The indian telecommunications market

Introduction

The Indian telecommunications market has been displaying sustained high growth rates. Riding on expectations of overall high economic growth and consequent rising income levels, it offers an unprecedented opportunity for foreign investment. A combination of factors is driving growth in the telecom market, promising rich returns on investments.

Over the past 10 years, India has registered the fastest growth among major democracies, having grown at over 7 per cent. It represents the fourth largest economy in terms of Purchasing Power Parity. According to a recent Goldman Sachs report, over the next fifty years, Brazil, Russia, India and China – the BRIC economies- could become a much larger force in the world economy. It reports, “India could emerge as the world’s third largest economy and of these four countries; India has the potential to show the fastest growth over the next 30 to 50 years”. The report also states that, “Rising incomes may also see these economies move through the ‘sweet spot’ of growth for different kinds of products, as local spending patterns change. This could be an important determinant of demand and pricing patterns for a range of commodities”. The share of the services sector as a percentage of total GDP is also predicted to rise from the current 46 per cent to about 60 per cent by 2020. The boom in the services sector is slated to come from India, emerging as a chosen destination for software and other IT enabled services, tourism etc. According to a Nasscom- McKinsey & Co. Study, by 2008, the Indian IT software and services sector will account for US$ 70-80 billion in revenues; it’ll employ 4 million people, and account for 7 per cent of India’s GDP and 30 per cent of India’s foreign exchange inflows.

Population projections from the Planning Commission of India suggest that the share of the working age population (15-64 years) in total population will grow from the current 59 per cent to about 65 per cent, translating into 882 million by year 2020.According to the Vision 2020 document for the Planning Commission of India, the country will witness continued urbanisation. The urban population is expected to rise from 28 per cent to 40 per cent of total population by 2020.Future growth is likely to be concentrated in and around 60 to 70 large cities, each having a population of one million or more. This profile of concentrated urban population will facilitate customised telecom offerings from operators. Over the years, spending power has steadily increased in India. Between 1995 and 2002, nearly 100 million people became part of the consuming and rich classes. Over the next five years, 180 million people are expected to move into the consuming and very rich classes. On an average, 30-40 million people are joining the middle class every year, representing huge consumption spending in terms of the demand for mobile phones, televisions, scooters, cars, credit goods and a consumption pattern associated with rising incomes.

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Overview of the Industry

Until the 1980s, the Department of Posts and Telegraphs (under the Ministry of the same name) had the mandate of regulating and offering telecommunications services. It was governed by the Indian Telegraph Act 1885 and the Wireless Act of 1933. In 1985, the Department of Posts and Telegraph was split up into the Department of Telecommunications (DoT) and the Department of Posts. The DoT was established as the state operator, regulator and licensor. It was only in October 1999 that the activities of the operator and licensor were somewhat separated, by the creation of the Department of Telecommunications Services (DTS). This separation, however, was a largely artificial one.

Although the DoT had been charged with operating telecommunications services, its efforts were seen as insufficient. Initial steps towards corporatisation saw the creation of Mahanagar Telephone Nigam Limited (MTNL), which started offering basic fixed services in Mumbai and Delhi in 1987. MTNL still holds a monopoly in those cities, where DoT/DTS is not present at the local level. MTNL is wholly owned by the Government of India and the DoT. Videsh Sanchar Nigam Limited (VSNL) was set up in 1986 as the monopoly operator for international gateway services.

On May 13, 1994, the government opened local basic and value-added telecommunications services to competition. Mobile services were introduced on a commercial basis in November 1994. India was thus divided into 21 “Telecom Circles”. Circles correspond approximately to states and are categorized as either “A”, “B” or “C” according to size and importance. Category A includes the heaviest volume areas such as Delhi, Uttar Pradesh, Maharashtra, Gujarat, Andhra, Karnataka and Tamil Nadu. Licenses for mobile services were also issued for the four metros (Delhi, Mumbai, Chennai, Calcutta). As part of the license conditions, traffic could be routed to VSNL’s international gateway only by passing through DoT/DTS’s network. In 1986, the Telecom Commission was set up with the mandate to accelerate the deployment of telecommunications services and to implement new telecommunication policy.

