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Applied Game Theory Lecture 5 Pietro Michiardi. Cash in a Hat game (1) Two players, 1 and 2 Player 1 strategies: put $0, $1 or $3 in a hat Then, the hat.

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Presentation on theme: "Applied Game Theory Lecture 5 Pietro Michiardi. Cash in a Hat game (1) Two players, 1 and 2 Player 1 strategies: put $0, $1 or $3 in a hat Then, the hat."— Presentation transcript:

1 Applied Game Theory Lecture 5 Pietro Michiardi

2 Cash in a Hat game (1) Two players, 1 and 2 Player 1 strategies: put $0, $1 or $3 in a hat Then, the hat is passed to player 2 Player 2 strategies: either match (i.e., add the same amount of money in the hat) or take the cash

3 Cash in a Hat game (2) Payoffs: Player 1: Player 2: $0 $1 if match net profit $1, -$1 if not $3 if match net profit $3, -$3 if not Match $1 Net profit $1.5 Match $3 Net profit $2 Take the cash $ in the hat

4 Cash in a Hat game (3) Lets play this game in class What would you do? How would you analyze this game? This game is a toy version of a more important game, involving a lender and a borrower

5 Lender & Borrower game Lets make a couple of motivating examples – Lenders: Banks, VC Firms, … – Borrowers: you guys having a cool project idea to develop The lender has to decide how much money to invest in the project After the money has been invested, the borrower could – Go forward with the project and work hard – Shirk, and run to Mexico with the money

6 Simultaneous vs. Sequential Moves Question: what is different about this game with regards to all the games weve played so far? This is a sequential move game – What really makes this game a sequential move game? – It is not the fact that player 2 chooses after player 1, so time is not the really key idea here – The key idea is that player 2 can observe player 1s choice before having to make his or her choice – Notice: player 1 knows that this is going to be the case!

7 Analyzing sequential moves games A useful representation of such games is game trees also known as the extensive form For normal form games we used matrices, here well focus on trees – Each internal node of the tree will represent the ability of a player to make choices at a certain stage, and they are called decision nodes – Leafs of the tree are called end nodes and represent payoffs to both players

8 Cash in a hat representation (0,0) (1, 1.5) (-1, 1) (3, 2) (-3, 3) $0 $1 $3 $1 - $1 $3 - $3 What do we do to analyze such game?

9 Analyzing sequential moves games The idea is: players that move early on in the game should put themselves in the shoes of other players Here this reasoning takes the form of anticipation Basically, look towards the end of the tree and work back your way along the tree to the root

10 Backward Induction Start with the last player and chose the strategies yielding higher payoff This simplifies the tree Continue with the before-last player and do the same thing Repeat until you get to the root This is a fundamental concept in game theory

11 Backward Induction in practice (1) (0,0) (1, 1.5) (-1, 1) (3, 2) (-3, 3) $0 $1 $3 $1 - $1 $3 - $3

12 Backward Induction in practice (2) (0,0) (1, 1.5) (-3, 3) $0 $1 $3

13 Backward Induction in practice (3) (0,0) (1, 1.5) (-1, 1) (3, 2) (-3, 3) $0 $1 $3 $1 - $1 $3 - $3 Player 1 chooses to invest $1, Player 2 matches

14 What is the problem in the outcome of this game? (0,0) (1, 1.5) (-1, 1) (3, 2) (-3, 3) $0 $1 $3 $1 - $1 $3 - $3 Very similar to what we learned with the Prisoners Dilemma

15 The problem with the lenders and borrowers game It is not a disaster: – The lender doubled her money – The borrower was able to go ahead with a small scale project and make some money But, we would have liked to end up in another branch: – Larger project funded with $3 and an outcome better for both the lender and the borrower What does prevent us from getting to this latter good outcome?

