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Optimal Price Discrimination for Randomized Mechanisms

Publication ,  Conference
Ko, SH; Munagala, K
Published in: EC 2022 - Proceedings of the 23rd ACM Conference on Economics and Computation
July 12, 2022

We study the power of price discrimination via an intermediary in bilateral trade, when there is a revenue-maximizing seller selling an item to a buyer with a private value drawn from a prior. Between the seller and the buyer, there is an intermediary that can segment the market by releasing information about the true values to the seller. This is termed signaling, and enables the seller to price discriminate. In this setting, Bergemann et al. showed the existence of a signaling scheme that simultaneously raises the optimal consumer surplus, guarantees the item always sells, and ensures the seller's revenue does not increase. Our work extends the positive result of Bergemann et al. to settings where the type space is larger, and where optimal auction is randomized, possibly over a menu that can be exponentially large. In particular, we consider two settings motivated by budgets: The first is when there is a publicly known budget constraint on the price the seller can charge and the second is the FedEx problem where the buyer has a private deadline or service level (equivalently, a private budget that is guaranteed to never bind). For both settings, we present a novel signaling scheme and its analysis via a continuous construction process that recreates the optimal consumer surplus guarantee of Bergemann et al. and further subsumes their signaling scheme as a special case. In effect, our results show settings where even though the optimal auction is randomized over a possibly large menu, there is a market segmentation such that for each segment, the optimal auction is a simple posted price scheme where the item is always sold. The settings we consider are special cases of the more general problem where the buyer has a private budget constraint in addition to a private value. We finally show that our positive results do not extend to this more general setting, particularly when the budget can bind in the optimal auction, and when the seller's mechanism allows for all-pay auctions. Here, we show that any efficient signaling scheme necessarily transfers almost all the surplus to the seller instead of the buyer.

Duke Scholars

Published In

EC 2022 - Proceedings of the 23rd ACM Conference on Economics and Computation

DOI

ISBN

9781450391504

Publication Date

July 12, 2022

Start / End Page

477 / 496
 

Citation

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Ko, S. H., & Munagala, K. (2022). Optimal Price Discrimination for Randomized Mechanisms. In EC 2022 - Proceedings of the 23rd ACM Conference on Economics and Computation (pp. 477–496). https://doi.org/10.1145/3490486.3538335
Ko, S. H., and K. Munagala. “Optimal Price Discrimination for Randomized Mechanisms.” In EC 2022 - Proceedings of the 23rd ACM Conference on Economics and Computation, 477–96, 2022. https://doi.org/10.1145/3490486.3538335.
Ko SH, Munagala K. Optimal Price Discrimination for Randomized Mechanisms. In: EC 2022 - Proceedings of the 23rd ACM Conference on Economics and Computation. 2022. p. 477–96.
Ko, S. H., and K. Munagala. “Optimal Price Discrimination for Randomized Mechanisms.” EC 2022 - Proceedings of the 23rd ACM Conference on Economics and Computation, 2022, pp. 477–96. Scopus, doi:10.1145/3490486.3538335.
Ko SH, Munagala K. Optimal Price Discrimination for Randomized Mechanisms. EC 2022 - Proceedings of the 23rd ACM Conference on Economics and Computation. 2022. p. 477–496.

Published In

EC 2022 - Proceedings of the 23rd ACM Conference on Economics and Computation

DOI

ISBN

9781450391504

Publication Date

July 12, 2022

Start / End Page

477 / 496