Communication and Learning - CiteSeerX
Communication and Learning ∗Luca Anderlini(Georgetown University)Dino Gerardi(Collegio Carlo Albertoand Yale University)Roger Lagunoff(Georgetown University)January 2010Abstract. We study strategic information transmission in an organizationconsisting of an infinite sequence of individual decision makers. Each decision makerchooses an action and receives an informative but imperfect signal of the once-andfor-allrealization of an unobserved state. The state affects all individuals’ preferencesover present and future decisions. Decision makers do not directly observe the realizedsignals or actions of their predecessors. Instead, they must rely on cheap-talk messagesin order to accumulate information about the state. Each decision maker is thereforeboth a receiver of information with respect to his decision, and a sender with respectto all future decisions.We show that if preferences are not perfectly aligned “full learning” equilibria —ones in which the individuals’ posterior beliefs eventually place full weight on the truestate — do not exist. This is so both in the case of private communication, in which eachindividual only hears the message of his immediate predecessor, and in the case of publiccommunication, in which a decision maker hears the message of all his predecessors.Surprisingly, in the latter case full learning may be impossible even in the limit as allmembers of the organization become perfectly patient. We also consider the case whereall individuals have access to a mediator who can work across time periods arbitrarilyfar apart. In this case full learning equilibria exist.JEL Classification: C70, C72, C73, D80, D83.Keywords: Communication, Learning, Dynamic Strategic Information Transmission.Address for correspondence: Luca Anderlini, Georgetown University, 37 th and OStreets NW, Washington DC 20057, USA. email@example.com∗ We are grateful to Bruno Biais, three anonymous referees, Axel Anderson, Leonardo Felli, JohannesHörner, Navin Kartik, Qingmin Liu, George Mailath, Stephen Morris, Marco Ottaviani, Larry Samuelson,Leeat Yariv and numerous seminar audiences for helpful comments. Any remaining errors are our ownresponsibility. All three authors are grateful to the National Science Foundation for financial support (GrantSES-0617789).