16 Moral Hazard One player (the borrower) has incentives to do things that are not in the interests of the other player (the lender) – By giving a too big loan, the incentives for the borrower will be such that they will not be aligned with the incentives on the lender – Notice that moral hazard has also disadvantages for the borrower

17 Moral Hazard: an example Insurance companies offers full-risk policies People subscribing for this policies may have no incentives to take care! In practice, insurance companies force me to bear some deductible costs (franchise)

18 How can we solve the Moral Hazard problem? Weve already seen one way of solving the problem keep your project small Are there any other ways?

19 Introduce laws Similarly to what we discussed for the PD Today we have such laws: bankruptcy laws But, there are limits to the degree to which borrowers can be punished The lender can say: I cant repay, Im bankrupt And he/shes more or less allowed to have a fresh start

20 Limits/restrictions on money Another way could be to asking the borrowers a concrete plan (business plan) on how he/she will spend the money This boils down to changing the order of play! But, whats the problem here? Lack of flexibility, which is the motivation to be an entrepreneur in the first place! Problem of timing: it is sometimes hard to predict up-front all the expenses of a project

21 Break the loan up Let the loan come in small installments If a borrower does well on the first installment, the lender will give a bigger installment next time It is similar to taking this one-shot game and turn it into a repeated game – Do you recall what happens to the PD game with repeated interactions?

22 Change contract to avoid shirk The borrower could re-design the payoffs of the game in case the project is successful (0,0) (1, 1.5) (-1, 1) (1.9, 3.1) (-3, 3) $0 $1 $3 $1 - $1 $3 - $3

23 Incentive Design (1) Incentives have to be designed when defining the game in order to achieve goals Notice that in the last example, the lender is not getting a 100% their money back, but they end up doing better than what they did with a smaller loan Sometimes a smaller share of a larger pie can be bigger than a larger share of a smaller pie

24 Incentive Design (2) In the example we saw, even if $1.9 is larger than $1 in absolute terms, we could look at a different metric to judge a lenders actions Return on Investment (ROI) – For example, as an investment banker, you could also just decide to invest in 3 small projects and get 100% ROI

25 Incentive Design (3) So should an investment bank care more about absolute payoffs or ROI? It depends! On what? There are two things to worry about: – The funds supply – The demand for your cash (the project supply)

26 Incentive Design (4) There are two things to worry about: – The funds supply – The demand for your cash (the project supply) If there are few projects you may want to maximize the absolute payoff If there are infinite projects you may want to maximize your ROI

27 Examples of incentives Incentives in contracts for CEOs – Bad interpretation, they screw up the world – Mild interpretation, they align CEOs actions towards the interests of the shareholders Manager of sport teams In the middle age, piece rates / share cropping Incentive design is a topic per-se, we wont go into the details in this lecture

28 Beyond incentives… Can we do any other things rather than providing incentives? Ever heard of collateral? – Example: subtract house from run away payoffs Lowers the payoffs to borrower at some tree points, yet makes the borrower better off!

29 Collateral example The borrower could re-design the payoffs of the game in case the project is successful (0,0) (1, 1.5) (-1, 1 - HOUSE) (3,2) (-3, 3 - HOUSE) $0 $1 $3 $1 - $1 $3 - $3

30 Collaterals They do hurt a player enough to change his/her behavior Lowering the payoffs at certain points of the game, does not mean that a player will be worse off!! Collaterals are part of a larger branch called commitment strategies – Next, an example of commitment strategies

31 Norman Army vs. Saxon Army Game Back in 1066, William the Conqueror lead an invasion from Normandy on the Sussex beaches Were talking about military strategy So basically we have two players (the armies) and the strategies available to the players are whether to fight or run

32 Norman Army vs. Saxon Army Game N S N N (0,0) (1,2) (2,1) (1,2) invade fight run fight run Lets analyze the game with Backward Induction

33 Norman Army vs. Saxon Army Game N S N N (0,0) (1,2) (2,1) (1,2) invade fight run fight run

34 Norman Army vs. Saxon Army Game N S N N (1,2) (2,1) invade fight run

35 Norman Army vs. Saxon Army Game N S N N (0,0) (1,2) (2,1) (1,2) invade fight run fight run Backward Induction tells us: Saxons will fight Normans will run away What did William the Conqueror did?

