IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2310.04576.html
   My bibliography  Save this paper

Challenges in Statistically Rejecting the Perfect Competition Hypothesis Using Imperfect Competition Data

Author

Listed:
  • Yuri Matsumura
  • Suguru Otani

Abstract

We theoretically prove why statistically rejecting the null hypothesis of perfect competition is challenging, known as a common problem in the literature. We also assess the finite sample performance of the conduct parameter test in homogeneous goods markets, showing that statistical power increases with the number of markets, a larger conduct parameter, and a stronger demand rotation instrument. However, even with a moderate number of markets and five firms, rejecting the null hypothesis of perfect competition remains difficult, irrespective of instrument strength or the use of optimal instruments. Our findings suggest that empirical results failing to reject perfect competition are due to the limited number of markets rather than methodological shortcomings.

Suggested Citation

  • Yuri Matsumura & Suguru Otani, 2023. "Challenges in Statistically Rejecting the Perfect Competition Hypothesis Using Imperfect Competition Data," Papers 2310.04576, arXiv.org, revised Aug 2024.
    • Handle: RePEc:arx:papers:2310.04576
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2310.04576
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Steen, Frode & Salvanes, Kjell G., 1999. "Testing for market power using a dynamic oligopoly model," International Journal of Industrial Organization, Elsevier, vol. 17(2), pages 147-177, February.
    2. Shaffer, Sherrill, 1993. "A Test of Competition in Canadian Banking," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 25(1), pages 49-61, February.
    3. 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)

    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. Manthos D. Delis & K. Christos Staikouras & Panagiotis T. Varlagas, 2008. "On the Measurement of Market Power in the Banking Industry," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(7‐8), pages 1023-1047, September.
    2. Nguyen-Ones, Mai & Steen, Frode, 2018. "Measuring Market Power in Gasoline Retailing: A Market- or Station Phenomenon?," Discussion Paper Series in Economics 6/2018, Norwegian School of Economics, Department of Economics.
    3. Manthos D. Delis & K. Christos Staikouras & Panagiotis T. Varlagas, 2008. "On the Measurement of Market Power in the Banking Industry," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(7‐8), pages 1023-1047, September.
    4. Samantas, Ioannis, 2013. "Income-specific estimates of competition in European banking," MPRA Paper 51098, University Library of Munich, Germany.
    5. Nguyen-Ones , Mai & Steen, Frode, 2018. "Market Power in Retail Gasoline Markets," Discussion Paper Series in Economics 21/2019, Norwegian School of Economics, Department of Economics, revised 01 Jul 2019.
    6. Aydın ÇELEN, 2019. "Anticompetitive Effects of the Banking Cartel in Turkish Loan MarketAbstract: The aim of this paper is to measure the effect of the banking cartel on the competition in the Turkish loan market. In doi," Sosyoekonomi Journal, Sosyoekonomi Society, issue 27(40).
    7. Chang, Shun-Chiao & Chang, Jui-Chuan Della & Huang, Tai-Hsin, 2012. "Assessing market power in the U.S. commercial banking industry under deregulation," Economic Modelling, Elsevier, vol. 29(5), pages 1558-1565.
    8. Toolsema, Linda A., 2002. "Competition in the Dutch consumer credit market," Journal of Banking & Finance, Elsevier, vol. 26(11), pages 2215-2229, November.
    9. Hansen, Lars Peter, 2013. "Uncertainty Outside and Inside Economic Models," Nobel Prize in Economics documents 2013-7, Nobel Prize Committee.
    10. Bruce N. Lehmann, 2005. "The Role of Beliefs in Inference for Rational Expectations Models," NBER Working Papers 11758, National Bureau of Economic Research, Inc.
    11. Ho, Chun-Yu, 2012. "Market structure, welfare, and banking reform in China," Journal of Comparative Economics, Elsevier, vol. 40(2), pages 291-313.
    12. Menzel, Konrad, 2014. "Consistent estimation with many moment inequalities," Journal of Econometrics, Elsevier, vol. 182(2), pages 329-350.
    13. Verdier Valentin, 2018. "Local Semi-Parametric Efficiency of the Poisson Fixed Effects Estimator," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-10, January.
    14. Murinde, Victor & Zhao, Tianshu, 2009. "Bank competition, risk taking and productive efficiency: Evidence from Nigeria's banking reform experiments," Stirling Economics Discussion Papers 2009-23, University of Stirling, Division of Economics.
    15. Arthur Lewbel, 2012. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80.
    16. Kirill Borusyak & Peter Hull & Xavier Jaravel, 2023. "Design-Based Identification with Formula Instruments: A Review," NBER Working Papers 31393, National Bureau of Economic Research, Inc.
    17. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    18. Xiaohong Chen & Victor Chernozhukov & Sokbae Lee & Whitney K. Newey, 2014. "Local Identification of Nonparametric and Semiparametric Models," Econometrica, Econometric Society, vol. 82(2), pages 785-809, March.
    19. 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.
    20. Joachim Inkmann, 2000. "Finite Sample Properties of One-Step, Two-Step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation," Econometric Society World Congress 2000 Contributed Papers 0332, Econometric Society.

    More about this item

    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:arx:papers:2310.04576. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.