Project Report - CCI

COMPETITION EFFECTS
AND ECONOMIC
CONSEQUENCES OF
SPECTRUM AUCTIONS IN
INDIA
INTERNSHIP REPORT
July 2015
Competition Commission of India
Guide: Mr. Mohan Ronanki
Dy. Director (Economics Division)
Submitted by:
Rosmin Varghese
M.A. Applied Economics (2014-16)
Centre for Development Studies (JNU), Trivandrum

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DISCLAIMER
This study report has been prepared by the researcher as an intern under the
Internship Programme of the Competition Commission of India for academic
purposes only. The views expressed in the report are personal to the intern
and do not necessarily reflect the views of the Commission Hon‘ble
Chairperson / Members or its officers in any manner. This report is the
intellectual property of the Competition Commission of India and the same or
any part thereof may not be used in any manner, whatsoever, without express
permission of the Competition Commission of India

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ACKNOWLEDGMENT
I take this opportunity to express my gratitude towards my Guide, Mr Mohan
Ronanki, Deputy Director (Economics Division) for extending to me all possible
help for the successful completion of my project during my internship at the
Commission. Not only did he grrom my approach towards the topic but also
gave me the freedom and liberty to carry out my research.
I also thank my fellow interns for the valuable inputs on Competition Law that
they provided me through our discussions.
Last, but not the least, I thank the Competition Commission of India for
providing me with this prestigious opportunity.

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TABLE OF CONTENTS
Industry Overview..............................................................................................5
Spectrum and Its Management..........................................................................8
Evolution of Spectrum Management in India...................................................11
Auctions vis-a-vis Other Ways of Allocation.....................................................19
Spectrum as an Economic Good.......................................................................22
Auctions in India ..............................................................................................26
Competition Issues in Auctions........................................................................28
Auction Design – India .....................................................................................31
Competition and Allocative Efficiency of Spectrum Allocation ................35
Spectrum Auctions and their Effect on Prices of Services ................................37
Theory .....................................................................................................37
Reserve Price ...........................................................................................40
Empirical Evidence ..................................................................................41
The Way Forward ............................................................................................47
Bibliography ....................................................................................................50

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INDUSTRY OVERVIEW
The Indian telecommunications industry is one of the fastest growing in the world. In the
last two decades, the Indian Telecom Sector and mobile telephony in particular has caught
the imagination of India by revolutionizing the way we communicate, share information,
and through its staggering growth helped millions stay connected.
Telecommunication services are globally recognised as one of the driving forces for overall
economic development in a nation. They are also one of the prime support services needed
for rapid growth and modernisation of various sectors of the economy.
The sector has become more competitive, while enhancing the accessibility of
telecommunication services at affordable tariffs to the consumers.
Current Scenario and Trends
Subscriber Base
In the Indian telecom sector, the number of telephone subscribers (wireless and wireline) in
India increased from 970.97 million at the end of December 2014 from 915.19 million at the
end of December 2013 – an increase of 6.09%. The trends of the subscriber base for every
quarter since 2011 till 2014 has been given in the graph below.
Source: (TRAI, 2014) (TRAI, 2013) (TRAI, 2012) (TRAI, 2011)
846.322
885.99
906.93
926.53
951.34
965.52
937.7
895.51898.02903.09899.96
915.19
933.01942.95
957.61
970.97
Subsciber Base (Million)
Subsciber Base (Million)

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Number of wireless subscribers has grown from 886.30 million in December 2013 to 943.97
million in December 2014 - an increase of 6.5%.
Teledensity
Telephone density or teledensity is defined as the number of telephone connections for
every hundred individuals living within an area. The overall teledensity (wireless and
wireline) increased from 74.02 in December 2013 to 77.58 in December 2014.
The quarterly trends are given below.
The Wireless Teledensity has increased from 71.69 at the end of December 2013 to 755.43
at the end of December 2014.
Market Players
Bharti is the leading operator in access segment in terms of number of subscribers. During
the quarter, Idea recorded the highest net addition of 6.98 million subscribers followed by
Bharti (5.68 million). BSNL recorded the highest net decline of 5.77 million subscribers
during this quarter.
The market share of the current players for the whole country is given below:
70.89
73.97
75.48
76.86
78.66
79.58
77.04
73.7473.3273.573.01
74.02
75.23
75.8
76.75
77.58
66
68
70
72
74
76
78
80
82
Teledensity
Teledensity

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Source: (TRAI, 2015)
23%
18%
16%
11%
10%
8%
7%
4%
1% 1% 1%
0%
Market Share
Bharti
Vodafone
IDEA
Reliance Comm
BSNL
Aircel
Tata
Telewings
Sistema
MTNL
Videocon

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SPECTRUM AND ITS MANAGEMENT
Radio frequency spectrum is a limited natural resource. The word spectrum refers to a
collection of various types of electromagnetic radiations of different wavelengths.
Spectrum is the most important resource or raw material for the telecommunications
industry
In India, currently, the radio frequencies are arbitrarily confined between 9kHz and 3000
GHz and are being used for different types of services like fixed communication, mobile
communication, broadcasting, radio navigation, radiolocation, fixed and mobile satellite
service, aeronautical satellite service, radio navigational satellite service etc.
Some of the important and typical characteristics of the radio frequency spectrum are as
below:
(a) Radio frequency spectrum does not respect international geographical boundaries as it is
spread over a large terrestrial area.
(b) Use of radio frequency spectrum is susceptible to overlapping interference and requires
the application of complex engineering tools to ensure interference free operation of
various wireless networks.
(c) Unlike other natural resources, radio frequency spectrum is not consumed upon its
usage. It is also liable to be wasted if it is not used optimally and efficiently. Radio frequency
spectrum usage is therefore to be shared amongst the various radio services and must be
used efficiently, optimally and economically in conformity with the provisions of national
and international laws.
Spectrum Management at International Level
All nations share the electromagnetic spectrum and reserve their right to its unlimited use.
However, for international telecommunications cooperation to support trade,
transportation, communications, and mutual protection against interference, they have

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agreed to an International Telecommunications Convention. This serves as the basic
instrument of the International Telecommunications Union (ITU) and its two supporting
bodies. The United Nations recognizes the ITU as the specialized agency in the
telecommunications field. The ITU maintains cooperation to improve all
telecommunications. The ITU allocates the international radio frequency (RF) spectrum,
registers frequency assignments, and coordinates resolving interference. Upon ratification
by member nations, ITU regulations have treaty status. Each ITU member nation imposes
regulatory measures within its administration. These measures must comply with the
current Radio Regulations (RR) unless expressly excluded by either footnotes or by special
arrangements.
Spectrum Management at National Level
The Wireless Planning & Coordination (WPC) Wing of the Ministry of Communications,
created in 1952, is the National Radio Regulatory Authority responsible for Frequency
Spectrum Management, including licensing and caters for the needs of all wireless users
(Government and Private) in the country. It exercises the statutory functions of the Central
Government and issues licenses to establish, maintain and operate wireless stations. WPC is
divided into major sections like Licensing and Regulation (LR), New Technology Group (NTG)
and Standing Advisory Committee on Radio Frequency Allocation (SACFA). SACFA makes the
recommendations on major frequency allocation issues, formulation of the frequency
allocation plan, making recommendations on the various issues related to International
Telecom Union (ITU), to sort out problems referred to the committee by various wireless
users, Site clearance of all wireless installations in the country etc.
TRAI (Telecommunication Regulatory Authority of India) was set up in 1997 by the
government of India. The Telecommunication Regulatory Authority of India acts as an
independent regulator of the business of telecommunications in the country. The mission of
TRAI is to create and nurture such conditions that encourage the growth of the
telecommunications sector in India so that the country can play an important role in the
world telecommunications society. The main objective of TRAI is to form a transparent and
fair policy environment that encourages fair competition. The authority recommend the
timing and need for the introduction of a service provider that is new, ensure successful

10
inter- connection and technical compatibility between various service providers, and
suggest the conditions and terms on which license would be provided to a service provider.
NATIONAL FREQUENCY ALLOCATION PLAN - The National Frequency Allocation Plan (NFAP)
forms the basis for development and manufacturing of wireless equipment and spectrum
utilization in the country.

