Robust Price Discrimination
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866912638743609344 |
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| author | Arieli, Itai Babichenko, Yakov Madmon, Omer Tennenholtz, Moshe |
| author_facet | Arieli, Itai Babichenko, Yakov Madmon, Omer Tennenholtz, Moshe |
| contents | We consider a model of third-degree price discrimination where the seller's product valuation is unknown to the market designer, who aims to maximize buyer surplus by revealing buyer valuation information. Our main result shows that the regret is bounded by a $\frac{1}{e}$-fraction of the optimal buyer surplus when the seller has zero valuation for the product. This bound is attained by randomly drawing a seller valuation and applying the segmentation of Bergemann et al. (2015) with respect to the drawn valuation. We show that this bound is tight in the case of binary buyer valuation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_16942 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Robust Price Discrimination Arieli, Itai Babichenko, Yakov Madmon, Omer Tennenholtz, Moshe Theoretical Economics Computer Science and Game Theory We consider a model of third-degree price discrimination where the seller's product valuation is unknown to the market designer, who aims to maximize buyer surplus by revealing buyer valuation information. Our main result shows that the regret is bounded by a $\frac{1}{e}$-fraction of the optimal buyer surplus when the seller has zero valuation for the product. This bound is attained by randomly drawing a seller valuation and applying the segmentation of Bergemann et al. (2015) with respect to the drawn valuation. We show that this bound is tight in the case of binary buyer valuation. |
| title | Robust Price Discrimination |
| topic | Theoretical Economics Computer Science and Game Theory |
| url | https://arxiv.org/abs/2401.16942 |