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The Evolution of U.S. Spectrum Values Over Time

Author

Listed:
  • Michelle Connolly

    () (Duke University)

  • Nelson Sa

    () (Brandeis University)

  • Azeem Zaman

    (Harvard University)

  • Chris Roark

    (University of Chicago)

  • Akshaya Trivedi

    (Trinity College,Duke University)

Abstract

We consider 1997 to 2015 data from FCC spectrum auctions related to cellular services to attempt to identify intrinsic spectrum values. Relative to previous literature, we control for license specific auction rules, and introduce measures to separate out technological progress that effectively reduces spectrum scarcity from progress that increases demand. Results confirm that technological changes have led to increases in the relative value of higher frequencies. Surprisingly, 47 percent of these licenses have been won by “small” bidders, representing 27 percent of the real value of these licenses. The use of bidding credits further appears to consistently reduce auction competition.

Suggested Citation

  • Michelle Connolly & Nelson Sa & Azeem Zaman & Chris Roark & Akshaya Trivedi, 2018. "The Evolution of U.S. Spectrum Values Over Time," Working Papers 121, Brandeis University, Department of Economics and International Businesss School.
  • Handle: RePEc:brd:wpaper:121
    as

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    File URL: http://www.brandeis.edu/economics/RePEc/brd/doc/Brandeis_WP121.pdf
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    References listed on IDEAS

    as
    1. Ciccone, Antonio & Hall, Robert E, 1996. "Productivity and the Density of Economic Activity," American Economic Review, American Economic Association, vol. 86(1), pages 54-70, March.
    2. Jeremy T. Fox & Patrick Bajari, 2013. "Measuring the Efficiency of an FCC Spectrum Auction," American Economic Journal: Microeconomics, American Economic Association, vol. 5(1), pages 100-146, February.
    3. Thomas W. Hazlett, 2008. "Property Rights and Wireless License Values," Journal of Law and Economics, University of Chicago Press, vol. 51(3), pages 563-598, August.
    4. Paul Klemperer, 2002. "What Really Matters in Auction Design," Journal of Economic Perspectives, American Economic Association, vol. 16(1), pages 169-189, Winter.
    5. Lawrence M. Ausubel & Peter Cramton & R. Preston McAfee & John McMillan, 1997. "Synergies in Wireless Telephony: Evidence from the Broadband PCS Auctions," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 6(3), pages 497-527, September.
    6. Thomas W. Hazlett & Roberto E. Muñoz, 2009. "A welfare analysis of spectrum allocation policies," RAND Journal of Economics, RAND Corporation, vol. 40(3), pages 424-454, September.
    7. McMillan, John, 1995. "Why auction the spectrum?," Telecommunications Policy, Elsevier, vol. 19(3), pages 191-199, April.
    8. Klemperer, Paul, 2002. "How (not) to run auctions: The European 3G telecom auctions," European Economic Review, Elsevier, vol. 46(4-5), pages 829-845, May.
    9. Gregory Rosston, 2014. "Increasing the Efficiency of Spectrum Allocation," Discussion Papers 13-035, Stanford Institute for Economic Policy Research.
    10. Gregory Rosston, 2014. "Increasing the Efficiency of Spectrum Allocation," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 45(3), pages 221-243, November.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    HSpectrum; spectrum Scarcity; Auctions; FCC; Auction Rules; Mobile Applications; Spectral Efficiency; Broadband Speeds; Closed Auctions; Small Bidders; The Google Effect;

    JEL classification:

    • L5 - Industrial Organization - - Regulation and Industrial Policy
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • K2 - Law and Economics - - Regulation and Business Law

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