Managerial Economics
Economics of Strategy
and Games
Economics of Strategy
Patrick McNutt
www.patrickmcnutt.com
Abridged ©
What is game theory?
• Observed behaviour in a game dimension. G
• Identify the players in the game and the
players type
• Finding the patterns in rival behaviour
• Updating belief systems.
• Independent decision making v
interdependence; one-shot v repeated play
Game Embedded Strategy and
Strategic Analysis
• Knowledge of the
identity of near rival:
Actionyou -> Reactionrival
-> NashReplyyou
Why the focus?At the frontier
of economic analysis…..
• Understand management as ‘they are’ not as theory hitherto
‘assumed them’ to be
• Management can be ranked (by type) and are faced with
indifference trade-offs => something must come ‘top of the
menu’: the 3rd variable or z. Trade off (x, y) to max z.
• Firms are conduits of information flows (vertical chain)
• Supply chain capacity constraints and technology-lag
• Reducing price does not necessarily lead to an increase in
revenues (elasticity)
• Prices are primarily signals (observed behaviour)
• Companies understand the competitive threat as
(recognised) interdependence (zero-sum and entropy)
Workshop Lesson plan….
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Plan is to follow Besanko’s Economics of Strategy 6th Edition
Day 1 : Revision of Chapters 3 and 4 (Agency and Co-ordination)
and Introduce Chapter 2 (Economies of Scale and Scope)
Day 1 Workshop Study Groups & Case Analysis
Break-out Sessions at 330-530pm Day 1 and Day 2 with group
Presentation Day 3 at 2pm start
Day 2 & 3: Focus on Besanko Part II: Chapters 5,6,7 and 8 and link
into Units 3 and 4
Day 1: Introduction and setting the scene using McNutt’s Game
Embedded Strategy Chapters 1 and 2
Workshop Focus
• Management type and relevance of TCE: Unit 1.
Besanko Ch 3 & 4 and 5, McNutt Ch 1
• Cost leadership and economics of capacity: Unit 2.
Besanko Ch 2 and McNutt Ch 5
• Market-as-a-game…market structure, oligopoly,
and dynamic games…Units 3 and 4. Besanko Ch
5,6,7 and 8 and McNutt Ch 6,7,8 and 9
• Real Time case Analysis…go to Page 45 of colourcoded Storybook
The competitive threat!
• Traditional Analysis is biased
towards answering this question for
Company X:
what market are we in and how can we
do better?
• Economics of strategy (GEMS) asks:
what market should we be in?
•
Co-ordination
Coase asked in ‘ The Nature of Firms’ in 1937:
Why are not all
economic
transactions
coordinated by
markets?
•
•
•
When transaction costs are
too high, exchange to be
coordinated by
organisations
Transaction costs: costs of negotiating, monitoring and enforcing contracts.
Behavioural assumptions: bounded rationality & opportunism.
The relative cost of organising transaction through different forms of governance
determined by:
• Extent to which complete contracts are possible. Where contract refers to
agreement between two parties which could be explicit or not.
• Extent to which there is a threat of opportunism by parties in the transaction.
• Degree of asset specificity in the transaction.
• Frequency with which the transaction is repeated.
Storybook p.12
Companies as Players in a
Market-as-a-game?
• Principal-agent relationship
• Shareholders as principals and
management as agents
• Who are decision makers?
Management ≈ firms ≈ companies
=
PLAYERS (key decision makers)
Costs of not being a Player
• Agency costs can accrue..across the shareholders (esp
institutional)..changing CEOs
• Bounded rationality and opportunity costs with trade-offs
• Make or Buy dilemma
• First Mover Advantage (FMA) v Second Mover Advantage
(SMA)
• Play to win v Play not to lose!
• Follower status ‘behind the curve’
• Technology lag and failure to differentiate ‘fast enough’ to
sustain a competitive advantage
Bridging Unit 1 and Unit 3:
Game analysis
• Binary reaction;
Will Player B
react? Yes or No?
• If YES, decision
may be parked
• If NO, decision
proceeds on error
• Surprise
• Non-binary
reaction: Player B
will react.
Probability = x%
• Decision taking on
conjecture of likely
reaction
• No Surprise
Lets’ begin! Unit 1: Why the
emphasis on behaviour (of
players)?
