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Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market

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Listed:
  • Stephanie Assad
  • Robert Clark
  • Daniel Ershov
  • Lei Xu

Abstract

Economic theory provides ambiguous and conflicting predictions about the association between algorithmic pricing and competition. In this paper we provide the first empirical analysis of this relationship. We study Germany’s retail gasoline market where algorithmic-pricing software became widely available by mid-2017, and for which we have access to comprehensive, high-frequency price data. Because adoption dates are unknown, we identify gas stations that adopt algorithmic-pricing software by testing for structural breaks in markers associated with algo-rithmic pricing. We find a large number of station-level structural breaks around the suspected time of large-scale adoption. Using this information we investigate the impact of adoption on outcomes linked to competition. Because station-level adoption is endogenous, we use brand headquarter-level adoption decisions as instruments. Our IV results show that adoption in-creases margins by 9%, but only in non-monopoly markets. Restricting attention to duopoly markets, we find that market-level margins do not change when only one of the two stations adopts, but increase by 28% in markets where both do. These results suggest that AI adoption has a significant effect on competition.

Suggested Citation

  • Stephanie Assad & Robert Clark & Daniel Ershov & Lei Xu, 2020. "Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market," CESifo Working Paper Series 8521, CESifo.
    • Handle: RePEc:ces:ceswps:_8521
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    1. Robert Clark & Jean-Fran?ois Houde, 2013. "Collusion with Asymmetric Retailers: Evidence from a Gasoline Price-Fixing Case," American Economic Journal: Microeconomics, American Economic Association, vol. 5(3), pages 97-123, August.
    2. Slade, Margaret E, 1987. "Interfirm Rivalry in a Repeated Game: An Empirical Test of Tacit Collusion," Journal of Industrial Economics, Wiley Blackwell, vol. 35(4), pages 499-516, June.
    3. Francesco Decarolis & Gabriele Rovigatti, 2021. "From Mad Men to Maths Men: Concentration and Buyer Power in Online Advertising," American Economic Review, American Economic Association, vol. 111(10), pages 3299-3327, October.
    4. Severin Boreinstein & Andrea Shepard, 1996. "Dynamic Pricing in Retail Gasoline Markets," RAND Journal of Economics, The RAND Corporation, vol. 27(3), pages 429-451, Autumn.
    5. Michael Gelman & Yuriy Gorodnichenko & Shachar Kariv & Dmitri Koustas & Matthew D. Shapiro & Dan Silverman & Steven Tadelis, 2023. "The Response of Consumer Spending to Changes in Gasoline Prices," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(2), pages 129-160, April.
    6. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "The Economics of Artificial Intelligence: An Agenda," NBER Books, National Bureau of Economic Research, Inc, number agra-1.
    7. Hal Varian, 2018. "Artificial Intelligence, Economics, and Industrial Organization," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 399-419, National Bureau of Economic Research, Inc.
    8. David P. Byrne & Nicolas de Roos, 2019. "Learning to Coordinate: A Study in Retail Gasoline," American Economic Review, American Economic Association, vol. 109(2), pages 591-619, February.
    9. Benjamin Reed Shiller, 2013. "First Degree Price Discrimination Using Big Data," Working Papers 58, Brandeis University, Department of Economics and International Business School, revised Jan 2014.
    10. Robert Clark & Jean-François Houde, 2014. "The Effect of Explicit Communication on pricing: Evidence from the Collapse of a Gasoline Cartel," Journal of Industrial Economics, Wiley Blackwell, vol. 62(2), pages 191-228, June.
    11. Agrawal, Ajay & Gans, Joshua & Goldfarb, Avi (ed.), 2019. "The Economics of Artificial Intelligence," National Bureau of Economic Research Books, University of Chicago Press, number 9780226613338, September.
    12. Zhongmin Wang, 2009. "(Mixed) Strategy in Oligopoly Pricing: Evidence from Gasoline Price Cycles Before and Under a Timing Regulation," Journal of Political Economy, University of Chicago Press, vol. 117(6), pages 987-1030, December.
    13. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    14. Zhongmin Wang, 2008. "Collusive Communication and Pricing Coordination in a Retail Gasoline Market," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 32(1), pages 35-52, February.
    15. Waltman, Ludo & Kaymak, Uzay, 2008. "Q-learning agents in a Cournot oligopoly model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3275-3293, October.
    16. Carsten J. Crede, 2019. "A Structural Break Cartel Screen for Dating and Detecting Collusion," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 54(3), pages 543-574, May.
    17. Jeanine Miklós-Thal & Catherine Tucker, 2019. "Collusion by Algorithm: Does Better Demand Prediction Facilitate Coordination Between Sellers?," Management Science, INFORMS, vol. 65(4), pages 1552-1561, April.
    18. Ben Shiller & Joel Waldfogel, 2011. "Music for a Song: An Empirical Look at Uniform Pricing and Its Alternatives," Journal of Industrial Economics, Wiley Blackwell, vol. 59(4), pages 630-660, December.
    19. William L. Cooper & Tito Homem-de-Mello & Anton J. Kleywegt, 2015. "Learning and Pricing with Models That Do Not Explicitly Incorporate Competition," Operations Research, INFORMS, vol. 63(1), pages 86-103, February.
    20. Can Erutku & Vincent A. Hildebrand, 2010. "Conspiracy at the Pump," Journal of Law and Economics, University of Chicago Press, vol. 53(1), pages 223-237, February.
    21. Catherine Tucker, 2008. "Identifying Formal and Informal Influence in Technology Adoption with Network Externalities," Management Science, INFORMS, vol. 54(12), pages 2024-2038, December.
    22. Pai, Mallesh & Hansen, Karsten, 2020. "Algorithmic Collusion: Supra-competitive Prices via Independent Algorithms," CEPR Discussion Papers 14372, C.E.P.R. Discussion Papers.
    23. Margaret E. Slade, 1992. "Vancouver's Gasoline-Price Wars: An Empirical Exercise in Uncovering Supergame Strategies," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 59(2), pages 257-276.
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    More about this item

    Keywords

    artificial intelligence; pricing-algorithms; collusion; retail gasoline;
    All these keywords.

    JEL classification:

    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels

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