论文标题
观察学习下的声誉建设
Reputation Building under Observational Learning
论文作者
论文摘要
我研究了一种社会学习模型，其中学习的对象是战略参与者的内源性行为，而不是外源性状态。患者卖方面临一系列买家，并决定是否在提供高质量产品的情况下建立声誉。每个买家都无法访问卖方的完整记录，而可以观察所有以前的买家的行动，以及有关卖方行动的信息。我研究了买家的私人信号如何影响社会学习速度以及卖方建立声誉的激励措施。当每个买家私下观察卖方过去行动的有限子集时，学习速度严格是积极的，但随着卖方的患者的患者，学习速度可能会消失到零。结果，声誉建设可能会导致卖方和社会福利较低的低收入。当每个买家观察到有关卖方当前周期动作的无限信息的私人信号时，学习速度从下面统一界定，并且患者卖方可以从建筑声誉中获得高回报。我的结果阐明了各种政策在加速社会学习方面的有效性，并鼓励卖方建立良好的声誉。
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.
