Skip to main content

Problematic Merging and Cartels: A Collusion Risk Factors Analysis

  • Chapter
  • First Online:
Applications of Artificial Intelligence and Neural Systems to Data Science

Abstract

The economic literature acknowledges that market factors and corporate decisions may increase the likelihood that various forms of collusive agreements will be successful. In order to identify collusive behaviours, the European Commission proposes merger control and anti-cartel decisions. The European Commission's actions are occasionally seen as case-driven, and antitrust intervention is frequently carried out too slowly. We propose a novel approach to evaluate the features of a manufacturing sector that can be considered as a warning for future infractions. We investigate, in terms of decision rules, the relationship between risk indicators and the detection of collusive behaviour using the Dominance-based Rough Set Approach (DRSA). Data refer to various institutional sources concerning different manufacturing sectors from 5 countries (France, Germany, Italy, Spain and United Kingdom). Making use of a “Hybrid” information system, taking into account the conditional attributes’ original numerical values, and classifying decision attributes in a less granular way, allows a more straightforward interpretation of the results. The size of the firm and market concentration seem to be the most crucial factors when it comes to mergers, while unexpectedly, market stability and asymmetry seem to be less important for spotting collusion.

All authors contributed equally to this work.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    The Four-Firm Concentration Ratio is a market concentration metric that identifies the total market share owned by the top four companies in a certain sector.

  2. 2.

    The Herfindahl–Hirschman Index is determined by adding the squares of each firm's market share in a specific market, i.e., it calculates the total squared market share percentages held by each company in the market.

References

  1. Antonielli M, Mariniello M (2014) Antitrust risk in EU manufacturing: A sector-level ranking. Bruegel WP, 1–29

    Google Scholar 

  2. Pawlak, Z.: Rough Sets. Int J Comput Inf Sci 11, 341–356 (1982)

    Article  MATH  Google Scholar 

  3. Greco, S., Matarazzo, B., Słowiński, R.: Rough approximation of a preference relation by dominance relations. Eur J Oper 117, 63–83 (1999)

    Article  MATH  Google Scholar 

  4. Greco, S., Matarazzo, B., Słowiński, R.: Rough sets theory for multi-criteria decision analysis. Eur J Oper 129, 1–47 (2001)

    Article  MATH  Google Scholar 

  5. Błaszczyński, J., Greco, S., Matarazzo, B., Słowiński, R., Szela̧g M,: jMAF-Dominance-based rough set data analysis framework. In: Skowron, A., Suraj, Z. (eds.) Rough Sets and Intelligent Systems-Professor Zdzisław Pawlak in Memoriam, pp. 185–209. Springer, Berlin, Heidelberg (2013)

    Chapter  Google Scholar 

  6. Motta, M.: Competition policy: theory and practice. Cambridge University Press (2004)

    Book  Google Scholar 

  7. Błaszczyński, J., Greco, S., Słowiński, R.: Multi-criteria classification—A new scheme for application of dominance-based decision rules. Eur J Oper 3, 1030–1044 (2007)

    Article  MATH  Google Scholar 

  8. Ellero, A., Ferretti, P., Zocchia, E.: A multi-criteria study of collusion risk factors. Department of Management, Università Ca’ Foscari Venezia Working Paper No. 2016/21 (2016). Available at https://doi.org/10.2139/ssrn.2893247

  9. Nguyen, H.S., Nguyen, S.H.: Discretisation methods in data mining. In: Polkowski, L., Skowron, A. (eds.) Rough sets in knowledge discovery, 1, pp. 451–482. Physica-Verlag, New York (1998)

    Google Scholar 

  10. Baranas, E., Mirabel, F., Poudou, J.C.: Collusion sustainability with multi- market contacts: revisiting HHI tests. Theor Econ Lett 2, 307–315 (2012)

    Article  Google Scholar 

  11. Käseberg, T.: Intellectual Property, Antitrust and Cumulative Innovation in the EU and the US, Hart Studies in Competition Law, Hart Studies (2012)

    Google Scholar 

  12. Mariniello, M.: Do European Union fines deter price-fixing?, Bruegel Policy Brief, Bruegel 2013/4 (2013)

    Google Scholar 

  13. Friederiszick, H.W., Maier-Rigaud, F.P.: (2007) The role of economics in cartel detection in Europe. In: Schmidtchen D, Albert M, Voigt S (eds.) The More Economic Approach in European Competition Law, Mohr Siebeck

    Google Scholar 

  14. Grout, P.A., Sonderegger, S.: (2005) Predicting Cartels, Economic Discussion Paper, Office of Fair Trading, OFT 773

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Paola Ferretti .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ellero, A., Ferretti, P., Zocchia, E. (2023). Problematic Merging and Cartels: A Collusion Risk Factors Analysis. In: Esposito, A., Faundez-Zanuy, M., Morabito, F.C., Pasero, E. (eds) Applications of Artificial Intelligence and Neural Systems to Data Science. Smart Innovation, Systems and Technologies, vol 360. Springer, Singapore. https://doi.org/10.1007/978-981-99-3592-5_22

Download citation

  • DOI: https://doi.org/10.1007/978-981-99-3592-5_22

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-3591-8

  • Online ISBN: 978-981-99-3592-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics