Optimal Noise Manipulation in Asymmetric Tournament

• Zhiqiang Dong

• Zijun Luo

First Online:29 December 2018   

• Part of the  Advances in Intelligent Systems and Computing book series (AISC, volume 805)

  Abstract

  We fill a gap in the literature of asymmetric tournament by allowing the  principal to optimally alter noise in relative performance evaluation,  such that the observed performance of each agent is less or more  dependent of ability and effort. We show that there exists an optimal  noise level from the principal’s standpoint of expected profit  maximization. It is shown that this optimal noise level is higher than  what would induce the highest efforts from the two agents.

  Keywords

  Asymmetric tournament Noise manipulation Incentive contract