IDEAS home Printed from https://ideas.repec.org/p/smu/ecowpa/1101.html
   My bibliography  Save this paper

Efficiency or Competition? A Structural Analysis of Canada's AWS Auction and the Set-Aside Provision

Author

Listed:
  • Kyle Hyndman

    (Southern Methodist University)

  • Christopher F. Parmeter

    (University of Miami)

Abstract

In 2008 Industry Canada auctioned 105MHz of spectrum to a group of bidders that included incumbents and potential new entrants into the Canadian mobile phone market, raising $4.25 billion. In an effort to promote new entry, 40MHz of spectrum was set-aside for new entrants. We adapt the methodology of Bajari and Fox (2009) to the Canadian auction setting in an effort to estimate the implicit cost (in terms of lower auction efficiency) of this policy. Our results indicate that revenue would have been approximately 10% higher without the set-aside.

Suggested Citation

  • Kyle Hyndman & Christopher F. Parmeter, 2011. "Efficiency or Competition? A Structural Analysis of Canada's AWS Auction and the Set-Aside Provision," Departmental Working Papers 1101, Southern Methodist University, Department of Economics.
    • Handle: RePEc:smu:ecowpa:1101
    as

    Download full text from publisher

    File URL: https://ftp1.economics.smu.edu/WorkingPapers/2011/HYNDMAN/HYNDMAN-2011-02.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Horowitz, Joel L., 2002. "Bootstrap critical values for tests based on the smoothed maximum score estimator," Journal of Econometrics, Elsevier, vol. 111(2), pages 141-167, December.
    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. Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
    2. Kaplan, David M. & Sun, Yixiao, 2017. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," Econometric Theory, Cambridge University Press, vol. 33(1), pages 105-157, February.
    3. Tom Ahn, 2017. "Strategic Matching of Teachers and Schools with (and without) Accountability Pressure," Education Finance and Policy, MIT Press, vol. 12(4), pages 516-535, Fall.
    4. Lei, J., 2013. "Smoothed Spatial Maximum Score Estimation of Spatial Autoregressive Binary Choice Panel Models," Other publications TiSEM d63bf400-7ff2-4a1c-8067-1, Tilburg University, School of Economics and Management.
    5. Costas Meghir & Luigi Pistaferri, 2004. "Income Variance Dynamics and Heterogeneity," Econometrica, Econometric Society, vol. 72(1), pages 1-32, January.
    6. Jeremy T. Fox, 2018. "Estimating matching games with transfers," Quantitative Economics, Econometric Society, vol. 9(1), pages 1-38, March.
    7. Xiaofeng Lv & Rui Li, 2013. "Smoothed empirical likelihood analysis of partially linear quantile regression models with missing response variables," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(4), pages 317-347, October.
    8. Lei, J., 2013. "Smoothed Spatial Maximum Score Estimation of Spatial Autoregressive Binary Choice Panel Models," Discussion Paper 2013-061, Tilburg University, Center for Economic Research.
    9. Chen, Songnian & Zhang, Hanghui, 2015. "Binary quantile regression with local polynomial smoothing," Journal of Econometrics, Elsevier, vol. 189(1), pages 24-40.
    10. Chen, Xirong & Gao, Wenzheng & Li, Zheng, 2018. "A data-driven bandwidth selection method for the smoothed maximum score estimator," Economics Letters, Elsevier, vol. 170(C), pages 24-26.
    11. Yan, Jin & Yoo, Hong Il, 2019. "Semiparametric estimation of the random utility model with rank-ordered choice data," Journal of Econometrics, Elsevier, vol. 211(2), pages 414-438.
    12. Yoshihiko Nishiyama & Peter M. Robinson, 2005. "The Bootstrap and the Edgeworth Correction for Semiparametric Averaged Derivatives," Econometrica, Econometric Society, vol. 73(3), pages 903-948, May.
    13. Francisco Alvarez-Cuadrado, 2006. "Improving The Efficiency And Robustness Of The Smoothed Maximum Score Estimator," Departmental Working Papers 2004-01, McGill University, Department of Economics.
    14. Marcin Owczarczuk, 2015. "Improving the Effectiveness of Maximum Score Estimators for Binary Regression Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 7(4), pages 205-217, December.
    15. Maurizio Mazzocco & Shiv Saini, 2006. "Testing Efficient Risk Sharing with Heterogeneous Risk Preferences: Semi-parametric Tests with an Application to Village Economies," 2006 Meeting Papers 108, Society for Economic Dynamics.
    16. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    17. Sadat Reza & Paul Rilstone, 2019. "Smoothed Maximum Score Estimation of Discrete Duration Models," JRFM, MDPI, vol. 12(2), pages 1-16, April.
    18. Horowitz, Joel L., 2004. "Semiparametric models," Papers 2004,17, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    19. Marcin Owczarczuk, 2009. "Maximum Score Type Estimators," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(1), pages 7-34, March.
    20. Chen, Qihui & Fang, Zheng, 2019. "Inference on functionals under first order degeneracy," Journal of Econometrics, Elsevier, vol. 210(2), pages 459-481.

    More about this item

    Keywords

    Spectrum Auction; Set-Aside; Efficiency;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions

    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:smu:ecowpa:1101. 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: Ömer Özak (email available below). General contact details of provider: http://www.smu.edu/economics .

    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.