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Dynamic Games of Complete Information

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Title: Dynamic Games of Complete Information


1
Dynamic Games of Complete Information
  • .

2
Extensive form games
  • To model games with a dynamic structure
  • Main issues with a dynamic structure
  • 1. Information structure who knows what and
    when?
  • 2. Credibility
  • 3. Commitment
  • 4. The idea of Backward Induction

3
The Stackelberg game
  • A dynamic version of the Cournot game
  • Player 1, Stackelberg leader chooses output q1
    first
  • Player 2, Stackelberg follower chooses output
    q2 next
  • Demand is linear p(q)12-q
  • Player is utility is ui(q1 , q2 )12- (q1
    q2)qi
  • What is the Stackelberg equilibrium?
  • Are there other Nash equilibria?

4
Model of strategic investment
  • Firms 1, 2 have average cost of 2 per unit
  • Firm 1 can install new technology at cost f. Then
    average cost is zero
  • Firm 2 can observe firm 1s investment
  • The two firms then move simultaneously to set
    quantity. Demand is p(q)14-q
  • How should firm 1 forecast its rivals output?
  • Backward induction not directly applicable. Why?

5
The Extensive form
  • Building blocks of the extensive form game
  • 1. The set of players
  • 2. The order of moves - i.e. who moves when
  • 3. The players payoffs as a function of moves
  • 4. What the players choices are when they move
  • 5. What a player knows when making his choice
  • 6. Probability distribution over any exogenous
    events

6
Extensive form trees
  • Rules for forming trees
  • 1. Single starting point
  • 2. No cycles
  • 3. One way to proceed
  • Define precedence relation a b a precedes
    b
  • 1. is asymmetric a b, means b a
  • 2. is transitive
  • 3. x/ x and x// x implies x/ x//
    or x// x/
  • 4. There is single initial node

7
Formalizing the extensive form
  • 1. Let i ?I be the finite set of players
  • 2. Let i(x) bet set of players that move at node
    x
  • 3. Let Z be set of terminal nodes. Maps uiZ?R
    with values ui(z) are is payoffs to a sequence
    of moves z
  • 4. Let A(x) be set of feasible actions at node x
  • 5. Information Sets h partition nodes of the
    tree
  • a. Each node x is in only one information set
    h(x)
  • b. If x/?h(x), then player moving at x does not
    know if he is at x or x/
  • c. If x/?h(x), then the same player moves at x
    x/
  • d. If x/?h(x), then A(x) A(x/). Thus A(h) is
    action set at information set h

8
Example
  • Two people want to go to a Broadway musical in
    great demand
  • There is exactly one ticket left, and whoever
    arrives first gets it
  • There are three transportation choices c(cab)
    b(bus) s(subway)
  • Player 1 leaves home a little earlier
  • A cab is faster than the subway, which is faster
    than a bus

9
Strategies equilibria in extensive form
  • Let Hi be set of player is information sets
  • Let be the set of all actions for i
  • A pure strategy for i is a map si Hi ? Ai , with
  • si(hi) ? A(hi) for all hi ? Hi
  • The set of pure strategies for i is Si
  • The number of is pure strategies is given by the
    product
  • Mixed strategies in extensive form are called
    behavior strategies. Let ?(A(hi)) be prob dist on
    A(hi)
  • A behavior strategy for i, denoted bi, is an
    element of Cartesian product

10
Strategic-form versus extensive-form
  • Using its pure strategies and payoffs, an
    extensive form can be transformed to strategic
    form
  • Extensive form interpretation player i waits
    until hi is reached before deciding how to play
    there
  • Strategic form interpretation player i makes a
    complete contingent plan in advance
  • Games of perfect information with all singleton
    information sets constitute a special class
  • Any mixed strategy si (strat form) generates a
    behavior strategy bi (ext form), but many
    different sis can generate the same bi
  • Theorem (Kuhn 1953)
  • In a game of perfect recall, mixed and behavior
    strategies are equivalent

11
Backward induction Subgame perfection
  • Theorem (Zermelo 1913 Kuhn 1953)
  • A finite game of perfect information has a pure
    strategy Nash equilibrium
  • Subgame perfection is the analog of backward
    induction for multi-player situations
  • G is a proper subgame of an extensive form game T
    if it
  • 1. Starts at a single node x of T
  • 2. Contains all successors of x
  • 3. If x/? G, and x//? h(x/), then x//? G
  • A behavior strategy s of an extensive form game
    is a subgame perfect equilibrium if the
    restriction of s to G is a Nash equilibrium of G
    for every proper subgame G

12
Multi-stage games with observed actions
  • 1. There are k stages 0, 1, , k-1
  • 2. All players know the actions chosen at all
    previous stages
  • 3. All players move simultaneously in each stage
  • 4. This includes games where players move
    alternately (all other players have strategy do
    nothing)

