IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-03352449.html
   My bibliography  Save this paper

Market Entry, Fighting Brands and Tacit Collusion: Evidence from the French Mobile Telecommunications Market

Author

Listed:
  • Marc Bourreau

    (SES - Département Sciences Economiques et Sociales - Télécom ParisTech, ECOGE - Economie Gestion - I3 SES - Institut interdisciplinaire de l’innovation de Telecom Paris - Télécom ParisTech - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Yutec Sun
  • Frank Verboven

Abstract

We study a major new entry in the French mobile telecommunications market, followed by the introduction of fighting brands by the three incumbents. Using an empirical oligopoly model, we find that the incumbents' fighting brand strategies are difficult to rationalize as unilateral best responses. Instead, their strategies are consistent with a breakdown of tacit semi-collusion: before entry, the incumbents could successfully coordinate on restricting product variety to avoid cannibalization; after entry, this outcome became harder to sustain because of increased business stealing incentives. Consumers gained considerably from the added variety and, to a lesser extent, from the incumbents' price responses.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Marc Bourreau & Yutec Sun & Frank Verboven, 2021. "Market Entry, Fighting Brands and Tacit Collusion: Evidence from the French Mobile Telecommunications Market," Post-Print halshs-03352449, HAL.
  • Handle: RePEc:hal:journl:halshs-03352449
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Reynaert, Mathias & Verboven, Frank, 2014. "Improving the performance of random coefficients demand models: The role of optimal instruments," Journal of Econometrics, Elsevier, vol. 179(1), pages 83-98.
    2. Sanderson, Eleanor & Windmeijer, Frank, 2016. "A weak instrument F-test in linear IV models with multiple endogenous variables," Journal of Econometrics, Elsevier, vol. 190(2), pages 212-221.
    3. Steven T. Berry & Philip A. Haile, 2014. "Identification in Differentiated Products Markets Using Market Level Data," Econometrica, Econometric Society, vol. 82, pages 1749-1797, September.
    4. Justin P. Johnson & David P. Myatt, 2003. "Multiproduct Quality Competition: Fighting Brands and Product Line Pruning," American Economic Review, American Economic Association, vol. 93(3), pages 748-774, June.
    5. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    6. Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang, Shengxing & Vialle, Pierre & Whalley, Jason, 2022. "Is disruption the second time around harder to do? The entry of Iliad into the Italian telecommunications market," 31st European Regional ITS Conference, Gothenburg 2022: Reining in Digital Platforms? Challenging monopolies, promoting competition and developing regulatory regimes 265674, International Telecommunications Society (ITS).
    2. Marcoux, Mathieu, 2022. "Strategic interactions in mobile network investment with a new entrant and unobserved heterogeneity," International Journal of Industrial Organization, Elsevier, vol. 82(C).
    3. Marc Bourreau & Yutec Sun, 2022. "Competition and Quality: Evidence from the Entry of Mobile Network Service," Working Papers 22-04, NET Institute.
    4. Steinbach, Sandro, 2023. "The Corporatization of Veterinary Medicine: An Empirical Analysis of Its Impact on Independent Practices," 2023 Annual Meeting, July 23-25, Washington D.C. 335481, Agricultural and Applied Economics Association.
    5. Martin, Simon & Schmal, W. Benedikt, 2021. "Collusive compensation schemes aided by algorithms," DICE Discussion Papers 375, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    6. Pál, László & Sándor, Zsolt, 2023. "Comparing procedures for estimating random coefficient logit demand models with a special focus on obtaining global optima," International Journal of Industrial Organization, Elsevier, vol. 88(C).
    7. Kandelhardt, Johannes, 2023. "Flexible estimation of random coefficient logit models of differentiated product demand," DICE Discussion Papers 399, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Brett Hollenbeck & Kosuke Uetake, 2021. "Taxation and market power in the legal marijuana industry," RAND Journal of Economics, RAND Corporation, vol. 52(3), pages 559-595, September.
    2. Verboven, Frank & Bourreau, Marc & Sun, Yutec, 2018. "Market Entry, Fighting Brands and Tacit Collusion: The Case of the French Mobile Telecommunications Market," CEPR Discussion Papers 12866, C.E.P.R. Discussion Papers.
    3. Laura Grigolon, 2021. "Blurred boundaries: A flexible approach for segmentation applied to the car market," Quantitative Economics, Econometric Society, vol. 12(4), pages 1273-1305, November.
    4. Rodrigo Adão & Costas Arkolakis & Federico Esposito, 2019. "General Equilibrium Effects in Space: Theory and Measurement," NBER Working Papers 25544, National Bureau of Economic Research, Inc.
    5. Mogens Fosgerau & Julien Monardo & André de Palma, 2019. "The Inverse Product Differentiation Logit Model," Working Papers hal-02183411, HAL.
    6. Dearing, Adam, 2022. "Estimating structural demand and supply models using tax rates as instruments," Journal of Public Economics, Elsevier, vol. 205(C).
    7. Wang, Ao, 2021. "A BLP Demand Model of Product-Level Market Shares with Complementarity," The Warwick Economics Research Paper Series (TWERPS) 1351, University of Warwick, Department of Economics.
    8. Øyvind Thomassen & Howard Smith & Stephan Seiler & Pasquale Schiraldi, 2017. "Multi-category Competition and Market Power: A Model of Supermarket Pricing," American Economic Review, American Economic Association, vol. 107(8), pages 2308-2351, August.
    9. Amit Gandhi & Jean-François Houde, 2019. "Measuring Substitution Patterns in Differentiated-Products Industries," NBER Working Papers 26375, National Bureau of Economic Research, Inc.
    10. Matthew Backus & Christopher Conlon & Michael Sinkinson, 2021. "Common Ownership and Competition in the Ready-to-Eat Cereal Industry," NBER Working Papers 28350, National Bureau of Economic Research, Inc.
    11. Rodrigo Ad'o & Costas Arkolakis & Federico Esp'sito, 2019. "Spatial Linkages, Global Shocks, and Local Labor Markets: Theory and Evidence," Cowles Foundation Discussion Papers 2163, Cowles Foundation for Research in Economics, Yale University.
    12. Christopher Conlon & Jeff Gortmaker, 2020. "Best practices for differentiated products demand estimation with PyBLP," RAND Journal of Economics, RAND Corporation, vol. 51(4), pages 1108-1161, December.
    13. Fernando Broner & Daragh Clancy & Aitor Erce & Alberto Martin, 2022. "Fiscal Multipliers and Foreign Holdings of Public Debt [When Should You Adjust Standard Errors for Clustering?]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(3), pages 1155-1204.
    14. Whitney K. Newey & Frank Windmeijer, 2005. "GMM with many weak moment conditions," CeMMAP working papers CWP18/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2016. "Inference in High-Dimensional Panel Models With an Application to Gun Control," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 590-605, October.
    16. A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012. "Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain," Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
    17. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2022. "Media-expressed tone, option characteristics, and stock return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    18. Blundell, Richard & Bond, Stephen, 2023. "Reprint of: Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 234(S), pages 38-55.
    19. Steven T. Berry & Philip A. Haile, 2021. "Foundations of Demand Estimation," Cowles Foundation Discussion Papers 2301, Cowles Foundation for Research in Economics, Yale University.
    20. Áureo De Paula & Gil Shapira & Petra E. Todd, 2014. "How Beliefs About Hiv Status Affect Risky Behaviors: Evidence From Malawi," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(6), pages 944-964, September.

    More about this item

    JEL classification:

    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L21 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Business Objectives of the Firm
    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:halshs-03352449. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.