Career concerns and incentive compatible task design

This paper studies the optimal disclosure of information about an agent's talent when it consists of two components. The agent observes the first component of his talent as his private type, and reports it to a principal to perform a task which reveals the second component of his talent. Based on the report and performance, the principal discloses information to a firm who pays the agent the wage equal to his expected talent. We study incentive compatible disclosure rules that minimize the mismatch between the agent's true talent and his wage. The optimal rule entails full disclosure when the agent's talent is a supermodular function of the two com- ponents, but entails partial pooling when it is submodular. Under a mild degree of submodularity, we show that the optimal disclosure rule is obtained as a solution to a linear programming problem, and identify the number of messages required under the optimal rule. We relate it to the agent's incentive compatibility conditions, and show that each pooling message has binary support.