dc.contributor.author | Sethi, Rajiv | |
dc.contributor.author | Yildiz, Muhamet | |
dc.date.accessioned | 2013-12-10T00:22:18Z | |
dc.date.available | 2013-12-10T00:22:18Z | |
dc.date.issued | 2013-12-06 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/82900 | |
dc.description.abstract | Consider a group of individuals with unobservable perspectives (subjective prior beliefs) about a sequence of states. In each period, each individual receives private information about the current state and forms an opinion (a posterior belief). He also chooses a target individual whose opinion is then observed. This choice involves a fundamental trade-off between well-informed targets, whose signals are precise, and well-understood targets, whose perspectives are well known by the observer. Observing an opinion provides information not just about the current state, but also about the target's perspective; hence observed individuals become better-understood over time. This leads to path dependence and the possibility that some individuals never observe certain others in the long run. We identify a simple condition under which long-run behavior is efficient and history-independent. When this condition fails, with positive probability, a single individual emerges as an opinion leader in the long-run. Moreover, the extent to which an individual learns about a target's perspective depends on how well-informed both agents are in the period of observation. This gives rise to symmetry breaking, and can result in observational networks involving information segregation, or static graphs with rich and complex structures | en_US |
dc.publisher | Cambridge, MA: Department of Economics, massachusetts Institute of Technology | en_US |
dc.relation.ispartofseries | Working paper, Massachusetts Institute of Technology, Dept. of Economics;13-23 | |
dc.subject | Beliefs, heterogeneous priors, network Formation, Opinion Leadership, Segregation | en_US |
dc.title | Perspectives, Opinions, and information Flows | en_US |
dc.type | Working Paper | en_US |