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How to Use Data Science in Economics -- a Classroom Game Based on Cartel Detection

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  • Hannes Wallimann
  • Silvio Sticher

Abstract

We present a classroom game that integrates economics and data-science competencies. In the first two parts of the game, participants assume the roles of firms in a procurement market, where they must either adopt competitive behaviors or have the option to engage in collusion. Success in these parts hinges on their comprehension of market dynamics. In the third part of the game, participants transition to the role of competition-authority members. Drawing from recent literature on machine-learning-based cartel detection, they analyze the bids for patterns indicative of collusive (cartel) behavior. In this part of the game, success depends on data-science skills. We offer a detailed discussion on implementing the game, emphasizing considerations for accommodating diverging levels of preexisting knowledge in data science.

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  • Hannes Wallimann & Silvio Sticher, 2024. "How to Use Data Science in Economics -- a Classroom Game Based on Cartel Detection," Papers 2401.14757, arXiv.org.
    • Handle: RePEc:arx:papers:2401.14757
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    References listed on IDEAS

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    1. Correa, Manuel & García-Quero, Fernando & Ortega-Ortega, Marta, 2016. "A role-play to explain cartel behavior: Discussing the oligopolistic market," International Review of Economics Education, Elsevier, vol. 22(C), pages 8-15.
    2. Porter, Robert H & Zona, J Douglas, 1993. "Detection of Bid Rigging in Procurement Auctions," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 518-538, June.
    3. Huber, Martin & Imhof, David, 2019. "Machine learning with screens for detecting bid-rigging cartels," International Journal of Industrial Organization, Elsevier, vol. 65(C), pages 277-301.
    4. Charles A. Holt, 1999. "Teaching Economics with Classroom Experiments: A Symposium," Southern Economic Journal, John Wiley & Sons, vol. 65(3), pages 603-610, January.
    5. David Imhof & Hannes Wallimann, 2021. "Detecting bid-rigging coalitions in different countries and auction formats," Papers 2105.00337, arXiv.org.
    6. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    7. Rieko Ishii, 2014. "Bid Roundness Under Collusion in Japanese Procurement Auctions," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 44(3), pages 241-254, May.
    8. David Imhof & Yavuz Karagök & Samuel Rutz, 2018. "Screening For Bid Rigging—Does It Work?," Journal of Competition Law and Economics, Oxford University Press, vol. 14(2), pages 235-261.
    9. Imhof, David & Wallimann, Hannes, 2021. "Detecting bid-rigging coalitions in different countries and auction formats," International Review of Law and Economics, Elsevier, vol. 68(C).
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