Reputation Building under Observational Learning

TL;DR

This paper models how private signals influence social learning and reputation building for strategic sellers, showing that information structure critically affects the speed of reputation formation and seller incentives.

Contribution

It introduces a model where private signals about actions impact social learning speed and analyzes conditions under which reputation building is effective for sellers.

Findings

Private signals can slow social learning when bounded, reducing reputation incentives.

Unbounded private signals ensure rapid learning and higher seller payoffs.

Policy implications for accelerating reputation formation are discussed.

Abstract

I study a social learning model in which the object to learn is a strategic player's endogenous actions rather than an exogenous state. 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 buyers' private signals 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 learning is strictly positive but can vanish to zero as the seller becomes patient. As a result, reputation building can lead to low payoff for the patient seller and low social welfare. When each buyer observes an unboundedly informative private signal about the seller's current-period action, the speed of learning is uniformly bounded from below and a patient seller can secure high returns from building reputations. My results shed light on the effectiveness of various policies in accelerating social learning and encouraging sellers to establish good reputations.