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•
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The Firm as a ‘nexus of contracts’
Vertical chains and agency costs
Shareholders and management-as-agent
Make-buy dilemma and incomplete
contracting
• Type of management and Bounded
rationality
Management Models
• Understand Penrose effect
• Understand Bounded Rationality
• Go to Table 1.2 pp14 McNutt Game
Embedded Strategy
Compare with Next Slide where you
add in Williamson/TCE
Behavioural
Baumol
Marris
Williamson
Objective
Multiple goals
TR:Sales
Growth:gd
Managerial Utility or Value
Approach
Satisficing –
subject to Profit
Constraint
Maximisation–
subject to
Profit
Constraint
Maximisation
- subject to
Security
Constraint
Maximisation - subject to Profit
Constraint
Principal
Agent Issue
Yes
Yes
Yes
Yes
Short
v
Long Term
Varies
Short and also
dynamic
Long
Short
Reaction &
Interaction
Yes
Partial
Partial
Partial
Decision
Making
Coalitions
Yes
Management
and zero-sum
Relevance of
shareholders
Yes,..TCE
Baumol strategy or
Maximising Market Share:
MMS
• Recognise zero sum constaint and entropy
(redistribution within market shares)
• Market Shares (before): 40+30+20+10
• Zero-sum (after): 30+40+20+10
• Entropy (after): 30+35+25+10
• Iff {∆qi/∆Q} > 0 market exhibits nonprice competition:
• Check {∆qNOKIA/∆QSmartphones} < 0
Total Cost
£
Total Revenue
Min Profit Constraint
Output
Sales driven beyond the point
of max profit but within the
minimum profit constraint
Profit/Loss
Precis on a Marris model…
• McNutt Ch 4: Understand balanced
equation gc = gd to identify parameters of
profitability
• Supply of capital: debt v equity
• Demand for capital: R&D exp v dividends
• Instrumental variables influencing growth
– visit Diageo case in Kaelo v2.0
• KFIs: profits/output and output/capital
• Tobins q and Marris v ratio
U1
U2
U3
U4
Valuation ratio
V1
Shareholders perference
x
Best to management
y
V2
Valuation curve
V(min)
0
G1
G2
Growth rate
Marris equations/dividends
paradox
• Calculating share price by DCF formula
• P = eps/r : Static firm no growth opportunities
• P = eps/r + PV(GO): Dynamic firm with growth
opportunities…this is a Marris firm
• Common denominator is the plough-back ratio (PBR) = 1 –
divs/eps…This is a Marris equation
• More dividends can signal an absence of R&D growth
• But more R&D from G1 to G2 can accrue an agency cost as
Bayesian shareholders SELL as value falls V1 to V2.
Unit 2: Cost leadership [CL]
as a type (of player)
• Profitabiltiy v scale and (size and scope)
• Production as a Cost-volume constraint
• Understanding the economcis of
productivity as exemplar for incentives
• Normalisation equation
• Sources of Cost Efficiency [next slide]
• Cost leadership checklist..McNutt p61
Sources of cost efficiency
• Measure of the level of resources needed to
create given level of value
Capacity utilisation
How much to produce given capital size?
Other
Economies of scale
X-inefficiencies, location, timing, external
environment, organisation discretionary policies
How big should the scale of the operation be?
Transaction costs
Production-cost
relationship
Economies of scope
Which are the vertical boundaries of the firm?
What product varieties to produce?
Learning and experience
factors
How long to produce for?
MES Point: Production - demand - production
to attain cost leadership
£
SAC1
SAC
2
Lower per unit
cost for more units sold
SAC
3
LAC
Av.Cost = marginal cost
0,0
q1
qt
Current plan of plant
closures to lower cost
base not completed
q
2
Q
Why? Capacity Constraints:
• Case A: Unexhausted economies of scale due to
product differentiation
• Case B: Firm-as-a-player does not produce large
enough output to reach MES
• Case C: Firm-as-a-player restraints production
(deliberate intent)..McNutt’s dilemma as
production drives demand…(Veblen monopoly type)
• Convergence of technology increases the firmspecific risk of Case C:
• Strategic Choice A or B or C?
Bridge Unit 1 and Unit 2
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Shareholder as principals expect max value
Management to minimise the agency costs
Positive Learning Transfer, PLT
Nomenclature on type: Baumol type (signal
= price), Marris type (signal = dividends).
• Cost leadership type (link into Besanko Ch
11 & 13 on strategic cost advantage)
Unit 3: Game type and
signalling
• Decisions are interpreted as signals
• Observed patterns and Critical Time
Line.see Nissan example pp20 in McNutt
• Recognition of market interdependence
(zero-sum and entropy)
• Price as a signal v Baumol model of TR max
• Scale and size: cost leadership
• Dividends as signals in a Marris model
Oligopoly and Game Theory
T3 + GEMS
•
•
Study of strategic interactions: how firms adopt alternative strategies
by taking into account rival behaviour
Structured and logical method of considering strategic situations. It
makes possible breaking down a competitive situation into its key
elements and analysing the dynamics between the players.
•
Key elements:
• Players. Company or manager.
• Strategies.
• Payoffs
•
Equilibrium. Every player plays her best strategy given the strategies
of the other players.
Objective. To explore oligopolistic industries from a game embedded
strategy (GEMS) perspective.
The use of T3 framework, which considers 3 key dimensions (Type,
Technology & Time), will allow oligopolists to better predict the likely
strategic response of competitors when analysing competition from
game embedded strategy perspective.
•
•
Describe (prices as
signals) game dimension
• Players and type of players
• Prices interpreted as signals
• Understand (price) elasticity of demand and
cross-price elasticity
• Patterns of observed behaviour
• Leader-follower as knowledge
• Accommodation v entry deterrence
• Reaction, signalling and ‘best you can do, given
reaction of competitor’
Link Units 3 and 4: Game
Dimension
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What is a game – loss of independence?
