MODELING THE EFFICIENCY PROPERTIES OF SPECTRUM
MANAGEMENT REGIMES
Carol Ting, Steven S. Wildman, Johannes M. Bauer
Johannes M. Bauer
Quello Center for Telecommunication Management and Law
Michigan State University
406 Communication Arts and Sciences, Michigan State University
East Lansing, MI 48824-1212, USA
Email bauerj@msu.edu
Carol Y. F. Ting
Quello Center for Telecommunication Management and Law
Michigan State University
406 Communication Arts and Sciences, Michigan State University
East Lansing, MI 48824-1212, USA
Email tingyife@msu.edu
Steven S. Wildman
Quello Center for Telecommunication Management and Law
Michigan State University
406 Communication Arts and Sciences, Michigan State University
East Lansing, MI 48824-1212, USA
Email swildman@msu.edu
JEL code: L960, D230, Q210
Keywords: Spectrum commons, Spectrum property rights
This study presents an economic framework for modeling service provider and user
decisions in wireless communications. The framework makes it possible to model the
defining characteristics of different spectrum management regimes and, for the first time,
directly compare the welfare properties of different spectrum management regimes.
Using computational methods, we compare key aspects of a commons and a propertybased regime. Both the methodology and the comparative analysis move the present
debate over the relative merits of different spectrum management regimes beyond the
speculative and purely conceptual comparisons that have characterized this debate to
date. Because the framework presented can be used to model a wider range of spectrum
governance models than the two examined in this paper, it should prove helpful to
policymakers in the search for the most efficient mix of different spectrum governance
models.
A key challenge in spectrum welfare analysis is the high uncertainty over the
development of technologies that might permit less disruptive co-existence of users of the
same or neighboring spectrum. Among others, work is underway to develop devices with
a higher interference tolerance as well as devices with improved capability to recognize
and adjust to their radio environment. The outcome of these technological searches
directly affects the interdependence of spectrum users and market demand. Furthermore,
the development of technologies is intertwined with the choice of governing-regime and,
in turn, has implications for the most efficient governance regime.
Our models tackle these issues by integrating several features: (1) engineering insights on
how receiver design affects the externality imposed by one user on another in a model of
demand for wireless services; (2) demand-driven incentives and profit-maximizing
strategies for device manufacturers (assuming Cournot behavior) under spectrumgoverning regimes of interest; and (3) a computer program that computes equilibria and
welfare performance for each regime.
We present and compare results for two very different spectrum-governance regimes. In
our first model setting, which belongs to the class of common property regimes
(commons), firms have free access to spectrum to serve a specific market segment, and
the interference problem is addressed by having a “commons governing body” set a
minimum level of interference robustness for devices. In the second model setting, the
government establishes property rights for firms seeking to serve a market segment by
assigning a fixed and unique band of frequencies within a larger band of fixed size
reserved for the service in question. Each firm determines the interference robustness of
its devices and the government determines the number of firms allowed to offer service in
the band. In both cases, increasing the interference tolerance of a device increases its
cost.
The results of the first case show that, while mandated minimum robustness levels may
improve welfare, the costs of more robust devices overwhelm the benefits of interference
reduction fairly quickly in an open access commons regime. The second case gives quite
intuitive results: firms adjust the level of interference robustness of their devices to cope
with interference from competitors’ devices, and absolutely interference-free protection
set by the government may not be necessary for maximizing welfare. The comparative
merits of the two regimes vary with market demand parameters and spectrum allocation.
References
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communications, Berlin: Springer, 2004
[2]Bauer, J. M., “Impact of license fees on the prices of mobile services,”
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[3]Maitland, C. F., Bauer, J. M., and Westerveld, R., “The European market for mobile
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[4] Ting, C, Bauer, J. M., and Wildman, S. S., “The U.S. Experience with Non-traditional
Approaches to Spectrum Management: Tragedies of the Commons and Other Myths
Reconsidered.” Paper presented at the 31st Research Conference on Communication,
Information and Internet Policy, Arlington, VA, September 19-21, 2003.
[5] Ting, C, “Pathways to the Wireless Promised Land: Advances in Wireless
Technology and Their Implications for Spectrum Policy.” Upcoming presentation at ICA
2004 Annual Conference, New Orleans, LA, May 27-31, 2004.
[6] Wildman, S. S., Electronic Services Networks: A Business and Public Policy
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