CARTELS AND TACIT COLLUSION - CREST | Center for … · 2016-06-17 · 5 Cartels and Competition...

CARTELS AND TACIT COLLUSIONAdvanced Industrial Organization 1

THIBAUD VERGÉ

CREST-LEI

ENSAE 3A / Master APE (2009-2010)

THIBAUD VERGÉ ( CREST-LEI ) Collusion Advanced IO 1 1 / 47

Introduction

Outline

1 Introduction

2 Basic Theoretical Model

3 Factors Facilitating Collusion

4 Informational issues

5 Cartels and Competition Policy


Introduction

Cartels and Competition Policy

Fighting cartels is at the core of competition policy.

Biggest European Cartel Cases2008 Car Glass 1384 me Saint-Gobain (896 me), Pilkington (370 me)2009 Gaz 1106 me E.O.N (553 me), GDF-Suez (553 me)2007 Elevators 992 me ThyssenKrupp (480 me)2001 Vitamins 790 me Hoffmann-LaRoche (462 me)2007 Switchgear 750 me Siemens (396 me)

In France2009 Temporary Work 94 me Manpower (42 me), Adecco (32 me)2008 Steel 575 me ArcelorMittal (309 me), KDI (169 me)2005 Mobiles 534 me Orange (256 me), SFR (220 me)


Introduction

What is Collusion?

Explicit or Tacit CollusionCollusion ≡ collusive agreement that should be outlawed

Collusion ≈ high prices, prices above the “competitive” level

Explicit Collusion: firms act through an organized cartel

Tacit Collusion: firms maintain high prices in a non-cooperativeway


Introduction

Reading List

MOTTA, M. (2004), Competition Policy: Theory and Practice,Cambridge (Chapter 4).

TIROLE, J. (1988), Theory of Industrial Organization, MIT Press(Chapter 6).

GREEN, E. and R. PORTER (1984), “Noncooperative CollusionUnder Imperfect Competition”, Econometrica, 52, pp. 87-100.

JULLIEN, B. and REY, P. (2007), “Resale Price Maintenance andCollusion”, Rand Journal of Economics, 38, pp. 983-1001.


Introduction

The Main Ingredients of Collusion

Prisoners’ DilemmaP2

C NC

P1C (2,2) (−1,3)

NC (3,−1) (0,0)

Unique Nash Equilibrium: No cooperation (strictly dominantstrategies), zero payoffs.

Cooperation is Pareto dominant

When is cooperation possible?


Introduction

The Main Ingredients of Collusion

Suppose the game is repeated over time

Players could agree to cooperate (and obtain higher payoffs)

However, at any stage, a player would have a strong incentive todeviate

In order for cooperation to be sustainable, the rival player needs tobe able to detect the deviation . . .

. . . and to enforce the “agreed” (credible) punishment


Basic Theoretical Model

Outline

1 Introduction






Basic Theoretical Model General Framework

(Tacit) Collusion in a General Framework

The important variables1 πC the per-firm collusive profit

2 πD the profit of the deviating firm

3 πNC the per-firm non-cooperative profit (i.e. the equilibrium payoffin the Nash-equilibrium of the static game)

4 δ the discount factor

Idea: Collusion is a SPNE ifThe short term gain of deviation is lower than the long term loss(punishment).


Basic Theoretical Model Finite Number of Repetitions

Unique Subgame Perfect Nash Equilibrium

Backward Induction: Start with the last periodLast stage⇐⇒ Static GameUnique Nash Equilibrium, without cooperation.

Penultimate PeriodLast period profits are not affected by the historyPenultimate stage⇐⇒ Static GameUnique Nash Equilibrium, without cooperation.

Unique SPNENE of the static game repeated over time. No cooperation.


Basic Theoretical Model Infinitely Repeated Game

Multiple Subgame Perfect Nash-Equilibria

General ResultThe NE of the static game is always a SPNE of the infinitelyrepeated game

No cooperation is always a SPNE.

FormallyIn an infinitely repeated game, strategies are complex

History: ht =(s1,0, s2,0; . . . ; s1,t−1, s2,t−1

)Choice at t depends on ht



Cooperation (collusion) as a SPNE?

QuestionCan collusion be an equilibrium?

Are there other equilibria?

