1. Static Games of Complete Information: Equilibrium Concepts
APEC 8205: Applied Game Theory

2. Objectives
Understand Common Solution Concepts for Static Games of Complete Information
Dominant Strategy Equilibrium
Iterated Dominance
Maxi-Min Equilibrium
Pure Strategy Nash Equilibrium
Mixed Strategy Nash Equilibrium

3. Introductory Comments On Assumptions
Knowledge
I know the rules of the game.
I know you know the rules of the game.
I know you know I know the rules of the game. …
Rationality
I am individually rational.
I believe you are individually rational.
I believe that you believe I am individually rational.

4. Normative Versus Positive Theory
How should people play games?
What should they be trying to accomplish?
Positive:
How do people play games?
What do they accomplish?
What are obstacles to the theory’s predictive performance?
Players do not always fully understand the rules of the game.
Players may not be individually rational.
Players may poorly anticipate the choices of others.
Players are not always playing the games we think they are.

5. What makes a good solution concept?
Existence
Uniqueness
Logical Consistency
Predictive Performance
In Equilibrium
Out of Equilibrium

6. Normal Form Games: Notation
A set N = {1,2,…,n} of players.
A finite set of pure strategies Si for each i  N where S = S1S2…Sn is the set of all possible pure strategy outcomes.
si is a specific strategy for player i (si  Si)
s~i is a specific strategy for everyone but player i (s~i  S~i = S1… Si-1Si+1 …Sn).
s is a specific strategy for each and every player (e.g. a strategy profile: s  S)
A payoff function gi: S  for each i  N.

7. Dominant Strategy Equilibrium
Definitions
Strategy si weakly dominates strategy ti if gi(si,s~i) ≥ gi(ti,s~i) for all s~i  S~i.
Strategy si dominates strategy ti if gi(si,s~i) ≥ gi(ti,s~i) for all s~i  S~i and gi(si,s~i) > gi(ti, s~i) for some s~i  S~i.
Strategy si strictly dominates strategy ti if gi(si,s~i) > gi(ti,s~i) for all s~i  S~i.
Strategy profile s*  S is a weakly/strictly dominant strategy equilibrium if for all i  N and all ti  S, si weakly/strictly dominates ti.
Note: In a dominant strategy equilibrium, your best strategy
does not depend on your opponents’ strategy choices!
Note: An equilibrium is defined by the strategy profile that
meets the definition of the equilibrium!

8. Example: Prisoners’ Dilemma
Player 1
Choose Defect if Player 2 Cooperates (3 > 2).
Choose Defect if Player 2 Defects (1 > 0).
Defect is a Dominant Strategy!
Player 2
Choose Defect if Player 1 Cooperates (3 > 2).
Choose Defect if Player 1 Defects (1 > 0).
(Defect, Defect) is a strictly dominant strategy equilibrium.

9. Example: Second Price Auction
Who are the players?
Bidders i = 1, …, n who value and are competing for the same object.
Who can do what when?
Players submit bids simultaneously.
Who knows what when?
Players know their value of the object before submitting their bid. They do not know the value of others.
How are players rewarded based on what they do?
vi: value to i of winning Auction
h~i: highest bid value of all players not including i
gi = vi – h~i if bi > h~i and 0 otherwise.
What is a players strategy?
bi ≥ 0 (e.g. bid value)

10. Claim: bi* = vi for all i is a weakly dominant strategy equilibrium!
Suppose bi > vi:
If h~i ≥ bi, gi = 0 (Same as if bi = vi).
If h~i < vi, gi = vi - h~i (Same as if bi = vi).
If bi > h~i ≥ vi, gi = vi - h~i ≤ 0 (0 if bi = vi).
Does not improve payoff under any circumstances and may reduce payoff!
Suppose vi > bi:
If h~i ≥ vi, gi = 0 (Same as if bi = vi).
If h~i < bi, gi = vi - h~i (Same as if bi = vi).
If vi > h~i ≥ bi, gi = 0 (vi - h~i ≥ 0 if bi = vi).