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EVOLUTION OF SPECTRUM MANAGEMENT IN INDIA
The management of spectrum in India can be divided into three stages across time. This
classification is based on varying degrees of spectrum market liberalization.
In the first stage, the market was relatively nascent but, in principle, auctions were the
preferred method for spectrum allocation. In the second phase, the market matured and
grew at a rapid pace, but spectrum was allocated through the administered route. This
highly administered spectrum environment was characterised by allegations of the
government having misused its discretionary power. Such an environment gave way to the
third phase where extensive liberalisation of spectrum is being attempted.
At the very outset, we should understand the method and challenges of spectrum allocation
in India. Frequency spectrum is used in the country by various stakeholders, and therefore is
a scarce resource.
It is also important to understand that this allocation is what determines the pace at which
the country will upgrade to next generation networks, the inclusiveness of telecom
penetration, and opportunities for indigenous manufacturing. And each of these is
dependent on the availability of spectrum within certain specific bands. The ability of DoT to
fulfil its obligations in turn depends on its ability to coordinate between the relevant
ministries and negotiate at the International Telecommunication Union (ITU) which aims to
harmonize frequencies to reap economies of scale and align with technological progress.
(Prasad & Sridhar, 2014)
Therefore, it can be concluded that a major portion of the spectrum used worldwide is not
available for mobile services in India. It is this context of the scarcity of spectrum for
commercial services that we analyse the different phases of spectrum management in India.
First Stage: Auction of Scarce Spectrum (1992-2003)
The first stage of spectrum management in India was characterised by a licensing process
that started in 1992, along with the liberalization efforts carried out in other sectors of the
economy. The government aimed to bring in private players in the mobile telephony

12
industry, and increase market participation.
Licenses were initially given for the four metros using a ‘beauty parade’1
method. In this
case, the bids were evaluated based on certain pre-qualification criteria including bidders’
financial net worth, and prior experience in telecom service provisioning. Metro licenses
were issued and the first digital cellular service started in the metros in 1995.
In August 1995, licences were awarded to cellular mobile service providers (CMSP) through
auction. The process consisted of a single-stage auction. This single-stage auction led to high
revenues for the government due to the particular pricing mechanism adopted. 2
The award of licenses through a single-stage auction brought in substantially high license
revenues for the government treasury. It also reduced the regulatory workload of allocating
spectrum.
Two operators were selected for each License Service Area (LSA). Himachal Futuristics
Communications Limited (HFCL) had the highest bid in 9 circles. In many cases its bid was
more than double the second highest bid. The government, fearing that public monopoly
would be replaced by a private monopoly, “allowed” the company to “choose” 3 circles.
The telecom industry being still nascent, the bidders were unaware of how to evaluate
market potential. Moreover, the bidders were provided with little leeway to revise their bid
amounts based on the information available, since the auction was single-staged. All this
resulted in high bids. (Prasad & Sridhar, 2014). This led to a very poor response from the
rest of the players, as there were few bidders with a general perception that the reserve
price was too high – nine circles remained without any service providers. Subsequently, only
six providers signed the license agreement. (Jain, 2001)
Despite the poor response, the origin of the telecom landscape in India was met with much
euphoria. However, this elation was short-lived.
As mentioned above, the bids were excessively high bids - specifically the license fee
payable over the license period.
1
A method where operators showcase their proposals for use of spectrum and are selected based on those
2
The minimum annual license fees due from the operators over a six-year horizon were specified in advance.
The bids were evaluated based on certain pre-qualification criteria including bidders’ financial net worth, and
prior experience in telecom service provisioning. The operator was to pay either the annual license fee as pre-
decided or Rs. 5000 per subscriber, whichever was higher.

13
Therefore this auction eventually led to the phenomenon of ‘the winner’s curse’. This is a
phenomenon that occurs in auctions, due to incomplete information, i.e., when bidders only
possess estimates of the value of the good. It is an example of adverse selection3
, similar to
the classic ‘lemons’ example. Usually, rational bidders anticipate the adverse selection prior
to bidding, and do not pay more than the good’s value. In cases where naive bidders ignore
adverse selection, and bid sufficiently higher than a rational bidder would, they end up
paying more than the good is worth.
This led to heavy losses incurred by the operators till 1999, and default in payments to the
government. This situation led to the government proposing a migration package for the
existing licenses from a fixed license fee payment to a revenue sharing one. Allocation of
spectrum beyond the start-up spectrum level was based on availability and attracted
additional revenue share as spectrum charges.
Moreover, the entire system was economically inefficient due to the problem of the
winner’s curse.
Later on, in 2001, a multistage auction was conducted for giving out the fourth cellular
license. A three-stage ascending auction procedure was used. There was considerable
reduction in bid amount compared to the first round, due to the information available and
ability to change bids accordingly at multiple stages. Probability of winner’s curse was
reduced. The reduction in bid amount was due to the fact that the cellular mobile service
market had grown and showed a certain maturity level and hence it became possible for
operators to bid realistically, after considering the market potential. Moreover, the payment
was to be made upfront as opposed to the deferred payment method adopted in 1995,
making the operators bid with more caution.
In addition to the entry fees, licensees were required to pay a percentage of annual revenue
as spectrum charges. Further allocation of spectrum beyond the start-up spectrum levels
was based on availability and justification and attracted additional revenue share as
spectrum charges. (Prasad & V., 2009)
3
Adverse selection is a phenomenon wherein the insurer is confronted with the probability of
loss due to risk not factored in at the time of sale.

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Then, in 2003, under the recommendation of the Lalwani Committee, the subscriber-linked
spectrum allotment procedure, referred to as Subscriber Based Criteria (SBC) was
introduced, under which spectrum allocation was contingent on the achievement of certain
subscriber measures.
Since telecom infrastructure was poor in the country, the initial policy objective was to
encourage and mandate private operators who got licence and spectrum to set up the
needed infrastructure, or start-up spectrum. The government, after assigning the spectrum
to licensees, expected them to develop infrastructure. Strict roll-out obligations were
imposed on the spectrum holders with penalty clauses for noncompliance.
The spectrum was based on the principles of maximal usage. (Prasad & Sridhar, 2014)
This method of spectrum allocation was very different from the methods followed in other
countries where a sizable spectrum block was given to the operators as start-up spectrum.
The reason for this was the scarcity of spectrum due to non-availability from the military.
Hence the Department of Telecommunications (DoT) released spectrum in smaller chunks
as and when spectrum was made available for commercial mobile services. (Prasad & V.,
2009)
Second Stage: Administered Spectrum Allocation (2003-2009)
The second stage of spectrum management in India was characterised by an administrated
approach of spectrum allocation and pricing. This stage saw the entry of CDMA operators as
well as, and more importantly, the introduction of the Unified Access Service Licence (UASL)
in November 2003, that allowed the operators the use of any access technology to provide
any access service.
This period also saw the introduction of the first come first serve basis allocation
methodology for assigning spectrum to licensees. License and start-up spectrum were still
bundled as before.

