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Uganda CommunicationsCommission (UCC)

Weighted Average Cost of Capital

January 2009

UCC – weighted average cost of capital for fixed line and mobile operators Confidential

PricewaterhouseCoopers i January 2009

Important noticeThis report has been prepared by PricewaterhouseCoopers LLP (“PwC”) for UgandanCommunications Commission in connection with the weighted average cost of capital for fixed andmobile operators under the terms of the PwC engagement letter with Ugandan CommunicationsCommission dated January 2009 (the “Engagement”) and its contents are strictly confidential.

This report contains information obtained or derived from a variety of sources as indicated within thereport. PwC has not sought to establish the reliability of those sources or verified the information soprovided. Accordingly no representation or warranty of any kind (whether express or implied) isgiven by PwC to any person (except to Ugandan Communications Commission under the relevantterms of the Engagement) as to the accuracy or completeness of the report. Moreover the report isnot intended to form the basis of any investment decisions and does not absolve any third party fromconducting its own due diligence in order to verify its contents.

PwC accepts no duty of care to any person (except to Ugandan Communications Commission underthe relevant terms of the Engagement) for the preparation of the report. Accordingly, regardless ofthe form of action, whether in contract, tort or otherwise, and to the extent permitted by applicablelaw, PwC accepts no liability of any kind and disclaims all responsibility for the consequences of anyperson (other than Ugandan Communications Commission on the above basis) acting or refrainingto act in reliance on the report or for any decisions made or not made which are based upon suchreport.

Copyright Notice© 2009 PricewaterhouseCoopers LLP. All rights reserved. “PricewaterhouseCoopers” refers toPricewaterhouseCoopers LLP a limited liability partnership incorporated in England or, as the contextrequires, other member firms of PricewaterhouseCoopers International Limited, each of which is aseparate legal entity.


PricewaterhouseCoopers ii January 2009

Contents

1 BACKGROUND AND SUMMARY .................................................................................................... 1

2 INTRODUCTION.......................................................................................................................... 2

2.1 Cost of Equity .............................................................................................................. 2

2.2 Cost of Debt................................................................................................................. 3

2.3 Weighted Average Cost of Capital (WACC).................................................................. 3

3 UGANDAN TELECOMMUNICATIONS SECTOR .................................................................................. 4

3.1 Mobile operators .......................................................................................................... 4

3.2 Fixed operators............................................................................................................ 5

4 GEARING RATIO ........................................................................................................................ 6

5 COST OF EQUITY....................................................................................................................... 8

5.1 Risk-free Rate.............................................................................................................. 8

5.2 Direct approach ........................................................................................................... 8

5.3 Synthetic approach...................................................................................................... 8

5.4 Equity Market Risk Premium (EMRP)........................................................................... 9

5.5 Beta........................................................................................................................... 10

6 COST OF DEBT........................................................................................................................ 13

6.1 Tax wedge uplift......................................................................................................... 14

7 WACC .................................................................................................................................. 15

8 CONCLUSIONS ........................................................................................................................ 17

APPENDIX 1: COUNTRY RISK PREMIUM METHODOLOGY ...................................................................... 18

APPENDIX 2: COMPARATOR INFORMATION ......................................................................................... 21

APPENDIX 3: UNLEVERING FORMULAE ............................................................................................... 22

REFERENCES .................................................................................................................................. 25


PricewaterhouseCoopers iii January 2009

Index of ChartsChart 1: Gearing ratios for fixed-line operators.......................................................................... 6

Chart 2: Gearing ratios for mobile operators.............................................................................. 7

Index of TablesTable 1: Uganda WACC............................................................................................................16

Table 2: Mobile companies ........................................................................................................21

Table 3: Fixed-line companies..................................................................................................21


PricewaterhouseCoopers 1 January 2009

1 Background and summary

PricewaterhouseCoopers (‘PwC’) has been commissioned by the Ugandan CommunicationsCommission (“UCC”) to provide an assessment of the cost of capital of mobile operators and fixedoperators in Uganda for the determination of interconnection charges.

Our current estimate of the Ugandan nominal pre-tax WACC is summarised below:

Min Max Midpoint

Mobile 24% 26% 25%Fixed 23% 25% 24%

This WACC can be used for general regulatory purposes, which includes regulating those activitiesthat require the use of Uganda’s core fixed telephony and mobile infrastructure. This includes settingprice controls, tariffs and interconnection rates.



2 Introduction

The cost of capital represents the minimum rate of return a company should earn on its investedcapital in order to provide sufficient returns to the investors who are financing the business. It followsthat it is the minimum return a regulator should allow in setting the prices of regulated activities.

The cost of capital can be applied in a wide range of regulatory situations. This includes:

Interconnection rates, access and wholesale prices. This is done by incorporating the cost ofcapital into cost-based pricing models;

Price control reviews and rate applications. Setting retail prices which incorporate a minimumreturn to enable the company to finance its regulated activities; and

Discounting regulated cash flows to present values.

