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Cheap Talk and Bargaining Power

This presentation explores the dynamics of information sharing in bargaining scenarios, examining how different strategies influence outcomes in various contexts, such as mergers and custody disputes. We analyze the balance between sharing information for efficiency and the strategic motivations for withholding it. By employing a theoretical model and experimental design, we investigate how the strength of the proposer or chooser affects information transmission and bargaining outcomes, highlighting the role of neologisms in creating instability. Key findings reveal the complex interplay between power dynamics and information flow in negotiation settings.

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Cheap Talk and Bargaining Power

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  1. CREED-CEDEX-UEA Meeting 6 June 2008 Cheap Talk and Bargaining Power Adrian de Groot Ruiz Sander Onderstal Theo Offerman

  2. Outline • Sharing information in bargaining • Relevant Situations • Questions • Model • Equilibria • Design • Results • Literature

  3. Introduction Consider the Following Situations: • Potential Merger • Merging firms send proposal to Market Authority • Merging firms prefer as large a firm as possible • Exact preference of Authority are unknown • Outside option is no merger • Legal dispute • Father and Mother fight over Custody • Mother wants the children all day • Father’s preferences are unknown • Lawyers try to find an agreement • Outside option is costly trial

  4. Introduction Sharing information in Bargaining • Incentive to share: efficiency • “common goals” • Efficiency • Incentive not to share: strategic • Vagueness • Deception • How much information can be transmitted? • Crawford/Sobel, Matthews, Dickhaut, Cai/Wang

  5. Introduction Questions • If you become more powerful, your incentives and credibility may change. • What is the effect of a neologism on the evolution of bargaining-language? • Farrell

  6. Model Model: Chooser and Proposer • Bargain over policy p in [0, 120] • Ideal policy Proposer is 0 • Ideal policy Chooser is private v ~ U[0,120] • Status quo δ (not in [0, 120]): ui(δ)=0 60 60 uP = 60 – 0.4*p uC = 60 – |p – v| 0 0 v 120 120

  7. Model Game Tree • Nature informs Chooser of value in [0,120] • Chooser sends suggestion s in [0,120] • Proposer makes proposal x in [0, 120] • Chooser accepts or rejects proposal x

  8. Theory 60 120 0 60 Cheap Talk Equilibria

  9. Theory Chooser stronger => More Information Transmission 60 30 120 0 30 90

  10. Theory Proposer stronger =>- Less information transmission - Less Stability (neologism) 60 30 120 0 30 40

  11. Experiment Experimental Design

  12. Experiment Experimental Procedure • Random matching, fixed roles • 50 periods per session • 10 subjects per matching group • Six matching groups per treatment • Social History

  13. Experiment Results: Values Suggestions Proposals Acceptance rates v v v None: uP(δ)=0 uC(δ)=0Chooser: uP(δ)=0 uC(δ)=30Both: uP(δ)=30 uC(δ)=30

  14. Experiment Results: Values

  15. Experiment Results: Variance Var(Suggestions|v) Var(Proposals|v) Var(Acceptance|v) v v v None: uP(δ)=0 uC(δ)=0Chooser: uP(δ)=0 uC(δ)=30Both: uP(δ)=30 uC(δ)=30

  16. Experiment Results: Distribution Proposals None Chooser Both

  17. Preliminary Conclusions • Experiments show mix between equilibrium behavior and naive behavior. • Chooser stronger implies more information transmission. • Proposer stronger implies less information transmission and more instability. • Neologisms cause instability.

  18. Literature Literature • Crawford & Sobel (Econometrica, 1982) • Matthews (QJE, 1989) • Farrell (Games, 1993) • Dickhout (JET, 1995) • Cai/Wang (Games, 2006)

  19. Questions & Suggestions

  20. End

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