36 Norman Army vs. Saxon Army Game N S N N (0,0) (1,2) (2,1) (1,2) fight run fight run S Not burn boats Burn boats fight run N N fight (0,0) (2,1)

37 Norman Army vs. Saxon Army Game N S N N (1,2) (2,1) fight run fight run S Not burn boats Burn boats fight run N N fight (0,0) (2,1)

38 Norman Army vs. Saxon Army Game N S (1,2) S Not burn boats Burn boats (2,1)

39 Norman Army vs. Saxon Army Game N S N N (0,0) (1,2) (2,1) (1,2) fight run fight run S Not burn boats Burn boats fight run N N fight (0,0) (2,1)

40 Lesson learned Sometimes, getting rid of choices can make me better off! Commitment: – Fewer options change the behavior of others – Do you remember another setting weve seen in class in which this applied? The other players must know about your commitments – Example: Dr. Strangelove movie

41 REVISITING ECONOMICS 101 From simultaneous to sequential moves settings

42 Cournot Competition (1) The players: 2 Firms, e.g. Coke and Pepsi Strategies: quantities players produce of identical products: q i, q -i – Products are perfect substitutes

43 Cournot Competition (2) Cost of production: c * q – Simple model of constant marginal cost Prices: p = a – b (q 1 + q 2 )

44 0 a q 1 + q 2 p Price in the Cournot Duopoly Game Slope: -b Demand curve Tells the quantity demanded for a given price

45 Cournot Competition (3) The payoffs: firms aim to maximize profit u 1 (q 1,q 2 ) = p * q 1 – c * q 1 Profits = Revenues – Costs Game vs. maximization problem

46 Cournot Competition (4) u 1 (q 1,q 2 ) = p * q 1 – c * q 1 p = a – b (q 1 + q 2 ) u 1 (q 1,q 2 ) = a * q 1 – b * q 2 1 – b * q 1 q 2 – c * q 1

47 Cournot Competition (5) First order condition Second order condition

48 Cournot Competition (6) First order condition Second order condition [make sure its a max]

49 When BR for Firm 1 is q 1 = 0 ? We simply take the BR expression and set it to zero That was the perfect competition quantity…

50 What is the NE of the Cournot Duopoly? Graphically weve seen it, formally we have: We have found the COURNOT QUANTITY

51 0 q1q1 q2q2 NE Monopoly Perfect competition BR 2 BR 1

52 Stackelberg Model (1) We are going to assume that one firm gets to move first and the other moves after – That is one firm gets to set the quantity first Assuming were in the world of competition, is it an advantage to move first? – Or maybe it is better to wait and see what the other firm is doing and then react? We are going to use backward induction

53 Stackelberg Model (2) Unfortunately we wont be able to draw trees, as the game is too complex First well go for an intuitive explanation of what happens, then well figure out the math

54 Stackelberg Model (3) Lets assume firm 1 moves first Firm 2 is going to observe firm 1s choice and then move How would you go about it?

55 0 q1q1 q2q2 BR 2 q1q1 q1q1 q2q2 q2q2

56 Stackelberg Model (4) By definition of Best Response, we know whats the profit maximizing strategy of firm 2, given an output quantity produced by firm 1 Alright, now we know what firm 2 will do, whats interesting is to look at what firm 1 will come up with

57 Stackelberg Model (5) What quantity should firm 1 produce, knowing that firm 2 will respond using the BR? – This is a constrained optimization problem One legitimate question would be: should firm 1 produce more or less than the quantity she produced when the moves were simultaneous? – In particular, should firm 1 produce more or less than the Cournot quantity?

