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
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)
2
 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
3
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
4
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
5
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
6
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”
7
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
8
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
9
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 “Ltype” bids
10
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
11
Subject Valuations
(Environment #1)
Value
400
L - Bidder for 1st Block
L - Bidder for 2nd Block
300
U - Bidder for 1st Block
A
200
A
B
100
U- Bidder for 2nd Block
A
B
C
400 300 250 200 120 120 80
D
80 60
C
D
60
40
E
F
E
F
G
H
G
H
Spectrum Blocks
12
Efficient Assignment
(Environment #1)
Valuations
500
Supply
400
#8
H
L - Bidder for 1st Block
A
L - Bidder for 2nd Block
#7
G
#6
F
300
#5
E
200
U - Bidder for 1st Block
B
U- Bidder for 2nd Block
#8
H
G
#7
A
F
#6
#4
D
B
#5
E
2
#4
D
100
#3
C
=440 400
C
#3
300
400 =280
300
4
250
200
Spectrum Blocks
13
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
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Type 0 Nash Equilibrium
(Environment #1)
Valuations
500
Supply
400
A
L - Bidder for 1st Block
B
300
L - Bidder for 2nd Block
A
U - Bidder for 1st Block
B
200
U - Bidder for 2nd Block
C-H
Price
C-H
100
400
250
250
<200 <200
201
4
Spectrum Blocks
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Type 1 Nash Equilibrium
(Environment #1)
Valuations
L - Bidder for 1st Block
500
L - Bidder for 2nd Block
Supply
U - Bidder for 1st Block
A
400
U- Bidder for 2nd Block
B
300
A
C-H
200
B
C-H
2
Price
100
400
250
250
=200
4
Spectrum Blocks
16
Type 2 Nash Equilibrium
(Environment #1)
Valuations
500
Supply
C-H
#8
400
L - Bidder for 1st Block
A
L - Bidder for 2nd Block
U - Bidder for 1st Block
B
300
U - Bidder for 2nd Block
C-H
A
Price
B
200
2
100
=440
#3
400
300400 300
=280
4
250
200
Spectrum Blocks
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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
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Experimental Results
Blocks Designated to Unlicensed
Average
Efficiency
# Auctions
Zero
One
Two
Total
Auctions
0
11
2
13
.82
.98
1.00
2
17
2
.80
.99
1.00
Environment
#1
Efficiency
.95
# Auctions
21
Environment
#2
Efficiency
.95
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Computational Results for Different
Auction Mechanisms
Payoffs
L
U
Number
Winning
U-Bids
0.450
0.380
0.151
1.41
0.908
0.412
0.456
0.040
0.309
0.995
0.200
0.421
0.373
1.83
Total
Surplus
Auction
Revenue
First
Price
0.981
Second
Price
ClarkeGroves
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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 (Stype firms) may be harmed by increased signal
interference
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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
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Hypothetical Bidder Valuations
Bidder License Valuations
Bidders
Service Rule E
Service Rule S
Incumbent Licensee
(E-Type)
$18
$6
Spectrally Adjacent Licensee #1
(S-Type)
$6
$14
Spectrally Adjacent Licensee #2
(S-Type)
$4
$11
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Environment 1: No Enforceable
Property Rights
Case 1: E-Bid = $10
Bidder #2
Strategies
$3
$5
$6
$6
($6)
($8)
$8
Bidder #1
Strategies
$4
$6
$4
$4
$4
($8)
$6
($8)
$6
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Environment 1: No Enforceable Property
Rights
Case 1: E-Bid = $8
Bidder #2
Strategies
$3
$5
$8
$6
$6
($6)
($6)
$8
$8
Bidder #1
Strategies
$6
$4
$4
($6)
$10
($10)
$6
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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
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Hypothetical Bidder Valuations
Bidder License Valuations
Bidders
Service Rule E
Service Rule S
Incumbent Licensee
(E-Type)
$30
$6
Spectrally Adjacent Licensee #1
(S-Type)
$6
$14
Spectrally Adjacent Licensee #2
(S-Type)
$4
$11
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Environment 2: Property Right in NonInterference
Case 1: E-Bid = $18
Licensee #2
Ask Price
$12
$8
$12.2
$9
($12.5)
$15.3
Licensee #1
Ask Price
$11
($6)
$14
$11
$13
$11
($6)
$14
($6)
$14
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Environment 2: Property Right in NonInterference
Case 1: E-Bid = $22
Licensee #2
Ask Price
$12
$8
$13.2
$9
($10.5)
$16.3
Licensee #1
Ask Price
$16.3
($8.5)
$15.2
$12.2
$13
$11
($8.5)
$19.3
($6)
$14
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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
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References
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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
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