13
Multi-stage games with observed actions
  • Let a0 be the stage-0 action-profile
  • At the beginning of stage1, players know history
    h1 which is just a0
  • Let Ai(h1) be player is action set at stage 1
    with history h1
  • hk1 is history at end of stage k, hk1(a0,
    a1, ak), and Ai(hk1) is player is action set
    at stage k1
  • If game is K stages, HK is set of all terminal
    histories
  • A pure strategy for i is seq. of maps such that
  • where

14
Multi-stage games with observed actions
  • Payoffs are defined on terminal histories,
  • ui Hk1?R
  • In most applications, payoffs are additively
    separable over stages. This isnt necessary
  • The game from stage k on with history hk is a
    proper subgame G(hk), and a strategy profile s
    for whole game induces sihk for subgame G(hk)
  • A Nash equilibrium s satisfies the familiar
    condition
  • ui(si , s-i) ui(s/i , s-i) for all s/i
  • A Nash equilibrium s is subgame perfect if sihk
    is a Nash equilibrium for every subgame G(hk)

15
Principle of optimality and subgame perfection
  • For multi-stage games with observed actions, we
    have a useful characterization of subgame
    perfection for the finite-horizon case
  • Theorem (One-stage-deviation principle)
  • A strategy profile s is subgame perfect iff no
    player i can gain by deviating from s in a
    single stage and conforming to s thereafter
  • This theorem can be extended to the infinite
    horizon case

16
Rubinstein Bargaining model
  • Two players have to share a pie of size 1
  • The game
  • Step1 In periods 0, 2, 4,, player 1 proposes a
    split (x, 1-x)
  • Step 2 If player 2 accepts in period 2k, game
    ends. If he rejects, he proposes (x, 1-x) in
    period 2k1
  • Step 3 If player 1 accepts, game ends. Else,
    Step 1
  • Discount factors are d1, d2, and if split (x,
    1-x) is accepted at time t payoffs are (dt1x,
    dt2(1-x))
  • This is an infinite-horizon game of perfect info

17
Subgame perfect equilibrium
  • A continuation payoff of a strategy profile in
    subgame starting at t is utility in time-t units
    of outcome induced by that profile
  • Let , be player 1a lowest and highest
    continuation payoffs in any subgame that begins
    with player 1 making an offer
  • Let , be player 1a lowest and highest
    continuation payoffs in any subgame that begins
    with player 2 making an offer
  • Similarly define for player 2

18
Subgame perfect equilibrium
  • When I makes offer, 2 will accept if he gets more
    than d2 . Hence, . Also, by symmetry,
  • Suppose player 1 makes offer (x, 1-x). If 2
    accepts, the min he can get is , and
    therefore, 1-x . Thus, x1- . This
    implies that, ,
  • Again, by symmetry,

19
Subgame perfect equilibrium
  • Now, , so,
  • Similarly, , which gives,
  • But, , and thus,
  • Proceeding similarly,
  • What is the effect of patience?
  • As d1?1, for fixed d2, we have v1?1, and player
    1 gets entire pie.

20
A model of RD race
  • Firms R and S are conducting RD
  • Several stages need to be completed
  • Simplifying assumptions
  • 1. Distance from goal can be measured. E.g. firm
    S is n-steps away from completion
  • 2. Either firm can move 1, 2, or 3 steps
  • 3. It costs 2/7/15 to move 1/2/3 steps
  • 4. Firm completing all the steps first gets
    patent worth 20
  • What would happen if R-S were a cartel,
    maximizing joint profits?
  • - Since only one firm gets patent, only it does
    RD
  • - Chosen firm moves 1-step at a time, and firm
    closer to finishing is chosen

21
The extensive form of RD game
  • Suppose the firms take turns deciding on RD
    investment becomes a game of perfect info
  • Converting to extensive-form
  • 1. Transform to location-space picture
  • 2. Let (r, s) be coordinates of R and S , with r
    depicting how far R is from finishing

22
Subgame perfect equilibrium of RD game
  • If S is in Rs safety zone- whatever the zone
    number -it should drop out of the race
  • Firm S in its own safety zone spends the minimum
    amount on RD, moves one step at a time and wins
    the patent
  • In Trigger zone n, each firm spends what it needs
    to- profitably -to get an advantage and move the
    game to its safety zone n-1

23
David vs Goliath in Entry Decisions
  • Suppose Goliath has 700 and David has 300
  • They are gambling types, and prefer roulette
  • Whoever ends up with more money after the next
    round will win ultimately
  • Suppose David moves first and makes the safest
    bet
  • He can never win ?

