2022RePEc: Research Papers in EconomicsOpen access

Optimally Biased Expertise

Pavel Ilinov, Andrei Matveenko, Maxim Senkov, Egor Starkov

Open full text 0 citations

Abstract

We show that in delegation problems, a principal benefits from belief misalignment vis-à-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.

Open-access reader

About this research paper

What this paper is about

We show that in delegation problems, a principal benefits from belief misalignment vis-à-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.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

We show that in delegation problems, a principal benefits from belief misalignment vis-à-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.

Key concepts: Principal (computer security), Delegation, Private information retrieval, Ex-ante, Action (physics), Class (philosophy), Principal–agent problem, Cheap talk

Related papers

Back to paper searchBrowse research topicsOriginal source
Optimally Biased Expertise — Research Paper | ScholarLens