Focus on particular equilibria with trigger strategiesIf nobody has deviated in the past, each player chooses tocooperate at date t

If somebody deviates from the collusive path at date t − 1, thenfrom t onwards players revert to the non-cooperation solution

Trigger strategies or reversal to Nash



Existence condition for a collusive equilibrium

Short-term gain (at t = 0)

Deviation: πD

Collusion: πC

Gain: πD − πC

Long Term Loss

Deviation:∑+∞

t=1 δtπNC = δ

1−δπNC

Collusion:∑+∞

t=1 δtπC = δ

1−δπC

Loss: δ1−δ

(πC − πNC)



Tradeoff Today / Future: Summary

Collusion as an equilibrium iff loss > gain

Loss: δ1−δ

(πC − πNC)

Gain: πD − πC

δ1−δ

(πC − πNC) > πD − πC ⇐⇒ δ > δ̃ ≡ πD−πC

πD−πNC

Conclusion

If firms are patient enough(δ > δ̃

)there exists a subgame perfect

Nash equilibrium (with trigger strategies) with collusion.


Basic Theoretical Model Collusion under Price Competition

Price Competition with Perfect Substitutes

Bertrand Competition between n firms

πNC = 0

πC = ΠM

n

πD = ΠM (−ε)

Discount Factor Threshold

δ̃ =ΠM − ΠM

nΠM − 0

=n − 1

n= 1− 1

n


Factors Facilitating Collusion

Outline

1 Introduction








1 Concentration2 Entry3 Cross-ownership4 Regularity and frequency of orders5 Evolution of demand6 Symmetry7 Multi-market contacts8 Excess Capacities9 Price transparency / Exchange of information

10 Antitrust enforcement11 Leniency programs


Factors Facilitating Collusion Structural Factors

Concentration and Entry

ConcentrationMany identical firms under price competition

The gains from collusion are smaller the larger the number of firms

However, non-cooperation and deviation profits do not depend on the number offirms

Collusion is easier to sustain when the number of players is smaller

EntryThe easier the entry into an industry, the more difficult to sustain collusiveprices

If the entrant behaves aggressively, the incumbent firms (cartel members) willhave to react by lowering prices

If the entrant is willing to join the cartel, then collusion is more difficult as thenumber of firms increases



Cross-ownership

Symmetric case with 2 firmsTwo identical firms competing in prices, each owning a share α ofthe rival firmπNC = 0πC = (1+α)ΠM

2

πD = ΠM + 0

Therefore: δ̃ =ΠM− (1+α)ΠM

2ΠM−0 = 1−α

2

ConclusionCollusion is easier when firms own shares of their rivals



Evolution of DemandRotemberg and Saloner, American Economic Review, 1986

Stochastic DemandAt each period, demand can be either high (dH) or low (dL)

Demand shocks are i.i.d.Equal probabilitiesWe denote by:

ΠMH and ΠM

L the corresponding monopoly (collusive) profits

ΠM =ΠM

L +ΠMH

2 the expected monopoly profit

Collusion and deviation expected profits (state s = H, L at t)

Collusion: ΠMs

2 + (δ + . . .+ δt + . . .) ΠM

2 = ΠMs

2 + δΠM

2(1−δ)

Deviation: ΠMs + (δ + . . .+ δt + . . .)0 = ΠM

s



Evolution of DemandRotemberg and Saloner, American Economic Review, 1986

Collusion is sustainable whenever:

ΠMs2

+δΠM

2(1− δ)> ΠM

s ⇐⇒δΠM

1− δ> ΠM

s ⇐⇒ δ > δ̃s ≡ΠM

s

ΠM + ΠMs

ConclusionNote that ΠM

H > ΠML ⇐⇒ δ̃H > δ̃L

Collusion is more difficult to sustain when demand is high

Short term gains are higher when demand is high

Long term (expected) losses are the same in the two states



Growing and Declining Industries

Evolving industriesDemand is certain but changes over time

Monopoly profit in period t is given by θt ΠM

ConclusionWe then have: δ̃(θ) = 1

2θ

Collusion is easier to sustain in growing industries (θ > 1) than indeclining industries (θ < 1)

At t = 0, short term gains are identical but long term losses arehigher when future demand is expected to be higher


Informational issues

Outline

1 Introduction






Informational issues Temporary Price Wars

Identifying Deviations to Sustain CollusionGreen and Porter, Econometrica, 1984

Stigler (JPE, 1964): Collusion would break down because ofsecret price cuts

Green and Porter: If actual prices are not observable, collusion ismore difficult to sustain, but could still arise in equilibrium.

