Measuring the Efficiency of an FCC Spectrum Auction

doi:10.1017/9781316471609.005

4 - Measuring the Efficiency of an FCC Spectrum Auction

from Part I - The Simultaneous Multiple-Round Auction

Published online by Cambridge University Press: 26 October 2017

Jeremy T. Fox and

Patrick Bajari

Edited by

Martin Bichler and

Jacob K. Goeree

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Jeremy T. Fox: Affiliation:
Department of Economics, Rice University
Patrick Bajari: Affiliation:
Department of Economics, University of Washington
Martin Bichler: Affiliation:
Technische Universität München
Jacob K. Goeree: Affiliation:
University of New South Wales, Sydney

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Summary

Introduction

The US Federal Communications Commission (FCC) auctions licenses of radio spectrum for mobile phone service, employing an innovative simultaneous ascending auction. We study data from the 1995–1996 auction of licenses for the C Block of the 1900 MHz PCS spectrum band. The C block divided the continental United States into 480 small, geographically distinct licenses. A mobile phone carrier that holds two geographically adjacent licenses can offer mobile phone users a greater contiguous coverage area. One intent of auctioning small licenses is to allow bidders, rather the FCC, to decide where geographic complementarities lie. Bidders can assemble packages of licenses that maximize the benefits from geographic complementarities. The US practice of dividing the country into small geographic territories differs markedly from European practice, where nationwide licenses are often issued. These nationwide licenses ensure that the same provider will operate in all markets, so that all geographic complementarities are realized.

Economic theory suggests that the allocation of licenses in a simultaneous ascending auction need not be allocatively efficient. Brusco and Lopomo (2002) and Engelbrecht- Wiggans and Kahn (2005) demonstrate that bidders may implicitly collude through the threat of bidding wars. For example, a bidder might not add an additional license to a package to take advantage of complementarities because of threats of higher, retaliatory bids on the bidder's other licenses. For auctions of multiple homogeneous items, Ausubel and Cramton (2002) demonstrate that bidders may find it profitable to unilaterally reduce demand for licenses, similarly to a monopolist raising prices and profits by reducing supply. The concern about intimidatory collusion and demand reduction in FCC spectrum auctions is well founded. Cramton and Schwartz (2000, 2002) show that bidders in the AB block did not aggressively compete for licenses and in the later DEF block auction used the trailing digits of their bids to signal rivals not to bid on other licenses.

Type: Chapter
Information: Handbook of Spectrum Auction Design , pp. 62 - 108

DOI: https://doi.org/10.1017/9781316471609.005 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2017

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References

Akkus, Oktay, J., Anthony Cookson, and Ali, Hortacsu, “The Determinants of Bank Mergers: A Revealed Preference Analysis,” 2012. University of Chicago working paper.

Athey, Susan and Philip A., Haile, “Nonparametric Approaches to Auctions,” Handbook of Econometrics, 2008, 6.

Ausubel, Lawrence M. and Peter, Cramton, “Demand Reduction and Inefficiency in Multi-Unit Auctions,” July 2002. University of Maryland working paper.

Ausubel, Lawrence M. and Peter, Cramton, R., Preston McAfee, and John, McMillan, “Synergies in Wireless Telephony: Evidence from the Broadband PCS Auctions,” Journal of Economics and Management Strategy, Fall 1997, 6 (3): 497–527.Google Scholar

Avery, Christopher, “Strategic Jump Bidding in English Auctions,” Review of Economic Studies, 1998, 65, 185–210.Google Scholar

Bajari, Patrick and Ali, Hortacsu, “Are structural estimates of auction models reasonable? Evidence from experimental data,” Journal of Political Economy, 2005, 113 (4): 703–741.Google Scholar

bajari, Jeremy T. Fox, and Stephen, Ryan, “Evaluating Wireless Carrier Consolidation Using Semiparametric Demand Estimation,” Quantitative Marketing and Economics, 2008, 6 (4): 299–338.Google Scholar

Banks, Jeffrey,Mark, Olson, David, Porter, Stephen, Rassenti, and Vernon, Smith, “Theory, experiment and the federal communications commission spectrum auctions,” Journal of EconomicBehavior and Organization, 2003, 51, 303–350.Google Scholar

Brusco, Sandro and Giuseppe, Lopomo, “Collusion via Signalling in Simultaneous Ascending Bid Auctions with Heterogenous Objects, with and without Complementarities,” Review of EconomicStudies, April 2002, 69 (2): 407–436.Google Scholar

Bulow, Jeremy, Jonathan, Levin, and Paul, Milgrom, “Winning Play in Spectrum Auctions,” February 2009. Stanford University working paper.