A bill passed in 1995 envisaged the creation of an independent and autonomous agency for the regulation of telecommunications, the Telecommunications Regulatory Authority of India (TRAI). Set up in 1997, the TRAI is responsible facilitating interconnection and technical interconnectivity between operators, regulating revenue sharing, ensuring compliance with license conditions, facilitating competition and settling disputes between service providers. The TRAI cannot grant or renew licenses and this remains the DoT’s responsibility. The TRAI may also set the rates for telecommunications services. Its decisions can only be challenged by the High Courts or Supreme Courts of India.

Market Structure

India boasts of 300 million telephone subscribers today and has become the second largest telecom network in the world, after China. Also, the number of new mobile subscribers is growing by 8.5 to 10 million every month, making it one of the fastest growing telecom markets of the world.

In 2006-07, the telecom industry also saw an estimated $8.5 bn in investment flow, out of which 6% or $550 million was in the form of foreign direct investment (FDI). According to a report by RNCOS, a market research consulting Services Company, mobile phones account for 80.2% of the subscriber base in India, at the end of March 2007.

The growth of telecom in India can be attributed to liberalization, reforms and competition. The telecom policy of 1999 envisaged a tele-density of 15 percent by the year 2010. The overall tele-density of the country is already over 26 percent now. Out of 300 million telephone subscribers today, 13% are wire-line subscribers. These developments in telecom sector have resulted in massive investments and explosion in supply, which are signs of a vigorous, competitive and fast-growing sector.

The major players in the Indian telecom industry, excluding Reliance and Tata Teleservices, are operating in the GSM market. After the release of TRAI recommendations in September 2007, there was a flood of applications for UASL (Unified Access License Seekers). This was probably because of the hope of pan-India start-up GSM allocation at a very economical price (US$240m). The armed forces are expected to vacate 20MHz of GSM spectrum. This would be around 70% of average GSM allocation currently.

ECONOMIC INDICATORS:

The economic indicators will give a perspective of the market structure and will help to discuss about the Indian Telecom industry

CONCENTRATION RATIO

In Economics the concentration ratio of an industry is used as an indicator of the relative size of firms in relation to the industry as a whole. This may also assist in determining the market form of the industry. One commonly used concentration ratio is the four-firm concentration ratio, which consists of the market share, as a percentage, of the four largest firms in the industry. In general, the N-firm concentration ratio is the percentage of market output generated by the N largest firms in the industry. Market forms can often be classified by their concentration ratio. Listed, in ascending firm size, they are:

• Perfect competition, with a very low concentration ratio,
• Monopolistic competition, below 40% for the four-firm measurement,
• Oligopoly, above 40% for the four-firm measurement, (Example automobile manufacturers)
• Monopoly, with a near-100% four-firm measurement

The top four companies constitute almost 83% of the market, thus showing a high concentration ratio; this implies the industry is dominated by top 4 players thus it shows a oligopolistic market.

H INDEX:

H Index (The Herfindahl-Hirschman Index): H index stands for Herfindahl-Hirschman index, which is a way of measuring the concentration of market share held by particular suppliers in a market. The H index is the sum of squares of the percentages of the market shares held by the firms in a market.

Since H Index is 0.19, it shows that the industry has moderate competition i.e. it is a monopolistic economy. There are three to four players which are dominant in the industry, thus confirming the concentration ratio. Here, from our H Index we can conclude that Bharti Airtel, Vodafone Essar, Reliance Communication and to some extent, BSNL are the major players which constitutes around 83 percent of the total market share. The remaining five players constitute just 17 percent of the total market share. Out of these five, IDEA has 10 percent share of the Indian telecom market. Therefore, we can clearly conclude that the Indian telecom industry is dominated by the 4-5 major players mentioned above.

Barriers to Entry in a telecom market

Barriers to entry, plays a major role in analysing an industry, since it determines the number of players to be present in the industry. The following factors play a major role in understanding the Barriers to entry in the Telecom industry of India.