With secret price cuts, a firm does not know if a low demand isdue to a price cut (deviation from the collusive path) or a negativedemand shock (on the collusive path)

Idea: trigger a price war (reversal to Nash) but for a limitednumber of periods

A period of low prices (price war) does not necessarily meanthat there is no collusion



Green and Porter, Econometrica, 1984A simplified version

n identical firms selling a homogenous product.Price competition.Uncertain demand shocks (i.i.d over time): demand can be eitherlow (D(p) = 0 for any price p) with probability α or high(D(p) > 0).Firms never observe the actual state of demand.Firms do not observe prices set by rival firms.

→ A firm facing a zero demand does not know whether it is:1 Because the demand was low.2 Because some rival(s) undercut its price.



Temporary Price Wars

Temporary Price Wars in EquilibriumEach firm sets the collusive price pm at the outset of the game.It continues to do so as long as all firms have positive demands.When at least one firm observes zero demand (which is assumedto be common knowledge), the industry enters the “punishmentphase”: each firm sets price equal to marginal costs for the next Tperiods.Collusive phases restarts at the end of the “price war”.

Some notationsV + represents the present discounted value of a firm in eachperiod which belongs to the collusive phase.V− represents the present discounted value of a firm at the startof the punishment phase.



Temporary Price Wars

Relationships between V + and V−

The following two equations holds:

V + = (1− α)

(π (pm)

n+ δV +

)+ αδV− and V− = δT V +

This yields:

V + =(1− α)

π(pm)n

1− (1− α) δ − αδT +1 and V− = δT V +

Collusion is possible as long as

V + ≥ (1− α)(π

(pm)

+ δV−)

+ αδV−

i.e. (after some computation . . .)

[δn(1− α)− (n − 1)] + δT +1 (αn − 1) ≥ 0 (1)



When is collusion feasible?

Three possible cases

1 If α < α1 ≡ 1− n−1nδ

(which may be impossible if δ is too small or n is too large),then the left term is positive while the right term is negative. There may thereforeexist a values of T that satisfy (1).

2 If α1 ≥ α < α2 ≡ 1n , both terms are negative and equation (1) never holds.

3 If α ≤ α2, the left term is negative while the right term is positive. But:

n − 1− δn(1− α) = (n − 1)(1− δ) + δ(αn − 1) > δ(αn − 1) > δT +1(αn − 1),

and thus equation (1) cannot hold.

Collusion is feasible whenever:

α < α1 and T ≤ T min ≡ (ln δ)−1 ln(δn(1− α)− (n − 1)

δ(1− αn)

)(2)



Some Conclusions

Temporary price wars may help sustaining collusion whendeviations are not easily observable.

Collusion is not feasible if the probability to be in the bad state istoo high.

The “punishment period” needs to be longer when the probabilityof the being in the bad state increases (i.e. ∂T min/∂α > 0).


Informational issues Some other informational problems

Information Exchange

Past (or Present) Prices and QuantitiesExchanging information about past (or present)

(Individual) prices and/or quantities

Aggregate demand

helps collusion.

French mobile phone cartel (e(534m) fines for Orange, SFR and BouyguesTelecom)

Future PricesPrivate (“cheap talk”) or public (credible) announcements about future prices help tosustain collusion

Airline Tariff Publishers (ATP) in the US

British Airways (fuel surcharges)

Collusion in multi-unit auctions


Informational issues Some other informational problems

Other Practices that Facilitate Collusion

Most-Favored Nation ClausesAlso called price matching clauses

Way of exchanging information through consumers)

Note that price comparison engines (Kelkoo, . . . ) or online agencies co-ownedby rivals (Expedia, Opodo, Orbitz, . . . ) can also serve the same purpose.

Resale Price MaintenanceJullien and Rey (RAND Journal of Economics, 2007)

Resale price maintenance prevents retailers from reacting to local demandshocks.

