Rahul Deb, University of Toronto

“Multi-Dimensional Screening with Buyer-Optimal Learning”

Coautoreado con Anne-Katrin Roesler

Abstract: A monopolist seller of multiple goods screens a buyer whose type is initially unknown and drawn from a commonly known distribution. The buyer learns about his type via a signal and the seller chooses an optimal mechanism in response. The signal distribution is commonly known but signal realizations are private to the buyer. We show that, under the buyer-optimal signal, the seller maximizes profits by pure bundling. We discuss the implications of this result for the economics of multidimensional screening and derive comparative statics.