Control ofresources

The most important factor in the telecom industry being the spectrum bandwidth and since existing companies hold majority of the spectrum, it is difficult for new players to enter the market unless Government issues new spectrum

Customer loyalty

Customer loyalty is prominent in telecom industry though it is because of loyalty to an operator but because of the loyalty to the mobile number. Still we can find many people switching the companies because of price tariffs. Moreover if the concept of “Number portability” is implemented in the future, then Customer loyalty would no longer be present and hence it poses a great challenge to the telecom companies

Government regulations

Government regulations play a major role in the presence/absence of entry barriers. Since the government has the control over the spectrum, it may make entry more difficult or impossible. Requirements for licenses and circles to operate would raise the investment needed to enter a market, creating an effective barrier to entry.

Investment

Since huge initial investment is required to enter the markets which include Spectrum cost, circle of operation cost along with the huge initial investment for infrastructure make the entry for barrier tough for new operators.

Network effect

The competing players have difficulties in entering the market since established companies have already captured a significant user base and it is difficult for new players to capture the base. This is one of the reasons that new players still have very less market base and Top 4 players continue to dominate the market.

Sunk costs

Since sunk costs cannot be recovered, and since telecom companies face a huge sunk cost, companies think twice before entering the market. This creates a big entry barrier for players to enter the market.

Predatory pricing

In a recent article given by Bharti, “http://economictimes.indiatimes.com/News/News-By-Industry/Telecom/Bharti-now-wants-TRAI-to-look-into-predatory-pricing/articleshow/5298033.cms” Bharti has raised the question of Predatory pricing tactics by players to create entry barrier for players. Some players feel that the current price war might wipe out some new entrants or effectively result as an entry barrier for new players

Strategies

Threat of New Entrants

It comes as no surprise thatin the capital-intensive telecom industry the biggestbarrier to entryis access to finance. To cover high fixed costs, serious contenders typically require a lot of cash. When capital markets are generous, the threat of competitive entrants escalates. When financing opportunities are less readily available, the pace of entry slows. Meanwhile, ownership of a telecom license can represent a huge barrier to entry. Moreover any new telecom operators must apply to theTARI to receive regulatory approval and licensing. There is also a finite amount of “good” radio spectrum that lends itself to mobile voice and data applications. In addition, it is important to remember that solid operating skills and management experience is fairly scarce, making entry even more difficult.

Power of Suppliers

At first glance, it might look like telecom equipment suppliers have considerable bargaining power over telecom operators. Indeed, without high-tech broadband switching equipment, fiber-optic cables, mobile handsets and billing software, telecom operators would not be able to do the job of transmitting voice and data from place to place. But there are actually a number of large equipment makers around. There are enough vendors, arguably, to dilute bargaining power. The limited pool of talented managers and engineers, especially those well versed in the latest technologies, places companies in a weak position in terms of hiring and salaries.

Power of Buyers

With increased choice of telecom products and services, the bargaining power of buyers is rising. Let’s face it; telephone and data services do not vary much, regardless of which companies are selling them. For the most part, basic services are treated as acommodity. This translates into customers seeking low prices from companies that offer reliable service. At the same time, buyer power can vary somewhatbetween market segments. While switching costs are relatively low for residential telecom customers, they can get higher for larger business customers, especially those that rely more on customized products and services.

Availability of Substitutes

Products and services from non-traditional telecom industries pose serioussubstitutionthreats. Cable TV and satellite operators now compete for buyers. The cable guys, with their own direct lines into homes, offer broadband internet services, and satellite links can substitute for high-speed business networking needs. Railways and energy utility companies are laying miles of high-capacity telecom network alongside their own track and pipeline assets. Just as worrying for telecom operators is the internet: it is becoming a viable vehicle for cut-rate voice calls. Delivered byISPs- not telecom operators – “internet telephony” could take a big bite out of telecom companies’ core voice revenues.

