1. Arbitration and Mediation
L17
Goltsman et al. (JET 2006)
Institutional approach

2. Institutions
CS assumes a particular extensive form of communication game
Some institutions improve upon CS
Two approaches
Design of institutions given incentive constraints
Particular extensive forms
Mechanisms though which they improve communication
How they compare to best CS equilibrium?

3. Sender-Receiver model
Two agents: Sender (S) and Receiver (R)
Type space:
Preferences
S sends message to intermediary, who makes recommendations to R
Recommendation rule
Intermediary:
Arbitration (binding recommendations)
Mediation (not binding)
We look for rules that are ex ante optimal for R

4. Observations Commitment: Myerson’s revelation principle
Direct truth telling mechanism
Welfare rankings for R:
- Arbitration
- Mediation
- SPN equilibrium in ``any’’ communication game
Upper bounds
For mediation and SPN equilibrium ex ante welfare of R and S aligned

5. Arbitration Problem: Incentive compatibility:
Truth telling required to be ex post optimal for S (IC-S)
Rule need not be (ex post) optimal for R.

6. Important trick Fix recommendation rule
Sufficient statistics for S expected payoff
Expectation is an ``action’’ and variance is a ``transfer’’

7. Incentive compatibility (IC-S)
L: satisfies IC-S condition iff
a) Is nondecreasing b) c)
Proof

8. Incentive compatibility (IC-S)
Is IC-S for some
Is IC-S for some

9. Optimal arbitration rule
Assume
T: Optimal mechanism is deterministic with
Melumad and Shibano (RAND 91)
Remarks:
Delegation with cap is optimal
For bubbling is optimal for R (no information transmission)
S -optimal rule

11. Heuristic argument :

12. Mediation Problem: Incentive compatibility:
Truth telling required to be ex post optimal for S (IC-S)
Rule has to be (ex post) optimal for R.
Can optimal arbitration rule be implemented in a mediation setting?

13. Optimal Mediation Mechanism
L: Upper bound for receivers ex ante utility is
Partition
T: Optimal mediation mechanism
Mechanism is random
Arbitrage mediation most informative equilibrium in CS
Mediator’s only role is to introduce noise

15. Interpretation ``Broken’’ phone paradox
Blume, Bord and Kawamura (TE 2007)
With probability instead of signal receiver observes
Informative equilibrium implements optimal mediation outcome
Two effects of noise
Makes the signal less informative
Relaxes IC constraint for S fostering more truthful revelation
The latter effect dominates

16. Negotiations
Multistage cheap talk Aumann and Hart 2003, Krishna and Morgan 2004
Better than most informative CS
Upper bound for welfare of R –mediation outcome-sometimes achieved
Intuition: multistage noise allows for randomisation

17. Conclusions Commitment of external party improves welfa
Delegation is optimal if feasible
Noisy cheap talk can improve information transition
Can be implemented as multistage cheap talk