Cartel Detection

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On the Use of Economic Analysis in Cartel Detection

byPatrick Rey1

A. Introduction

In principle, various economic approaches are available to detect cartels. For example,

following the structure-conduct-performance paradigm, astructuralapproach could seek to

identify the industry characteristics that make the industry prone to collusion; a conduct

approach could look at behavioural patterns that are more likely to be associated with

collusion than with competition; and a performance approach could, for example, look for

supra-competitive profitability. These approaches can be useful, particularly in contexts, such

as merger control, where the spotlight is already placed on a given industry and competition

agencies must figure out whether collusion is likely to be there. However, these methods are

costly to adopt in a routine way to detect collusion, in the absence of warnings already

attracting attention to a particular case. Moreover, at this stage, these approaches do not

provide robust, clear-cut answers. Overall, while further theoretical and empirical research is

probably warranted in this area, it is still difficult to use these approaches in a systematic way.

Yet economic analysis can also be used in a different way. By nature, cartels cannot

depend on binding, legally enforceable contracts; they must therefore rely on some form of

self-enforcement. This can make cartels fragile, and economic analysis can help to identify

the critical factors that may exacerbate this fragility and induce cartel participants to comeforward and report their activity. To put it another way, playing firms against each other

might make it possible to move from a police patrol to a fire alarm mode of operation, to

use the terminology of McCubbins and Schwartz:2 rather than sending out police patrols in

the street and looking for evidence of trouble, it may be better to try to induce those engaged

in illegal activity at least some of them to denounce it. This approach can also contribute

to deterring the formation of new cartels.

This paper is organized as follows. First, I briefly review the structural factors that

may facilitate collusion, which may be used to identify candidates for further investigation.

Then, I discuss the factual evidence that might be further indicative of collusion, before

presenting some of the conclusions from recent developments in the economics literature on

leniency and whistleblowing programmes.

1

Professor of economics, University of Toulouse, Ecole Polytechnique and Institut Universitaire de France.2 See McCubbins M. and Schwartz T. (1984): Congressional Oversight Overlooked: Police Patrols vs FireAlarms, 28American Journal of Political Science165.

EUI-RSCAS/EU Competition 2006 Proceedings

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B. Structural factors3

The economic literature on collusion4 has identified several factors that may facilitate

collusion.

First, there are some basicstructural variables,5such as:- Low number of competitors: the larger the number of parties involved, the more

difficult coordination becomes;6and as the number of firms increases, each firm gets a

smaller share of the pie generated by collusion, which makes deviation more tempting

(short-run gains from deviation increase, while the long-run benefit of maintained

collusion is reduced).7

- High entry barriers: in the absence of entry barriers, any attempt to maintain supra-

competitive prices would trigger market entry (e.g., short-term or hit-and-run entry

strategies), and this would erode the profitability of collusion;8moreover, the prospect

of future entry tends to reduce the scope for retaliation.

- Frequent interaction between the firms: firms can more easily sustain collusion when

they interact more frequently, since they can then react more quickly to deviations.- Market transparency: quick retaliation when one firm undercuts the others requires

such deviation to be identified by the other participants; as a result, collusion is more

difficult to sustain when individual behaviour is not readily observable and cannot

easily be inferred from available market data.9

3This discussion borrows from the IDEI report for DG Comp, The economics of tacit collusion, available athttp://ec.europa.eu/comm/competition/mergers/review/the_economics_of_tacit_collusion_en.pdf. For a general

overview of the economics literature on collusion, see Motta M. (2004): Competition Policy: Theory andPractice, Cambridge University Press.4

The economic literature focuses mainly on tacit collusion, which, in contrast to typical unlawful cartels, lacksexplicit coordination mechanisms or information exchanges. However, explicit cartels and tacit collusion sharemany common features, since in both cases firms must have proper incentives to implement the collusiveagreement. Therefore, the insights of the literature on tacit collusion, which rely on the analysis of self-

enforcement, apply as well to explicit collusion.5While the literature often relies on conceptual analyses, there are also some empirical studies on tacit collusion,

following the initial work of Posner R. (1970): A Statistical Study of Antitrust Enforcement, 13 Journal ofLaw and Economics 365, and of Hay G. and Kelley D. (1974): An Empirical Survey of Price FixingConspiracies, 17Journal of Law and Economics13. These studies are surveyed by Levenstein M. and SuslowV. (2004): What Determines Cartel Success?, Working Paper, University of Michigan, who emphasize their

disparity. However, they provide support for the importance of some of the structural factors discussed here(such as the number of firms, entry barriers, and market stability). Symeonidis G. (In Which Industries Is

