Saddle Point

Engine · Chapter 3, Bargaining, Commitment, and Repeated Cooperation

The forgiving trigger

How patient must two sides be for cooperation to survive noisy monitoring?

Monitoring

90
50
90 the weight on the future

Stage payoffs (T > R > P > S)

3
5
1
0

The book's scenarios

Each player's value under the best forgiving trigger

≈ 2.5000

against under perfect monitoring: the price of noise is , and it does not depend on patience.

The trigger

Informativeness margin
Patience needed
Punishment probability at δ = 9/10
Chance of an unjust punishment per period
Expected cooperative periods before it

D The book certifies , , , . Agreement, exactly.

0.0000.80.250.251.50.50.52.30.750.753.011q, the chance that a defection still looks cleanV*δ_minno cooperation from q = 4/5
V*, the value of the best forgiving trigger (left axis) · δ_min, the patience it needs (right axis), at p = 9/10. Two levers: at the margin, raising p is worth 25/4 per unit and lowering q is worth 5/4, a ratio of 5 = (1 − q)/(1 − p), whatever the payoffs.
The formulas

The value satisfies ; a one-shot defection gains and raises the chance of punishment by ; the smallest punishment rate that deters is best, since punishment also falls on the innocent.

The model it runs

Model B4 · p. 132

What does noisy monitoring cost, and how should punishments be calibrated?

1Decision-makers
two players
2Time
infinitely repeated; discount
3Information
imperfect public monitoring: only the signal and the lottery are seen
4Commitment
none
5Payoffs
as in Model B3
6Strategies
the class of trigger profiles with forgiveness, indexed by

Analysis contract

(i) concept
perfect public equilibrium within the stated class
(ii) deviations
one-shot deviations from cooperation (mutual defection is a stage equilibrium)
(iii) beliefs
public signals only
(iv) selection
the incentive-compatible with the highest value
(v) attainment
attained; exact; optimality is within the class only