Optimally Biased Expertise

Pavel Ilinov, Andrei Matveenko, Maxim Senkov and Egor Starkov

Papers from arXiv.org

Abstract: We show that in delegation problems, a principal benefits from belief misalignment vis-\`a-vis an agent when the latter can flexibly acquire costly information. The agent optimally succumbs to confirmatory learning, leading him to favor the ex ante optimal action. We show that the principal prefers to mitigate this by hiring an agent who is ex ante more uncertain about which action is optimal. This is optimal even when the principal is herself biased towards some action: the benefit always outweighs the cost of a small misalignment. Optimally misaligned agent considers weakly more actions than an aligned agent. All results continue to hold when delegation is replaced by communication.

Date: 2022-09, Revised 2025-07
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http://arxiv.org/pdf/2209.13689 Latest version (application/pdf)

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Working Paper: Optimally Biased Expertise (2022)
Working Paper: Optimally Biased Expertise (2022)
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