Learning and Strategic Pricing
研究消费者从不同卖家重复购买时，卖家通过定价竞争影响消费者学习产品价值的过程。所有马尔可夫完美均衡都是有效的，且存在一个简单、看似短视的定价规则，其中低于边际成本的价格自然出现以支持实验。
We consider the situation where a single consumer buys a stream of goods from different sellers over time. The true value of each seller's product to the buyer is initially unknown. Additional information can be gained only by experimentation. For exogeneously given prices the buyer's problem is a multi-armed bandit problem. The innovation in this paper is to endogenize the cost of experimentation to the consumer by allowing for price competition between the sellers. The role of prices is then to allocate intertemporally the costs and benefits of learning between buyers and sellers. We examine how strategic aspects of the oligopoly model interact with the learning process. All Markov perfect equilibria (MPE) are efficient. We identify an equilibrium which besides its unique robustness properties has a strikingly simple, seemingly myopic pricing rule. Prices below marginal cost emerge naturally to sustain experimentation. Intertemporal exchange of the gains of learning is necessary to support efficient experimentation. We analyze the asymptotic behavior of the equilibria.