FCC Office of Strategic Planning and Policy Analysis Kellogg School Conference: Spectrum Management: Challenges Ahead

1. Employing Market Mechanisms to Manage Spectrum Mark Bykowsky and William Sharkey FCC Office of Strategic Planning and Policy Analysis Kellogg School Conference: Spectrum Management: Challenges Ahead June 3, 2011

2. Market Mechanisms and Collective Decision Making in Spectrum Allocation • Coase (1959) first suggested that a market mechanism could efficiently assign spectrum rights to the highest bidder • More recently Benkler (1998), Lessig (2001), Reed (2002) and others have argued for a “commons” model for spectrum use • See also Coase (1974) and Faulhaber and Farber (2002)

3. Fundamental Question: Can market participants solve a variety of collective action problems that may be required to reach an efficient allocation and assignment of spectrum? • Licensed vs. unlicensed spectrum • Definition of other spectrum characteristics such as transmission power levels

4. Policy Question #1 • Does society have the “right” amount of spectrum designated to licensed and unlicensed operations? • “Right” is defined as that designation of spectrum across the two license regimes such that the value that society places on spectrum is maximized

5. Current Situation • Regulators employ an administrative process to determine whether spectrum should be designated to either licensed or unlicensed operations • Incentive Problem: Interested parties have an incentive to mis-represent the value they place on a given license regime

6. One Potential Solution • Induce interested parties to reveal more truthfully the value they place on a given license regime by creating a “market” for licensing rules • Define a New Auction Form: An auction that simultaneously determines the “auction winner(s)” and the license rules that are associated with the sold spectrum

7. Impediments to a Market-based Solution • Efficiency requires inducing parties to reveal enough information about the value they place on a particular licensing regime • Valuations may be too high if bidders desire to acquire spectrum for strategic reasons (e.g., entry deterrence) • Given the common pool nature of unlicensed operations, efficiency may require solving an important “collective action problem” • Beneficiaries of unlicensed operations may excessively “free-ride”

8. Economic Analysis • Employ economic theory and experimental analysis to examine whether a market can be used to determine the efficient set of auction winners and the efficient license regime assigned to several blocks of spectrum

9. A Stylized Example • Four new blocks of spectrum available • Two bidders (L-type) are interested in acquiring ownership of either one or two blocks for their exclusive use • Six bidders (U-type) are interested in bidding for one or two blocks to be managed as a “common property” resource

10. Market Description • Participants place bids conditional on their preferred license regime • Bidders who prefer to have spectrum designated to unlicensed use place “U-type” bids, which will be subsequently aggregated • The highest L-type bid is compared to the sum of the U-type bids • Comparison not only determines the auction winners, but also the use to which spectrum is designated • Bidders who desire licensed (fully private) spectrum, bid as in current auctions by placing “L-type” bids

11. Pricing Rules • Various rules can be used to define prices paid by winning bidders • First price • Second price • Clarke-Groves • Each of the four blocks of spectrum is sold at a single, uniform price. L-Type winners pay this price • U-Type winners pay a price that is proportional to the contribution they made to the U-Type winning bid

12. L - Bidder for 1st Block L - Bidder for 2nd Block U - Bidder for 1st Block U - Bidder for 2nd Block Subject Valuations(Environment #1) Value 400 300 A A 200 B A B 100 C D C D E F E F G H 400 300 250 200 120 120 80 80 60 60 40 G H Spectrum Blocks

13. L - Bidder for 1st Block L - Bidder for 2nd Block U - Bidder for 1st Block U - Bidder for 2nd Block Efficient Assignment(Environment #1) Valuations 500 Supply #8 H A 400 G #7 #6 F B 300 H #8 A #5 E G #7 F B #6 200 #5 2 E D #4 #4 D 100 #3 C C #3 =440 400 300 400 300 =280 250 200 4 Spectrum Blocks

14. Nash Equilibria Selection Problem • Assume that each bidder has complete information about the number of bidders, bidder valuations, and bidder “type” • It can be shown that, for a given set of valuations, both the efficient and numerous inefficient assignments can be sustained as Nash equilibria • Total surplus and individual payoffs vary substantially across the different Nash equilibria • There are three “types” of Nash Equilibria. Game theory is silent on which type of equilibrium is most likely to be selected

15. Valuations 500 Supply A 400 B L - Bidder for 1st Block 300 A L - Bidder for 2nd Block U - Bidder for 1st Block B 200 C-H U - Bidder for 2nd Block Price C-H 100 400 250 <200 <200 250 201 Spectrum Blocks Type 0 Nash Equilibrium(Environment #1) 4

16. L - Bidder for 1st Block L - Bidder for 2nd Block U - Bidder for 1st Block U - Bidder for 2nd Block Type 1 Nash Equilibrium(Environment #1) Valuations 500 Supply A 400 B 300 A C-H C-H B Price 200 2 100 =200 250 250 400 Spectrum Blocks 4