15
During 2001-2006, incumbents were operating with sub-optimal quantities of spectrum and
did not have enough spectrum to accommodate existing or new subscribers. Therefore, it
was believed that the incumbents would have the first right to additional spectrum.
This stance can be clearly understood by the TRAI’s recommendation papers during 2001-
2006.
For instance, the TRAI Recommendation on Spectrum, 2005 says –
‘From the analysis of the level of competition it is evident that with 4 to 7 mobile operators
in different service areas, there is adequate competition in almost all service areas. It is
therefore recommended that before we consider allocating spectrum to new service
providers it is necessary to ensure that existing service providers have adequate spectrum.’
(TRAI, May 2005)
TRAI (2006) continued to maintain that there was a shortage of 2G spectrum.
As long as TRAI was of the view that the 2G spectrum was in short supply, it recommended
that the 3G spectrum be treated as an extension of the 2G spectrum and be restricted to
incumbents.
Meanwhile, additional spectrum was also getting vacated by the defence ministry. Along
with this, based on enhanced spectral efficiencies in relation to market demand, TRAI
came to believe that 2G spectrum was not in short supply. The authority recommended
that the Government should not treat the allocation of 3G spectrum as an extension of 2G
spectrum.
TRAI in 2007 recommended that no cap be placed on the number of telecom access
service providers in the country allowed more new firms to enter the market by paying
the low fixed entry fee.
The operators rushed to acquire licenses, as the mobile subscriber base grew considerably.
The growth of the subscriber base was so high that over 10 million subscribers were being

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added every month. In the year 2006, India became the fifth country where the number of
subscribers crossed the 100 million mark. It soon overtook China as the fastest growing
market in telecom in the world. In 2008, India overtook USA in terms of number of
subscribers. (Gupta, 2011)
This growth was further fuelled post 2008 due to the following developments:
1. Lifetime prepaid scheme launched (2008)
2. Dual technology (CDMA-GSM) services launched (2008)
3. Paisafication of voice call rates (2009)
4. More new entrants launched service (Starting from early 2008)
Hyper-Competition and Fall in Price of Service
During this period, there was hyper-competition among players as they rushed to make
gains of the rising demand for mobile services, and this included new entrants. The industry
experienced tremendous growth as well. Vodafone acquired Hutchison Telecom India’s 67%
stake for USD 19.3 billion. Bharati became the third largest mobile operator in the world.
Tata Teleservices in a strategic move introduced per second billing and others followed.
(Gupta, 2011). This was called the one paisa revolution where an innovative marketing and
packaging concept called ‘price point pack’ (PPP) - a strategy that is used in other products
as well where a small portion of the product is sold at an affordable price - was applied to
call rates. Prior to this scheme, customers were billed per minute, even if they talked for a
few seconds.
Therefore, the intense competition led to a substantial reduction in prices of services as
well, directly benefitting consumers.
This policy of spectrum assignment was quite unusual, if not unique. Elsewhere in the world
operators typically received the full amount of spectrum in a specified band at the time they
were licensed. (Lewin, et al., 2008)

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However, this policy was famously controversial due to irregularities and inconsistencies in
the process used for allocation of spectrum. These irregularities were mainly of two kind:
1. The spectrum was pegged at the value determined in the 2001 fourth license auction
2. There was severe arbitrariness in the due date set for the receipt of applications for UAS
licences.
Apart from these irregularities, the government came under severe scrutiny for other
misdeeds. The faulty and arbitrary manner in which spectrum was allocated by the DoT was
highlighted on a large scale by the media as well as opposition parties, alleging that the
government ‘cherry-picked’ TRAI’s recommendations to benefit a few firms.
The speculations were put to rest when on 2 February 2012, the Supreme Court of India
delivered its judgment on a public interest litigation directly related to the ‘2G spectrum
scam’. The Court declared the allotment of spectrum as ‘unconstitutional and arbitrary’ and
quashed all the licences issued on or after 1 January 2008 during the tenure of A. Raja (the
then Minister of Communications and IT and the main official accused in the 2G scam case.
The court further stated that the minister ‘wanted to favour some companies at the cost of
the public exchequer’ and ‘virtually gifted away an important national asset’
These irregularities cost the exchequer a loss of Rs. 1.76 lakh crore, estimated on the basis
of the price discovered in the 36 and BWA auctions conducted later in 2010 by the
Comptroller and Auditor General of India. The CAG contended that these “presumptive” or
“notional” losses incurred by the country were due to the following: (a) under-pricing 2G
spectrum (b) allowing companies to use two competing technologies – GSM and CDMA –
with the same licence, and (c) allocating more spectrum to companies than what their
licences specified. (Thakurta & Kaushal, 2010)
Third Stage: Liberalisation of Spectrum Allocation (Post 2009)
In the aftermath of the tumultuous events that followed the 2008 licensing policy, the move
to a liberalized spectrum regime was hastened, although the first steps towards this

18
direction were taken in 2006 itself through TRAI’S consultation on the auction of the 3G
spectrum. In 2010, the spectrums for 3G and broadband wireless access (BWA) were
assigned. The auction design used for these auctions was the simultaneous ascending
auction. For the first time in the history of spectrum allocation in India, the licence was
explicitly delinked from spectrum. A license was a prerequisite for providing service but no
longer for obtaining spectrum.
Due to the controversial assignment of spectrum in 2008 and the ensuing political upheaval,
the incumbents were not assigned any 2G spectrum post 2008 based on the extant
subscriber based criterion.
One significant change in the eligibility criterion for the BWA spectrum auction was that
Internet Service Providers were also allowed to participate in the auction process, mainly to
improve broadband penetration in the country.
The uproar over the 2008 licensing policy brought home the need for a new framework for
spectrum management. The New Telecom Policy was unveiled in 2012. The policy envisaged
a liberalization of spectrum management. Some of the key recommendations were:
1. To move at the earliest towards liberalisation of spectrum to enable use of spectrum
in any band to provide any service in any technology as well as to permit spectrum
pooling, sharing, and later trading to enable optimal utilization of spectrum.
2. To re-farm spectrum and allot alternative frequency bands or media to service
providers from time to time to make spectrum available for introduction of new
technologies for telecom applications.
3. To prepare a roadmap for availability of additional spectrum every 5 years.
4. To identify additional frequency bands periodically, for exempting them from
licensing requirements for operation of low power devices for public use.
5. To review the existing geographical unit of allocation of spectrum with a view to
identifying scope for optimization.

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AUCTIONS VIS-A-VIS OTHER WAYS OF ALLOCATION
Private party access to public property can be assigned through various ways.
The government must determine the selection mechanism for deciding who has access to
these resources. The government may carry this out using the following four methods to
allocate private parties the rights to use public property – administrative process, lottery,
first-come-first-served, and auction.
In administrative processes, the decision on the allocation of the resource is made by
politicians or bureaucrat, either by some ad hoc process or through formally constituted
hearings. The government can choose decision criteria under its own discretion and use
these to address its policy goals. However, such processes are usually slow and
cumbersome. They usually involve assigning valuable public resources for less than their full
value and often for free. They also lack transparency. (Afualo & McMillan, 1996)
Lotteries are an assignment of public resources through random draws. Although attractive
because of relative quickness and low costs to government, and the perception of being fair,
they have drawbacks in the form attracting frivolous applicants and speculators. The state
cannot be ensured that the winner is capable and competent enough to maintain and utilise
the resource efficiently.
First-come-first-served involves a public announcement of the type of queue to be used, as
well as the number of people at the front of the line who will receive public property lines.
(Afualo & McMillan, 1996). FCFS, like the lottery has the same random character and
inefficient outcomes as a lottery. It is difficult on the part of the government to analyse the
value of the resource to each entity and therefore, to ensure its efficient utilisation.
In the case of the Indian Telecom Sector, up until , the prices were decided by government
in each of the cases so we learn that there was no price discovery mechanism to decipher
efficient market prices. The weakness of the previous mechanism and its vulnerability to
corruption is an established fact after the Supreme Court verdict in February, 2012 which
recognised the FCFS method of allotment of 2G licenses as arbitrary and deliberately