11. Good & Bad Of Dominance Equilibrium
Tends to predict behavior pretty well!
Bad
Often does not exist!

12. Iterative Dominance Definition: Intuition: Messy Not Very Instructive
Easy! No rational player will ever choose a dominated strategy.
Repeatedly eliminate dominated strategies for each player until no dominated strategies remain!

13. Example: Iterative Dominance
R strictly dominates C, so C is gone.
U strictly dominates M, so M is gone.
U strictly dominates D, so D is gone.
L strictly dominates R, so R is gone.
(U,L) is the iterative dominant strategy.

14. Good & Bad Of Iterative Dominance
May be able to use it when there is not dominant strategy equilibrium!
Bad
Does not predict as well. Particularly, if lots of iterations are involved.

15. Maxi-Min Equilibrium Motivation: Definition:
How should we play if we want to be particularly cautious?
Definition:
Strategy si* is a maxi-min strategy if it maximizes i’s minimum possible payoff:
s* is a maxi-min equilibrium if si* is a maxi-min strategy for all i.

16. Example: MaxiMin Equilibrium
Player 1
The minimum possible reward from choosing U is 0.
The minimum possible reward from choosing D is 1.
D maximizes Player 1’s minimum possible reward.
Player 2
The minimum possible reward from choosing L is 0.
The minimum possible reward from choosing R is 1.
R maximizes Player 2’s minimum possible reward.
(D, R) is the Maxi-Min equilibrium strategy.

17. Comments on Maxi-Min Equilibrium
Popular Solution Concept for Zero Sum Games
Your gain is your opponents loss, so they are out to get you and it makes sense to be cautious.
Game theorist version of the precautionary principle.

18. Pure Strategy Nash Equilibrium
Definition:
s*  S is a pure strategy Nash equilibrium if for all players i  N, gi(si*,s~i*) ≥ gi(si,s~i*) for all si  Si (there are no profitable unilateral deviations).
Alternative Definition:
Best Response Function: bri(s) = {si  Si: gi(si,s~i) ≥ gi(si’,s~i) for all si’  Si}.
Best Response Correspondence: br(s) = br1(s)  br2(s) … brn(s).
s*  S is a pure strategy Nash equilibrium if s*  br(s*) (s* is a best response to itself).

19. Example: Prisoners’ Dilemma
Player 1
Defect is the best response to Cooperate (3 > 2).
Defect is the best response to Defect (1 > 0).
Player 2
(Defect, Defect) is a pure strategy Nash equilibrium.
Same as dominant strategy equilibrium! * * * *

20. Welfare & Nash First Fundamental Welfare Theorem:
A competitive equilibrium is Pareto efficient.
A Nash equilibrium need not be Pareto efficient! g2
(0,3)
Pareto Efficient
(2,2)
Pareto Efficient
(1,1)
Nash
(3,0)
Pareto Efficient g1

21. Iterative Dominance Example Revisited
Player 1
U is a best response to L.
D is a best response to C.
U is a best response to R.
Player 2
L is a best response to U.
R is a best response to M.
R is a best response to D.
(U, L) is a pure strategy Nash equilibrium.
Same as the iterative dominant equilibrium! * * * * * *

22. Maxi-Min Example Revisited
Player 1
D is a best response to L.
U is a best response to R.
Player 2
R is a best response to U.
L is a best response to D.
Pure strategy Nash equilibria:
(U, R)
(D, L)
Multiple Nash!
Neither is the Maxi-Min equilibrium! * * * *

23. How can we choose between these two equilibria?
Motivation for equilibrium refinements!
What may make sense for this game?
Pareto Dominance! * * * *

24. Is Pareto dominance always a good strategy?
Player 1
U is a best response to L.
D is a best response to R.
Player 2
L is a best response to U.
R is a best response to D.
Pure strategy Nash equilibria:
(U, L) Pareto Dominant
(D, R)
Is (U, L) really more compelling than (D, R)? * * * *

