In many environments, expertise is costly. Costs can manifest themselves in numerous ways, ranging from the time that is required for a financial consultant to study companies’ performances, to the resources necessary for academic referees to produce knowledgeable reports, to the attention and thought needed for jurors to construct informed convictions. The current paper asks a natural question germane to such contexts: how should a committee of potential experts be designed, in terms of the number of participants, their a priori preferences, as well as the rules by which their recommendations are aggregated into a collective policy?
We consider a model in which a principal makes a binary decision (e.g., continue or abort a project), the value of which depends on the realization of some underlying state that is unknown (say, whether the project is great or inferior). The principal can hire a committee of experts from a pool varying in their preferences. All experts have access to an information technology providing (public) information regarding the underlying state. Information comes at a private cost to the experts, who care both about the final decision the principal takes, and about the amount they had personally spent on information acquisition
