Abstract
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.
| Original language | English |
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| Title of host publication | EC 2025 - Proceedings of the 26th ACM Conference on Economics and Computation |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 641-665 |
| Number of pages | 25 |
| ISBN (Electronic) | 9798400719431 |
| DOIs | |
| State | Published - 2 Jul 2025 |
| Event | 26th ACM Conference on Economics and Computation, EC 2025 - Stanford, United States Duration: 7 Jul 2025 → 10 Jul 2025 |
Publication series
| Name | EC 2025 - Proceedings of the 26th ACM Conference on Economics and Computation |
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Conference
| Conference | 26th ACM Conference on Economics and Computation, EC 2025 |
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| Country/Territory | United States |
| City | Stanford |
| Period | 7/07/25 → 10/07/25 |
Bibliographical note
Publisher Copyright:© 2025 Copyright held by the owner/author(s).
Keywords
- bilateral trade
- mechanism design