We generalize the canonical problem of Nash implementation by allowing agents to voluntarily provide discriminatory signals, i.e. evidence. Evidence can either take the form of hard information or, more generally, have differential but non-prohibitive costs in different states. In such...

We generalize the canonical problem of Nash implementation by allowing agents to voluntarily provide discriminatory signals, i.e. evidence. Evidence can either take the form of hard information or, more generally, have differential but non-prohibitive costs in different states. In such...

We generalize the canonical problem of Nash implementation by allowing agents to voluntarily provide discriminatory signals, i.e. evidence. Evidence can either take the form of hard information or, more generally, have differential but non-prohibitive costs in different states. In such...

This paper studies the design of a recommender system for organizing social learning on a product. To improve incentives for early experimentation, the optimal design trades off fully transparent social learning by over-recommending a product (or “spamming”) to a fraction of agents in the...