Competing mechanisms in games played through agents: Theory and experiment

Seungjin Han and Andrew Leal

Journal of Economic Behavior & Organization, 2026, vol. 246, issue C

Abstract: This paper proposes Competing Mechanism Games Played Through Agents (CMGPTA), an extension of GPTA (Prat and Rustichini, 2003), where competing principals can offer arbitrary mechanisms that specify a transfer schedule for each agent conditional on all agents’ messages. We identify the set of equilibrium allocations using deviator-reporting mechanisms (DRMs) on the path and single transfer schedules off the path. We design a lab experiment implementing DRMs. A majority of the time, agents tell the truth on the identity of a deviating principal, despite potential gains from (tacit) collusion on false reports. As the game progresses, coordination on both truthful and false reports improves. The average predicted probability of collusion on false reports across groups increased from about 9% at the beginning of the experiment to just under 20% by the end. However, group heterogeneity is significant.

Keywords: Competing mechanisms; Truthful communication; Collusion; Experiment (search for similar items in EconPapers)
JEL-codes: C92 D43 D82 D86 (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167268126001526
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Competing Mechanisms in Games Played Through Agents: Theory and Experiment (2025)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:246:y:2026:i:c:s0167268126001526

DOI: 10.1016/j.jebo.2026.107566

Access Statistics for this article

Journal of Economic Behavior & Organization is currently edited by Houser, D. and Puzzello, D.

More articles in Journal of Economic Behavior & Organization from Elsevier
Bibliographic data for series maintained by Catherine Liu ().