Journal of Competition Law & Economics, 12(3), 541–555 doi:10.1093/joclec/nhw016 Advance Access publication 20 September 2016 USING NETWORK THEORY TO DETECT DOMINANT CARTEL FIRMS Pilar Grau-Carles* & Miguel Cuerdo-Mir† Downloaded from https://academic.oup.com/jcle/article/12/3/541/2236264 by guest on 27 September 2021 ABSTRACT Despite multiple applications of network theory in different fields of social and legal sciences in general, the possibility of applying this theory to the economic analysis of the antitrust law and, more specifically, to the study of cartels has not yet been considered. Nevertheless, the study of cartels as networks can advance some general elements and measurements that can help the detection and elimination of these organizational forms that cause evident harm to general well-being. This is the first time that the approach of network theory has been used to analyze cartels. This article uses a set of classical measures such as clus- tering and centrality measures, taken from network theory, and applies them to a specific case of a cartel sanctioned as such by the European Commission. This approach has enabled us to quantify some characteristic elements of the cartel, such as, for instance, a remarkable asymmetry between operators (nodes in the network), its different degree of influence (study of links), as well as the critical importance of some operators versus other cartelized agents, such that their elimination from the organization would not enable them to create their own cartel. This finding warrants reconsidering the antitrust policy based on leniency programs. JEL: K21; D85; L22 I. INTRODUCTION Antitrust law considers cartel formation to be the most serious infraction. A cartel is an illegal, and therefore secret, agreement among competitors in the same market that is generally complex and continued over time, the pur- pose of which is to impose monopoly-like conditions on the market in ques- tion, resulting in effects on quantity and price equilibrium, in detriment of * Universidad Rey Juan Carlos, Campus Vicálvaro. Facultad de Ciencias Jurídicas y Sociales. Departamento Economía Aplicada I. Paseo Artilleros s/n 28032 Madrid, Spain. Email: pilar. [email protected]. † Universidad Rey Juan Carlos, Campus Vicálvaro. Facultad de Ciencias Jurídicas y Sociales. Departamento Economía Aplicada I. Paseo Artilleros s/n 28032 Madrid, Spain. Email: miguel. [email protected]. This article was supported by grants from the Research Project, “La Potestad Sancionadora de los Organismos Reguladores’ (Ref. DER 2011-22549, Spanish Education Ministry) and “Gobierno Corporativo, Mercados de Capitales y Crisis Financiera” (Ref. ECO2012-32554, Spanish Economic Ministry). © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected] 542 Journal of Competition Law & Economics general wellbeing. This is because there is no longer competition among them.1 Different cartel organizations might be more suitable than others to apply entry barriers or fulfil the agreements on which they are based. Also critical is the weight and position of each cartelist in the organization, often determin- ing its very existence. If we assume that there has to be one operator or organization with greater responsibility in the cartel, then its elimination could be expected to put an end to the cartel itself. According to this reason- Downloaded from https://academic.oup.com/jcle/article/12/3/541/2236264 by guest on 27 September 2021 ing, the organization of cartels can determine different levels of centrality and different role for each of the members. It is clear that a study of centrality structure could show how decisions are made inside the cartel, which could differ depending on the type of organization. If we consider cartels as organizations, they can be viewed as networks. These networks change the rate of substitution among competitors into a cooperative one. Somehow, cartelists turn each other into complementary agents. Cartelists do not already face a given price alone and in line with their costs. Extra revenue arises as all of them capture an externality from this cooperative behavior. What type of network is required for cartelization? For instance, a new node in the network will have an effect on other nodes in the shape of the marginal externality (the network effect), but also it will increase competition among nodes to get extra profits (the competitive effect). In case of a cartel, an increase in the size of the network leads to a problem of distribution with a monopoly price, although the cartel can be more effective (capture more of the externality) if it controls a larger market share. There will also be limited compatibility, determined by the marginal contribution of the last operator who enters the cartel to make the monopoly price effective. To be able to capture these extra profits, one interesting aspect is the study of the cartel’s degree of cohesion and stability. Sometimes, the role played by certain agents is explained by their market position, which makes them cen- tral agents