20
designed to favour certain undeserving candidates. The apex court cancelled all the 122
licenses which were distributed in 2010 and ordered the regulatory authority to make fresh
recommendations to the Department of Telecommunication for the assignment of
spectrum.
Auctions - The primary advantage of an auction is that it assigns spectrum to those who
value it the most. This is accomplished by competition among the applicants. The
government needs to know how highly firms value the public resource if it is to allocate it
efficiently. A bid reveals the bidder’s approximate valuation of the resource. The bid
underestimates value, since the bidder is bidding for some profit. Bids are quite close to
values as the theory of auctions shows, if (a) there are enough bidders to generate
significant bidding competition; and (b) bidders are reasonably confident of the precision of
their value estimates. An auction, therefore, reveals information: how valuable the bidders
believe the resource to be, and which bidder values it the most.
A second important advantage of auctions is it generates revenues for the government.
Finally, an auction, unlike administrative processes, is a transparent means of assigning
licenses. All parties can see who won the auction and why.
Auctioning forces the government to be explicit about its criteria, since in an auction the
rules must be states fully in advance.
We explain the first two advantages below:
Price Discovery
The efficiency of an auction lies in its ability to facilitate the valuation of the scarce
resources through the market mechanism. When the forces of demand and supply interact
in a competitive market structure then the resultant prices are the most efficient prices
(since they are discovered through competition). This role of well-designed efficient
auctions in discovering the market determined price is known as price discovery. True and
efficient price discovery is only possible in a competitive market, and such a market is
ensured by auctions.

21
Revenue and Efficiency
Efficient allocation of spectrum means placing spectrum in the hands of those able to create
greatest overall benefit from it. Provided that competition between spectrum licensees in
providing telecoms services is effective, efficient allocation can usually be achieved by
licensing spectrum to whoever values it most.
Spectrum sales are an important source of revenue for governments. Therefore, some
governments have taken an explicit approach of maximising revenue, provided there is
sufficient downstream competition in the industry.
Given the importance of services derived from spectrum for the wider economy,
governments are typically best served by seeking to maximise the overall benefit to society
from spectrum, rather than simply maximising receipts from spectrum sales in the short-
run.

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SPECTRUM AS AN ECONOMIC GOOD
The Economic Classification of Goods
Good can be classified along two dimensions – EXCLUDABILITY and RIVALRY.
A good is called excludable if it is possible to exclude users from its use – possible from the
viewpoint of social acceptability, economic feasibility, and engineering capability.
Examples of excludable goods include iron ore, or a cone of icecream.
If it costs an enormous amount of money to exclude users, or if exclusion is infeasible from a
social standpoint, or if the state-of-the art engineering solutions are unable to create
exclusionary systems, then the good is said to be non-excludable.
Fishing rights on open seas, or power in rural India, or a pasture that is traditionally shared
by a village community are non-excludable goods.
If the use of a good by a user precludes its consumption by another user, then the good is
said to be rivalrous.
An ice-cream bar or a pen being used at a particular point in time is rivalrous.
On the other hand, if the use of a good by one user does not in any way reduce its
consumption by another user, then it is said to be non-rivalrous.
For example, a movie in a theatre is non-rivalrous, up to the capacity of the theatre.
Most goods are not perfectly rivalrous or non-rivalrous but somewhere in between, that is,
they are partially rivalrous.
It is important to understand that classifying a good along one of the categories often
required a clear specification of the amount of the good in question, the time over which it
is used, and the number of users in question. For instance, a tennis court is rivalrous to the
extent that two sets of players cannot use it at the same time, but if shared use over time is
not a problem, and if simultaneous use can be avoided, then it can be used by multiple

23
users without reducing anyone’s enjoyment. Therefore, the context in which the good is
used is important in the classification.
Combining the two independent dimensions of excludability and rivalrousness, all goods in
specific contexts can be classified in one of the following groups:
Excludable and rivalrous: Private goods – anything for which private property rights can be
defined and which cannot be shared without reducing each individual’s enjoyment. Such
goods can be efficiently allocated with the use of market mechanisms, assuming certain
necessary conditions for competition hold.
Non-excludable and rivalrous: Commons goods – These are goods where exclusion is not
feasible and a user’s consumption partly curtails the possibility of consumption by others.
Examples include village pastures, ponds, and fishing rights in open sea. The market
mechanism breaks down for such goods since potential users would try to ‘free-ride’ on
account of the non-excludability.
Excludable and non-rivalrous: toll goods – These are goods for which exclusion is possible
and users can undertake consumption without curtailing the consumption of others (up to a
point). Examples include toll road, social clubs etc. Market mechanism breaks down because
of the inappropriateness of levying fees associated with non-rivalrous goods. Such goods are
often provided through a model of public-private partnership, where a private party is
contracted by the government.
Non-excludable and nonrivalrous: pure public goods – examples are - a lighthouse that
uniformly gives light to all, and cannot be limited to seafarers alone. Other examples are
national defence and basic research. Government provision and provision of subsidies to
private producers through competitive bidding are some ways to allocate public goods
efficiently.

24
We analyse the nature of spectrum in terms of these characteristics:
Excludability – Technological solutions for monitoring exclusive use of spectrum blocks are
available. Licensing the use of spectrum is also commonly practised. Therefore, spectrum
can be considered an excludable good.
Rivalry – The rivalrousness of spectrum is contingent on a number of factors. Users of
telephony (or data service) use specific frequencies to transmit signals. The transmission of
signals of sufficiently high power by multiple users at the same time and at the same
frequency in close physical proximity leads to interference that can render the system
unusable. This interference makes spectrum use rivalrous, at least partially.
However, the degree of interference depends on technology, device capability, number of
users, and application needs. For instance, Time Division Multiple Access (TDMA) systems
send powerful signals over narrow spectrum channels, in which case interference is a real
possibility. However, there are devices today that use sophisticated multiplexing
arrangements that significantly reduce the risk of interference with other devices.
EXCLUDABLENON-EXCLUDABLE
RIVAL
NON-RIVAL

25
This partial rivalrousness of spectrum could lead us to treat it as a common property
resource. But such a good is subject to the tragedy of the commons, or congestion. This
situation arises when the partially rivalrous good is over-utilised in the absence of
coordination, when individuals seek maximise their returns. In order to resolve this
problem, government can control the good, by deciding the amount of good that is optimal
for use by the potential users, and levying a toll on them. In addition to alleviating
congestion, the toll serves to defray the cost of setting up and maintaining the toll good.
The case of spectrum as a toll good however, presents an additional complexity, as due to
the lack of dynamic sensing of signals, there could be congestion even in the absence of
rivalrousness. Given the lack of such a line of sight in the case of wireless technologies and
the rivalrousness of spectrum, the allocation of private property rights over spectrum blocks
has been considered necessary for efficient management.
The noted economist, Ronald Coase, in as early as 1959, suggested the use of auctions as a
way of allocating property rights in spectrum.