Competitive Rivalry

Competition is “cut throat”. The wave of industry deregulation together with the receptive capital markets of the late 1990s paved the way for a rush of new entrants. New technology is prompting a raft of substitute services. Nearly everybody already pays for phone services, so all competitors now must lure customers with lower prices and more exciting services. This tends to drive industry profitability down. In addition to low profits, the telecom industry suffers from high exit barriers, mainly due to its specialized equipment. Networks and billing systems cannot really be used for much else, and their swift obsolescence makesliquidationpretty difficult.

Regulatory issues: Role of Government

Theoretically, the allocation of any scarce resource can be done in any one of the five modes namely,

• Muscle power
• Luck power
• Time power (FIFO)
• Political power
• Market power

In India, spectrum being a scarce resource of telecom industry, have followed the Political power based approach which is the Government regulatory body. In spectrum allocation literature this is known as beauty contest. The main argument against beauty contest is that it encourages rent seeking and generates corruption. Moreover it is often arbitrary and lacks transparency for which this practice is prone to controversies. Accordingly, this method can lead to litigation and eventual delay. Market power is another much applied method of spectrum allocation and instrument and is called as auction.

On the debate between auction and beauty contest, many favour the auction because it is efficient on a theoretical consideration, as only the efficient firm can be the highest bidder and claimant of scarce resource. Secondly auction generates revenue for the government. Thirdly it is transparent and therefore subject to less controversy. However experiences have shown that auction has lead to problem, known as winners’ curse. The winner commits an exorbitant amount which it finally fails to pay and becomes broke. Another problem is post contract opportunism where after winning the spectrum the winner may refuse to pay the committed amount. Hence no method is foolproof and it becomes a tough job for the government to come out with a good solution of the spectrum allocation problem.

The crux of the problem of allocating spectrum on a discretionary beauty contest basis is in determining the optimal spectrum requirement. There is no empirical formula which can establish the exact figure in this regard. Additional spectrum requirement depends on various parameters like number of subscribers, the density of subscribers and geographic morphology. Similar determinants are type of applications (voice, data, multimedia application such as video/audio, mobile TV etc.) and the technology itself {2G (CDMA IS95A, GSM), 3G (WCDMA/CDMA2000), WiFi, WiMax etc }. In a multi-operator scenario it is difficult to assess the value of various parameters mentioned above.

Even for past data while a few parameters such as current subscriber base, current growth rate, etc. are known, there are several indeterminate factors, which can substantially alter the spectrum requirement estimates. In case of major technologies like GSM and CDMA, the pattern of spectrum use is distinctly different. Hence it has become doubly difficult to determine the efficient distribution of spectrum between the two. Market makes a choice between two technologies on the basis of cost of production and quality of services. But in this case both cost and quality are dependent on quantum of spectrum allocated and therefore no independent basis for cost comparison is available

Spectrum allocation

Presently spectrum is allocated on the basis of subscriber numbers and the technology used. The entrenched operators, who are typically operate on the GSM standard, would like this practice to continue as it will inhibit entry and cement their current positions. The newer entrants, prominent among them the Tatas, would like spectrum to be made available based on auctions.

This has been interpreted as a fight between GSM and CDMA operators, though it is better interpreted as a fight between older and newer operators. The existing operators also oppose allowing firms to offer both GSM and CDMA services and are in favour of capping the number of operators.

Their argument is that larger numbers of operators reduce the efficient use of spectrum. Taking this argument to its logical conclusion one could argue that mobile telephony is a natural monopoly and so there should be only one mobile operator which didn’t work when BSNL was a monopoly. So the spectrum allocation is best served through properly designed auctions. The technological developments will assuage the inefficiency problem. Also new firms might emerge with new products to solve this problem. Finally, if spectrum is really an issue the market would nudge the existing firms to merge.

