IDEAS home Printed from https://ideas.repec.org/a/kap/ejlwec/v34y2012i2p241-263.html
   My bibliography  Save this article

Using accounting data in cartel damage calculations: blessing or menace?

Author

Listed:
  • Johannes Paha

Abstract

Standard methods for calculating cartel-damage rely on data of prices charged and quantity sold. Such data may not easily be available. In this paper, it is shown that accounting data can be used for computing a lower bound for cartel-damage. Previous literature indicates that economic profits can hardly be inferred from accounting data. Therefore, it is shown under which econometrically testable assumptions on accounting costs a meaningful lower bound for cartel-damage can consistently be estimated when using accounting data. However, the aggregation-level and the publication-frequency of accounting data pose a challenge to the estimation of cartel-damage. A further challenge is to appropriately reflect the strength respectively effectiveness of the collusive agreement in the specification of any such estimation. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Johannes Paha, 2012. "Using accounting data in cartel damage calculations: blessing or menace?," European Journal of Law and Economics, Springer, vol. 34(2), pages 241-263, October.
  • Handle: RePEc:kap:ejlwec:v:34:y:2012:i:2:p:241-263
    DOI: 10.1007/s10657-011-9253-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10657-011-9253-8
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10657-011-9253-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. John Haltiwanger & Joseph E. Harrington Jr., 1991. "The Impact of Cyclical Demand Movements on Collusive Behavior," RAND Journal of Economics, The RAND Corporation, vol. 22(1), pages 89-106, Spring.
    2. Rotemberg, Julio J & Saloner, Garth, 1986. "A Supergame-Theoretic Model of Price Wars during Booms," American Economic Review, American Economic Association, vol. 76(3), pages 390-407, June.
    3. Paul A. Grout & Anna Zalewska, 2008. "Measuring The Rate Of Return For Competition Law," Journal of Competition Law and Economics, Oxford University Press, vol. 4(1), pages 155-176.
    4. Long, William F & Ravenscraft, David J, 1984. "The Misuse of Accounting Rates of Return: Comment," American Economic Review, American Economic Association, vol. 74(3), pages 494-500, June.
    5. Green, Edward J & Porter, Robert H, 1984. "Noncooperative Collusion under Imperfect Price Information," Econometrica, Econometric Society, vol. 52(1), pages 87-100, January.
    6. Fisher, Franklin M, 1984. "The Misuse of Accounting Rates of Return: Reply," American Economic Review, American Economic Association, vol. 74(3), pages 509-517, June.
    7. Johannes Paha, 2011. "Empirical methods in the analysis of collusion," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 38(3), pages 389-415, July.
    8. Fisher, Franklin M & McGowan, John J, 1983. "On the Misuse of Accounting Rates of Return to Infer Monopoly Profits," American Economic Review, American Economic Association, vol. 73(1), pages 82-97, March.
    9. Marshall, Robert C. & Marx, Leslie M. & Raiff, Matthew E., 2008. "Cartel price announcements: The vitamins industry," International Journal of Industrial Organization, Elsevier, vol. 26(3), pages 762-802, May.
    10. Bartholdy, Jan & Peare, Paula, 2005. "Estimation of expected return: CAPM vs. Fama and French," International Review of Financial Analysis, Elsevier, vol. 14(4), pages 407-427.
    11. Peasnell, Kenneth V., 1996. "Using accounting data to measure the economic performance of firms," Journal of Accounting and Public Policy, Elsevier, vol. 15(4), pages 291-303.
    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. Katsoulacos, Yannis & Motchenkova, Evgenia & Ulph, David, 2020. "Combining cartel penalties and private damage actions: The impact on cartel prices," International Journal of Industrial Organization, Elsevier, vol. 73(C).

