We develop a method of solving heterogeneous agent models in which individual decisions depend on the entire cross-sectional distribution of individual state variables, such as incomplete market models with liquidity constraints. Our method is based on the principle of reinforcement learning,...

Using peer-to-peer (P2P) lending as an example, we show that learning by doing plays an important role in alleviating the information asymmetry between market players. Although the P2P platform (Prosper.com) discloses part of borrowers' credit histories, lenders face serious information problems...

We study how market structures, along with asymmetries in learning technologies, affect trade in a product market. In this market, a new product of unknown quality is introduced to challenge a pre-existing product of known quality. We show that market efficiency (the first-best) is achieved both...