Nash premise: Action, Reaction and Reply
Non-cooperative sequential (dynamic) games
Introduce oligopoly and players (companies) n < 5
TR Test and Elasticity McNutt pp36
Single shot price reduction: (i) fail TR test and
revenues fall; (ii) near rival misreads the price as
a signal.
• Limit price [to avoid entry] and predatory pricing
to force exit.
Type of Players
• Incumbent type v entrant type
• Dominant type v predatory incumbent
• De novo entrant type and geography of the
market
• Potential entrant type and the threat of
entry as a credible threat
• Contestable markets, newborn players and
extant (incumbent) type
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Entry Deterrent Strategy &
Barriers to entry
Reputation of the incumbents
Capacity building
Entry function of the entrant
De novo and entry at time period t
Potential entrant - forces reaction at
time period t from incumbent
Coogans bluff strategy (classic poker
strategy) and enter the game.
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•
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Limit Pricing Model in Besanko
pp207-211 and McNutt pp71-76
Outline the game dimension: dominant
incumbents v camouflaged entrant
type
Define strategy set for incumbents
Allow entry and define the
equilibrium
Preference - entry deterrent
strategy v accommodation [next
slide]
0,10
Do Not Enter
1
Agressive
-7,2
Enter
2
Accommodating
5,8
Continuing with Unit 4:
Define a price war
• Determine the Bertrand reaction function:
• Besanko Fig 5.3 pp190
• Compute a Critical Time Line (CTL)from
observed signals..Examples of CTL in
McNutt pp 20 Figure 2.1 and pp94 Fig
7.4
• Find a price point of intersection
• Case Analysis of Sony v Microsoft at
McNutt pp 114-116 and also in Kaelo v2.0
Nash Equilibria
• Define the Nash equilibria [next slide]
• Analyse the Payoff matrix
(B,Y) > (A, X)
• Commitment and chat: one-shot and
repeated play
• Punishment ‘grim’ strategy
• Strategic ToolBox in terms of credible
mechanisms
Player 2
Strategy A
Strategy X
Strategy Y
0,0
8,-5
-5,8
10,10
Player 1
Strategy B
Prisoners’ Dilemma
Player 2
Don’t Confess
Confess
Player 1
Confess
8
Don’t confess
20
8
0
0
20
3
3
•Would outcome change if the game is repeated?
• Apply Prisoners’ Dilemma to Pricing Policy: Independent v Interdependent
Firm 2
Firm 1
High Price
Low Price
High Price
8
8
0
20
Low Price
20
0
3
3
Visit Kaelo v2.0 and
Games/Signalling
• Example: Critical Time Line in Sony v
Microsoft in Kaelo v2.0, Apple v Nokia
game dimension McNutt pp92
• Play a PD game and investment game in
Kaelo v2.0
• Selfish gene [one-shot], dominant strategy
to cheat.
• Altruism, fairness – repeated
play/learning.
• Understand the ‘no signalling’ payoff
matrices [next slide]
The ‘no signalling’
payoffs
•
Simultaneous game between A & B who must decide on how to spend the evening
.
B
A
•
•
•
in
out
in
10,5
2,4
out
0,1
4,8
Problem of coordination where players have different preferences but common interest in
coordinating strategies.
One key application includes the battles for standards:
• VHS by JVC vs Betamax by Sony in the 1980s
• BlueRay DVD by Sony vs HD DVD by Toshiba in 2008
Effect of sequentialisation? Solution. Commitment? Signalling?
Application of ‘no
signalling’ game
• Two pharmaceutical companies must
simultaneously decide which products to
research.
A
O
A
-2,-2
20,10
O
10,20
-1,-1
• Does this example illustrate the concept of
‘first mover advantage[FMA]?
• How could companies signal? Signing contracts
with leading universities, hiring expert.
Games as Strategy:
Strategic ToolBox
• Segmentation strategy to obtain FMA
• Relevance of chain-store paradox
• Dark Strategy and 3 Mistakes in McNutt
pp95-97
• Second Mover Advantage, SMA v FMA
• Strategic ToolBox in terms of identifying
the competitive threat v cartel
coordination on (High. High)..Cheating
Player 2
Low Prices
Low Prices
High Prices
2,2
13,0
0,13
10,10
Player 1
High Prices
Absence of price wars?
Link into the HBR articles
• Hypothesis: Bertrand Price Wars occur
due to a mis-match in price signals.
• Mismatch can occur due to (i) declining
volumes ∆qi/∆Q < 0; (ii) uncompetitive
cost structure; (iii) decreasing
productivity; (iv) management type
(predator); (v) calling-my-bluff
Locate Your Company’S
game dimension
Scenario A?
Scenario B?
Scenario C?
GEMS & T3 Framework pp130-132 in McNutt
Final Scenarios for YOUR
Company……
• The Rationale
• The Strategy
Markets evolve
Non-binary
• The Rationale
• The Strategy
Type, Technology and
Game metrics,
Time
feedback &
analytics
• The Rationale
Know your near-rival • The Strategy
GEMS
Thank you for
participating………
Sapere aude
‘That which one can know, one
should dare to know’