Helps to sustain collusion among producers since deviations are more easilydetected.


Informational issues Vertical Relations

Resale Price Maintenance and CollusionJullien and Rey, Rand Journal of Economics, 2007

2 differentiated producers, selling through different retailers.Price competition between retailers.

Uncertain local demand shocks (i.i.d over time and acrossproducts):

Di(pi ,pj

)= d + εi − pi + σpj , with εi ∼ U ([−∆,∆]) .

The exact terms of the contracts between a manufacturer and itsretailer is never observed by the rival manufacturer.

Retail prices are observed at the end of each period.Contracts consists of two-part tariffs (of the form Ti(q) = wiq + Ai )and (only allowed) an imposed retail price.

A new retailer at each period (⇔ myopic retailers + no long termcontracts). This implies that retailers are in essence passive.



Equilibrium of the Static Game

Timing of the stage game1 Producers make take-it-or-leave-it offers.2 Retailer Ri observes εi and chooses its retail price pi (unless RPM

is used).3 Demands and profits are realized.

Retailer Ri ’s pricing decision

pi = arg maxp (pi − wi)(

d + εi − pi + σpej

)=

d + εi + wi + pej

2=

d + wi + pej

2+εi

2= pe

i +εi

2




Retailer Ri ’s expected profit

ERi (wi) = E((

pei +

εi

2− wi

)(d + εi −

(pe

i +εi

2

)+ σpe

j

))(3)

Manufacturer Mi ’s expected profit

EMi = E(

wi

(d + εi −

(pe

i +εi

2

)+ σpe

j

))+ ERi

= E((

pei +

εi

2

)(d + εi −

(pe

i +εi

2

)+ σpe

j

))= pe

i

(d − pe

i + σpej

)︸︷︷︸

≡π(

pei ,p

ej

)+

14

E(ε2

i

)︸︷︷︸≡v(∆)= ∆2

12

= π(

pei ,p

ej

)+ v (∆) .




Equilibrium of the Static GameExpected equilibrium prices:

pei = arg maxpπ

(p,pe

j

)=

d + σpej

2=⇒ wN

1 = wN2 = 0.

“Competitive” retail prices: pN1 = pN

2 = pN ≡ d2−σ

Manufacturer’s expected profits: EMN1 = EMN

2 = Π(pN)+ v (∆).

RPM in the Static Game

If Mi imposes a retail price pi , its expected profit is only π(

pi ,pej

).

It thus looses the benefit of retail prices that adjust to localdemand shocks (i.e., looses v(∆)).RPM is never used in the static game.



Scope for Collusion

DefinitionCollusive prices:(

pM1 ,p

M2

)= arg max(p1,p2) (π (p1,p2) + π (p2,p1) + 2v (∆)) .

Recall: Π (p) = π(p,p).

Assumptions

k ≤ Π(

pN)

+ v (∆) ≤ Π(

pM)

First part: k is a per-period fixed cost paid by the manufacturers.The assumption ensures that selling is indeed profitable.Second inequality: There is scope for collusion (under RPM).



Collusion without RPM

Denote by ΠF (resp. ΠF ) the maximal (resp. minimal) averageper-period profit that can be obtained in a fully symmetricequilibrium, and by sF (resp. sF ) the corresponding strategy.

Most profitable strategy: the strategy sF is of the form “chargean expected price equal to pF as long as past retail prices belongto[pF − ∆

2 ,pF + ∆

2

], and sF otherwise.

Necessary Condition 1: Perfect Detection

maxp

π(

p,pF)− Π

(pF)≤ δ

1− δ

(Π(

pF)

+ v (∆)− ΠF

)(PD)



Collusion without RPM

Necessary Condition 2: Small DeviationsSmall deviations are less easily detected.

Indeed, if p ∈[pF −∆,pF + ∆

], the deviation may be undetected.

Therefore, the following condition must also hold for anyp ∈

[pF −∆,pF + ∆

]:

π(

p,pF)− Π

(pF)≤ δ

1− δ

∣∣p − pF∣∣

∆

(Π(

pF)

+ v (∆)− ΠF

)(SD)

Collusion without RPMMost profitable collusive equilibrium is such that pF maximizesΠ(pF)+ v(∆) subject to (PD) and (SD).



