Social Learning with Coordination Motives
Yangbo Song

TL;DR
This paper models social learning where agents' actions impact others' payoffs, showing that larger communities improve learning outcomes, especially with strategic observation and private beliefs, through coordination motives.
Contribution
It introduces a model where agents' actions influence others' payoffs, demonstrating how community size and observation structures affect social learning and equilibrium selection.
Findings
Coordination motives increase the probability of correct actions with larger communities.
Community size threshold exists for asymptotic learning with unbounded private beliefs.
Community size effects vary under different observation and belief conditions.
Abstract
The theoretical study of social learning typically assumes that each agent's action affects only her own payoff. In this paper, I present a model in which agents' actions directly affect the payoffs of other agents. On a discrete time line, there is a community containing a random number of agents in each period. Before each agent needs to take an action, the community receives a private signal about the underlying state of the world and may observe some past actions in previous communities. An agent's payoff is higher if her action matches the state or if more agents take the same action as hers. I analyze two observation structures: exogenous observation and costly strategic observation. In both cases, coordination motives enhance social learning in the sense that agents take the correct action with significantly higher probability when the community size is greater than a threshold.…
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Taxonomy
TopicsGame Theory and Applications · Experimental Behavioral Economics Studies · Culture, Economy, and Development Studies