Cantillon, Estelle and Martin, Pesendorfer, “Combination Bidding in Multiple Unit Auctions,” 2006. Université Libre de Bruxelles working paper.

Chapman, James T.E., David, McAdams, and Harry J., Paarsch, “Bounding Best-Response Violations in Discriminatory Auctions with Private Values,” American Economic Review, May 2007, 97 (2): 455–458.Google Scholar

Chiappori, Pierre-Andre Bernard, Salanie, and Yoram, Weiss, “Partner Choice and the Marital College Premium,” 2012. Columbia University working paper.

Choo, Eugene and Aloysius, Siow, “Who Marries Whom and Why,” The Journal of Political Economy, November 2006, 114 (1): 175–201.Google Scholar

Coase, Ronald H, “The Federal Communications Commission,” Journal of Law and Economics, 1959, 2, 1–40.Google Scholar

Cramton, Peter, “Simultaneous Asending Auctions,” in Peter, Cramton, Yoav, Shoham, and Richard, Steinberg, eds., Combinatorial Auctions, MIT Press, 2006.

Cramton, Peterand Jesse A. Schwartz, “Collusive Bidding: Lessons from the FCC Spectrum Auctions,” Journalof Regulatory Economics, May 2000, 17 (3): 229–252.Google Scholar

Cramton, Peterand Jesse A. Schwartz, “Collusive Bidding in the FCC Spectrum Auctions,” Contributions to Economic Analysis & Policy, 2002, 1 (1), Article 11.Google Scholar

Cramton, Peterand Jesse A. Schwartz, Yoav, Shoham, and Richard, Steinberg, Combinatorial Auctions, MIT Press, 2006.

Crawford, Vincent P. and ElsieMarie, Knoer, “JobMatching with Heterogeneous Firms andWorkers,” Econometrica, 1981, 49 (2): 437–450.Google Scholar

Dagsvik, John K., “Aggregation in Matching Markets,” International Economic Review, February 2000, 41 (1): 27–57.Google Scholar

Day, Robert and Paul, Milgrom, “Core-Selecting Package Auctions,” International Journal of GameTheory, June 2007.

Demange, Gabrielle, David, Gale, and Marilda A., Oliveira Sotomayor, “Multi-Item Auctions,” The Journal of Political Economy, August 1986, 94 (4): 863–872.Google Scholar

Edelman, Benjamin, Michael, Ostrovsky, and Michael, Schwarz, “Internet Advertising and the Generalized Second Price Auction: Selling Billions of Dollars Worth of Keywords,” AmericanEconomic Review, March 2007, 97 (1).Google Scholar

Engelbrecht-Wiggans, Richard and Charles M., Kahn, “Low revenue equilibria in simultaneous auctions,” Management Science, 2005, 51 (3): 508–518.Google Scholar

Fevrier, Philippe, Raphaelle, Preget, and Michael, Visser, “Econometrics of Share Auctions,” 2004. CREST working paper.

Fox, Jeremy T., “EstimatingMatching Games with Transfers,” 2010. University of Michigan working paper.

Fox, Jeremy T., “Identification in Matching Games,” Quantitative Economics, 2010, 1 (2): 203–254.Google Scholar

Fox, Jeremy T. and Hector, Perez-Saiz, “Mobile Phone Mergers and Market Shares: Short Term Losses and Long Term Gains,” September 2006. NET Institute Working Paper 06-16.

Gentzkow, Matthew, “Valuing New Goods in aModel with Complementarity: Online Newspapers,” The American Economic Review, 2007, 97 (3): 713–744.Google Scholar

Haile, Philip A. and Elie, Tamer, “Inferencewith an IncompleteModel of EnglishAuctions,” Journalof Political Economy, February 2003, 111 (1): 1–51.Google Scholar

Han, A. K., “Non-parametric analysis of a generalized regression model,” Journal of Econometrics, 1987, 35, 303–316.Google Scholar

Hatfield, John William and Paul R., Milgrom, “Matching with Contracts,” American EconomicReview, September 2005, 95 (4): 913–935.Google Scholar

Hong, Han and Matthew, Shum, “Econometric models of asymmetric ascending auctions,” Journalof Econometrics, 2003, 112, 327–358.Google Scholar

Horowitz, Joel L., “A SmoothedMaximum Score Estimator for the Binary ResponseModel,” Econometrica, May 1992, 60 (3): 505–551.Google Scholar