Collusion with RPM

When RPM is used on the collusive path, all deviations areautomatically detected.

Necessary and sufficient condition

maxp

π(

p,pRPM)

+ v (∆)− Π(

pRPM)≤ δ

1− δ

(Π(

pRPM)− ΠRPM

)(RPM)

Collusion with RPMMost profitable collusive equilibrium is such that pRPM maximizesΠ(pRPM) subject to (RPM).



Comparing without / with RPM

Constraints (PD) and (RPM)

maxp

π(

p,pF)

+ v(∆) +δ

1− δΠF ≤

11− δ

(Π(

pF)

+ v (∆))

(PD)

maxp

π(

p,pRPM)

+ v(∆) +δ

1− δΠRPM ≤

11− δ

Π(

pRPM)

(RPM)

RPMFacilitates collusion:

ΠRPM < ΠF , i.e., harsher punishments.Perfect detection for all deviations (no equivalent to (SD)).

But yields lower expected profits for identical average prices:additional term v(∆) in (PD).



Welfare Effect and Conclusions

There exist values of the parameters (especially forintermediate values of the discount factor), for which RPM wouldbe used by firms to facilitate collusion.

Retail prices are then higher on average.

But they no longer react to local shocks.

With retail cost shocks, rigid prices are bad for consumers and totalwelfare.But for local demand shocks, consumers prefer rigid prices.

Overall, ambiguous effect with local demand shocks. But, inthe linear demand example, RPM can only be bad for welfareif σ ≤ 2

3 .


Cartels and Competition Policy

Outline

1 Introduction






Cartels and Competition Policy Detecting Collusion

Detecting Collusion

Need for hard evidence (minutes, memo, . . . )

What is a collusive price?

Uncertainty about price or demand

Problems using historical price data (i.e. price evolution)

“Price parallelism” can be explained by common shocksUnless “extreme parallelism” (e.g. Dyestuffs)

Facilitating practices can only be stopped but not used to findfirms guilty

Tacit (rk: requires coordination) or explicit collusion?


Cartels and Competition Policy Deterring Collusion

Deterring Collusion (Ex ante policies)

Heavy punishment when detectedExpected fines (fine x probability of audit), damages to “injured”parties, prison sentences

Black list of facilitating practices

Exchange of information about individual prices and/or quantitiesBest price clausesMinority shareholdings. . .

Auction design


Cartels and Competition Policy Leniency Programs

Leniency programs

As used against organized crime in order to obtain hard evidence

Leniency ≡ immunity from fines and/or prisonBreaking trust within the cartel (preventing cartel formation but alsodetecting cartel more easily)Saving resources for antitrust authorities

Ambiguous theoretical effects on deterrenceReduces the gains from collusionReinforces the possibility of punishment

Optimal leniency programs

See Spagnolo (mimeo, 2000), Motta and Polo (IJIO, 2003), . . .Automatic full immunity (from fines but also damages, possibly evenrewards) even after an investigation has started



Leniency programs in the U.S.

First introduced in 1978 but redesigned in 1993

Automatic immunity from fines and prison sentences

Provide hard evidence before an investigation has begunFirst arrived only and conditional on leaving the cartel

Discretionary leniency for evidence provided once theinvestigation has been launched

Number of applicants rose from 1 a year to 2 a month



Leniency program in the EU

First introduced in 1996 (inefficient) but redesigned in 2002

Complete immunity from finesProvide hard evidence even after investigation has begunFirst arrived only but discretionary partial immunity for second andthird arrived if it helps convict firmsNot for the ring-leader

Recent case (November 2006): Producers and traders ofsynthetic rubber fined a total of e519m

Bayer applied for leniency in December 2002 (was granted fullimmunity from a e204m fine)Once the investigation had started, Dow applied for leniency (wasgranted partial immunity - 40% - from a e107m fine)Eni (e272m), Shell (e160m), Unipetrol (e17.6m) and Trade-Stomil(e3.8m) were also involved


CARTELS AND TACIT COLLUSION - CREST | Center for … · 2016-06-17 · 5 Cartels and Competition...

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Transcript of CARTELS AND TACIT COLLUSION - CREST | Center for … · 2016-06-17 · 5 Cartels and Competition...