in the cartel itself. Without them, cartels can be said to lose eco- nomic significance, or at least the ability to be successful. From this perspective, the study of some measures taken from network theory enables us to identify the cohesion and efficiency of these networks, focusing on the nodes that are network effective, resulting in a positive differ- ence in relation with the competitive effect that they generate. Frank Schweitzer, Giorgio Fagiolo, Didier Sornette, Fernando Vega-Redondo, Alessandro Vespignani, and Douglas White underline the need to study eco- nomic networks through a better understanding of these frameworks over time, with a closer analysis of the role, function, and influence of each agent 1 Richard A. Posner, ANTITRUST LAW:AN ECONOMIC PERSPECTIVE (Univ. Chicago Press 2d ed. 2001). Using Network Theory to Detect Dominant Cartel Firms 543 in the cartel organization.2 In social and economic networks, other research- ers3 have shown that there is a selection inside the network of the members that obtain higher profits, who become leaders and make the network more hierarchical. This finding would mean that sustainable cooperation depends critically on these leaders, creating asymmetric collaboration structures.4 This question is connected to the traditional practice of antitrust law in which different obligations are defined for each operator, depending on its importance in the market. So it has to be known which of them are critical Downloaded from https://academic.oup.com/jcle/article/12/3/541/2236264 by guest on 27 September 2021 for the survival of the network and which are not, at least in terms of ability to affect effective competition. The above perspective could be relevant for reviewing all competition pol- icies based on the idea of a leniency program related to the detection of car- tels. The idea of reviewing leniency program using different methodologies is not new. For instance, by means of game theory several studies have tried to evaluate the impact of such leniency programs.5 To a certain extent, it is clear that leniency programs should not only con- sider when the cartelists decide to collaborate and to what extent. Indeed, it is not so peculiar that the main market operator, the most active cartel mem- ber, would be totally exempted from the fine. This leniency program result creates an incentive for those who are capable of better and more directly controlling the cartel’s dynamics, who report the cartel’s existence when con- venient. These agents would be able to weaken their competitors, avoiding administrative sanctions and generating an administrative cost for their com- petitors, especially those with financial difficulties.6 In this regard, network theory can be used to study cartels, allowing, on one hand, to find the most important or central nodes within it and, on the other, measuring the network cohesion, and studying the possibilities of net- work partitioning. Regarding the use of network theory in market cartelization, this article studies a case file, using a set of measures derived from network theory to 2 Frank Schweitzer, Giorgio Fagiolo, Didier Sornette, Fernando Vega-Redondo, Alessandro Vespignani & Douglas R. White, Economic Networks: The New Challenges, 325 SCIENCE 593422 (2009). 3 Martín G. Zimmermann & Víctor M. Eguíluz, Cooperation, Social Networks, and the Emergent of Leadership in a Prisoner’s Dilemma with Adaptive Local Interactions,72PHYSICAL REV. E 056118 (2005). 4 See Sanjeev Goyal & Sumit Joshi, Networks of Collaboration in Oligopoly (Tingergen Institute Discussion Paper, Paper No. TI 2000-092/1, 2000). 5 Nathan H. Miller, Strategic Leniency and Cartel Enforcement,99AM.ECON.REV. 750 (2009); see also Cécile Aubert, Patrick Rey & William E. Kovacic, The Impact of Leniency and Whistle- Blowing Programs on Cartels,24INT’L J. INDUS.ORG. 1241 (2006). 6 Miguel Cuerdo-Mir & Pilar Grau-Carles, Networks, Cartels, and Antitrust Policy, (unpublished manuscript) (Oct. 30, 2014), http://dx.doi.org/10.2139/ssrn.2518988; see also Pilar Grau- Carles & Miguel Cuerdo-Mir, Stability and Cohesion of Cartels Through Network Theory (URJC Working Paper, 2014), http://hdl.handle.net/10115/12272. 544 Journal of Competition Law & Economics study this file from a novel approach. The object of our analysis is the vitamin cartel, European Commission case file COMP/E-1/37.512—Vitamins.7 The results of the study can be used as a basis for subsequent approaches more appropriate for cartel formation and organization. It seems that these new approaches could be increasingly useful, not only for better development of an effective competition policy against such pernicious agreements, but also as a new instrument for their detection, prosecution, and sanction. The structure of this article is as follows: Part II contains the information Downloaded from https://academic.oup.com/jcle/article/12/3/541/2236264 by guest on 27 September 2021 and the resulting network obtained by the study of the agreements of the car- telized companies explained in the case file.