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Application of time series techniques in relevant market delimitation

Author

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  • Cuiabano, Simone
  • Nicolini de Moraes, João Carlos
  • Pinha, Lucas

Abstract

A key issue in the analysis of mergers in antitrust is the relevant market definition. The application of time-series techniques can be useful in this process, since only prices are required for the analysis, allowing for relatively rapid estimates. The objective of this work is to make an overview of the main time-series techniques used in the delineation of the relevant markets and make a qualitative analysis of the votes and technical notes of the cases involving the discussion of the application of time series in the relevant market definition submitted to the Brazilian Antitrust Authority (CADE). In this analysis, despite of its importance, there is a clear need for a careful assessment so the model can deliver robust and believable results. In addition, the importance of the hypothetical monopolist test and simulation methodologies for merger impact analysis are hardly replaced by time series techniques accordingly to Cade’s recent decisions.

Suggested Citation

  • Cuiabano, Simone & Nicolini de Moraes, João Carlos & Pinha, Lucas, 2017. "Application of time series techniques in relevant market delimitation," TSE Working Papers 17-801, Toulouse School of Economics (TSE).
    • Handle: RePEc:tse:wpaper:31666
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    References listed on IDEAS

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    1. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    2. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, June.
    3. Haldrup, Niels, "undated". "Empirical analysis of price data in the delineation of the relevant geographical market in competition analysis," Economics Working Papers 2003-9, Department of Economics and Business Economics, Aarhus University.
    4. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    5. Mario Forni, 2004. "Using Stationarity Tests in Antitrust Market Definition," American Law and Economics Review, American Law and Economics Association, vol. 6(2), pages 441-464.
    6. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    7. MacKinnon, James G & Haug, Alfred A & Michelis, Leo, 1999. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 563-577, Sept.-Oct.
    8. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521839198, June.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • K21 - Law and Economics - - Regulation and Business Law - - - Antitrust Law
    • L40 - Industrial Organization - - Antitrust Issues and Policies - - - General

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