CFDP 2035

Motivational Ratings

Publication Date: April 2016

Pages: 102

Abstract: 

Rating systems not only provide information to users but also motivate the rated agent. This paper solves for the optimal (effort-maximizing) rating system within the standard career concerns framework. It is a mixture two-state rating system. That is, it is the sum of two Markov processes, with one that re-effects the belief of the rater and the other the preferences of the rated agent. The rating, however, is not a Markov process. Our analysis shows how the rating combines information of different types and vintages. In particular, an increase in effort may affect some (but not all) future ratings adversely.

Keywords: 

Career Concerns, Mechanism Design, Ratings

JEL Classification Codes: C72, C73