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technological solutions (that tend to reduce delays) that raise efficiency and organiza-
tional solutions in the form of dis-intermediation. However, institutional solutions are
different from such organizational solutions. Coordination in Ecom is an institutional
problem and therefore it requires an institutional solution. Normative coordination is an
institutional solution. Normative coordination limits the failures in coordination. An



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Re-Intermediation and Deferment through E-Commerce 35


institution might not offer a particular organizational solution as the preferred mode.
Several organizational or quasi-organizational, including contractual, solutions might be
considered as specific solutions. Vertical solution, we would argue, need not be
considered as the only preferred solution to coordination with long deferment. Vertical
solution can be considered only when information being exchanged across firms refers
to a pre-reconciled plan. Information that cannot unambiguously describe a situation or
that can remain incomplete evidence and is required to adjust to envelopes of expecta-
tions on the future cannot even while exchanged help formation of vertical integration.
Ecom offers such intricacies and hence eludes organizational solution such as achieved
through dis-intermediation. Moreover, deferment in the received theories is undesirable
and technological solutions that raise efficiency have been proposed for reduction of its
length. We argue technology fails to reduce the duration of average period of production.
Contrarily technology increases this period of deferment, which represents capital.
Technologies from firms who are not vertically integrated and who make non-durable
investments need not reduce the deferment period, and in circumstances might even
hasten deferment.




Conclusions
At the end of the day following the introduction of Ecom there could be fewer
intermediaries in a vertical value chain. However, vertical value chains have lost their
attractiveness in a time of increasing returns based on scope-wise innovations in
product. Products in this setting of Ecom offer sequential competition. Firms and their
customers coordinate their expectations based on the next versions of products.
Similarly, firms that are competing in sequence or at the same time must coordinate their
expectations on each other because products from their stables must fulfill obligations
of interoperability, as well as satisfy mutually agreed upon restrictions on quantity and
prices. Coordination amongst producers too affords a cascaded deferment of both
consumption and completion of a systemic product. These two types of coordination
involve incompleteness of contracts, uncertainties and liquidity of investment. The
length between production and consumption thus must create enough number of
economic agents who can trade in risks, insurances, information and liquidity. The
intermediaries, who in this Ecom environment are the cybermediaries, offer this service
as the microstructure of market. Cybermediaries therefore emerge to fulfill this novel task.
The economic-value-adding activities by these cybermediaries lengthen the circuit of
production that terminates in consumption. A lengthened circuit indicates deferred
consumption and a consequent rise in capital and in profit. Ecom therefore requires
possibly more quantity of intermediation and surely novel modes of mediation. Neces-
sarily little of this novel mediation takes place along the previous value chain. Most of
the novel cybermediations appear in the scope direction and away from the vertical
industrial segment. The economy under Ecom increases in the scope but not through
Chandlerian large multidivisional firms. The economy increases through highly differen-
tiated and variegated cybermediaries who lengthen the circuit of capital and as a
consequence of increasing the riskiness of a business increase the profit. This profit does


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36 Banerjee


not arise in technological innovations particularly of the kind that increase efficiency.
Contrarily this profit is strategic because the cybermediaries arrange and then rearrange
the configurations of a market and thus through bringing about surprise the cybermediaries
reap enhanced profit.




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permission of Idea Group Inc. is prohibited.
Risk and Investment in the Global Telecommunications Industry 39




Chapter III



Risk and
Investment
in the Global
Telecommunications
Industry
Irene Henriques
York University, Canada

Perry Sadorsky
York University, Canada




Abstract
In this chapter, quantitative modeling and simulation techniques are used to estimate
various risk measures and the associated cost of equity for the global telecommunications
industry. Our approach is to calculate several different cost-of-equity values and then
use simulation techniques to build up a probability distribution for each company™s
cost of equity. In this way, a clearer picture of where a company™s cost of equity lies is
developed. Closing the Digital Divide could bring many benefits to developing
countries but international investors and development planners must be able to make
their own cost-of-equity calculations so that they can see first hand how their
investment projects compare with other investment projects around the globe.




