Learning and Information Aggregation in Networks
‘Social learning’ is a process whereby economic agents learn by observing the behaviour of others. ‘Social learning in networks’ requires sophistication because individuals draw inferences from the behaviour of agents they cannot directly observe. Theoretical research suggests that, even if networks are very incomplete, social learning leads to uniform behaviour. Experimental evidence suggests that learning in networks conforms quite well to theoretical predictions. It also illustrates how the network architecture influences the pattern of learning and the efficiency of information aggregation.
KeywordsBala–Goyal model Bounded rationality Circle network Complete network Connected graph Directed graph Griliches, Z. Herd behavior Hubs Imitation principle Information aggregation Informational cascades Perfect information Pure information externality Scale-free networks Social experimentation Social learning Star network
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