24
David vs Goliath in Entry Decisions
  • He should take one of the more risky gambles
  • Bets 300 that the ball would land on a multiple
    of 3 wins 900 w.p. 12/37
  • What is Goliaths best response?
  • To exactly imitate Davids bet !
  • Again, David can never win ?
  • Is there any hope for David?

25
David vs Goliath in Entry Decisions
  • David should have gone second and differentiated
    himself
  • This situation is parallel to new product launch
    decisions when a firm with shallow pockets
    competes against a firm with deep pockets
  • If going second is not feasible, then entrant
    should take riskier bets like launching a
    product with some chance of failing!!

26
Patent races
  • When is there competition or monopoly?
  • Depends on possibility of preemption and
    leapfrogging
  • Not about chance of winning, but about chance of
    being favorite
  • Consider two firms i1,2, and let value of patent
    be V
  • Productivity of RD increases over time
  • Let ?i(t) be firm is total experience at time t
  • µ(?i(t)) is firm is hazard rate at t. Let
    µi(t)µ(?i(t))
  • Discovery probability is an exponential waiting
    time
  • Note, discovery is stochastic and firm 2 (enters
    t2gt0) could discover before firm 1 (enters t1 0)

27
Assumptions and preliminaries
  • Cost is c and common discount rate is r
  • Probability that no firm makes discovery before
    time t is
  • Expected value of patent race for firm i is
  • RD is viable for monopoly,
  • It is unprofitable for both firms to always do
    RD
  • State of competition is pair of experiences

28
Model without leapfrogging
  • Result 1 (?-preemption) In the unique subgame
    perfect equilibrium, whatever t2, firm 1 engages
    in RD and firm 2 drops out of the race.
  • Sketch of proof
  • i. Let O(?) be firm 1s experience such that it
    has zero payoff when firm 2 has experience ?, and
    both firms do RD
  • ii. Show that a firm does RD until discovery or
    drops out immediately
  • a) Suppose not. Let initial state be and
    both firms do RD till time t and firm 1 drops
    out at t with zero profits
  • b) Then and
  • c) Firm 1s expected profit at is

29
Sketch of proof of Result 1 (contd.)
  • d) Since for st,
    implies so firm 1 would not join
    patent race a contradiction
  • iii. The strategy If ?i ?j, firm i stays in
    and j drops out iff
  • ?j O(?i), is subgame perfect
  • iv. Suppose there exists t such that,
    conditional on neither having dropped out at t,
    firm 1 drops out with some prob.
  • v. Let be the supremum of such times for
    firm 1. for firm 2
  • vi. Claim
  • vii. Claim Firm 2 drops out with probability 1
    at time
  • viii. Then, firm 1 will not drop out at time
    -? for small ?
  • ix. Proceeding similarly, firm 1 never drops out
  • x. Then, firm 2 never does RD

30
Model with leapfrogging
  • There are 2 stages preliminary and final stages
  • Costs are c1 and c2
  • Time-t experience for firm i in stage j is
    ?ji(t)
  • Probability of making 1st, 2nd stage discovery at
    time t if it has not been made before are µi(t),
    ?
  • Cannot accumulate 2nd stage experience without
    making 1st stage discovery
  • Payoff for 2nd stage monopolist,
  • (?V-c2)/(r ?), and for a 2nd stage duopolist
    is
  • W2 (?V-c2)/(r 2?),

31
Model with leapfrogging
  • Result 2 There exists a SPNE where the leading
    firm always does RD unless the rival does RD
    and completes the 1st stage before . The
    follower either, (i) drops out at the start, (ii)
    does RD until , or (iii) always does RD
    unless the leader passes the 1st stage before (
    t2)

32
Model with leapfrogging
  • Sketch of proof of Result 2
  • i. There are 2 decision points one firm has
    finished 1st stage, or both are in 1st stage
  • ii. Let be level of 1st stage experience
    such that a firm with experience less (greater)
    than will drop out (stay in) even if the
    rival has completed stage 1. It is defined by
  • iii a. If 2 has completed stage 1, firm 1 should
    stay in if t
  • b. If 1 has completed stage 1, firm 2 should
    stay in if t-t2

33
Model with leapfrogging
  • Sketch of proof of Result 2
  • iv. Suppose neither has made 1st stage discovery
    at time
  • v. Firm 1 will hit experience level before
    firm 2. After that it will stay in.
  • vi. Can 2 do RD profitably when both stay in
    forever? If yes, both do RD unless firm 1
    passes stage 1 before
  • t2 . Else, the subgame from onwards
    resembles the no-leapfrogging situation. From
    result 1, 2 will drop at
  • vii. Consider race before time .
    Straightforward extension of arguments in Result
    1 show that
  • - there is ?-preemption and 2 quits at t0
  • - firm 2 does RD till t t2
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