collusion

List Price Collusion (2021, JICT)

Firms sometimes collude by agreeing on increases in list prices. Yet, the efficacy of such list price collusion is subject to discussion as colluding firms might, in principle, deviate secretly from the elevated prices by granting their customers discounts. This article reviews cases of list price collusion in the USA and Europe, and it presents a theory of harm suggesting that a combination of anchoring, orientation on reference points, and loss aversion may render list price collusion effective in raising transaction prices—even if firms set transaction prices in a non-coordinated fashion.


Boshoff, W. and Paha, J. (2021), Journal of Industry, Competition, and Trade. Vol. 21 No. 3, S. 393-409

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Non-Controlling Minority Shareholdings and Collusion (2021, RIO)

This article merges theoretical literature on non-controlling minority shareholdings (NCMS) in a coherent model to study the effects of NCMS on competition and collusion. The model encompasses both the case of a common owner holding shares of rival firms as well as the case of cross ownership among rivals. We find that by softening competition, NCMS weaken the sustainability of collusion under a greater variety of situations than was indicated by earlier literature. Such effects exist, in particular, in the presence of an effective competition authority.


De Haas, S. and Paha, J. (2021), Review of Industrial Organization. Vol. 58 No. 3, pp. 431-454

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Kartellschadensersatz – Unverzerrte Ermittlung erfordert Analyse der Kartellauslöser (2021, ÖZK)

Der vorliegende Beitrag zeigt anhand einer Analyse von Entscheidungen der Europäischen Kommission in Kartellverfahren auf, dass die Bildung von Absprachen systematischen Mustern folgt. So wirken Änderungen in der Nachfrage(macht), den Produktionskapazitäten, dem wettbewerblichen Umfeld oder den regulatorischen Rahmenbedingungen als Auslöser der Absprachen. Diese Erkenntnisse sind für die ökonometrische Bestimmung der durch die Absprache bewirkten Preisüberhöhung in Schadensersatzverfahren relevant. Denn die als Kartellauslöser identifizierten Faktoren hätten sich auch ohne die Absprachen auf die Preise ausgewirkt, sodass die Analyse der Umstände der Kartellbildung hilfreich ist, um die Preisüberhöhung unverzerrt bestimmen zu können.


Herold, D. und Paha, J. (2021) Österreichische Zeitschrift für Kartellrecht, Vol. 15 Nr. 1, 3-11

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Cartels as Defensive Devices: Evidence from Decisions of the European Commission 2001-2010 (2018, RLE)

Why would an industry that was not colluding yesterday start colluding today? This article distills insights about cartel formation from 41 cases prosecuted by the European Commission between 2001 and 2010. The case studies examine the events occurring prior to the cartels’ set-up. Cartel formation is affected by changes in prices, demand and customer conduct, capacity utilization, increased imports and entry by competitors, as well as events in the legal and regulatory environment of the firms. Yet, none of these factors serves as a good marker of cartel formation when being regarded in isolation. It rather needs to be analyzed how changes in these factors interact and whether they raise the intensity of competition. In this context, factors that are commonly deemed to destabilize cartels, like entry of new competitors or buyer power, are found to actually foster cartel formation.


Herold, D. und Paha, J. (2018), Review of Law and Economics Vol. 14 No.1, 1-31

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The Value of Collusion with Endogenous Capacity and Demand Uncertainty (2016, JINDEC)

Collusion has often been alleged in industries where long-lived capacity investments are important. This article develops a computational duopoly model with capacity investments, demand shocks and either competitive or collusive pricing. It shows that allowing for endogenous capacity investments can sometimes make collusion less valuable than competition and that it can change the normal relationships between the profitability of collusion and both the discount rate and industry-wide demand shocks.


Paha, J. (2016), Journal of Industrial Economics. Vol. 65, No. 3, 623–653

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Using Accounting Data in Cartel Damage Calculations – Blessing or Menace? (2012, EJLE)

Standard methods for calculating cartel-damage rely on data of prices charged and quantity sold. Such data may not easily be available. In this paper, it is shown that accounting data can be used for computing a lower bound for cartel-damage. Previous literature indicates that economic profits can hardly be inferred from accounting data. Therefore, it is shown under which econometrically testable assumptions on accounting costs a meaningful lower bound for cartel-damage can consistently be estimated when using accounting data. However, the aggregation-level and the publication-frequency of accounting data pose a challenge to the estimation of cartel-damage. A further challenge is to appropriately reflect the strength respectively effectiveness of the collusive agreement in the specification of any such estimation.


Paha, J. (2012), European Journal of Law and Economics. Vol. 34 No. 2, 241-263

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Empirical Methods in the Analysis of Collusion (2011, Empirica)

Regression methods are commonly used in competition lawsuits for, e.g., determining overcharges in price-fixing cases. Technical evaluations of these methods’ pros and cons are not necessarily intuitive. Appraisals that are based on case studies are descriptive but need not be universally valid. This paper opens up the black box called econometrics for competition cases. This is done by complementing theoretical arguments with estimation results. These results are obtained for data that is generated by a simulation-model of a collusive industry. Using such data leaves little room for debate about the quality of these methods because estimates of, e.g., overcharges can be compared to their true underlying values. This analysis provides arguments for demonstrating that thoroughly conducted econometric analyses yield better results than simple techniques such as before-and-after comparisons.


Paha, J. (2011), Empirica. Vol. 38, 389-415

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