26
AUCTIONS IN INDIA
The government of India has maintained throughout (DoT, 2010) (DoT, 2012) (DoT, 2013),
that the following are the objectives of the auctions conducted:
 Obtain a market determined price of 3G/ BWA spectrum through a transparent
process;
 Ensure efficient use of spectrum and avoid hoarding;
 Stimulate competition in the sector;
 Promote rollout of 3G and Broadband services;
 Maximise revenue proceeds from the Auctions;
 Resolve congestion issues related to second generation (“2G”) mobile services.
Hence the primary criterion is to ensure efficiency, second is to promote competition (tackle
collusion and concentration) and the third objective is revenue generation.
3G and BWA Auction
The government of India, following the liberalisation policies of spectrum, auctioned the
following frequencies in 2010:
3G Auction - 2.1GHz, paired, in blocks of 5MHz, i.e. each block of 2X5MHz
BWA Auction ƒ 2.3GHz, unpaired, in blocks of 20MHz
Spectrum usage rights were assigned separately and independently for specific service
areas.
1800 MHz and 800 MHz Auction – 2012
In 2012, the following two frequencies spectrum were auctioned -

27
a) 1800MHz Auction - block size was of 1.25MHz (Paired). 8 blocks each of 1.25MHz (10
MHz) were put to auction in all 22 Service Areas. In addition, a provision was made for
spectrum up to 3 blocks each of 1.25MHz (3.75MHz
b) 800MHz Auction - block size was of 1.25MHz (Paired). 3 blocks each of 1.25MHz
(3.75MHz) was put to auction. In addition, a provision was made for spectrum of one block
of 1.25MHz, wherever available, for topping up the 3 blocks of spectrum put to auction.
However, this auction was characterised by very high reserve prices, which led to very low
applications and saw some withdrawals before the auction as well. The government
received bids worth a total of Rs 94.07 billion (US$1.5 billion), far lower than its target
of Rs 280 billion. No one bid on the India-wide spectrum, which had a reserve price of Rs
140 billion.
800 MHz -2013 Auction
In the 2013 spectrum auction, the Government planned to auction 50 MHz of airwaves in
the 1800 MHz band and 76.25 MHz of spectrum in the 800 MHz band. The Government put
CDMA spectrum worth ₹64 billion (US$1.0 billion) up for auction.
However, no bidders expressed interest in the 1800 MHz and 900 MHz bands and as a
result, the auction for those bands was postponed indefinitely.
The high reserve price issue was repeated in this auction and the sole bidder in the auction
was Sistema Shyam TeleServices Limited (SSTL), under the brand name MTS, who bid for
spectrum in the 800 MHz band.
1800 MHz and 900 MHz Auction – 2014
In 2014, the Dot auctioned 2G telecom spectrum in the frequency range of 900Mhz and
1800 MHz. The winners were awarded spectrum in February. The Government earned Rs
612 billion from the spectrum auction. The government learnt from its past mistakes and
this auction turned out to be highly competitive, with eight participants in the auction.

28
800 MHz, 900 MHz, 1800 MHz and 2100 MHz Auction - 2015
The 2015 spectrum auction concluded on March 25, after 19 days and 115 rounds of
bidding. Spectrum in the 800 MHz, 900 MHz, 1800 MHz and 2100 MHz bands was
auctioned. The Government accrued a total of ₹109.874 crore (US$17 million) from the
auction, the highest so far.

29
COMPETITION ISSUES IN AUCTIONS
AUCTION DESIGN
The participation of operators and competition effects of auctions are closely related to the
design of the auctions.
The following are the competition issues in auction designs:
Collusion and Bid rigging
The primary threat to the success of any auction design (in being transparent and ensuring
competitiveness) is Collusion. There is always the risk with any design that participants may
explicitly or tacitly collude to avoid bidding up prices.
Often the participants in the bidding process may take recourse to some signalling (signal by
bid figures or press statements etc.) whereby the bidders tacitly collude and succeed in
suppressing the prices or they may get into credible collusive agreements of keeping the
bids low or abstain from bidding in expectation of sharing the spoil later. This causes severe
harm to competitive price discovery and efficiency.
Bid rigging is a much wider concept and encompasses activities like collusion, bribing and
other such practices. These concepts are explicitly stated in Section 3 of the Competition
Act, 2002, India.
Entry Problem
The second major concern of practical auction design is to attract bidders, since an auction
with too few bidders risks being unprofitable for the auctioneer) and potentially inefficient.
The format of the auction can very well determine whether incumbents can deter entrants
from being involved in bidding procedure, or depress the bidding of rivals. Entry is of utmost
importance to check concentration of power, help price discovery and encourage healthy
competition in the bidding process.
Predatory behaviour (abuse of dominance)
Often the effectiveness of an auction format as an efficient, competition friendly and
transparent mechanism is greatly reduced to the threat of predation by dominant

30
incumbents. A strong bidder also has an incentive to create a reputation for aggressiveness
that reinforces its advantage.
Mergers and acquisitions
Mergers and acquisitions may be either post-auction (takeovers and agreements after
assignment through auctions) or pre-auction (mergers and acquisitions before the auction).
Both of these activities are strategic in nature and may be detrimental to competition and
change the market structure. In the Indian context, with reference to the
telecommunication sector which comes under the purview of the competition authority and
therefore the Competition Act, 2002-
‘Entering into a combination which causes or is likely to cause an appreciable adverse effect
on competition within the relevant market in India is prohibited and such combination shall
be void’. However auctions are prone to merger and acquisition concerns.
Such activities can be kept in check under a good competition policy, as is the case in the
country today.
Bid snipping and activity rules
While studying auction designs and its competition friendliness, bid snipping concept is
indispensable. Bid snipping is a strategy player by a bidder whereby he/she is able to keep
his/her true preferences for a particular object in an auction (multiple-round auction) secret
until the end. Considering a spectrum auction for various circles, when a bidder in a multiple
round auction does not disclose his interest in bidding for a particular until the last round
when he suddenly jumps into competition for that particular circle and bids highly for it, we
name it bid snipping. This strategy of hiding interest for a particular object helps in keeping
the final bid price low. Bid snipping violates transparency and consistency in bidding
behaviour.
Activity rules may be quantity (of spectrum bid in each round) based or preference
revelation (consistency requirement in bidding for particular circles) based. (Kankrania,
2012)
AUCTION DESIGN - INDIA

31
The Indian design for the auction of spectrum licenses is called the Simultaneous
Multiple Round Auction (SMRA). It has been designed keeping in mind the clock auction4
.
Now, let us analyse the Indian auction format.
The format consists of a two stage process of allocating the lots among the bidders the first
being the clock phase and second the assignment phase (frequency identification phase).
In the first phase, which is modelled on the Simultaneous Clock Auction, the auctioneer
begins by setting the clock prices to the reserve price for each of the 22 telecom circles for
which the licenses are being auctioned ( there is one clock for each telecom circle). The
bidders are expected to indicate in a 1 / 0 format their demand for lots in the desired circles
at the prevalent clock prices. In case the demand for lots exceeds the supply in a given
circle, the clock prices are then increased relative to the previous round clock price
according to a pre-specified formula. At the end of each round provisionally winning bids
were declared. The clock round continues simultaneously and independently in every circle
(all service areas remain in play till the end) till the demand is no more than the number of
available lots in every service area and the activity level reaches 100%
The bidders were required to maintain certain activity level in each round based on the
eligibility point system so as to qualify for bidding in the subsequent rounds (the activity
level tightens as the auction proceeds to higher rounds). (Kankrania, 2012)
In the second phase i.e. the frequency identification stage specific frequencies available to
Winning bidders are identified.
We now critically analyse this auction design, with respect to its effect on competition:
A few pros and cons of this design which are as under:
 Since it’s a multiple round clock auction predatory jump bidding is not possible
4
In this mechanism, the seller starts the auction at a low price (possibly zero). Bidders
express their willingness to buy the object at every price. If the number of bidders who want
to buy the object at the current price is more than one, then the seller increases the price by
a predetermined amount, called the bid increment. The auction stops when there is exactly
one bidder who wants to buy the object. The highest value bidder wins the object and pays
a price (close to the) equal to the second highest value.

32
 Restricting the bids to quantity bids at specified clock prices and nondisclosure of
identity of provisional winners (bidders can only know the total demand in each
area, not who is bidding for what), the possibility of use of collusive and retaliatory
strategies is precluded. By limiting the release of information to the excess demand
at the end of each clock round and eliminating the need for disclosing the identities
of the provisionally winning bidders, an effective trade-off between releasing
sufficient information to aid the price discovery process and prevent collusion and
retaliation has been achieved.
 Activity rules aimed at avoiding ‘bid snipping’ do not prevent the bidders from
employing parking strategies to hide their intent until the late stages thereby
impeding the process of price discovery. The reason is that the quantity based
activity rule in simultaneous ascending auctions which entails a big bidder at the end
of the auction to be a big bidder throughout does not take into account that the
bidder may retain his eligibility to bid by just sitting on an area with weightage
similar to his area of interest. For example, a bidder may retain his eligibility to bid
for, say Delhi Circle, by submitting parking bids for the eligibility -wise equivalent
Mumbai circle, till such time he feels that the auction for the Delhi circle is reaching
the final stage, at which moment the bidder can switch without any cost. Thus
parking strategy permits bidders to hide their true bidding intent from their rivals
and inhibits the revelation of common value information so critical to the price
discovery process. (Kankrania, 2012)
 One of the most important competition issues being entry and post-auction market
structure. In an open auction format adopted by India, it is difficult to attract
entrants since they participate in the auction with a relative disadvantage against the
existing 2G incumbents with their existing customer bases, established brand names
and lower cost of rolling out network ( as they can ride on the existing 2G
infrastructure).
Inability to attract sufficient number of entrants results in the incumbents dividing
the licenses amongst themselves and lower revenue realization from the auction. In

33
India’s case, the number of licenses on offer (between 3 and 4) is much lower than
the number of incumbents (approx. 7).
However, by international yardsticks, India has comparatively far larger number of
incumbent operators. HHI can be used as a measure to measure the concentration in the
industry.
The Herfindahl–Hirschman Index (HHI) is a commonly accepted measure of market
concentration. It is a measure of the size of firms in relation to the industry and an indicator
of the amount of competition among them. Named after economists Orris C.
Herfindahl and Albert O. Hirschman, it is an economic concept widely applied in competition
law, antitrust and also technology management. The HHI is calculated by squaring the
market share of each firm competing in the market and then summing the resulting
numbers.
The HHI takes into account the relative size distribution of the firms in a market. It
approaches zero when a market is occupied by a large number of firms of relatively equal
size and reaches its maximum of 1 when a market is controlled by a single firm. The HHI
increases both as the number of firms in the market decreases and as the disparity in size
between those firms increases.
We look at the subscriber-based Herfindahl - Hirschman Index (HHI) for the telecom
industry. The subscriber data has been sourced from the Cellular Operators Association of
India Subscriber Reports.

34
Source: (COAI, 2015)
Given that the current Herfindahl-Hirschman Index (HHI) for mobile telephone industry (for
GSM services) at the circle level is around 0.3 on an average the market does not appear to
be unduly concentrated.
Such a level of concentration is acceptable for an industry like telecom and its particular
characteristics: This is closely related to the allocative efficiency of spectrum allocation
mechanisms and is elaborated below.
COMPETITION AND ALLOCATIVE EFFICIENCY OF SPECTRUM
ALLOCATION
When designing any spectrum allocation mechanism, it is important to maximise economic
efficiency. In order to do so, the following two should be balanced: dynamic efficiency and
allocative efficiency.
 Dynamic efficiency gains are achieved through increased competition between
cellular operators. One obvious way to make such gains is to increase the number of
operators.
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4 Delhi
Mumbai
Chennai
Kolkata
Maharashtra
Gujarat
AP
Karnataka
T.N.
Kerala
Punjab
Haryana
U.P(W)
U.P(E)
Rajasthan
M.P
W.B&A.N
H.P
Bihar
Orissa
Assam
N.E
J&K
HHI - June 2015
HHI

35
 Allocative efficiency – when there are gains in which the overall costs of the industry
are minimised.
A report prepared by Plum Consulting submitted to the GSMA identifies two effects here
(Lewin, et al., 2008)
– First each new operator incurs fixed costs in terms of core network and IT systems,
marketing, management and network coverage costs regardless of the scale of its
operations. In particular in areas where cells are coverage limited each operator must
deploy the same radio access network, with the same number of cells as its rivals, if it is to
offer competitive coverage. So total costs are lower with fewer operators. Such effects
mean that there are economies of scale in the production of mobile services and, for a given
level of competition and market size, each additional mobile operator raises the unit costs
of the industry
– Secondly the industry's combined radio access network costs rise in areas where the radio
access network is capacity rather than coverage limited, as the number of operators
increases and the amount of spectrum per operator decreases. There are two main reasons:
– The total number of cells required increases as the number of operators grows
– Fragmentation of spectrum assignment has technical effects which reduce the traffic
carrying capacity per MHz.
Although improving dynamic efficiency should be a prime concern of the policy makers,
They should attempt to maximise allocative efficiency as well.
A commonly held view is that competition is the most effective market structure for
ensuring low prices and high quality. However in industries such as telecom and electricity
distribution, economies of scale and scope are large enough to warrant low levels of
competition to minimise unit costs. Telecom operators face huge initial costs, or fixed costs
like laying down copper lines, constructing cell sites and base transceiver stations (BTSs) in
case of mobile service etc, but very low or negligible marginal costs of providing services to
each additional customer, once the network is operational. Therefore, a carrier’s long run
average costs within the defined geographical area may well decline with every increase in

36
the size of the network. In other words, it is often cheaper to provide services to the one-
millionth customer than to the one-thousandth customer.
Because of these particular characteristics of the mobile industry, allocative efficiency is
achieved when there is enough competition but not hyper-competition. The economies of
scale in this industry lead to increasing costs for the individual operator as the number of
operators grow.

37
SPECTRUM AUCTIONS AND THEIR EFFECT ON PRICES OF
SERVICES
There is a view held by many that if telecom operators have to shell out huge amounts for
acquiring spectrum, they will have to pass on these costs to consumers in the form of higher
prices of telecom services, thereby dampening the expansion of the telecom market. Often,
this argument is used to keep spectrum prices low by administrative fiat, thereby giving an
implicit subsidy to the telecom firms. (Malik, n.d.)
It is widely believed that if operators pay for spectrum instead of getting them for free, they
would have higher costs and that these costs would be passed on to their customers in the
form of higher prices.
However, both economic theory and empirical evidence can be used to substantiate that
this conventional wisdom is actually a myth.
A widely held misconception about auctions for spectrum licenses is that they will raise the
price of wireless communications services. If licensees pay for their licenses instead of
getting them for free, it is argued that they would have higher costs and that these costs
would be passed on to their customers in the form of higher prices. This conventional
wisdom is, however, contradicted by both economic theory and empirical evidence.
Theory
Standard economic theory predicts that sunk costs are irrelevant to the pricing and output
decisions of firms. A sunk cost is one that is not escapable. It does not vary with output or
even if the firm goes out of business, and thus should have no effect on any business
decision. The amount paid for a spectrum license in an auction is such a sunk cost. Once it is
paid, the payment cannot be recovered from the government and it does not vary with
output. Therefore, as long as there is no secondary market for trading spectrum, the
historical cost of winning bids at auctions should have no effect on the price or availability of
spectrum-based communications services for customers. (Kwerel, 2000)

38
This is because firms charge prices that maximize profits that are based on forward-looking
variable costs and revenues independent of sunk costs, such as auction fees.
The price of spectrum is typically a function of current supply and demand conditions and
the level of competition, and is not dependent upon the historical cost at which the firms
acquired their spectrum. Since spectrum licences are granted for a 20 year period, the bid
amount, a lump sum payment upfront, is amortized across the duration of licence,
eliminating the chances of a hike in telecom tariff based on historical costs.
There is enough competition in the telecom industry (as also indicated by the low HHI) for
the prices of services to be determined in the market, with each individual firm having
negligible or no market power at all. Moreover, to the extent that auctions assign licenses to
the most efficient producers, facilitate efficient aggregation of spectrum, and move
spectrum into the production of services consumers value the most, they will tend to
expand the supply and reduce the prices of the wireless services most valued by consumers.
The profit maximizing level of output for a firm is determined by equating marginal cost and
marginal revenue. Marginal cost and marginal revenue are independent of sunk costs since
it does not vary with output. The decision to operate or shut down depends on whether
Price exceeds Average Variable Cost, which is independent of sunk costs.

