Multi-Dimensional Screening: Buyer-Optimal Learning and Informational Robustness

30 Pages Posted: 14 Jul 2021

See all articles by Rahul Deb

Rahul Deb

University of Toronto

Anne-Katrin Roesler

University of Toronto - Department of Economics

Date Written: May 2021

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.

Suggested Citation

Deb, Rahul and Roesler, Anne-Katrin, Multi-Dimensional Screening: Buyer-Optimal Learning and Informational Robustness (May 2021). Available at SSRN: https://ssrn.com/abstract=3886648

Rahul Deb (Contact Author)

University of Toronto ( email )

Toronto, Ontario M5S 3G8
Canada

HOME PAGE: http://www.economics.utoronto.ca/debrahul/

Anne-Katrin Roesler

University of Toronto - Department of Economics ( email )

150 St. George Street
Toronto, Ontario M5S3G7
Canada

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