Skip to main content
Log in

The Rise and Fall of Cartels with Multi-market Colluders

  • Published:
Review of Industrial Organization Aims and scope Submit manuscript

Abstract

The majority of cartels that were discovered by the European Commission (EC) over the last 30 years involved firms that engaged in collusion in more than one market. I investigate the impacts of the EC’s cartel enforcement on the hazards that firms join and leave cartels in multiple markets. I estimate discrete-time recurrent event hazard models for a set of 126 multi-market colluders that were prosecuted between 1985 and 2014. EC investigations in a market decrease the rate at which the cartel members join new cartels and increases the rate at which they leave cartels in other markets. My results shed light on enforcement efforts against cartels and other forms of organized crime .

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. Marx et al. (2015, p. 3) make the same remark.

  2. Lefouili and Roux (2012) also note that conspirators in a specific product or geographic market are likely to have engaged in cartel activities in the other markets.

  3. Under the “Amnesty Plus” program, the US Department of Justice (DOJ) offers a cartel member a penalty discount for disclosing previously undetected cartels that are different from the one that first brought that cartelist to the DOJ’s attention.

  4. See also Marx et al. (2015), especially footnote 10.

  5. The DOJ maintains strict confidentiality regarding the schedule of its cartel investigation. Although it is possible to find data or make inferences in some cases, more commonly the starting date of an investigation is unknowable from publicly available data.

  6. These cartels are operated by trade associations or shipping conferences that are the addressees of the EC decisions. The identity of the individual firms is usually undisclosed in the published decisions.

  7. For example, Degussa AG joined the Hydrogen Peroxide and Perborate cartel in January 1994 and ended its collusion in the cartel in December 2000. FMC Corporation joined the cartel in May 1997 and stopped collusion in December 1999.

  8. Alternative approaches to handle linked failure times in continuous-time hazard frameworks have been developed in the literature. See, e.g., Breslow (1974). While computationally undemanding, Breslow’s method will be inaccurate if there are many links in the data set, which happens to be my case.

  9. I obtain similar results from probit models.

  10. Formally, if we define the risk set in month m, \(R_m\), as the number of spells that do not experience an event by the start of month m, and the number of events in month m as \(S_m\), the Kaplan–Meier empirical hazard is defined as \(S_m/R_m\).

  11. To my best effort, I am not able to find information of the dates of the DOJ’s investigation initiation for the majority of cartels that affected the American markets.

References

  • Allison, P. D. (1982). Discrete-time methods for the analysis of event histories. Sociological Methodology, 13, 61–98.

    Article  Google Scholar 

  • Aubert, C., Patrick, R., & Kovacic, W. E. (2006). The impact of leniency and whistle-blowing programs on cartels. International Journal of Industrial Organization, 24(6), 1241–1266.

    Article  Google Scholar 

  • Bernheim, B. D., & Whinston, M. D. (1990). Multimarket contact and collusive behavior. RAND Journal of Economics, 21(1), 1–26.

    Article  Google Scholar 

  • Bigoni, M., Fridolisson, S., Le Coq, C., & Spagnolo, G. (2012). Fines, leniency, and rewards in antitrust. RAND Journal of Economics, 43(2), 368–390.

    Article  Google Scholar 

  • Brenner, S. (2009). An empirical study of the European corporate leniency program. International Journal of Industrial Organization, 27(6), 639–645.

    Article  Google Scholar 

  • Breslow, N. (1974). Covariance analysis of censored survival data. Biometrics, 30(1), 89–99.

    Article  Google Scholar 

  • Buccirossi, P., & Spagnolo, G. (2006). Leniency policies and illegal transactions. Journal of Public Economics, 90(6–7), 1281–1297.

    Article  Google Scholar 

  • Buccirossi, P., & Spagnolo, G. (2007). Optimal fines in the era of whistleblowers: Should price fixers still go to prison? In V. Ghosal & J. Stennek (Eds.), The political economy of antitrust (pp. 81–122). New York: Elsevier.

    Chapter  Google Scholar 

  • Chen, J., & Harrington, J. E. (2007). The impact of the corporate leniency program on cartel formation and the cartel price path. In V. Ghosal & J. Stennek (Eds.), The political economy of antitrust (pp. 59–80). New York: Elsevier.

