A welfare analysis of spectrum allocation policies

• Date: 01 September 2009
• Author: Thomas W. Hazlett,Roberto E. Muñoz
• Published date: 01 September 2009
• DOI: http://doi.org/10.1111/j.1756-2171.2009.00072.x

RAND Journal of Economics

Vol.40, No. 3, Autumn 2009

pp. 424–454

A welfare analysis of spectrum

allocation policies

Thomas W. Hazlett∗

and

Roberto E. Mu˜

noz∗∗

Economic analysis of spectrum policy focuses on government revenues derived via competitive

bidding for licenses. Auctions generating high bids are identified as “successful” and those with

lower receipts as “fiascoes.” Yet spectrum policies that create rents impose social costs. Most

obviously, rules favoring monopoly predictably increase license values but reduce welfare. This

article attempts to shift analytical focus to efficiency in output markets. In performance metrics

derived by comparing 28 mobile telephone markets, countries allocating greater bandwidth to

licensed operators and achieving more competitive market structures are estimated to realize

efficiencies that generally dominate those associated with license sales. Policies intended to

increase auction receipts(e.g., reserve prices and subsidies for weak bidders) should be evaluated

in this light.

1. Introduction

Competitive bidding to assign wireless licenses constitutes a substantial policy advance.

Following their suggestion byLeo Herzel (1951) and Ronald Coase (1959), auctions were finally

adopted by New Zealand in 1989 (Crandall, 1998), India in 1991 (Jain, 2001), and the United

States in 1993 (McMillan, 1994). At least 25 other countries have instituted license auctions in

recent years (Hazlett, 2008b).

The argument for using the “price system” to allocate wireless licenses is premised on three

types of economic efficiencies:

(i) elimination of rent dissipation associated with “comparative hearings” or “beauty contest”

awards (Kwerel and Felker, 1985);

(ii) assignment of licenses to the most productive suppliers, savingthe costs of secondar y market

reassignments (Cramton, 2002);

∗George Mason University; thazlett@gmu.edu.

∗∗Universidad T´

ecnica Federico Santa Mar´

ıa (Santiago, Chile); roberto.munoz@usm.cl.

The authors would like to thank Robert Hahn, Ricardo Smith, three anonymous referees, the editors of this journal, and

seminar participants at George Mason University and the HooverInstitution at Stanford University for valuable comments

on an earlier version of this article. The superb research assistance of Diego Avanziniis also acknowledged. Of course,

any errors should be attributed solely to the authors.

424 Copyright C

2009, RAND.

HAZLETT AND MU ˜

NOZ / 425

(iii) generation of public revenues, displacing taxes;the consensus estimate is that $0.33 in social

cost is saved for every tax dollar saved (Cramton, 2001; Klemperer, 2002b).1

A healthy literature on the implementation of wireless auctions has emerged.2Revenues

raised by government auctions are seen both as indicators of auction design efficiency and

as appropriated surplus that increases social welfare by offsetting activity-distorting taxes.

Consequently, auction success is typically measured by license receipts.3

In evaluating alternative bidding mechanisms, Paul Klemperer has written: “What really

matters in auction design are the same issues that any industry regulator would recognize as key

concerns: discouraging collusive, entry-deterring and predatory behavior. ...By contrast, most

of the extensive auction literature ...is of second-order importance for practical auction design”

(Klemperer, 2002b, emphasis in original).4

This approach, “just good undergraduate industrial organization” (Klemperer, 2002b), is

unassailable. But an essential analytical conflict is left intact: auction rules that alter market

structure or operator performance produce welfare effects, and these spillovers may not be

systematically incorporated. For instance, arguments are often advanced to improve license

auctions by imposing reserve prices,5extending credits to “weak bidders,”6or restricting the

number of licenses (to increase scarcity value).7In addition, the social discount rate is ignored in

auction processes that delay productive use of frequencies for months or years.

The problem is put into perspective with some simple estimates of social value. Empirical

research undertaken a decade ago found the annual consumer surplus associated with U.S.

cellular telephone licenses (issued in the 1980s) at least 10 times as large as annual producers’

surplus (Hausman, 1997; Rosston, 2001). Today, U.S.wireless phone market data yield an annual

consumer surplus estimate of at least $150 billion.8The total revenue obtained from selling all

wireless licenses (not just for mobile telephony) is just $53 billion.9Given that the latter is a

present value and the former an annual flow, these data suggest that the ratio (CS to PS) is much

above an order of magnitude.

Policies undertaken to improve license revenues, then, focus on a small fraction of the

economic value at stake. Rules that increase auction bids but risk collateral damage—say, by

reducing operator efficiency or market competitiveness—generate potential costs not properly

evaluated by reference to rent extraction alone. This is true evenwhen revenues raised by license

auctions do, ceteris paribus, increase welfare.

Weoffer an extension of the Klemperer critique. Economists should not only consider market

structure effects within auctions but should incorporate consumer welfare effects from wireless

output markets whenever alternative auction rules influence not only public rent extraction but

retail prices.

We hasten to note that Paul Klemperer has correctly diagnosed the temptation

to favor monopoly rent creation over competitive output markets. Klemperer (2002b)

1Cramton (2002) cites a range of 17–56 cents.

2See McMillan (1994); McAfee and McMillan (1996); Cramton (1995, 2002); Moreton and Spiller (1998); Grimm,

Riedel, and Wolfstetter (2001); Wolfstetter (2001); Binmore and Klemperer (2002); van Damme (2002); Klemperer

(2002a, 2002b).

3It is customary to adjust receipts by bandwidth allocated licenses and the population of the franchise area, such

that prices are quoted in terms of “$ per MHz per pop.”

4Support for this view is also supplied in Binmore and Klemperer (2002) and Klemperer (2002a).

5See Cramton (2002); Krishna (2002); Klemperer (2002a).

6See Ayres and Cramton (1996); Rothkopf,Harstad, and Fu (2003).

7See Wolfstetter(2001); van Damme (2002); Rothkopf and Bazelon (2003).

8This lower bound can be calculated from historical price-quantity pairs for wireless minutes of use (Hazlett,

2008a). Hausman (2002) and Entner and Lewin (2005) obtain similar estimates.

9The Federal Communications Commission raised $52.6 billion through (and counting) the 700 MHz license

auction completed in March 2008. Chloe Albanesius, FCC Spectrum Auction Ends, Successfully,PC Magazine (March

18, 2008), http://www.pcmag.com/article2/0,2817,2277146,00.asp.

C

RAND 2009.