Speaker: Kangning Wang (stanford postdoc)
Title: Fair Price Discrimination
Abstract: A seller is pricing identical copies of a good to a stream of unit-demand buyers. Each buyer has a value on the good as his private information. The seller only knows the empirical value distribution of the buyer population and chooses the revenue-optimal price. We consider a widely studied third-degree price discrimination model where an information intermediary with perfect knowledge of the arriving buyer's value sends the seller a signal, which changes the seller's posterior and induces the seller to set a personalized price. We show the surprising existence of a novel signaling scheme that is "fair" to the buyer population: it simultaneously approximately maximizes all welfare functions that are non-negative, monotonically increasing, symmetric, and concave (including the utilitarian social welfare, the Nash welfare, and the max-min welfare). This is based on joint work (https://arxiv.org/abs/2305.07006) with Siddhartha Banerjee, Kamesh Munagala, and Yiheng Shen.