Collusion More Likely? Evidence from the UK, 51Journal of Industrial Economics45 (2003)) uses a natural

experiment (the adoption of the 1956 Restrictive Trade Practices Act) to identify the industries subject to price-fixing agreements in the 1950s. His analysis suggests that collusion is more likely the higher the degree ofcapital intensity, and that it is less likely in advertising-intensive industries than in low-advertising industries. He

also finds a non-monotonic relationship between market growth and the likelihood of collusion (moderategrowth makes collusion more likely, while rapid growth makes it less likely). However, he finds no clear link

between concentration and the incidence of collusion.6 See for example Compte O. and Jehiel P. (2002): Multi-Party Negotiations, mimeo, CERAS.7 This insight is valid when holding all other factors constant. However, the number of firms is endogenous andreflects other structural factors, such as barriers to entry and product differentiation.8 However, John Sutton has stressed the possibility of durable situations where the profits from high priceswould simply be dissipated through inefficient duplication of fixed costs and an excessive number of market

participants.9 This issue was first highlighted by Stiglers classic paper, A Theory of Oligopoly, 72 Journal of Political

Economy 44 (1964). Since then, it has been formally analyzed by Green E. and Porter R. (1984): Non-Cooperative Collusion under Imperfect Price Information,52 Econometrica87, and Abreu D., Pearce D. andStachetti E. (1985): Optimal Cartel Equilibria With Imperfect Monitoring, 39 Journal of Economic Theory


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Second, there are characteristics of the demand side:

- Market growth: collusion is easier to sustain when short-term gains from a deviation

are small compared with the cost of future retaliation; thus, for a fixed number of

market participants, collusion is easier to sustain in growing markets, where todays

profits are small compared with those of tomorrow.10

-

Absence of significant fluctuations or business cycles: collusion is less sustainable inmarkets that are subject to demand fluctuations (see FTC v. Arch Coal),11since peak

periods exacerbate short-term gains from a deviation, relative to the potential cost of

later retaliation.12 Hence, demand fluctuations hinder collusion, particularly when

fluctuations are deterministic(as in the case of seasonal cycles, where it is anticipated

that the future will be less rosy) as opposed to random.

- Demand elasticity: elasticity of demand has no clear impact on the sustainability of

collusive prices, but collusion is more profitable when demand elasticity is low, which

in turn can influence the firms willingness to establish a cartel and facilitate its

implementation despite the risk of being caught by antitrust authorities. Similarly,

collusion is a greater concern for consumers when demand is inelastic, both because

there is more scope for large price increases and because consumers are hurt more by agiven price increase when they have few alternatives.13

- Buying power: even a perfect cartel may find it difficult to impose high prices on

powerful buyers, which makes cartel activity less profitable and, by the same token,

more fragile.14

- The absence of club and network effects: club effects (that is, when consumers benefit

from being in the same club: using the same software, typing on the same type of

keyboard, subscribing to the same operator, and so forth.) tilt the market in favour of a

single participant, thereby creating a winner take all type of competition which is not

prone to collusion. In addition, club effects create lock-in effects that reinforce the

position of the market leader and thus increase the benefits derived from such a

position.

Finally, there are characteristics related to thesupply side:

- Mature industries with stabilized technologies: by allowing one firm to gain a

significant advantage over its rivals, innovation limits the scope for collusion; the

prospect of innovation reduces the value of future collusion as well as the cost from

possible retaliation from these rivals.