58 Stackelberg Model (6) Question: should firm 1 produce more than Remember, we are in a strategic substitutes setting – The more firm 1 produces, the less firm 2 will produce and vice-versa Firm 1 producing more firm 1 is happy

59 Stackelberg Model (7) If q1 increases, then q2 will decrease (as suggested by the BR curve) What happens to firm 1s profits? – They go up, for otherwise firm 1 wouldnt have set higher production quantities What happens to firm 2s profits? – The answer is not immediate What happened to the total output in the market? – Even here the answer is not immediate

60 Stackelberg Model (8) What happened to the total output in the market? – Consumers would like the total output to go up, for that would mean that prices would go down! My claim is that the total output went indeed up – This is a direct consequence of the BR curve

61 0 q1q1 q2q2 BR 2 q1q1 q1q1 q2q2 q2q2 The increment from q1 to q1 is larger than the decrement from q2 to q2

62 Stackelberg Model (9) So, what happens to firm 2s profits? q1 went up, q2 went down q1+q2 went up prices went down Firm 2s costs are the same Firm 2s profit went down

63 Stackelberg Model (10) Lets have a nerdy look at the problem: Lets apply the Backward Induction principle – First, solve the maximization problem for firm 2, taking q1 as given – Then, focus on firm 1

64 Stackelberg Model (11) Lets focus on firm 2: We now can take this quantity and plug it in the maximization problem for firm 1

65 Stackelberg Model (12) Lets focus on firm 1:

66 Stackelberg Model (13) Lets derive F.O.C. and S.O.C.

67 Stackelberg Model (14) This gives us:

68 Stackelberg Model (15) All this math to verify our initial intuition!

69 Observations (1) Is what weve looked at really a sequential game? Despite we said firm 1 was going to move first, theres no reason to assume shes really going to do so! What do we miss?

70 Observations (2) We need a commitment In this example, sunk cost could help in believing firm 1 will actually play first Assume firm 1 was going to invest a lot of money in building a plant to support a large production: this would be a credible commitment!

71 Observations (3) Lets make an example: assume the two firms are NBC and Murdoch trying to gain market shares for newspapers production in a city Suppose theres a board meeting where the strategy of the firms are decided What could Murdoch do to deviate from Cournot?

72 Observations (4) An example would be to be somehow dishonest and hire a spy to gain more information on NBCs strategy! To make the scenario even more intriguing, lets assume NBC knows that theres a spy in the board room – What should NBC do?

73 Simultaneous vs. Sequential There are some key ideas involved here 1.Games being simultaneous or sequential is not really about timing it is about information 2.Sometimes, more information can hurt! 3.Sometimes, more options can hurt!

74 First mover advantage Advocated by many economics books Is being the first mover always good? – Yes, sometimes: as in the Stackelberg model – Not always, as in the Rock, Paper, Scissors game – Sometimes neither being the first nor the second is good, as in the I split you choose game

75 The NIM game We have two players There are two piles of stones, A and B Each player, in turn, decides to delete some stones from whatever pile The player that remains with the last stone wins Lets play the game

76 The NIM game (2) If piles are equal second mover advantage – You want to be player 2 – Correct tactic: You want to make piles unequal If piles are unequal first mover advantage – You want to be player 1 – Correct tactic: You want to make piles equal Youll know who will win the game from the initial setup You can solve through backward induction

77 The Zermelo Theorem (1) Lets try to draw a grander lesson out of the games weve seen so far Would it be possible to state, when and if a game has a solution? In this case, would it be possible to state whether there is any advantage for players moving first or second?

78 The Zermelo Theorem (2) Consider a general 2 Player game We assume perfect information – Players know where they are in the game tree and how they got there We assume a finite game, i.e. a game-tree with a finite number of nodes There can be three or fewer outcomes: W1 (player 1 wins), L1 (player 2 wins), T (tie)

79 The Zermelo Theorem (3) The result (or solution) of this game is: – Either player 1 can force a win (over player 2) – Or player 1 can force a tie – Or player 2 can force a loss (on player 1)

80 The Zermelo Theorem (4) This theorem appears to be trivial: – Three possible outcomes – Games are subdivided in three categories: Those in which, whatever player 2 does, player 1 can win (provided he/she plays well) Those in which player 1 can always force a draw/tie Those in which, player 1 is toast, and can only loose

81 Examples of games NIM, that we played earlier Tic-tac-toe: – If players play correctly, you can always force a tie – If players make wrong moves, they can loose Checkers has a solution! – Two players – Perfect information – Finite – Three outcomes Chess has a solution! In fact, the theorem doesnt tell you how to play, it just tells you there is a solution!

