Description:
This paper studies the optimal refund mechanism when an uninformed buyer can privately acquire information about his valuation over time. In principle, a refund mechanism can specify the odds that the seller requires the product returned while issuing a (partial) refund, which we call stochastic return. It guarantees the seller a strictly positive minimum revenue and facilitates intermediate buyer learning. In the benchmark model, stochastic return is sub-optimal. The optimal refund mechanism takes simple forms: the seller either deters learning via a well-designed nonrefundable price or encourages full learning and escalates price discrimination via free return. This result is robust to both good news and bad news framework.