251. It may be noted that market stability can contribute to enhancing market transparency, since inferringdeviations from collusive conduct is easier and requires less detailed information when the market is stable. See

Khn K. (2001): Fighting Collusion by Regulating Communication between Firms,32 Economic Policy169,

discussing the role of information exchanges in this context.10This conclusion appears somewhat at odds with some court cases and opinions. Indeed demand growth is in

practice often interpreted as a factor hindering collusion. One possible reason for this apparent discrepancy is

that the above reasoning assumes that the number of market participants remains fixed despite market growth(due for example to regulations or limited access to key inputs or technologies), while in practice, entry may be

easier in growing markets. See, e.g., Case T-102/96 Gencor v Commission[1999] ECR II-753.11

329 F. Supp. 2d 109 (D.D.C. 2004),appeal dismissedper curiam.12

See Rotenberg J. and Saloner G. (1986): A Supergame-Theoretic Model of Business Cycles and Price Warsduring Booms, 76American Economic Review390; Haltiwanger J. and Harrington J. (1991): The Impact ofCyclical Demand Movements on Collusive Behavior,22RAND Journal of Economics89.13Thus, the less elastic the demand the greater the potential harm to consumers. However, the impact on total

welfare is more ambiguous, since price increases generate less distortion when demand is inelastic. See, e.g.,Tirole J. (1988): The Theory of Industrial Organization, MIT Press, Cambridge Massachusets, for a discussion

of this issue.14See Snyder C. (1996): ADynamic Theory of Countervailing Power,27 RAND Journal of Economics747,noting that large buyers can design procurement schemes that reduce the scope for collusion.


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- Symmetric costs: it is easier to collude with equals.15 First, cost asymmetry,16 for

example, may make it difficult to agree on a common pricing policy, since firms with

a lower marginal cost will insist on lower prices than what high-cost firms would wish

to sustain; more generally, different cost structures may rule out focal points and

may exacerbate coordination problems. Second, technical efficiency would require

allocating market share to low-cost firms, which might be difficult to achieve in theabsence of side-transfers.17 Third, low-cost firms may be more tempted to deviate

from a cartel agreement, both because they may gain more from undercutting their

rivals and because they have less to fear from a possible retaliation by high-cost

firms.18

- Symmetric capacities: an asymmetric distribution of production capacities hinders

collusion; the firm with the largest capacity has more incentive to undercut its rivals,

particularly if their production capacities limit their retaliatory power.19

- Product homogeneity: a firm with a better product is in a situation similar to that of a

firm with lower costs, i.e., it has more to gain from cheating on the cartel (or, put

another way, it may favour a different net price, adjusted for the quality differential),

and has less to fear from retaliation;20 in addition, product differentiation maycontribute to reducing market transparency.21

- Multi-market contact: firms can more easily sustain collusion when they are present

on several markets.22 First, multi-market contact may make firms interact more

frequently and allow them to maintain a cartel in markets where industry

characteristics would otherwise prevent them from doing so. Second, multi-market

contact may soften asymmetries arising in individual markets for example, one firm

15This intuition may also explain the informal discussions about the role of so-called mavericks. A maverick

firm can be interpreted as a firm with a drastically different cost structure (or a drastic difference in any otherrelevant dimension), which is thus unwilling to participate in or stick to collusive action.16

See Bain J. (1948): Output Quotas in Imperfect Cartels, 62 Quarterly Journal of Economics 617 for an earlydiscussion.17

However, side-transfers need not be monetary. For a discussion of these issues, see Osborne M. and Pitchik C.(1983): Price Competition in a Capacity-Constrained Duopoly, 38 Journal of Economic Theory 238;

Schmalensee R. (1987): Competitive Advantage and Collusive Optima,5 International Journal of IndustrialOrganization351.18

See Harrington J. (1989): Collusion Among Asymmetric Firms: The Case of Different Discount Factors,7International Journal of Industrial Organization 289; Thalm J. (2005): Optimal Collusion under Cost

Asymmetry, mimeo, University of Toulouse. See also Mason C., Phillips O. and Nowell C. (1992): DuopolyBehavior in Asymmetric Markets: An Experimental Evaluation, 74 Review of Economics and Statistics 662,

noting that, in experimental duopoly games, cooperation is more likely when players face symmetric production

costs.19See Lambson V. (1987): Optimal Penal Codes in Price-Setting Supergames with Capacity Constraints,54