82 Theorem proof (1) Were going to prove the theorem, in a sketchy way, as this is relates to backward induction Proof methodology: Induction on maximum length of a game N – Well start with an induction hypothesis – And well prove this is true for longer games

83 Theorem proof (2) If N = 1 1 W1 T T L1 1 W1 T L1 1 T 1 11

84 Theorem proof (3) Induction hypothesis: Suppose the claim is true for all games of length N We claim, therefore it will be true for games of length N+1 Lets take an example

85 Theorem proof (4) Example of a more complex game What is the maximum length of the game?

86 Theorem proof (5) We have two sub- games The upper sub- game: follows 1 and it has length 3 The lower sub- game: follows 1 and has length 2

87 Theorem proof (6) By induction hypothesis (for N=3), upper sub- game has a solution, say W1 Again, by induction hypothesis (N=2), lower sub-game has a solution, say L1 W1 L1 1 This game has a solution, it is a game of length 1 we know already!

88 A more complex example Suppose we have an array of stones, and two players Sequential moves, each player can delete some stones – Select one, delete all stones that lie above and right The looser is the person who ends up removing the last rock

89 A more complex example According to Zermelos Theorem, this game has a solution and the advantage depends on NxM, the size of the array Think hard about it, could come at the exam…

90 SOME FORMAL DEFINITIONS Sequential move games, and their interpretation

91 Definition: Perfect Information A game of perfect information is one in which at each node of the game tree, the player whose turn is to move knows which node she is at and how she got there

92 Definition: Pure Strategy A pure strategy for player i in a game of perfect information is a complete plan of actions: it specifies which action i will take at each of its decision nodes

93 Example (1) Strategies – Player 2: [l], [r] – Player 1: [U,u], [U,d] [D, u], [D,d] (1,0) (0,2) (2,4) (3,1)U D l r d Hey, they look redundant!! u

94 Example (2) Note: – In this game it appears that player 2 may never have the possibility to play her strategies – This is also true for player 1! (1,0) (0,2) (2,4) (3,1)U D l r d u

95 Example (3) Backward Induction – Start from the end d higher payoff – Summarize game r higher payoff – Summarize game D higher payoff (1,0) (0,2) (2,4) (3,1)U D l r d u BI :: {[D,d],r}

96 Example (4) 2,40,2 3,10,2 1,0 (1,0) (0,2) (2,4) (3,1)U D l r d u l r U u U d D u D d From the extensive form To the normal form

97 Example (4) 2,40,2 3,10,2 1,0 (1,0) (0,2) (2,4) (3,1)U D l r d u l r U u U d D u D d Nash Equilibrium {[D, d],r} {[D, u],r} Backward Induction {[D, d],r}

98 A Market Game (1) Assume there are two players – An incumbent monopolist (MicroSoft, MS) of O.S. – A young start-up company (SU) with a new O.S. The strategies available to SU are: Enter the market (IN) or stay out (OUT) The strategies available to MS are: Lower prices and do marketing (FIGHT) or stay put (NOT FIGHT)

99 A Market Game (2) What should you do? Analyze the game with BI Analyze the normal form equivalent and find NE (0,3) MS (1,1) IN OUT F NF SU (-1,0)

100 A Market Game (3) (0,3) MS (1,1) IN OUT F NF SU (-1,0) -1,01,1 0,3 F NF IN OUT Nash Equilibrium (IN, NF) (OUT, F) Backward Induction (IN, NF) This is a NE, but relies on an incredible threat


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