Bilateral Trade with Interdependent Values: Information vs. Approximation

Shahar Dobzinski, Alon Eden, Kira Goldner, Ariel Shaulker, Thodoris Tsilivis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publicationEC 2025 - Proceedings of the 26th ACM Conference on Economics and Computation
PublisherAssociation for Computing Machinery, Inc
Pages641-665
Number of pages25
ISBN (Electronic)9798400719431
DOIs
StatePublished - 2 Jul 2025
Event26th ACM Conference on Economics and Computation, EC 2025 - Stanford, United States
Duration: 7 Jul 202510 Jul 2025

Publication series

NameEC 2025 - Proceedings of the 26th ACM Conference on Economics and Computation

Conference

Conference26th ACM Conference on Economics and Computation, EC 2025
Country/TerritoryUnited States
CityStanford
Period7/07/2510/07/25

Bibliographical note

Publisher Copyright:
© 2025 Copyright held by the owner/author(s).

Keywords

  • bilateral trade
  • mechanism design

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