    Chapter  Google Scholar 

  • Chen, Z., & Rey, P. (2013). On the design of leniency programs. Journal of Law and Economics, 56(4), 917–957.

    Article  Google Scholar 

  • Choi, J. P., & Gerlach, H. (2013). Multi-market collusion with demand linkages and antitrust enforcement. Journal of Industrial Economics, 61(4), 987–1022.

    Article  Google Scholar 

  • Fabra, N. (2006). Collusion with capacity constraints over the business cycle. International Journal of Industrial Organization, 24(1), 69–81.

    Article  Google Scholar 

  • Feinberg, R. (1985). ‘Sales-at-risk’: A test of the mutual forbearance theory of conglomerate behavior. Journal of Business, 58(2), 225–241.

    Article  Google Scholar 

  • Feinberg, R., & Sherman, R. (1988). Mutual forbearance under experimental conditions. Southern Economic Journal, 54(4), 985–993.

    Article  Google Scholar 

  • Gaertner, D. & Zhou, J. (2013). Delays in leniency application: Is there really a race to the enforcer’s door?. Unpublished.

  • Haltiwanger, J. C., & Harrington, J. E. (1991). The impact of cyclical demand movements on collusive behavior. Rand Journal of Economics, 22(1), 89–106.

    Article  Google Scholar 

  • Harrington, J. E. (2008). Optimal corporate leniency programs. Journal of Industrial Economics, 56(2), 215–246.

    Article  Google Scholar 

  • Harrington, J. E., & Chang, M. (2009). Modeling the birth and death of cartels with an application to evaluating competition policy. Journal of European Economic Association, 7(6), 1400–1435.

    Article  Google Scholar 

  • Hinloopen, J., & Soetevent, A. R. (2008). Laboratory evidence on the effectiveness of corporate leniency programs. RAND Journal of Economics, 39(2), 607–616.

    Article  Google Scholar 

  • Lefouili, Y., & Roux, C. (2012). Leniency programs for multimarket firms: The effect of amnesty plus on cartel formation. International Journal of Industrial Organization, 30(6), 624–640.

    Article  Google Scholar 

  • Levenstein, M. C., & Suslow, V. Y. (2006). What determines cartel success? Journal of Economic Literature, 44(1), 43–95.

    Article  Google Scholar 

  • Levenstein, M. C., & Suslow, V. Y. (2011). Breaking up is hard to do: Determinants of cartel duration. Journal of Law and Economics, 54(2), 455–492.

    Article  Google Scholar 

  • Marx, L. M., Mezzetti, C., & Marshall, R. C. (2015). Antitrust leniency with multi-product colluders. American Economic Journal: Microeconomic, 7(3), 205–240.

    Google Scholar 

  • Miller, N. H. (2009). Strategic leniency and cartel enforcement. American Economic Review, 99(3), 750–768.

    Article  Google Scholar 

  • Motta, M., & Polo, M. (2003). Leniency programs and cartel prosecution. International Journal of Industrial Organization, 21(3), 347–379.

    Article  Google Scholar 

  • Spagnolo, G. (1999). On interdependent supergames: Multimarket contact, concavity, and collusion. Journal of Economic Theory, 89(1), 127–139.

    Article  Google Scholar 

  • Spagnolo, G. (2000). Self-defeating antitrust laws: How leniency programs solve bertrand’s paradox and enforce collusion in auctions. Unpublished.

  • Spagnolo, G. (2004). Divide et impera: Optimal leniency programs. Unpublsihed.

  • Zhou, J. (2012). Evaluating leniency with missing information on undetected cartels: Exploring time-varying policy impacts on cartel duration, Unpublished.

Download references

Acknowledgments

I thank Eric van Damme, Adriaan Dierx, Dennis Gaertner, Martin Holterman, Fabienne Ilzkovitz, Mario Mariniello, Leslie M. Marx, and Guntram B. Wolf for helpful conversations. I am indebted to Robert Feinberg and Lawrence J. White (the editors) for many perceptive comments and suggestions. Part of this work was carried out while the author was visiting Bruegel, whose hospitality is gratefully acknowledged. Any mistakes are my own.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jun Zhou.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhou, J. The Rise and Fall of Cartels with Multi-market Colluders. Rev Ind Organ 48, 381–403 (2016). https://doi.org/10.1007/s11151-016-9509-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11151-016-9509-0

Keywords

Navigation