Review of Economic Studies385; Lambson V. (1996): Some Results on Optimal Penal Codes in Asymmetric

Bertrand Supergames, 62Journal of Economic Theory444; Davidson C. and Deneckere R. (1984): HorizontalMergers and Collusive Behavior, 2 International Journal of Industrial Organization 117; Davidson C. and

Deneckere R. (1990): Excess Capacity and Collusion,31International Economic Review521.20

See, e.g., Ross T. (1992): Cartel Stability and Product Differentiation,10International Journal of IndustrialOrganization 1; Martin S. (1993): Endogenous Firm Efficiency in a Cournot Principal-Agent Model, 59Journal of Economic Theory445.21See Raith M. (1996): Product Differentiation, Uncertainty and the Stability of Collusion, London School ofEconomics-STICERD Discussion Paper Series EI/16:49.22

The classic reference is Bernheim B. and Whinston M. (1990): Is Everything Neutral?, 96 Journal ofPolitical Economy 308. See also Parker W. and Rller L.-H. (1997) Collusive Conduct in Duopolies:

Multimarket Contact and Cross-Ownership in the Mobile Telephone Industry," 28 RAND Journal of Economics304, and Evans W. and Kessides N. (1994) Living by the Golden Rule: Multimarket Contact in the U.S.Airline Industry, 109 Quarterly Journal of Economics 341.


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may have a competitive advantage in one market and its rival may have its own

competitive advantage in another market; while a (single) market-level analysis may

then suggest that collusion is difficult to sustain, multi-market contact in such a case

restores an overall symmetry that facilitates collusion. International cartels such as the

vitamins cartel provide good examples of such multi-market contacts.

-

Structural links: structural links can facilitate collusion among firms. For example,cross-shareholdings reduce the gains derived from undercutting the other firm. Joint

venture agreements may further enlarge the scope for retaliation because a

participating firm can a deviating partner by, e.g., investing less in the venture.23For

these reasons, collusion is more likely to emerge in markets where competitors are tied

through structural links.

- Cooperative and other contractual agreements: even in the absence of structural links,

simple cooperative agreements can contribute to foster collusion. As in the case of

joint ventures, these cooperative agreements can for example enlarge the scope for

retaliation, thereby enhancing the ability to punish deviating partners. This may be

particularly relevant for industries such as the telecommunications industry, where

competitors need to reach interconnection agreements in order to offer widespreadconnectivity. These agreements not only enlarge the scope for retaliation, they also

have a direct impact on the operators pricing strategies.24More generally, firms may

alter their contractual agreements, either between themselves or with third parties, so

as to facilitate collusion.25

This brief overview suffices to show that many factors may affect the scope for

collusion. Most often, a given market will have some characteristics that facilitate collusion,

and others that tend to hinder collusion. Predicting the likelihood of collusion on this bases

alone is thus a complex question.26

In addition, while these factors may help to identify those markets in which collusion

might be attractive or feasible, they cannot be relied upon to determine whether firms are

actually colluding.27 In the context of merger control, where the merger control office must

evaluate ex ante the future evolution of the industry, short of determining whether collusion

will indeed occur, a highly difficult if not impossible task, the merger control office can

review these factors to assess whether collusion will become easier to sustain.28In an ex post

23For a detailed analysis, see Martin S. (1995): R&D Joint Ventures and Tacit Product Market Collusion,24

European Journal of Political Economy 357.24

For example, telecoms operators that compete in linear prices could give each other incentives to maintainhigh prices, even in the absence of repeated interaction, by agreeing on a high reciprocal access charge see,

e.g., Armstrong M. (1998): Network Interconnection in Telecommunications,108 The Economic Journal545;

Laffont J., Rey P. and Tirole J. (1998): Network Competition: I. Overview and Nondiscriminatory Pricing,29RAND Journal of Economics 1.25Marketing agreements can be employed to that effect. Jullien B. and Rey P. (Resale Price Maintenance and