Hortacsu, Ali and David, McAdams, “Mechanism Choice and Strategic Bidding in Divisible Good Auctions: An Empirical Analysis of the Turkish Treasury Auction Market,” Journal of PoliticalEconomy, 2010, 118 (5): 833–865.Google Scholar

Kagel, John H. and Dan, Levin, “Behavior in Multi-Unit Demand Auctions: Experiments with Uniform Price and Dynamic Vickrey Auctions,” Econometrica, 2001, 69 (2): 413–454.Google Scholar

Kastl, Jakub, “Discrete Bids and Empirical Inference in Divisible Good Auctions,” Review of EconomicStudies, 2011, 78 (3): 974–1014.Google Scholar

Kelso, Alexander S. and Vincent P., Crawford, “Job Matching, Coalition Formation, and Gross Substitutes,” Econometrica, November 1982, 50 (6): 1483–1504.Google Scholar

Koopmans, Tjalling C. and Martin, Beckmann, “Assignment Problems and the Location of Economic Activities,” Econometrica, January 1957, 25 (1): 53–76.Google Scholar

Krasnokutskaya, Elena, “Identification and Estimation of Auction Models with Unobserved Heterogeneity,” The Review of Economic Studies, 2011, 78 (3): 293–327.Google Scholar

Kwasnica, Anthony M. and Katerina, Sherstyuk, “Collusion and Equilibrium Selection in Auctions,” The Economic Journal, 2007, 117 (516): 120–145.Google Scholar

Leonard, Herman B., “Elicitation of Honest Preferences for the Assignment of Individuals to Positions,” Journal of Political Economy, June 1983, 91 (3): 461–479.Google Scholar

List, John A. and David, Lucking-Reiley, “Demand Reduction in Multiunit Auctions: Evidence from a Sportscard Field Experiment,” American Economic Review, 2000, 90 (4): 961–972.Google Scholar

Manski, Charles F., “Maximum Score Estimation of the Stochastic Utility Model of Choice,” Journalof Econometrics, 1975, 3 (3): 205–228.Google Scholar

Matzkin, Rosa L., “Nonparametric identification and estimation of polychotomous choice models,” Journal of Econometrics, 1993, 58, 137–168.Google Scholar

McAfee, R. Preston and John, McMillan, “Analyzing the Airwaves Auction,” Journal of EconomicPerspectives, Winter 1996, 10 (1): 159–175.Google Scholar

Milgrom, Paul, “Putting Auction Theory to Work: The Simultaneous Ascending Auction,” Journalof Political Economy, 2000, 108 (2): 245–272.Google Scholar

Milgrom, Paul R. and Robert J., Weber, “A Theory of Auctions and Competitive Bidding,” Econometrica, 1982, 50 (5): 1089–1122.Google Scholar

Moreton, Patrick S. and Pablo T., Spiller, “What's In the Air: Interlicense Synergies in the Federal Communications Commission's Broadband Personal Communication Service Spectrum Auctions,” Journal of Law and Economics, October 1998, 41 (2, Part 2), 677–725.Google Scholar

Newey, W.K. and D., McFadden, “Large Sample Estimation and Hypothesis Testing,” in “Handbook of Econometrics,” Vol. 4, Elsevier, 1994, pp. 2111–2245.

Paarsch, Harry J. and Han, Hong, An Introduction to the Structural Econometrics of Auction Data, MIT Press, 2006.

Politis, Dimitris N. and Joseph P., Romano, “Large Sample Confidence Regions Based on Subsamples under Minimal Assumptions,” The Annals of Statistics, December 1994, 22 (4): 2031–2050.Google Scholar

Shapley, Lloyd S. and Martin, Shubik, “The assignment game I: the core,” International Journal ofGame Theory, 1972, 1, 111–130.Google Scholar

Sherman, Robert P., “The Limiting Distribution of the Maximum Rank Correlation Estimation,” Econometrica, January 1993, 61 (1): 123–137.Google Scholar

Sorensen, Morten, “How Smart is SmartMoney? A Two-Sided Matching Model of Venture Capital,” Journal of Finance, December 2007, LXII (6), 2725–2762.Google Scholar

Storn, Rainer and Kenneth, Price, “Differential Evolution –A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces,” Journal of Global Optimization, 1997, 115, 341–359.Google Scholar

Wolak, Frank A., “Quantifying the Supply-Side Benefits from Forward Contracting in Wholesale Electricity Markets,” Journal of Applied Econometrics, November 2007, 22, 1179–1209.Google Scholar

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