide information to users but also motivate the rated worker. This article solves for the optimal (effort-maximizing) rating within the standard career concerns framework. We prove that this rating is a linear function of past observations. The rating, however, is not a Markov process, but rather the sum of two Markov processes. We show how it combines information of different types and vintages. An increase in effort may adversely affect some (but not all) future ratings.
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