25. Example: Battle of the Sexes
Player 1
Football is the best response to Football.
Ballet is the best response to Ballet.
Player 2
Pure Strategy Nash Equilibria:
(Football, Football)
(Ballet, Ballet)
Neither strategy is Pareto dominant! * * * *

26. Focal Points (Schelling)
Suppose you and a friend go to the Mall of America to shop. As you leave the car in the parking garage, you agree to go separate ways and meet back up at 4 pm. The problem is you forget to specify where to meet.
Question: Where do you go to meet back up with your friend?
Historically, equilibrium refinement relied much on introspection.
With the emergence and increasing popularity of experimental methods, economists
are relying more and more on people to show them how the games will be played.

27. Matching Pennies Revisited
Mason
Heads is the best response to Heads.
Tails is the best response to Tails.
Spencer
Tails is the best response to Heads.
Heads is the best response to Tails.
There is no pure strategy Nash equilibrium! * * * *

28. Mixed Strategy Nash Equilibrium
Definitions:
i(si): probability player i will play pure strategy si.
i: mixed strategy (a probability distribution over all possible pure strategies).
i: set of all possible mixed strategies for player i (i  i).
 = { 1,  2, …,  n}: mixed strategy profile.
 =  1   2 …  n: set of all possible mixed strategy profiles (  ).
Gi(i,~i) =
 *   is a mixed strategy Nash equilibrium if for all players i  N, Gi(i*,~i*) ≥ Gi(si,~i*) for all si  Si.
Note: Dominant strategy equilibrium and iterative dominant strategy
equilibrium can also be defined in mixed strategies.

29. Mixed Strategy Nash Equilibrium
Another Definition:
Best Response Function: bri() = {i  i: Gi(i, ~i) ≥ Gi(si’, ~i) for all si’  Si}.
Best Response Correspondence: br() = br1()  br2() … brn().
 *   is a pure strategy Nash equilibrium if  *  br( *).

30. What is Mason’s best response for Matching Pennies?
(S ,1 – S): mixed strategy for Spencer where 1 ≥ S ≥ 0 is the probability of Heads.
(M,1 – M): mixed strategy for Mason where 1 ≥ M ≥ 0 is the probability of Heads.
M(H) = S – (1 – S) : Mason’s expected payoff from choosing Heads.
M(T) = -S + (1 – S) : Mason’s expected payoff from choosing Tails.
M(H) >/=/< M(T) for S >/=/< ½

31. What is Spencer’s best response for Matching Pennies?
S(H) = -M + (1 – M) : Spencer’s expected payoff from choosing Heads.
S(T) = M – (1 – M) : Spencer’s expected payoff from choosing Tails.
S(H) >/=/< S(T) for ½ >/=/< M

32. Do we have a mixed strategy equilibrium?
brS() 1
brM()
Nash Equilibrium:
{(½, ½), (½, ½)} 1 M

33. Battle of the Sexes Example Revisited
(1 ,1 – 1): mixed strategy for Player 1 where 1 ≥ 1 ≥ 0 is the probability of Football.
(2,1 – 2): mixed strategy for Player 2 where 1 ≥ 2 ≥ 0 is the probability of Football.
Player 1’s Optimization Problem
Player 2’s Optimization Problem

34. Solving for Player 1
Lagrangian
First Order Conditions
Implications

35. Solving for Player 2
Lagrangian
First Order Conditions
Implications

36. Do we have a mixed strategy equilibrium?
Is that all?
Nash Equilibrium:
{(1, 0), (1, 0)} 2
br2() 1
br1()
Nash Equilibrium:
{(2/3, 1/3), (1/3, 2/3)}
1/3
Nash Equilibrium:
{(0, 1), (0, 1)}
2/3 1 1

37. Why do we care about mixed strategy equilibrium?
Seems sensible in many games:
Matching Pennies
Rock/Paper/Scissors
Tennis
Baseball
Prelim Exams
If we allow mixed strategies, we are guaranteed to find at least one Nash in finite games (Nash, 1950)!
Games with continuous strategies also have at least one Nash under usual conditions (Debreu, 1952; Glicksburg, 1952; and Fan, 1952).
Actually, finding a Nash is usually not a problem. The problem is usually the multiplicity of Nash!

