Optimal Noise Manipulation in Asymmetric Tournament

  • Zhiqiang DongEmail author
  • Zijun Luo
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 805)


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.


Asymmetric tournament Noise manipulation Incentive contract 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Key Lab for Behavioral Economic Science and TechnologySouth China Normal UniversityGuangzhouChina
  2. 2.Department of Economics and International BusinessSam Houston State UniversityHuntsvilleUSA

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