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permission of Idea Group Inc. is prohibited.
40 Henriques & Sadorsky


Introduction
The new economy can be characterized in a number of different ways but one way to look
at the new economy is to identify industries that are undergoing the greatest amount of
structural change and have the greatest opportunity for growth. Three industries stand
out as having particularly promising futures: biotechnology, energy and information
technology (IT). Collectively these three industries may be called the BET economy. Of
these three industries, the IT industry (broadly comprised of the technology, media and
telecommunications (TMT) sub- industries) is the one industry that can contribute the
most to productivity improvements in countries. Technological progress can lead to
process innovation (lower cost ways of producing existing products) or product
innovation. Furthermore, from neoclassical growth theory, technological improvements
are the only way to increase the living standards in countries that have reached the
golden rule. An increase in technology raises the production function and increases the
steady state amounts of capital stock and output. In terms of economic performance,
maximizing productivity growth is the single most important objective for a country to
have since increases in productivity growth lead to higher living standards.
Productivity growth can be influenced by a number of different factors or drivers. Broadly
speaking, these factors include macroeconomic policy, regulatory environment, innova-
tion, industrial structure, human capital, management strategies and policies, trade, and
investment. For large industrialized countries like those in the G7 or G10, economic
performance depends in large part on coordinating the actions between these various
drivers to enhance productivity. The shortage of the necessary resources to accomplish
this objective is not that large of a problem. For developing countries, the situation is
often much more difficult because, in addition to successfully coordinating the actions
of the various drivers, developing countries also face a shortage of financial capital. As
a result, foreign investment is becoming an increasingly important driver behind
productivity growth in developing countries.
Business growth and the overall wealth generation process are hindered in developing
economies by the lack of affordable credit. This is particularly true in the IT industry. New
firms starting out in IT are often very small and face high start-up costs. These firms
usually have no source of financial capital to draw from, which means that they need to
seek external funding. In developing economies, the selection of financial instruments
available to start up companies is very limited (Chong and Micco, 2003). The source of
financial capital -where it exists- tends to be scarce and commands a very high price. This
problem is particularly acute in South America and Africa where domestic savings rates
are much lower than in other developing parts of the world. As a result, foreign investment
into developing countries can provide a much-needed source of financial capital.
Financial capital is probably the scarcest commodity in the world. More people demand
financial capital at any one time than are able to supply it. Financial capital is scarce,
mobile and very sensitive to economic and political conditions. Consequently, those
who have financial capital to invest are very selective about where they invest. Domestic
and global investors typically prefer investments with high returns and low risks. Risk
management is, therefore, an important component of global investing. Savings is the
only source of financial capital and the relationship between savings, investment and


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Risk and Investment in the Global Telecommunications Industry 41


