6. Folk Theorems

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What is a convex combination?

  • Given vectors x, y, z ∈ Rn, z is a convex combination of x and y if there exists a scalar α ∈ [0, 1] such that z = αx + (1 − α)y

  • This means that z is an average of x and y and lies on the line segment between them

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How do we define a convex hull?

  • Given a set of vectors X = {x1, x2, . . . , xk} in Rn , we define the convex hull of X as the smallest convex set containing X

  • Co(X) ={x ∈ Rn: ∃(α1, . . . , αk) ∈ Rk, kj=1 αj = 1, such that x = kj=1 αj xj

  • This essentially defines the smallest possible graphical space which includes all of the vectors

    • Every combination of different values (line segments between them) lies within or on the boundary of the set

  • Extended to economics, this defines the set of all possible payoffs

<ul><li><p>Given a set of vectors X = {x<sub>1</sub>, x<sub>2</sub>, . . . , x<sub>k</sub>} in R<sub>n</sub> , we define the convex hull of X as the smallest convex set containing X </p></li><li><p>Co(X) ={x ∈ R<sup>n</sup>: ∃(α<sub>1</sub>, . . . , α<sub>k</sub>) ∈ R<sup>k</sup>, <sup>k</sup>∑<sub>j=1</sub> α<sub>j</sub> = 1, such that x = <sup>k</sup>∑<sub>j=1</sub> α<sub>j </sub>x<sup>j</sup></p></li><li><p>This essentially defines the smallest possible graphical space which includes all of the vectors</p><ul><li><p>Every combination of different values (line segments between them) lies within or on the boundary of the set</p></li></ul></li><li><p>Extended to economics, this defines the set of all possible payoffs</p></li></ul><p></p>
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Feasible strategies

  • Rely heavily on the discount rate, δ, being sufficiently high; if it is, then a sequence of action strategies (at)t exists such that (1 − δ) t=0 δt ui(at) = πi

  • As the discount rate gets sufficiently high, almost any feasible strategy above the Nash equilibrium could be sustained by players alternating strategies in different periods (being willing to have a bad period followed by a good period for greater average payoffs)

  • These strategies can’t exist unless the discount rate is sufficiently high; when a person is patient enough, we can recognise that their long-run average discounted payoff is πi

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How does Nash reversion work?

  • To incentivise another player to cooperate, we threaten them with punishment; reversion to a Nash equilibrium

  • To ensure the maximum punishment, we want to choose the Nash equilibrium which gives them the minimum payoff: wiNE = min πi(s*), where s* is a Nash equilibrium

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What is the Friedman Folk Theorem?

  • For each feasible payoff vector π ∈ F such that πi > wiNE for all i ∈ N, there exists a discount factor δx such that π is the SPNE (average) payoff of the infinite repeated game for any discount factor greater than δx

  • To simplify, for every payoff which is feasible and affords every player a payoff greater than Nash reversion, there is a threshold discount factor such that, if the discount factor is above it, then these payoffs can be sustained as SPNE

<ul><li><p>For each feasible payoff vector π ∈ F such that π<sub>i</sub> &gt; w<sub>i</sub><sup>NE</sup> for all i ∈ N, there exists a discount factor δ<sup>x</sup> such that π is the SPNE (average) payoff of the infinite repeated game for any discount factor greater than δ<sup>x</sup></p></li><li><p>To simplify, for every payoff which is feasible and affords every player a payoff greater than Nash reversion, there is a threshold discount factor such that, if the discount factor is above it, then these payoffs can be sustained as SPNE</p></li></ul><p></p>
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How is Friedman’s Folk Theorem constructed?

  • Fix π ∈ F

  • Construct a sequence of actions (ai(t))t that generate payoff vector v

  • If a player deviates, the upper bound on payoffs is maxai u(ai , a−i) = ux in the current stage and wNE forever after, which amounts to (1 − δ)uix + δwiNE

  • Although πi > wNE , there exists δi such that πi = (1 − δ)uix + δwiNE

  • Set δx = maxi δi

  • Thus this punishment only works if the player is patient enough such that δ > δx incentivises cooperation

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How might players use a minmax vector to punish more harshly?

  • If a player is playing myopically pm, and thus only best responds in the stage game and doesn’t care about future consequences, the other players in the game - if hostile - will choose the worst environment for the myopic player to best respond to

  • Thus, the strategy profiles which pm can best respond to are minimised, and the response pm chooses towards these profiles is maximised, hence, the minmax vector

  • w˜ = minσ−i∈Πj̸=i∆Sj maxai π(ai , σ−i)

  • In any SPNE, every player achieves a payoff weakly greater than the minmax payoff, which we call individually rational

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What is the Fudenberg Maskin Folk Theorem?

  • For each feasible payoff vector π ∈ F such that πi > w˜i for all i ∈ N, there exists a discount factor δ¯ such that π is the SPNE (average) payoff of the infinite repeated game for any discount factor greater than δ¯

  • Essentially the same as Friedman’s folk theorem, but it changes wNE for w~, it changes the payoff of Nash Reversion to the payoff of the minmax vector

  • Again, if a person is patient enough, such that δ > δ¯, then a payoff can be sustained which is greater than the minmax vector

  • The minmax payoff vector includes mixed strategies

<ul><li><p>For each feasible payoff vector π ∈ F such that π<sub>i</sub> &gt; w˜<sub>i</sub> for all i ∈ N, there exists a discount factor δ¯ such that π is the SPNE (average) payoff of the infinite repeated game for any discount factor greater than δ¯</p></li><li><p>Essentially the same as Friedman’s folk theorem, but it changes w<sup>NE</sup> for w<sup>~</sup>, it changes the payoff of Nash Reversion to the payoff of the minmax vector </p></li><li><p>Again, if a person is patient enough, such that δ &gt; δ¯, then a payoff can be sustained which is greater than the minmax vector</p></li><li><p>The minmax payoff vector includes mixed strategies </p></li></ul><p></p>
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Why is the Fudenberg Maskin Folk Theorem more useful than Friedman’s?

  • It extends the set of feasible payoffs which can be supported; Friedman’s theorem argues only payoffs greater than wNE can be supported but if NE is high, there might not be any payoffs above it

  • w~ allows for harsher deviation punishments because w~ < wNE

  • Minmax allows for boundary results (payoffs equal to minmax)

  • Friedman uses Grim Trigger as the basis which is unrealistic, whereas Fudenberg-Maskin allows for cooperation after deviation thus is more adaptable to changes and is realistic

  • Where Friedman only provides the existence of some payoffs, Fudenberg-Maskin characterise the entire set of payoffs available

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Friedman vs Fudenberg-Maskin Folk Theorem Summary Table

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