Collective Sampling: An Ex Ante Perspective

Abstract

I study collective dynamic information acquisition. Players decide when to stop sequential sampling via a collective stopping rule, which specifies decisive coalitions that can terminate information acquisition upon agreement. I develop a methodology to characterize equilibria using an ex ante perspective. Instead of stopping strategies, players choose distributions over posterior beliefs subject to majorization constraints. Equilibrium sampling regions are characterized via a fixed-point argument based on concavification. Collective sampling generates learning inefficiencies and having more decisive coalitions typically reduces learning. I apply the model to committee search and competition in persuasion.