When is a Contrarian Adviser Optimal?

Abstract

We compare contrarian to conformist advice, a contrarian (conformist) expert being one whose preference bias is against (for) the decision-maker's prior optimal decision. We show that optimality of an expert depends on characteristics of prior information and learning. If either the expert is fully informed, or fine information can be acquired at low cost, then for symmetric distributions F of the state a conformist (contrarian) is superior if F is single-peaked (bimodal). If only coarse information can be acquired then a contrarian acquires more information on average, hence is superior. If information is verifiable a contrarian has less incentive to hide unfavorable evidence, and again is superior.