Working Paper: CEPR ID: DP16206
Authors: Annekatrin Roesler; Rahul Deb
Abstract: A monopolist seller of multiple goods screens a buyer whose type is initially unknown to both but drawn from a commonly known distribution. The buyer privately learns about his type via a signal. We derive the seller’s optimal mechanism in two different information environments. We begin by deriving the buyer-optimal outcome. Here, an information designer first selects a signal, and then the seller chooses an optimal mechanism in response; the designer’s objective is to maximize consumer surplus. Then, we derive the optimal informationally robust mechanism. In this case, the seller first chooses the mechanism, and then nature picks the signal that minimizes the seller’s profits. We derive the relation between both problems and show that the optimal mechanism in both cases takes the form of pure bundling.
Keywords: Multidimensional Screening; Buyer Learning; Informational Robustness
JEL Codes: D82; D83
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| buyer learning (D16) | seller's mechanism (D47) |
| buyer's type (D11) | seller's profit (D41) |
| buyer's learning signal (D83) | seller's mechanism choice (D47) |
| seller's mechanism (D47) | consumer surplus (D46) |
| buyer learning (D16) | optimal mechanism (D47) |
| seller's profit (D41) | min-max problem (C61) |
| optimal informationally robust mechanism (D82) | seller profit (D33) |
| optimal mechanism (D47) | pure bundling (M31) |