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Algorithmic Pricing What Implications for Competition Policy?

  • Emilio Calvano
  • Giacomo CalzolariEmail author
  • Vincenzo Denicolò
  • Sergio Pastorello
Article

Abstract

Pricing decisions are increasingly in the “hands” of artificial algorithms. Scholars and competition authorities have voiced concerns that those algorithms are capable of sustaining collusive outcomes more effectively than can human decision makers. If this is so, then our traditional policy tools for fighting collusion may have to be reconsidered. We discuss these issues by critically surveying the relevant law, economics, and computer science literature.

Keywords

Algorithmic pricing Competition policy Artificial intelligence Machine learning Collusion 

JEL Classification

D42 D82 L42 

Notes

Acknowledgements

We thank the editor Larry White, the guest editors Christos Genakos, Michael Pollitt, and the discussant Patrick Legros and participants at the conference “Celebrating 25 Years of the EU Single Market” organized by the Review of Industrial Organization in Cambridge Judge Business School, 2018. Financial support from the Digital Chair of the Toulouse school of economics is gratefully acknowledged.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Dipartimento di Scienze EconomicheUniversity of BolognaBolognaItaly
  2. 2.CEPRLondonUK
  3. 3.Toulouse School of EconomicsToulouseFrance
  4. 4.European University Institute and University of BolognaFlorenceItaly

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