Collusion, working paper, University of Toulouse, 2002) show, for example, that producers of consumer goodscan resort to Resale Price Maintenance to impose more uniform prices across local retail markets, thereby

making it easier to detect deviations from a collusive price. Record companies have been accused of marketingtheir offerings according to simple pricing grids (with only a few categories, instead of personalized prices foreach author or title) for a similar purpose.26Moreover, the interplay of the factors may be important, as illustrated by the effects of market growth andentry barriers. If entry barriers are so large that entry is highly unlikely to occur, market growth fosters collusion;if instead entry barriers are moderate, market growth may stimulate entry, which in turn impedes collusion.27

Formally speaking, the same market situation can give rise to different equilibria. In particular, firms may wellcompete in each period as if it were the last one, even if another equilibrium exists in which they maintain

monopoly prices in each and every period.28While many factors appear relevant when evaluating the impact of a merger on collusion, some may be moreimportant than others. First, whenever there are no entry barriers, or where firms interact rather infrequently, or


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antitrust context, these factors may be looked at to determine whether collusion is a plausible

concern, but their analysis will not suffice to establish the existence of actual cartel activity.

An analysis of the history of the industry might help to answer that question.

C. Factual evidence and behavioural patterns

Two types of factual evidence might be relevant to identify collusion: first, since the object or

effect of collusion is to impede competition, antitrust authorities could look at signs of supra-

competitive prices or profits; alternatively, they can look for behavioural patterns that are

more likely to be associated with collusion than with competition. I briefly discuss these two

types of evidence.

1. Supra-competitive performance

This approach relies on a comparison between the actual performance of the industry and the

performance that one would expect from normal competition in a comparable industry. This

requires reasonably good access to reliable price or accounting data, but it is also necessary to

have an idea of what the comparable competitive levels would be. The latter issue is clearly a

tough one, and it requires detailed data and analysis of costs and demand conditions (not only

in the current situation but in the supposedly competitive one as well). This exercise is all the

more difficult to realize in concentrated industries, which will often be subject to imperfect

competition anyway (that is, even a purely static, non-cooperative form of normal

competition would still yield significant price-cost margins and profits). More generally, thistype of in-depth study requires deep knowledge and expertise about the industry, and it is

more naturally associated with regulatory supervision than with the antitrust oversight.

One can also rely upon econometric methods when sufficiently rich data are available.

This approach can, for example, provide an estimate of the likelihood of collusion. However,

it is sensitive to various modelling assumptions and specifications with respect to the demand

and supply side.29Recently however, the development of structural models of oligopolistic

models using panel data have made predictions possible even in the absence of precise

information on costs: in essence, sufficiently detailed data on prices and quantities enable

econometricians to estimate both demand and cost parameters. This opens up new scope for

application. Furthermore, this approach allows one to distinguish supra-competitive mark-ups

from normal but imperfectly competitive ones.30

the industry is primarily driven by innovation, collusion is unlikely to constitute a significant concern. A second

series of factors, such as the number of market participants, the degree of symmetry among those participants,and the existence of contractual or other types of arrangements, are all relevant and likely to be directly affectedby mergers. The other factors (market transparency, product homogeneity, demand trend and fluctuations, multi-market contact, and so forth) may be relevant when the previous factors do not suffice to send a clear signal.29For example, using the same dataset, Porter R. (On the Incidence and Duration of Price Wars, 23Journal ofIndustrial Economics 415 (1985)) and Ellison G. (Theories of Cartel Stability and the Joint Executive

Committee, 25 RANd Journal of Economics 37 (1994)) reach different conclusions about the likelihood ofdifferent collusive schemes adopted by an 1880s US railroad cartel.30

For example, Nevo A.s analysis of the US ready-to-eat cereal industry (see Mergers with DifferentiatedProducts: The Case of the Ready-to-Eat Cereal Industry, 31 RAND Journal of Economics 395 (2000);Measuring Market Power in the Ready-to-Eat Cereal Industry, 69 Econometrica 307 (2001)) suggests that


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This approach can thus be useful in determining whether collusion is likely or not in a

given industry. However, it is time- and resource-consuming (data collection, to begin with,

can be a real issue). In addition, this approach cannot yield certainty: by their nature,

econometric methods rely on probabilities; they can provide an estimate of the likelihood of

collusion, as well as confidence intervals, but they cannot produce definite yes/no answers.