economic growth has been well documented (Miles and Scott, 2002). The role that foreign
direct investment plays in aiding a country™s economic development has also been
extensively studied.
Foreign investment can be categorized as either foreign direct investment (FDI) or
foreign indirect investment (portfolio investment). FDI adds to the receiving country™s
GDP because it involves investment in physical capital (roads, buildings, plants,
machinery and equipment, etc.). Portfolio investment has a less direct impact on
economic growth when it involves the buying and selling of existing equities and bonds.
Of course, portfolio investment used to finance initial public offerings adds directly to
GDP.
There are a number of interesting trends regarding foreign investment (Miles and Scott,
2002). First, richer countries tend to invest more overseas. Second, FDI assets (liabilities)
as a percentage of industrialized countries GDP are 16% (17%). Thus, a lot of FDI is
conducted between the rich industrialized countries. Third, total outward investment by
the industrialized countries is currently around $1500 billion (US) of which one-third is
FDI and two-thirds is portfolio investment. By comparison, FDI in 1990 was $300 billion
(US) and this was approximately equal to portfolio investment. Portfolio investment is
currently the fastest growing part of foreign investment. Fourth, FDI tends to be less
volatile than portfolio investment.
Developing or emerging economies seeking foreign investment must be aware of these
trends and realize that, while FDI might be the preferred choice of foreign investment,
portfolio investment is a much larger pool of money to tap. Portfolio investment, however,
requires risk management on the part of both the seller and the buyer. Provided a
developing or emerging economy can offer attractive risk and return characteristics to
investors of financial capital, portfolio investment should not be overlooked as a source
of investment capital.
Consequently, it is necessary to have good measures of equity risk for managers,
planners and investors. The cost of equity is important in valuing new investment
opportunities and in evaluating the ongoing performance of established business
projects. This is especially true in the new economy IT industry where an understanding
of equity risk aids in the examination of the relationship between the IT sector and
economic development.
The purpose of this chapter is to calculate the cost of equity for the global telecommu-
nications industry using a sample of 26 firms in 19 countries. The companies in the sample
are chosen primarily based on their inclusion in the www.adr.com telecommunications
database and having a reasonable length of market data (five years). Quantitative
modeling and simulation techniques are used to estimate various risk measures and the
associated cost-of-equity values for the telecommunications industry in each country
in the sample. The methodology is similar to that used by Sadorsky (2003) and Sadorsky
and Henriques (2003). The risk measures include systematic risk (Brealey and Myers,
2003; Campbell, Lo and Mackinlay, 1997), total risk (Shapiro, 2003), downside risk
(Estrada, 2000, 2002; Harvey, 2000; Alexander, 2001), regret (Dembo and Freeman, 2001),
and value at risk (JP Morgan/Reuters, 1996). A brief discussion of each of these risk
measures is provided. The risk measures are then used to calculate the cost of equity
(which is equal to a risk-free rate plus the product of a risk measure and a market risk



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42 Henriques & Sadorsky


premium) in the global telecommunications industry for each company in the sample. For
each company, the different cost-of-equity values are compared and contrasted. More-
over, a comparison between different cost-of-equity values is made with companies in
similar regions of the world.




Background
The term Digital Divide usually refers to the overall gap in information technology and
communication usage between developed and developing countries (Lu, 2002). Cur-
rently there are huge differences in the ability of people around the world to communicate
both locally and globally. The International Telecommunications Union (ITU) provides
free statistics, available on their Web site, on IT usage rates in five broad regions of the
world. These regions are: Africa, Americas (including North, Central and South), Asia,
Europe, and Oceania. Total telephone subscribers per 100 inhabitants in 2002 ranged from
a low of 6.60 in Africa to a high of 89.83 in Europe (Table 1). The number for the Americas
(64.92), represents the average of high wire-line usage in North America and low wire-
line usage in South America. For example, Canada and the United States have 101.26 and
114.70 total telephone subscribers per 100 inhabitants while Peru and Venezuela have
13.67 and 36.78 total telephone subscribers per 100 inhabitants. Statistics on cellular


Table 1. IT usage statistics (2002)

Africa Americas Asia Europe Oceania World



Wireline

subscribers per 100 inhabitants 6.6 64.92 23.89 89.83 88.93 36.35



Cellular subscribers

as % of total telephone subscribers 61 45.8 50.3 55.1 54.6 51

% digital 86.3 53.5 80.2 55.4 80 65.8

subscribers per 100 inhabitants 4.19 29.74 12.19 50.21 48.53 18.77



Internet usage

users per 10,000 inhabitants 99.62 2421.02 557.56 2079 3330.47 972.16




Source: http://www.itu.int/ITU-D/ict/statistics/


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Risk and Investment in the Global Telecommunications Industry 43


subscribers in 2002 show a great deal of variation. Africa had the lowest number (4.19)
of cellular subscribers per 100 inhabitants while Europe had the highest (50.21) number
of cellular subscribers per 100 inhabitants. Similarly, 2002 statistics on Internet usage
also reveals vast differences between regions of the world. Africa only had 99.62 users
per 10,000 inhabitants while Oceania had 3,330.47 users per 10,000 inhabitants. The high
number of Internet users for Oceania is heavily influenced by the widespread usage of
the Internet in Australia and New Zealand. The Americas also have a high number of

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