Reputation Building under Observational Learning

Abstract

A patient seller faces a sequence of buyers and decides whether to build a reputation for supplying high quality products. Each buyer does not have access to the seller's complete records, but can observe all previous buyers' actions, and some informative private signal about the seller's actions. I examine how the private signals the buyers receive affect the speed of social learning and the seller's incentives to establish reputations. When each buyer privately observes a bounded subset of the seller's past actions, the speed of social learning is strictly positive but vanishes to zero as the seller becomes patient. As a result, the patient seller receives a low payoff from building reputations, which also results in low social welfare. When each buyer observes an unboundedly informative private signal about the seller's current-period action, the speed of learning is bounded from below and a patient seller can secure high returns from building reputations. My results provide an explanation to empirical findings of reputation failures in developing countries. I also discuss the effectiveness of various policies in accelerating social learning and encouraging sellers to establish good reputations.

Keywords: social learning, reputation, stochastic network, information aggregation

JEL Classification: C73, D82, D83