2. Collusive patterns

Alternatively, one can look for behavioural patterns that are more naturally linked to collusion

than to competition. The usual suspects include price parallelism and stable market shares.

Concerns have also been raised by a lack of price response to changing demand conditions.

Courts have been reluctant to take such patterns as evidence of collusion. In my view,

this reluctance is justified and may even extend to interpreting these patterns as signals, if not

proof of collusion, since such patterns can be consistent with competitive as well as collusive

behaviour. Therefore, in the absence of any further empirical investigation, one cannotconclude that the industry has been, in fact, colluding. Three examples can illustrate that

point.

2.1. Price parallelism

Consider first a benchmark situation where all competitors offer the same, homogeneous

product. In those circumstances, by nature and whatever the effectiveness of competition, the

prices of all active firms will necessarily be always equal, since any price above the others

would attract no customer. All these prices are therefore deemed to move together: one should

expect a perfect parallelism in the evolution of prices, irrespective of whether firms are

colluding or competing head to head against each other. This case is admittedly an extreme

one, but by continuity the reasoning extends to situations where firms have similar offerings.

The more similar the firms offerings, the narrower the price range that one should expect,

regardless of whether firms collude or compete.

But parallelism can also obtain in industries with significant product differentiation.

To see this, let us use the simplest model of oligopolistic competition, the so-called linear

model, where both costs and demand are supposed to have a simple, linear shape.31In this

simple model, whatever the nature of the strategic interaction (in prices laBertrand or in

quantities la Cournot) and whatever the degree of product differentiation, prices are the

same across firms, whether they compete or perfectly collude. Thus, here again one should

expect as much parallelism with competition as with collusion. To explore the issue further,one can introduce some asymmetry on either the cost or the demand side. Doing so breaks

down the equality of the various firms collusive prices as well as of their competitive prices,

but it does not eliminate the scope for price parallelism. To see this, suppose for example that

mark-ups as high as 45% are more likely to be due more to product differentiation (making consumers willing topay for their favourite brand) and multi-branding (giving firms an incentive to maintain high prices on eachbrand, to avoid cannibalizing their other brands) rather than to collusion. Similarly, the analysis of Pinkse J. and .Slade M. (Mergers, Brand Competition, and the Price of a Pint,48European Economic Review 617 (2004))

suggests that the margins observed in the UK brewing industry result from intrinsically imperfect competition(due for the main part to product differentiation, and for the remaining part to local concentration).31

That is, firms have a constant unit cost and face a demand of the form qi= di aipi+ jaijpj , where d ireflects the size of the demand and the asparameters reflect the sensitivity of the demand with respect to thevarious prices.


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cost having a higher output and thus a higher market share than the other), the difference

between the output levels remains constant over time in spite of changes in the demand

parameter d, whether firms compete or collude.36This in turn implies that the difference in

market shares is smaller under competitive conditions than in the case of collusion, since the

output differential is the same and total output is larger with competition. In addition, a

declining shift in demand increases the market share differential under both competition andcollusion, but the adjustment is smaller in the case of competition.37Thus, in the light of this

simple example, a small adjustment of market shares when demand is declining should be

interpreted as a sign of competition rather than collusion.

2.3. Price reaction to changing demand conditions

Collusion concerns are sometimes raised when prices do not appear to react sufficiently to

changes in the environment, such as shocks to demand. However, even colluding firms would

have an incentive to revise their coordinated behaviour in reaction to changing demand

conditions. Furthermore, there is no clear reason suggesting that the optimal adaptation of

prices would systematically involve smaller price reductions under collusion than undercompetition. It could actually be argued that, as competitive prices are driven more by cost

considerations, they might respond even less than competitive ones to changes in demand.

Accordingly, a small change in prices should be interpreted as a sign of competition rather

than collusion.

On the magnitude of competitive price responses to changes in demand. Generally speaking,

the outcome of non-collusive competition among a limited number of competitors is primarily

driven by the level of their (marginal) costs of production and by the cross-elasticity of

demand for each firms product. For example, consider the benchmark situation in which

firms produce the same homogeneous product at the same constant unit cost. The competitive

price then simply reflects the level of the unit cost, and is entirely insensitive to demand

shocks. Thus, in this utmost competitive situation, prices would not change when demand

falls.

