IDEAS home Printed from https://ideas.repec.org/p/tse/wpaper/31666.html
   My bibliography  Save this paper

Application of time series techniques in relevant market delimitation

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.tse-fr.eu/sites/default/files/TSE/documents/doc/wp/2017/wp_tse_801.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    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.
    Full references (including those not matched with items on IDEAS)

    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. Algieri, Bernardina, 2013. "A Roller Coaster Ride: an empirical investigation of the main drivers of wheat price," Discussion Papers 145556, University of Bonn, Center for Development Research (ZEF).
    2. Pedro M. G. Martins, 2010. "Fiscal Dynamics in Ethiopia: The Cointegrated VAR Model with Quarterly Data," Working Paper Series 0910, Department of Economics, University of Sussex Business School.
    3. Elżbieta Szaruga & Elżbieta Załoga, 2022. "Environmental Management from the Point of View of the Energy Intensity of Road Freight Transport and Shocks," IJERPH, MDPI, vol. 19(21), pages 1-22, November.
    4. Batool, Irem & Goldmann, Kathrin, 2021. "The role of public and private transport infrastructure capital in economic growth. Evidence from Pakistan," Research in Transportation Economics, Elsevier, vol. 88(C).
    5. Kaminski, Jermain & Hopp, Christian & Tykvová, Tereza, 2019. "New technology assessment in entrepreneurial financing – Does crowdfunding predict venture capital investments?," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 287-302.
    6. Mohcine Bakhat & Klaas WŸrzburg, 2013. "Co-integration of Oil and Commodity Prices: A Comprehensive ApproachAbstract," Working Papers fa05-2013, Economics for Energy.
    7. Erie Febrian & Aldrin Herwany, 2009. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Economics and Development Studies (WoPEDS) 200911, Department of Economics, Padjadjaran University, revised Sep 2009.
    8. Ansgar Belke & Robert Czudaj, 2010. "Is Euro Area Money Demand (Still) Stable? Cointegrated VAR Versus Single Equation Techniques," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 56(4), pages 285-315.
    9. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2005. "Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study," Trinity Economics Papers tep20021, Trinity College Dublin, Department of Economics.
    10. Bernstein, Ronald & Madlener, Reinhard, 2015. "Short- and long-run electricity demand elasticities at the subsectoral level: A cointegration analysis for German manufacturing industries," Energy Economics, Elsevier, vol. 48(C), pages 178-187.
    11. Srinivasan Palamalai & Kalaivani M. & Christopher Devakumar, 2013. "Stock Market Linkages in Emerging Asia-Pacific Markets," SAGE Open, , vol. 3(4), pages 21582440135, November.
    12. Grau, Aaron Stephan Alexander & Hockmann, Heinrich, 2017. "Estimating oligopsony power on two vertically integrated markets," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 261277, European Association of Agricultural Economists.
    13. repec:zbw:rwirep:0171 is not listed on IDEAS
    14. Bushara, Mohammed O. A. & Abdelmahmod, Murtada Kh. A., 2016. "Efficiency of selected camel markets in Sudan: A multivariate approach (1995-2011)," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 246910, African Association of Agricultural Economists (AAAE).
    15. Jesser PALADINES, 2017. "Oil Price and Real GDP Growth of Ecuador: A Vector Autoregressive Approach," Journal of Economics and Political Economy, KSP Journals, vol. 4(1), pages 71-78, March.
    16. Ebenezer, Appiah Collins & Jatoe, John Baptist D. & Mensa-Bonsu, Akwasi, 2018. "Food Price Sensitivity To Changes In Petroleum Price And Exchange Rate In Ghana: A Cointegration Analysis," 2018 Conference (2nd), August 8-11, Kumasi, Ghana 277791, Ghana Association of Agricultural Economists.
    17. Robert Socha & Piotr Wdowiński, 2018. "Tendencje zmian cen na światowym rynku ropy naftowej po 2000 roku," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 1, pages 103-135.
    18. Le Fur, Eric, 2020. "Dynamics of the global fine art market prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 167-180.
    19. Jun, Sangjoon, 2015. "The Nexus between FDI and Growth in the SAARC Member Countries," East Asian Economic Review, Korea Institute for International Economic Policy, vol. 19(1), pages 39-70, March.
    20. Piotr Wdowiński, 2011. "Model monetarny kursu równowagi złoty/euro: analiza kointegracyjna," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 67-86.
    21. Tweneboah, George & Adam, Anokye M., 2008. "Implications of Oil Price Shocks for Monetary Policy in Ghana: A Vector Error Correction Model," MPRA Paper 11968, University Library of Munich, Germany.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:tse:wpaper:31666. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/tsetofr.html .

    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.