Experimentation in Markets
建立了一个包含贝叶斯学习和价格竞争的进入退出模型，分析新产品质量未知时，消费者从他人购买中学习导致的信息外部性如何影响市场均衡，发现单一市场中实验过度，而多市场时销售路径趋于有效。
We present a model of entry and exit with Bayesian learning and price competition. A new product of initially unknown quality is introduced in the market, and purchases of the product yield information on its true quality. We assume that the performance of the new product is publicly observable. As agents learn from the experiments of others, informational externalities arise. We determine the Markov Perfect Equilibrium prices and allocations. In a single market, the combination of the informational externalities among the buyers and the strategic pricing by the sellers results in excessive experimentation. If the new product is launched in many distinct markets, the path of sales converges to the efficient path in the limit as the number of markets grows.