Consider now another situation, where firms still have constant unit costs but offer

differentiated products. Competition is admittedly less intense in that case, so that competitive

prices reflect both cost and demand conditions. Suppose further that, for each firm, the

demand for its products exhibits a constant elasticity with respect to that firms prices.38 In

that case, the normal competition among the firms yields prices that depend on this constant

elasticity and not, for example, on the scale of the demand. Thus, as long as shifts in demand

have no impact on the own-elasticity of demand for one firms products with respect to its

own price, the competitive price levels remain unchanged.

Do collusive prices adjust less than competitive prices to changes in demand? As already

hinted, competitive prices tend to be driven more by cost considerations, and thus less by

36The output differential is given by (1+s)(c2 c1)/(2+s)(1 s) in the case of competition and by (1+s)(c2

c1)/2(1 s) in the case of perfect collusion. In both cases, an increase in, say, the degree of substitutabilityshas aqualitatively similar impact on (namely here, it induces an increase in) both output differentials.37The market share differential is given by (1+s)(2 s)(c2 c1)/(2+s)(1 s)2(d c1 +c2)/2) in the case of

competition and by (1+s)(c2 c1)/(1 s)2(d c1 +c2)/2) in the case of perfect collusion. The impact of areduction in the demand scale parameter don the market share differential is thus (2 s)/(2+s) (< 1)smaller

with competition than with collusion.38That is, the demand for firm is products is of the form qi= Q i(p-i)pi-, wherep-irepresents the other firms

prices.


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demand considerations, than collusive or monopolistic prices. To see this, let us again use the

simple linear model of oligopolistic competition already presented above. In this simple

model, whatever the nature of competition (in prices la Bertrand or in quantities la

Cournot) and whatever the degree of product homogeneity or differentiation:

- both the competitive and the collusive price level can be expressed as a

weighted average of the demand size parameter and of the unit costs; and- the weight put on the demand parameter is larger, not smaller, in the case of

perfect collusion.39

In the light of this simple illustration, a supposedly small change in prices should be

interpreted as a sign of competition rather than of collusion. Furthermore, as already

discussed in the previous section, downwards shifts in demand or demand fluctuations tend to

make collusion more difficult to sustain, particularly when demand is low or falling.40 It

follows that collusive prices then exhibit even larger adjustments to changes in demand

conditions, since firms cannot sustain as much collusion in bad times as they can in good

times.

However, as emphasized above, none of these features (i.e., price parallelism, stable

market shares, lack of price response to changing demand conditions) allows an outsideobserver to distinguish collusion from competition. They are all consistent with competition

as well as with collusion. Furthermore, while this paper has addressed each feature in turn for

the sake of exposition, it should be clear at this point that a combination of the three features

is also consistent with competition as well as with collusion.

More recently, some work has been done to explore new and promising ideas, in order

to identify specific behavioural patters that are more likely to be indicative of collusion than

competition. For example, Joseph Harrington has stressed the role of sudden changes in

behaviour. One the one hand, the establishment of a cartel would be expected to lead to rapid

price increases, while occasional collusion break-downs might lead to temporary price wars;

cartels will seek to avoid sending signals that are too obvious, which might lead them to adapt

prices more slowly.41One might expect a cat-and-mouse situation, where colluding firms try

to avoid adopting precisely the type of pattern that one would normally associate with cartels.

This would lead to revised expectations about cartel behaviour, and so on and so forth.

The issue is further complicated by the fact that many cartels probably operate in a

less than fully effective way, which multiplies the number of possible patterns. Overall, while

further research in this area is probably warranted, at the moment it appears difficult to rely

solely on this approach to detect cartels.

39 In the simplest case, where two firms produce homogeneous goods and the market demand then takes the

simple form Q = d p, the perfectly collusive price (i.e., the monopoly level) puts equal weights on the demand

and cost parameters (pm= (d + c )/2), whereas the competitive price just reflects the unit cost in the case of price

competition laBertrand (pB= c), and puts on the demand parameter a weight that is half of that put on cost in

the case of quantity competition laCournot (pC= (d + 2c )/3). In the latter case, the difference between the

two weights furthermore increases with the number of firms. For example, in the case of five firms, the ratiobetween the two weights becomes 1 to 5:p

C= (d + 5c)/6.

