Timing of messages and the Aumann conjecture: A multiple-selves approach

Research output: Contribution to journalArticlepeer-review

Abstract

The Aumann (In: Gabszewicz JJ, Richard JF, Wolsey L (eds) Economic decision making: games, econometrics and optimisation, 1990) conjecture states that cheap-talk messages do not necessarily help to coordinate on efficient Nash equilibria. In an experimental test of Aumann's conjecture, Charness (Games Econ Behav 33(2):177-194, 2000) found that cheap-talk messages facilitate coordination when they precede the action, but not when they follow the action. Standard game-theoretical modeling abstracts from this timing effect, and therefore cannot account for it. To allow for a formal analysis of the timing effect, I study the sequential equilibria of the signaling game in which the sender is modeled as comprising two selves: an acting self and a signaling self. I interpret Aumann's argument in this context to imply that all of the equilibria in this game are 'babbling' equilibria, in which the message conveys no information and does not affect the behavior of the receiver. Using this framework, I show that a fully communicative equilibrium exists-only if the message precedes the action but not when the message follows the action. In the latter case, no information is transmitted in any equilibrium. This result provides a game-theoretical explanation for the puzzling experimental results obtained by Charness (2000). I discuss other explanations for this timing-of-message effect and their relationship to the current analysis.

Original languageAmerican English
Pages (from-to)789-800
Number of pages12
JournalInternational Journal of Game Theory
Volume42
Issue number4
DOIs
StatePublished - 1 Nov 2013

Keywords

  • Coordination games
  • Multiple selves
  • Nash equilibrium
  • Pre-play communication

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Mathematics (miscellaneous)
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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