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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.23896 |
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| _version_ | 1866911029956444160 |
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| author | Dobzinski, Shahar Eden, Alon Goldner, Kira Shaulker, Ariel Tsilivis, Thodoris |
| author_facet | Dobzinski, Shahar Eden, Alon Goldner, Kira Shaulker, Ariel Tsilivis, Thodoris |
| contents | Welfare maximization in bilateral trade has been extensively studied in recent years. Previous literature obtained incentive-compatible approximation mechanisms only for the private values case. In this paper, we study welfare maximization in bilateral trade with interdependent values. Designing mechanisms for interdependent settings is much more challenging because the values of the players depend on the private information of the others, requiring complex belief updates and strategic inference. We propose to classify information structures by quantifying the influence that a player's private signal has on their own valuation. We then paint a picture of where approximations are possible and impossible based on these information structures. Finally, we also study the possible approximation ratios for a natural family of information structures. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_23896 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Interdependent Bilateral Trade: Information vs Approximation Dobzinski, Shahar Eden, Alon Goldner, Kira Shaulker, Ariel Tsilivis, Thodoris Computer Science and Game Theory Welfare maximization in bilateral trade has been extensively studied in recent years. Previous literature obtained incentive-compatible approximation mechanisms only for the private values case. In this paper, we study welfare maximization in bilateral trade with interdependent values. Designing mechanisms for interdependent settings is much more challenging because the values of the players depend on the private information of the others, requiring complex belief updates and strategic inference. We propose to classify information structures by quantifying the influence that a player's private signal has on their own valuation. We then paint a picture of where approximations are possible and impossible based on these information structures. Finally, we also study the possible approximation ratios for a natural family of information structures. |
| title | Interdependent Bilateral Trade: Information vs Approximation |
| topic | Computer Science and Game Theory |
| url | https://arxiv.org/abs/2506.23896 |