39
Therefore, subsidizing spectrum by giving away licenses for free or at lower prices has no
effect on the market behaviour of rational firms. This subsidy will simply be a windfall gain
that pads the profit of firms without the claimed effects of “lower prices” and “expanded
market size”
Theory predicts that when bidding for a spectrum license in an auction, a firm would never
knowingly bid more than the discounted value of the expected profits from acquiring the
license. Nevertheless, bidders may sometimes overestimate the value of a license and find
that they cannot cover their fixed debt payments. This could result in one-time losses for
the investors and a change in ownership. But even then, because the amount of the fixed
payments is a sunk cost, such losses should not affect pricing or output decisions, including
whether to exit the market. (Kwerel, 2000)
Therefore to say that large licence fees may corrode the finances of the firms is assuming
that firms are not aware of their own future prospects.
It is true that the exorbitant spectrum prices would leave telecom companies with
distressed balance sheets; however, concerns that the rising debt-servicing costs would be
passed onto customers is ill-founded. Robust price competition in the market with the
imminent entry of deep-pocketed players such as Reliance Jio (with the capacity to engage

40
in aggressive pricing strategies) and the proposed inter-circle mobile number portability
(with its significant impact on retaining customer loyalty), would make it tremendously
challenging for telecom firms to unilaterally lump-up tariffs.
RESERVE PRICES
Reserve price for an object or circle in a spectrum auction is the minimum payment the
winning bidder has to make. It is normally driven by some minimum revenue generation
consideration.
It is observed that reserve prices in spectrum auctions:
 discourage frivolous participation;
 represent minimum guaranteed revenue for the seller in case the object is sold as;
 underpin revenue in the case that competition for spectrum is weak;
The revenue v/s efficiency debate is closely related to the reserve price. The difficulty with
setting reserve prices is that if they are to have much effect on revenues, then they must
also run a risk of spectrum not being sold. For this reason, reserve prices are usually not a
particularly effective tool to extract additional revenue from strong bidders facing weak
rivals. The difficulty is that a spectrum authority will typically have relatively poor
information about the likely valuation of winning bidders and not know at what point
spectrum might just go unsold if reserve prices are set too high, as was the case in the 1800
MHz and 800 MHz auctions in India in 2012. It is also possible that high reserve prices deter
participation of entrants.
In practice, this risk means that reserve prices need to be set on a conservative basis relative
to likely market value. This again underlines the importance of making spectrum licences
attractive to potential bidders to boost participation. High reserve prices are a poor solution
to a situation in which competition for spectrum is likely to be weak due to underlying
problems with spectrum licences or regulatory uncertainty.

41
RESERVE PRICE AS A TOOL AGAINST ANTI-COMPETITIVE PRACTICES
Inadequate reserve prices increases the incentives for predation and/or collusion- a strong
bidder can bid aggressively if the reserve prices are low.
Also, bidders have a choice of tacitly colluding to keep the final price low and later sharing
the spoil which is not possible if the reserve price is high enough since then collusion would
be unprofitable to low valuation bidders.
In practice, the most useful function of reserve prices in auction design is not as
replacement for competition, but rather to limit the benefit for bidders from limiting the
field of bidders (for example through pre-auction mergers) or through collusion and so
discourage such behaviour.
As mentioned before, the firms make decisions regarding their fixed costs keeping in mind
their profitability and future prospects. The lump-sum payment is amortized or apportioned
across the period for which the licence is issued.
EMPIRICAL EVIDENCE
Empirically, it can be observed that in the Indian telecom space, the final bid price of
auctions in most service areas, especially the metros was substantially higher than the
reserve price.
In the 2014 auction, the final bid price was on an average 35% higher than the reserve price,
with some service areas garnering more than 100% times the reserve price. The same can
be said for the 2015 auction, where the average final bid price was a whopping 81% more
than the reserve price.
The two tables below give details of only those service areas that had bid prices more than
the reserve price.

42
Financials of the 2014 spectrum auction – Selected Service Areas
S. No. LSA Winners Winning Price (in
Rs Cr) per block of
200 KHz
Reserve price per
block of 200 KHz
(in Rs. Cr)
% increase
from
reserve
price
1 Assam R Jio, Telenor 7.22 1.4 415.71
2 Bihar Telenor 8.62 7.4 16.49
3 Delhi Bharti, Vodafone,
Idea, R Jio
72.8 43.8 66.21
4 Gujarat Voda, Idea, R Jio 47.56 28.6 66.29
5 Jammu &
Kashmir
Bharti, Aircel 1.22 1 22
6 Madhya
Pradesh
Bharti, Idea, R Jio 10.08 8.6 17.21
7 Maharashtra Idea, R Jio 58.07 34.6 67.83
8 Mumbai Bharti, Vodafone,
Idea, R Jio, RCOM
54.4 41.4 31.4
9 Uttar Pradesh
(E)
Voda, Telenor 12.8 12.2 4.92
10 Uttar Pradesh
(W)
Telenor 18.99 12.4 53.15
11 West Bengal Bharti, R Jio, Aircel 4.92 4.2 17.14
Source: DoT (2015)
Financials of the 2015 spectrum auction – Selected Service Areas
S.
No.
LSA Winners Winning
Price (in Rs
Crore) per
block
Reserve
price per
block (in
Rs. Crore)
Percentage
increase from
reserve price
1 Andhra Pradesh Tata Teleservices 757.48 292.5 158.97%
2 Assam RCOM, R Jio 102.77 35 193.63%
3 Bihar R Jio 107.31 106.25 1.00%
4 Delhi Tata Teleservices 1059.62 771.25 37.39%
5 Gujarat R COM 347.18 343.75 1.00%
6 Haryana RCOM, R Jio, Tata 70.71 47.5 48.86%

43
Teleservices
7 Himachal
Pradesh
RCOM, R Jio 24.46 23.75 2.99%
8 Jammu &
Kashmir
R COM, R Jio 35.35 35 1.00%
9 Madhya
Pradesh
R Jio 510.49 113.75 348.78%
10 Maharashtra Tata Teleservices 999.27 423.75 135.82%
11 Mumbai R Jio, Tata Teleservices 909.37 548.75 65.72%
12 North East R COM, R Jio 31.72 13.75 130.69%
13 Odisha R COM, R Jio 51.3 47.5 8.00%
14 Punjab R COM 107.31 106.25 1.00%
Source: DoT (2015)
This clearly shows that the reserve price is not a hindrance to competition in the spectrum
allocation process, at least not any more, since the 2012 experience. The companies work
on incentive structures, like any rational entity. These rational economic and accounting
principles form the basis for their decisions. The substantially high bids as compared to the
reserve price are a good evidence of the point we are trying to make.
We now look at the final list of winners for the auctions conducted in India. They are given
in the following tables:
3G Auction – 2010
S. No. Name of Bidder
1 Aircel Limited
2 Bharti Airtel Limited
3 Etisalat DB Telecom Private Limited
4 Idea Cellular Limited
5 Reliance Telecom Limited
6 S Tel Private Limited
7 Tata Teleservices Limited
8 Videocon Telecommunications Limited

