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License Complementarity and Package Bidding: The U.S. Spectrum Auctions

Author

Listed:
  • Mo Xiao

    (Eller College of Management, University of Arizona.)

  • Zhe Yuan

    (Alibaba Group)

Abstract

The U.S. spectrum licenses cover geographically distinct areas and are often complementary to each other. A bidder seeking to acquire multiple licenses is then exposed to risks of winning only isolated patches. To allocate licenses more efficiently, the Federal Communications Commission allowed bidders to bid for (predefined) packages of licenses in Auction 73. We estimate the magnitude of license complementarity by modeling the bidding process as an entry game with interdependent markets and evolving bidder belief. Bidders' decisions on bidding (and not bidding) provide bounds on licenses' stand-alone values and complementarity between licenses. We estimate the total complementarity to be around two thirds of the total bidding ($19 billion) in Auction 73. Complementarity in a 1 MHz nationwide license is worth $918 million to an average large bidder but only $120 million to an average small bidder. Our counterfactual analysis shows that the effects of package bidding on bidders' exposure risks depend on package format and package size. More importantly, mixed package bidding increases FCC revenue substantially at the cost of reducing bidder surplus and increasing license allocation concentration.

Suggested Citation

  • Mo Xiao & Zhe Yuan, 2018. "License Complementarity and Package Bidding: The U.S. Spectrum Auctions," Working Papers 18-06, NET Institute.
  • Handle: RePEc:net:wpaper:1806
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    References listed on IDEAS

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    1. Hong, Han & Shum, Matthew, 2003. "Econometric models of asymmetric ascending auctions," Journal of Econometrics, Elsevier, vol. 112(2), pages 327-358, February.
    2. Catherine D. Wolfram, 1997. "Strategic Bidding in a Multi-Unit Auction: An Empirical Analysis of Bids to Supply Electricity," NBER Working Papers 6269, National Bureau of Economic Research, Inc.
    3. 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.
    4. Jeremy Bulow & Jonathan Levin & Paul Milgrom, 2009. "Winning Play in Spectrum Auctions," NBER Working Papers 14765, National Bureau of Economic Research, Inc.
    5. Jeremy T. Fox, 2010. "Identification in matching games," Quantitative Economics, Econometric Society, vol. 1(2), pages 203-254, November.
    6. 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.
    7. Ali Hortaçsu & Jakub Kastl & Allen Zhang, 2018. "Bid Shading and Bidder Surplus in the US Treasury Auction System," American Economic Review, American Economic Association, vol. 108(1), pages 147-169, January.
    8. Sang Won Kim & Marcelo Olivares & Gabriel Y. Weintraub, 2014. "Measuring the Performance of Large-Scale Combinatorial Auctions: A Structural Estimation Approach," Management Science, INFORMS, vol. 60(5), pages 1180-1201, May.
    9. A. Pakes & J. Porter & Kate Ho & Joy Ishii, 2015. "Moment Inequalities and Their Application," Econometrica, Econometric Society, vol. 83, pages 315-334, January.
    10. Richard Ericson & Ariel Pakes, 1995. "Markov-Perfect Industry Dynamics: A Framework for Empirical Work," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 62(1), pages 53-82.
    11. Cramton Peter & Schwartz Jesse A, 2002. "Collusive Bidding in the FCC Spectrum Auctions," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 1(1), pages 1-20, December.
    12. John Asker, 2010. "A Study of the Internal Organization of a Bidding Cartel," American Economic Review, American Economic Association, vol. 100(3), pages 724-762, June.
    13. Ulrich Doraszelski & Katja Seim & Michael Sinkinson & Peichun Wang, 2017. "Ownership Concentration and Strategic Supply Reduction," NBER Working Papers 23034, National Bureau of Economic Research, Inc.
    14. Victor Chernozhukov & Han Hong & Elie Tamer, 2007. "Estimation and Confidence Regions for Parameter Sets in Econometric Models," Econometrica, Econometric Society, vol. 75(5), pages 1243-1284, September.
    15. Philip A. Haile & Elie Tamer, 2003. "Inference with an Incomplete Model of English Auctions," Journal of Political Economy, University of Chicago Press, vol. 111(1), pages 1-51, February.
    16. Donald W. K. Andrews & Xiaoxia Shi, 2013. "Inference Based on Conditional Moment Inequalities," Econometrica, Econometric Society, vol. 81(2), pages 609-666, March.
    17. Timothy G. Conley & Francesco Decarolis, 2016. "Detecting Bidders Groups in Collusive Auctions," American Economic Journal: Microeconomics, American Economic Association, vol. 8(2), pages 1-38, May.
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    Cited by:

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    3. Canzian, Giulia & Mazzarella, Gianluca & Ronchail, Louis & Verboven, Frank & Verzillo, Stefano, 2025. "Evaluating the impact of price caps - Evidence from the European roam-like-at-home regulation," International Journal of Industrial Organization, Elsevier, vol. 103(PA).

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    JEL classification:

    • L5 - Industrial Organization - - Regulation and Industrial Policy
    • L8 - Industrial Organization - - Industry Studies: Services

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