We incorporate a search-theoretic model of imperfect competition into an otherwise standard model of asymmetric information with unrestricted contracts. We develop a methodology that allows for a sharp analytical characterization of the unique equilibrium and then use this characterization to...

We incorporate a search-theoretic model of imperfect competition into a standard model of asymmetric information with unrestricted contracts. We characterize the unique equilibrium, and use our characterization to explore the interaction between adverse selection, screening, and imperfect...

In the market where inattentive buyers can fail to notice some feasible choices, the key role of marketing is to make buyers aware of products. However, the effective marketing strategy is often subtle since marketing tactics can make buyers cautious. This paper provides a framework to analyze...

A mediator, with no prior information and no control over the market protocol, attempts to redesign the information structure in the market by running an information intermediation mechanism with transfers that first elicits information from an agent, and then discloses information to another...

We study a model of adverse selection, hard and soft information, and mentalizing ability — the human capacity to represent others' intentions, knowledge, and beliefs. By allowing for a continuous range of different information types, as well as for different means of acquiring information, we...

We report on an experiment on decentralized markets in the presence of adverse selection. When allowing for costless and non-binding communication (cheap-talk), there exists a partially separating equilibrium that results in a substantially higher efficiency level than the adverse selection...

We relax the common assumption of homogeneous beliefs in principal-agent relationships with adverse selection. Principals are competitors in the product market and write contracts also on the base of an expected aggregate. The model is a version of a cobweb model. In an evolutionary learning...