    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. Johannes Paha, 2010. "Simulation and Prosecution of a Cartel with Endogenous Cartel Formation," MAGKS Papers on Economics 201007, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    2. Juan‐Pablo Montero & Juan Ignacio Guzman, 2010. "Output‐Expanding Collusion In The Presence Of A Competitive Fringe," Journal of Industrial Economics, Wiley Blackwell, vol. 58(1), pages 106-126, March.
    3. Kaplow, Louis & Shapiro, Carl, 2007. "Antitrust," Handbook of Law and Economics, in: A. Mitchell Polinsky & Steven Shavell (ed.), Handbook of Law and Economics, edition 1, volume 2, chapter 15, pages 1073-1225, Elsevier.
    4. Fabra, Natalia & Toro, Juan, 2005. "Price wars and collusion in the Spanish electricity market," International Journal of Industrial Organization, Elsevier, vol. 23(3-4), pages 155-181, April.
    5. Bagwell, Kyle & Wolinsky, Asher, 2002. "Game theory and industrial organization," Handbook of Game Theory with Economic Applications, in: R.J. Aumann & S. Hart (ed.), Handbook of Game Theory with Economic Applications, edition 1, volume 3, chapter 49, pages 1851-1895, Elsevier.
    6. Abolmassov Aleksandr & Kolodin Denis, 2003. "Structural changes in Russian electricity market," EERC Working Paper Series 01-016e, EERC Research Network, Russia and CIS.
    7. Andrea Vaona, 2016. "A nonparametric panel data approach to the cyclical dynamics of price-cost margins in the fourth Kondratieff wave," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 6(2), pages 155-170, August.
    8. Marcel Canoy & Patrick Rey & Eric van Damme, 2004. "Dominance and Monopolization," Chapters, in: Manfred Neumann & Jürgen Weigand (ed.), The International Handbook of Competition, chapter 7, Edward Elgar Publishing.
    9. Labrecciosa Paola & Colombo Luca, 2010. "Technology Uncertainty and Market Collusion," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-17, March.
    10. Chaim Fershtman & Ariel Pakes, 2000. "A Dynamic Oligopoly with Collusion and Price Wars," RAND Journal of Economics, The RAND Corporation, vol. 31(2), pages 207-236, Summer.
    11. Pedro Dal Bó, 2007. "Tacit collusion under interest rate fluctuations," RAND Journal of Economics, RAND Corporation, vol. 38(2), pages 533-540, June.
    12. Robert Gagné & Simon van Norden & Bruno Versaevel, 2003. "Testing Optimal Punishment Mechanisms Under Price Regulation: the Case of the Retail Market for Gasoline," CIRANO Working Papers 2003s-57, CIRANO.
    13. Kyle Bagwell & Robert Staiger, 1997. "Collusion Over the Business Cycle," RAND Journal of Economics, The RAND Corporation, vol. 28(1), pages 82-106, Spring.
    14. Knittel, Christopher R. & Lepore, Jason J., 2010. "Tacit collusion in the presence of cyclical demand and endogenous capacity levels," International Journal of Industrial Organization, Elsevier, vol. 28(2), pages 131-144, March.
    15. John J. Kania, 1987. "Profitability and Market Power in Industries with Regional-Local Markets," The American Economist, Sage Publications, vol. 31(2), pages 29-34, October.
    16. Carmen García & Joan Ramon Borrell & José Manuel Ordóñez-de-Haro & Juan Luis Jiménez, 2022. "Managers’ expectations, business cycles and cartels’ life cycle," European Journal of Law and Economics, Springer, vol. 53(3), pages 451-484, June.
    17. Granlund, David & Rudholm, Niklas, 2023. "Calculating the probability of collusion based on observed price patterns," Umeå Economic Studies 1014, Umeå University, Department of Economics, revised 13 Oct 2023.
    18. Philippe Cyrenne, 1999. "On Antitrust Enforcement and the Deterrence of Collusive Behaviour," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 14(3), pages 257-272, May.
    19. Ghosal, Vivek, 2000. "Product market competition and the industry price-cost markup fluctuations:: role of energy price and monetary changes," International Journal of Industrial Organization, Elsevier, vol. 18(3), pages 415-444, April.
    20. Woo-Hyung Hong & Daeyong Lee, 2020. "Asymmetric pricing dynamics with market power: investigating island data of the retail gasoline market," Empirical Economics, Springer, vol. 58(5), pages 2181-2221, May.

    More about this item

    Keywords

    Cartel damages; Accounting data; Collusion; Cartel prosecution; D43; L12; L13; L41;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • L12 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Monopoly; Monopolization Strategies
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices

    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:kap:ejlwec:v:34:y:2012:i:2:p:241-263. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.