We compare contrarian to conformist advice, a contrarian expert being one whose preference bias is against the decision-maker’s prior optimal decision. 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 cheaply, 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 on average and hence is superior. If information is verifiable, a contrarian has less incentive to hide unfavorable evidence and again is superior.
Collective reputation and its associated free-rider problem have been invoked to justify state licensing of professions and to explain the incidence of franchising. We examine the conditions under which it is possible to create a Pareto-improving collective reputation among groups of heterogeneous producers. If the regulator or franchisor cannot credibly commit to high quality then a common reputation can be created only if the groups are not too different and if marginal cost is declining. High cost groups benefit most from forming a common regime.