License Conditions Inhibiting Competition

Effect of taxation on business decisions

Demand and Supply Analysis

This part provides a simple picture of the demand and supply situation in India to illustrate some of the conditions prevailing in the market. The main points that emerge here are:

• Excess demand in the form of network congestion implies that the customers are not on the aggregate demand curve for the telecom service in question. Also, it is not clear which price will bring the customers to the desired demand curve. Hence, it would not be appropriate or easy to rely on pricing or mark-up based on demand.
• The fluctuations in prices are unlikely to affect overall demand, except in areas where the supply constraint does not apply.
• Since supply rather than demand is the main constraint, it would be useful to focus on increasing the supply of the network. This can now be feasible due to increased deregulation and increased FDI in the industry.
• Such a focus on investment is even more meaningful in a situation with excess demand in the form of a waiting list for connections, and where considerable additional demand is anticipated to arise in the future. For instance, in the next five years, the anticipated demand will be more than double the current network size. This could be met with the allocation of further 2G and 3G spectrum. This revolution has already taken place with the introduction of I-Phone in the Indian market. Also Google has announced the launch of its 3G mobile phone.
• Since there is likely to be such a major increase in demand, and it is not yet clear when the supply will increase enough to meet this demand, determining the demand curve is not an easy task.
• Even if supply increases enough to cater to the additional demand, the fact that demand is increasing at a rapid pace implies that the determination of the extent and nature of demand will not be an easy task. This will be further complicated by the new products that are emerging in the market.

The Figure below shows a simplified picture of the demand and cost situation relevant to telecom pricing. DD is the demand curve for a basic telecom service, MC is the marginal cost curve, and AC is the average cost curve. For simplification, marginal costs are shown to be the same for each unit of output. Since fixed costs do not change with a change in the output level, the average total costs (comprising average fixed and marginal costs) will be above marginal costs, but declining.

In the Figure above, the level of output Q0 is the level at which price is equal to marginal cost (i.e., the point of intersection of the demand curve and the marginal cost curve). It is evident that the price does not cover costs at that level because the average cost is above the price level. The Ramsey rule suggests the extent to which the price should be increased to obtain the revenue that would cover costs and provide an adequate return. The Ramsey rule requires that the prices be those given by the demand curve, i.e. there should not be any constraint for the customer to be operating on the demand curve.

In the Indian situation, however, there is likely to be a capacity constraint and thus the customers are unlikely to be on the demand curve. The capacity constraint in India arises for two reasons. One, the subscribers linked up to the network face congestion and are thus not able to make as many completed calls as they desire. Second, the existing network does not satisfy the demand of all those wanting to be linked up to the network. The first type of constraint (i.e. congestion) implies that the supply constraint shown by SS is the operating schedule for the subscribers.

Some tentative conclusions could be drawn from this discussion. Due to the prevailing excess demand, a change in price will not alter overall demand as long as there is excess demand. In such a situation, the price could be increased till the price is high enough to reach the demand schedule, i.e. till the point where the supply equals demand. This does not mean that certain subscribers will not reduce their demand, but that the reduction in demand will be compensated by the prevailing excess demand filling the gap till the price becomes so high that excess demand itself becomes zero.

Excess demand also implies that a high price could be charged for those telecom services for which subscribers are willing to pay a high price, i.e. service for which the price shown by the demand curve is high at a given level of the supply constraint. However, it is not clear what this price level should be, because the demand curve is not easy to determine.

EXCESS DEMAND AND CONGESTION:

MC is the marginal cost curve and DD is the demand curve. The congestion in the network due to a capacity constraint is reflected by the vertical line SS. The output Q1 corresponding to the vertical line shows the supply beyond which the volume of traffic cannot be increased (Technically, with increasing congestion, the vertical line could move to the left, thus showing decreasing capability of the network with a rise in congestion).

The fact that there is congestion is diagrammatically illustrated by the fact that the actual demand for the product is more than the capacity. With congestion, the customer is somewhere on the vertical line SS and not on the demand curve. The excess demand is shown by the horizontal distance between the vertical line SS and the demand curve. Therefore, the actual price is somewhere lower than P1.

For a proper implementation of the Ramsey rule, the point of reference from where the movement for mark-up has to occur is the point where the demand curve intersects the marginal cost curve, i.e. point R in the diagram above. In a situation with congestion, the starting point itself is away from the Ramsey reference point, and the position of this starting point is dictated by the available capacity. Furthermore, the position of this capacity constraint for different types of services (or demand) might be different, and it is highly unlikely that these constraints are positioned in such a way that the Ramsey rule for mark-up could be satisfied for different services.

