In many economic environments, a designer not only chooses a mechanism or contract but also shapes how agents learn their private information. This talk examines the role of endogenous information disclosure in mechanism and contract design, highlighting how it can fundamentally alter classical conclusions and reshape the structure of the designer’s problem.

In the first part, we study multi-product monopoly pricing where the seller jointly designs the selling mechanism and the information structure for the buyer to learn his values. Unlike the case with exogenous information, we show that when the seller controls information, even uniform pricing guarantees at least half of the optimal revenue. Moreover, for negatively affiliated or exchangeable value distributions, deterministic pricing is revenue-optimal. Our results highlight the power of information design in making pricing mechanisms approximately optimal in multi-dimensional settings.

The second part turns to a multi-agent contracting problem, where a principal designs a contract while also controlling the disclosure of a hidden state that affects the team’s chances of success. While prior literature establishes that full transparency is rarely optimal, identifying the best joint design of contracts and information has remained elusive. We establish a sharp dichotomy: when the team’s production function is submodular (or more generally XOS), full transparency achieves a constant-factor approximation (5.82 in the submodular case) to the optimal disclosure scheme. However, for supermodular success functions, full transparency may perform arbitrarily poorly.

This talk is based on two joint works: the first with Yang Cai and Yingkai Li, and the second with Paul Dütting, Yingkai Li, and Inbal Talgam-Cohen.