How is Cooperation/collusion Sustained in Repeated Multimarket Contact with Observation Errors?

Atsushi Iwasaki, Tadashi Sekiguchi, Shun Yamamoto, Makoto Yokoo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper analyzes repeated multimarket contact with observation errors where two players operate in multiple markets simultaneously. Multimarket contact has received much attention in economics, management, and so on. Despite vast empirical studies that examine whether multimarket contact fosters cooperation or collusion, little is theoretically known as to how players behave in an equilibrium when each player receives a noisy and different observation or signal indicating other firms' actions (private monitoring). To the best of our knowledge, we are the first to construct a strategy designed for multiple markets whose per-market equilibrium payoffs exceed one for a single market, in our setting. We first construct an entirely novel strategy whose behavior is specified by a non-linear function of the signal configurations. We then show that the per-market equilibrium payoff improves when the number of markets is sufficiently large.

Original languageEnglish
Title of host publicationAAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1369-1370
Number of pages2
ISBN (Electronic)9781450342391
Publication statusPublished - 2016
Event15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016 - Singapore, Singapore
Duration: May 9 2016May 13 2016

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Other

Other15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016
Country/TerritorySingapore
CitySingapore
Period5/9/165/13/16

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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