17. Valuations 500 Supply C-H #8 A 400 L - Bidder for 1st Block B L - Bidder for 2nd Block 300 C-H U - Bidder for 1st Block A Price U - Bidder for 2nd Block B 200 2 100 #3 =440 400 300 =280 400 300 250 200 4 Spectrum Blocks Type 2 Nash Equilibrium(Environment #1)

18. Experimental Methodology • Define an economic environment (e.g., # blocks of spectrum, # of bidders of each type, rights associated with each license regime, information assumptions) • Assign human subjects a “role” (L-type or S-type) and a willingness to pay for one or more blocks of spectrum • Use financial payments to motivate subject behavior • Identify the efficient designation of spectrum to licensed and unlicensed operations and compare it to the observed spectrum allocation generated in the experiment • Change the economic environment (i.e., participant valuations) and compare the observed designation of spectrum with the efficient designation

19. Experimental Results

20. Computational Results for Different Auction Mechanisms

21. Policy Question #2 • Can market forces be used to obtain an efficient allocation of signal interference rights? • Example: An incumbent license holder (E-type firm) seeks permission to offer “enhanced service” at higher transmitting power than currently authorized • License holders in spectrally adjacent bands (S-type firms) may be harmed by increased signal interference

22. Environment 1: No Enforceable Property Rights • An auction is held to determine whether or not to authorize an increase in transmission power • The E-type firm and each S-type firm simultaneously bid an amount representing their alleged benefit or harm • Enhanced service at higher power is authorized if and only if the E-bid is greater than the collective bids of S-type firms

23. Hypothetical Bidder Valuations

24. Bidder #2 Strategies $3 $5 $6 ($6) $8 $4 ($8) $6 $6 Bidder #1 Strategies $4 ($8) $6 $4 ($8) $6 $4 Environment 1: No Enforceable Property RightsCase 1: E-Bid = $10

25. Bidder #2 Strategies $3 $5 $8 ($6) $8 $6 ($6) $8 $6 Bidder #1 Strategies $6 ($6) $10 $4 ($10) $6 $4 Environment 1: No Enforceable Property RightsCase 1: E-Bid = $8

26. Environment 2: S-Type Firms Have a Right to Non-Inteference • E-type firms makes an offer to compensate each S-type firm for alleged harm • Each S-type firm submits an ask price representing harm from interference • Enhanced service is authorized if a mutually satisfactory compensation scheme is agreed upon

27. Hypothetical Bidder Valuations

28. Environment 2: Property Right in Non-InterferenceCase 1: E-Bid = $18 Licensee #2 Ask Price $12 $8 $12.2 ($12.5) $15.3 $11 ($6) $14 $9 Licensee #1 Ask Price $11 ($6) $14 $11 ($6) $14 $13

29. Environment 2: Property Right in Non-InterferenceCase 1: E-Bid = $22 Licensee #2 Ask Price $12 $8 $13.2 ($10.5) $16.3 $16.3 ($8.5) $15.2 $9 Licensee #1 Ask Price $12.2 ($8.5) $19.3 $11 ($6) $14 $13

30. Concluding Comments • “Collective Action Problems” underlie a wide variety of spectrum policy problems • Bidders for a common property use of spectrum • Incumbent license rule enhancement problem • “Treshhold problem” when independent bidders must bid against a rival bidder who wishes to purchase a collection of multiple geographic blocks • 700 MHz C-block “open” platform requirement • Re-assigning broadcast spectrum to alternative uses

31. References • Bykowsky, Mark M., Mark Olson, and William W. Sharkey (2010), “Efficiency Gains from Using a Market Approach to Spectrum Management,” Information Economics and Policy, 22: 73-90 • Bykowsky, Mark M. and William W. Sharkey (2011), “Using a Market to Obtain the Efficient Allocation of Signal Interference Rights,” unpublished • Benkler, Yochai (1998), “Overcoming Agoraphobia: Building the Commons of the Digitally Networked Environment, Harv. J. L & Tech., 287 • Coase, Ronald H. (1959), “The Federal Communications Commission,” Journal of Law & Economics, 2: 1-40 • Coase, Ronald H. (1974), "The Lighthouse in Economics", Journal of Law and Economics 17: 357–376 • Faulhaber, Gerald R. and David J. Farber (2002), “Spectrum Management: Property Rights, Markets, and The Commons,” AEI-Brookings Joint Center for Regulatory Studies, Working Paper 02-12 • Lessig, Lawrence (2001), The Future of Ideas: The Fate of the Commons in a Connected World, Random House: New York • Reed, David, 2002, “Comments for FCC Spectrum Task Force on Spectrum Policy,” available at www.newamerica.net/files/archive/Doc_File_142_1.pdf • Sharkey, William W., Fernando Beltrán and Mark M. Bykowsky (2011), “Computational Analysis of an Auction for Licensed and Unlicensed Use of Spectrum,” unpublished