40See, e.g., Rotemberg J. and Saloner G. (1986): A Supergame-Theoretic Model of Business Cycles and PriceWars during Booms, 76 American Economic Review390, or Haltiwanger J. and Harrington J. (1991): TheImpact of Cyclical Demand Movements on Collusive Behavior, 22RAND Journal of Economics89.41

See Harrington J. and Chen J., Cartel Pricing Dynamics with Cost Variability and Endogenous BuyerDetection,International Journal of Industrial Organization(forthcoming). In the same vein, it has been argued

that, once a cartel has been successfully prosecuted by antitrust agencies and is facing civil suits for damages, itsformer members might still maintain (unilaterally, this time) supra-competitive prices in order to minimize theevaluation of the damages.


Patrick Rey 10/11


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D. Leniency and whistleblowing programmes

Economic analysis, both conceptual and empirical, can also serve to better understand whatmakes cartels work or not work, in order to exacerbate cartel fragility and, by the same token,

contribute to cartel deterrence. Alternatively, one could say that competition agencies are

confronted with an information acquisition problem: firms know whether they collude; the

agencies do not. The agencies could therefore try and devise so-called revelation

mechanisms in order to induce the firms to report this information.42This is the purpose of

the leniency programmes that grant favourable treatment to cartel members who come

forward with information that helps competition authorities to dismantle a cartel.

Economic analysis can be used to study the design of these leniency programmes so as

to improve their effectiveness; and indeed, there has recently been a body of work in this area,

starting with the works of M. Motta and M. Polo43and G. Spagnolo.44Several messages stem

from this emerging literature,45for example:

it is good to restrict leniency to the first informant (provided that this informant

brings sufficient evidence or information leading to successful prosecution);

it may be a good idea to keep offering leniency (to a first informant) even once

an investigation is underway;

there is some complementarity between corporate and individual leniency

programmes;

it may be desirable to go further and offer bounties (monetary rewards, such as

a share in the fines imposed on the cartel members) to individual informants;

the stronger the stick (criminal sanctions such as fines and jail sentences) the

more effective the carrot of leniency; a weaker stick calls for larger amnestyrates (or larger rewards).

While this body of work is still very much in progress, there lies a strong hope for

enhancing cartel detection and deterrence.

42

Building on the pioneering work of Maskin E. (Nash Implementation and Welfare Optimality", MIT 1977,published in 66 Review of Economic Studies 23 (1999)), the literature on Nash and Subgame Perfectimplementation has confirmed the intuition that "a secret is no longer a secret when it is shared by several

agents". See Moores very nice survey, Implementation, contracts, and renegotiation in environments withcomplete information, in Laffont J., ed., Advances in Economic Theory, Sixth World Congress, Econometric

Society Monographs, Vol. 1, 182- (1992).43

Leniency Programs and Cartel Prosecution,2InternationalJournal of Industrial Organization347 (2003).44

Optimal Leniency Programs, Discussion Paper, Fondazione Enrico Mattei (2000).45Besides the papers already mentioned, see Aubert C., Kovacic W. and Rey P., The Impact of Leniency andWhistleblowing Programs on Cartels, International Journal of Industrial Organization (forthcoming);Harrington J., Optimal Corporate Leniency Programs, Johns Hopkins University (2005); Frezal S., On

Optimal Cartel Deterrence Policies, International Journal of Industrial Organization (forthcoming); Rey P.(2003): Toward a Theory of Competition Policy, in Dewatripont M., Hansen L. and Turnovsky L., eds.,

Advances in Economics and Econometrics: Theory and Applications, Eighth World Congress, CambridgeUniversity Press; Chen Z. and Rey P., Optimal Design of Leniency Mechanisms, mimeo, University ofToulouse.


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http://www.iue.it/Personal/Motta/leniency.pdfhttp://www.iue.it/Personal/Motta/leniency.pdf

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Cartel Detection