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Machine Learning in Cartel Screening—The Case of Parallel Pricing in a Fuel Wholesale Market

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  • Sylwester Bejger

    (Faculty of Economic Sciences and Management, Nicolaus Copernicus University in Toruń, 87-100 Toruń, Poland)

Abstract

The detection and deterrence of collusive agreements among firms, such as price-fixing cartels, remain pivotal in maintaining market competition. This study investigates the application of machine learning methodologies in the behavioral screening process for detecting collusion, with a specific focus on parallel pricing behaviors in the wholesale fuel market. By employing unsupervised learning techniques, this research aims to identify patterns indicative of collusion—referred to as collusion markers—within time series data. This paper outlines a comprehensive screening research plan based on the CRISP-DM model, detailing phases from business understanding to monitoring. It emphasizes the significance of machine learning methods, including distance measures, motifs, discords, and semantic segmentation, in uncovering these patterns. A case study of the Polish wholesale fuel market illustrates the practical application of these techniques, demonstrating how anomalies and regime changes in price behavior can signal potential collusion. The findings suggest that unsupervised machine learning methods offer a robust alternative to traditional statistical and econometric tools, particularly due to their ability to process large and complex datasets without predefined models. This research concludes that these methods can significantly enhance the detection of collusive behaviors, providing valuable insights for antitrust authorities.

Suggested Citation

  • Sylwester Bejger, 2024. "Machine Learning in Cartel Screening—The Case of Parallel Pricing in a Fuel Wholesale Market," Energies, MDPI, vol. 17(16), pages 1-17, August.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:16:p:4184-:d:1461545
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    References listed on IDEAS

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    1. Gérard Biau & Erwan Scornet, 2016. "A random forest guided tour," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 197-227, June.
    2. Juan Luis Jimenez Gonzalez & Jordi Perdiguero Garcia, 2011. "Could Transport Costs Be Lower?: The Use Of A Variance Screen To Evaluate Competition In The Petrol Market In Spain," Articles, International Journal of Transport Economics, vol. 38(3).
    3. Bolotova, Yuliya & Connor, John M. & Miller, Douglas J., 2008. "The impact of collusion on price behavior: Empirical results from two recent cases," International Journal of Industrial Organization, Elsevier, vol. 26(6), pages 1290-1307, November.
    4. Gérard Biau & Erwan Scornet, 2016. "Rejoinder on: A random forest guided tour," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 264-268, June.
    5. Sylwester Bejger, 2021. "Competition in a Wholesale Fuel Market—The Impact of the Structural Changes Caused by COVID-19," Energies, MDPI, vol. 14(14), pages 1-26, July.
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