38. Application: Cournot Duopoly
Who are the players?
Two firms denoted by i = 1, 2.
Who can do what when?
Firms choose output simultaneously.
Who knows what when?
Neither firm knows the other’s output before choosing its own. .
How are firms rewarded based on what they do?
gi(qi, qj) = (a – qi – qj)qi – cqi for i ≠ j.
Question: What is a strategy for firm i?
qi ≥ 0

39. Nash Equilibrium for Cournot Duopoly
Find each firm’s best response function:
FOC for interior: a – 2qi – qj – c = 0
SOC: –2 < 0 is satisfied
Solve for qi:
Find a Mutual Best Response: q2
a – c
q1(q2)
a – c 2
q2*
q2(q1)
a – c 2
a – c q1
q1*

40. But what if we have n firms instead of just 2?
Find each firm’s best response function:
FOC for interior: a – 2qi – q~i – c = 0
SOC: –2 < 0 is satisfied
Solve for qi:
Find a Mutual Best Response:
qi* = a – c – Q* where Q* = qi* + q~i*
Sum over i:
Solve for Q*:
Solve for qi*:

41. Implications as n Gets Large
Individual firm equilibrium output decreases.
Equilibrium industry output approaches a – c.
Equilibrium price approaches marginal cost c.
We approach an efficient competitive equilibrium!

42. Application: Common Property Resource
Who are the players?
Ranchers denoted by i = 1, 2, …, n.
Who can do what when?
Each rancher can put steers on open range to graze simultaneously.
Who knows what when?
No rancher knows how many steers other ranchers will graze before choosing how many he will graze.
How are ranchers rewarded based on what they do?
gi(qi, q~i) = p(aQ – Q2)qi/Q – cqi where Q is the total number of steers grazing the range land.
Question: What is a strategy for rancher i?
qi ≥ 0

43. Nash Equilibrium for Common Property Resource
Find each ranchers’s best response function:
FOC for interior: p(a – 2qi – q~i) – c = 0
SOC: –2p < 0 is satisfied
Solve for qi:
Find a Mutual Best Response:
pqi* = pa – c – pQ*
Sum over i:
Solve for Q*:
Solve for qi*:

44. Implications as n Gets Large
Individual rancher equilibrium stocking decreases.
Equilibrium industry stocking approaches a – c/p.
Individual rancher’s payoff approaches zero.
Stocking rate becomes increasingly inefficient!

45. Application: Compliance Game
Who are the players?
Regulator & Firm
Who does what when?
Regulator chooses whether to Audit Firm & Firm chooses whether to Comply.
Choices are simultaneous.
Who knows what when?
Regulator & Firm do not know each others choices when making their own.
How are the Regulator and Firm rewarded based on what they do?

46. Assuming S > CF & S > CA, what is the Nash equilibrium for this game?
Regulator
R(Audit) = F(BR – CA) + (1 – F)(S – CA)
R(Don’t Audit) = FBR + (1 – F)0
R(Audit) >/=/< R(Don’t Audit) for 1 – CA/S >/=/< F
Firm
F(Comply) = R(BF – CF) + (1 – R)(BF – CF)
F(Don’t Comply) = R(BF – S) + (1 – R)BF
F(Comply) >/=/< F(Don’t Comply) for R >/=/< CF/S

47. What is the equilibrium? We know we have at least one!F
brF() 1
Nash Equilibrium:
{(CF/S, 1 - CF/S),
(1 – CA/S, CA/S)}
1 – CA/S
brR() 1 R
CF/S

48. What are the implications of this equilibrium?
Equilibrium Audit Probability:
Increasing in the Firm’s cost of compliance!
Decreasing in the Regulator’s sanction!
Equilibrium Compliance Probability:
Decreasing in the Regulator’s cost of Auditing!
Increasing in the Regulators sanction!
Shoot Jaywalkers with Zero Probability!