44
9 Vodafone Essar Limited
Source: DoT (2010)
BWA Auction - 2010
1 Aircel Limited
2 Augere (Mauritius) Limited
5 Infotel Broadband Services Private limited
6 Qualcomm Incorporated
7 Reliance WiMax Limited
8 Spice Internet Service Provider Private Limited
9 Tata Communications Internet Services Limited
10 Tikona Digital Networks Private Limited
11 Vodafone Essar Limited
Source: DoT (2010)
1800 MHz and 900 MHz Auction - 2014
1 Aircel Limited
4 Reliance Jio Infocomm
5 Reliance Communications
6 Tata Teleservices
7 Telewings Communications Services Private Limited
8 Vodafone India
Source: DoT (2014)
3G Auction - 2015
1 Aircel Limited
4 Reliance Jio Infocomm

45
5 Reliance Communications
6 Tata Teleservices
7 Uninor
8 Vodafone India
The participation of companies remains the same, indicating their feasibility to acquire
spectrum through auction.
Moreover, the companies are incentivised enough to engage in bidding for a few weeks and
multiple rounds. For instance, for the 3G auctions in 2010, there were 183 rounds over 34
days, with about 5 rounds every day yielding total revenue of 50968 crores from the auction
and an additional 16751 crores from BSNL/MTNL combined. For BWA auctions, there were
117 rounds over 16 days grossing 38500 crores for the government.
The 2014 auction took place over 10 days and consisted of 68 rounds of bidding.
The 2015 spectrum auction concluded on March 25, after 19 days and 115 rounds of
bidding. The Government accrued a total of ₹109.874 crore (US$17 million) from the
auction.
FINANCIALS OF COMPANIES AS EVIDENCE
We also take a look at the financials indicating profitability of companies for five financial
years since the commencement of auctions for spectrum allocation. We specifically look at
the Earnings before Interest, Tax, Depreciation and Amortization (EBITDA) data for five
major players in the market.
It can be used to analyze and compare profitability between companies and industries
because it eliminates the effects of financing and accounting decisions.
Looking at the EBITDA details in the context of the telecom sector is particularly useful as it
gives a true indication of the trend of earnings of a company, before accounting for interest,
depreciation, tax and amortization.

46
The data clearly reveal an upward trend in this particular item of the companies’ Profit &
Loss Account (except for Reliance Communications’ decline in EBITDA in 2011-12, but it later
picked up).
Source: Individual Companies’ Annual Reports (2009-2014)
These positive looking trends are also an indicator of the fact that companies are
incentivised enough to acquire spectrum through auctions, since it is a one-time cost that is
apportioned over the entire horizon.
0
5000
10000
15000
20000
25000
30000
2009-10 2010-11 2011-12 2012-13 2013-14
EBITDA of Major Telecom Players
Bharti Airtel
Idea Cellular
Reliance Comm
Tata Teleservices
Vodafone India

47
THE WAY FORWARD
Both theory and empirical evidence point us towards the fact that auctions do not have
adverse effect on the prices of service rendered by operators. The tariff rates have not risen
substantially post an auction and they will not happen in the future either. (Malik, 2015).
The thumb rule is that spectrum pricing should be determined by scarcity and consumer
tariffs by competition and if that fails, through the Telecom Regulatory Authority of India’s
intervention.
There are many ways forward that the government can take, but here, I elaborate two
points that are essential for a more competitive and efficient allocation of spectrum in the
future in our country.
More Liberalization - Secondary Trading
The importance of secondary markets in maintaining efficient spectrum and wireless
markets is now an accepted fact. It can increase efficiency in allocation by correcting short-
run fluctuations in demand and supply of spectrum and long-run shifts. It also creates
significant valuation differences between an initial licensee and a prospective future user of
that spectrum
Secondary markets could emerge and reinforce the efficiencies created through the
auctions. Any initial allocation for sufficiently long time duration (20 years in Indian case)
does not necessarily ensure that the spectrum will be used efficiently in the future.
It can be seen that countries with the most liberalized spectrum policies (including broad
enabling rights to secondary spectrum markets) actually generate lower prices for spectrum
due to the increased competition that a more liberalized spectrum trading rights create.
The lack of a secondary market in India is a concern. However, government policy can
ensure efficient spectrum use only if it defines the parameters under which secondary-
market transactions can occur in addition to the parameters under which the spectrum is
initially allocated. Well-functioning secondary markets can help ensure that, as demand and
supply shift, spectrum will migrate to more efficient uses, including those by parties outside
of the initial allocation.

48
Artificial scarcity
At times when the revenue generation objective tries to supersede the efficiency and
competition stimulation objectives for the government, it may resort to creating artificial
scarcity. Artificial scarcity would hamper price discovery and cause inefficiency because the
true prices will not be determined by the demand supply interaction (since supply would be
artificially kept low). As such artificial scarcity or say withholding of spectrum in auctions
would cause inefficiency by artificially raising prices.
Spectrum is the basic raw material for telecoms and hundreds of MHz is lying idle with the
government while the networks are in desperate need for more of it. This ‘artificial scarcity’
needs to be resolved at the earliest such that it can be used to deliver on the connectivity
and broadband objectives of the country.
Auction of scarce resources such as spectrum is an attractive source of revenue for a
government which otherwise depends on tax payments and deficit financing to meet its
budgetary expenditure. However, if the sole objective is to raise revenue, then there arises
the problem of inefficiency in allocation and use of the resource which in turn is welfare
reducing. Provided properly designed and implemented, spectrum auctions should not
create significant economic distortions.
The key point is that if a government does not concern itself about downstream competition
in mobile service markets, then efficient allocation of spectrum and maximising revenue are
diametrically opposing objectives. However, if that government operates under the
constraint that it wants effective downstream competition then the objectives of efficient
allocation and maximising revenue are closely, but not entirely, aligned.
Thus, provided measures are taken to promote effective downstream competition, the
objectives of revenue maximization and efficient allocation of spectrum are largely aligned.
In particular, efficient allocation of spectrum requires that licensees pay the opportunity
cost of the spectrum they are awarded; in turn this entails raising some revenue as a by-
product of efficient allocation (defined as the highest valued bidder winning). Ensuring that
spectrum goes to whoever values it most is broadly compatible with obtaining the greatest
revenue; indeed if spectrum did not go to high-value users, then revenue could not be
maximised, although this alignment is not perfect. But for a developing economy like India,
the goal of revenue maximisation cannot be foregone completely in the near future, to say
the least.

49
Therefore, to conclude, the primary objective of the paper was to chart out India’s spectrum
management process over the years, and critically analyse each of the practices followed,
with the help of economic theory. Auctions have come to be an acceptable form of
spectrum allocation in the recent years in India, but a few debates and issues that surround
it have been discussed. With the use of economic theory as well as empirical evidence, we
saw how auctions really are the best way to allocate an important resource like spectrum, If
properly designed and implemented, it will have no adverse effects on competition or
consumer interest (in the form of rising prices).

50
BIBLIOGRAPHY
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and Evidence, s.l.: Federal Communications Commission.

51
Lewin, D., Jervis, V., Davis, C. & Pearson, K., 2008. An assessment of spectrum management
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implications for spectrum policy. Telecommunications Policy, 33(9), pp. 521-533.
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