The fact that the price is above marginal cost means that some mark-up already exists. Any change in the mark-up (due to a change in price) will not affect the level of demand as long as the customers face a capacity constraint, i.e. as long as they are on the vertical line SS above. Thus, in effect, the elasticity of demand for each service with a capacity constraint is the same, i.e. it is equal to zero on SS.

OVERALL EXCESS DEMAND:

The fact that there is overall excess demand due to congestion does not mean that such congestion operates everywhere. Thus, the situation would comprise those who do not face any supply constraints and others who face a supply constraint in certain parts of the country. This is shown by the two demand curves above, D1D1 and D2D2. Only D2D2 is subject to a supply constraint, and thus a change in price will affect the overall level of demand of those in situations D1D1 and not of those in situation D2D2. However, the presence of a supply constraint does reduce the elasticity (or responsiveness) of the overall demand for the telecom service.

EXCESS DEMAND FOR TELEPHONE CONNECTIONS:

There is considerable excess demand for telephone connections in India, and this demand is expected to rise sharply in the near future. The Department of Telecommunications has estimated that in the next five years, demand for telephones is likely to more than double. While capacity extension will continue to try to cater to this demand, this situation adds to the difficulty created by the abovementioned capacity constraint in using the demand situation in India to assess the telecom price or the mark-up.

In the Figure above, an expansion of capacity is shown by a rightward shift of the vertical line S1S1 to SS. This capacity expansion results in meeting the excess demand of those who were on the waiting list. The waiting list is shown by the difference between the demand curves D1D1 to D2D2. To this must be added the increase in demand over time. Adding these would give us the new demand curve as D4D4. The effect of these changes on the excess demand situation (or on congestion) would depend on the extent of the change in capacity and the extent of prevailing excess demand and the increase in demand over time. If those demanding a link-up with the network are not provided the link-up, then the actual demand at D3D3 will be to the left of D4D4. The difference between D3D3 and D4D4 shows the demand in waiting. Moreover, if there continues to be congestion for those linked up to the network, we are again in the same situation as the one discussed earlier, i.e. the consumer is likely to be on the supply constraint and not on the demand curve.

Even if the customer is not subject to the supply constraint, it may not be feasible to apply the Ramsey rule as long as the desired price is to the right side of the supply constraint. Moreover, when the link to the network is increasing as rapidly as 20 per cent per annum, and excess demand still continues to prevail, it is very difficult to estimate demand characteristics accurately or to use the demand curve for pricing telecom.

Elasticity

With a capacity constraint, the decline in price would take place without any change in the level of existing demand. On the other hand, if there is no capacity constraint, then the fall in price would take place along the demand curve. In this case, the short-term effect on revenue would depend on the elasticity of demand.

However, if the price decline increases demand to such an extent that the capacity constraint becomes binding again, then the elasticity of demand becomes irrelevant in calculating the change in revenue. This is shown in the diagram below. The starting point is price P1, and two different demand curves are considered, with different elasticities of demand. At price P2, the supply constraint becomes binding for demand curve D1D1, and at price P3 it becomes binding for demand curve D2D2. At prices lower than P3, the comparison of the old and the new levels of revenue do not depend on the elasticities of the demand curves.

Demand Function

According to Houthakker-Taylor model, the demand function for telecommunications is as follows

ln Qt = a * ln Qt-1 + ß * ln Pt + ? * ln X

where

Q – Demand

P – Price

X – all other explanatory variables

ß – short run price elasticities

ß/(1- a) – long run elasticity (0 < a < 1)

Conclusion

In our opinion, instead of taking a short-term view of paying capacity, the telecom companies should focus on a long-term game. There is one word that telecom companies are hearing a lot these days-“Volumes”. They need volumes to sustain the network and the large employee base they have enrolled. In this regard, companies like Reliance and Tata’s have been aggressive over the final rollout of connections to PCO owners. Reliance is giving upto 30% commission on each call. How they market and distribute these connections is a tough battle indeed. If and when the carrier acces