The cost of capital presented in this report should be used for general fixed-line and mobileregulatory purposes e.g. price controls and interconnection rate setting for those regulated activitiesthat involve the use of core fixed-line telephony and mobile infrastructure assets in Uganda.

The cost of capital used in any particular situation should reflect the risks of the activity undertaken1.Given that the cost of capital figures we have derived are for general fixed-line and mobile activities,if a regulated activity has a markedly different risk profile to the core telephony business then adifferent cost of capital should be used.

The cost of capital does vary over time and therefore should be reviewed on a timely basis. Bestpractice suggests that key components of the cost of capital calculation can move significantlythrough the course of a year. We therefore suggest that the cost of capital is reviewed annually, orspecifically reviewed if used as part a major regulatory determination.

The cost of capital itself requires the calculation of three components:

The cost of equity, being the rate of return equity investors would expect on an investment ofthis sort;

The cost of debt, being the interest rate debt providers would charge for providing debt to suchan investment; and

The gearing ratio, being the relative proportions of debt and equity used to finance theinvestment.

2.1 Cost of Equity

The standard framework for calculating the cost of equity is the Capital Asset Pricing Model (CAPM).This framework assumes that equity investors require their investment to yield at least the returnavailable on risk-free instruments (e.g. US Government bonds). Added to this risk-free rate of return,equity investors expect a premium for the risk involved in making an equity investment.

This premium is defined as the general equity market risk premium multiplied by the beta. Theformer is the additional return required above the risk-free return to compensate an average investor

1 See Brealey and Myers “Principles of Corporate Finance”, 7th Edition



for investing in equities of average risk. Beta is a measure of the risk associated with a particularinvestment under consideration, relative to the average risk of investing in the equity market. If aparticular equity investment is of average risk, beta = 1; beta is greater than 1 for a more thanaverage risky investment and less than 1 for a less risky investment. The higher is beta, the higheris the cost of equity.

2.2 Cost of Debt

The cost of debt is the sum of the risk-free rate and the margin (premium) that lenders require abovethe risk-free rate. We adjust this return by the tax shield to reflect the fact that interest payments ondebt reduce the taxable profit of the underlying investment, and hence reduce the tax burden and theeffective post-tax cost of servicing debt. The corporate tax rate used for the tax shield calculation isthe standard corporate tax rate of 30% in Uganda.

2.3 Weighted Average Cost of Capital (“WACC”)

To calculate the Weighted Average Cost of Capital (“WACC”), the cost of equity and cost of debt areweighted together using the proportion of total investment funding accounted for by each as theweights. The WACC is the measure of the minimum expected return investors of all forms of capitalrequire in order to be incentivised to invest capital in a business.

The WACC therefore represents the minimum rate of return a company should expect to achievefrom its overall activities to satisfy its various capital providers.



3 Ugandan telecommunications sector

3.1 Mobile operators

The major operators in Uganda are:

Clovergem Celtel Limited

MTN Group Limited

Uganda Telecom

Warid

Zain Uganda

The mobile telecommunications market in Uganda has been experiencing significant growth insubscriber numbers in recent years. Subscriber estimates from the four largest operators: MTN,Uganda Telecom, Warid and Zain Uganda indicate that the number of active mobile subscribers inUganda has risen to more than 7.7 million up from 5.7 million in March 2008.

The increase represents 35 per cent growth between March and August 2008 and the operators stillexpect to gain more customers.

The chart below summarises the development of the fixed line penetration rate from 1997-2007 (insubscribers/population):

Source: UCC. Quoted from “Market analysis, interconnection and retail cost study”, UCC, October 2008



Current subscriber numbers surpass Uganda Communication Commission (“UCC”)'s projectionestimates of six million subscribers by the end of 2008. Officials from the four companies attributedthe growth to the on-going market promotions, innovation and penetration of their networks in newareas2.

MTN Group Limited is the only listed operator that operates in Uganda. It is listed on the SouthAfrica JSE under the Industrial – Telecommunications sector and is used in our comparator group oflisted companies summarised in Appendix 2.

3.2 Fixed operators

The largest fixed-network operator is Uganda Telecom Limited.

The fixed telecommunications market in Uganda varies significantly from the mobiletelecommunications market and compared with fixed-line operators in other emerging markets. Incontrast to the mobile sector, fixed penetration has stagnated. This means that the risks faced byfixed companies are much higher than those faced by fixed-line operators in most other markets whotypically occupy a mature incumbent position.

The chart below summarises the average and expected growth in mobile subscribers for Uganda (in‘000):

Source: Pyramid Research. Quoted from “Market analysis, interconnection and retail cost study”,UCC, October 2008

2 http://allafrica.com: “Uganda: Telecom companies boast of 8 million subscribers”, 9 September 2008.



4 Gearing ratio

As noted above, in order to calculate WACC we need a view on the appropriate proportions of debtand equity finance in a business represented by a gearing ratio (Value of Debt/ (Value of Debt +Value of equity), D/D+E).

When deciding on the level of gearing it is important that reference is made to the market values ofdebt and equity. An assessment of current market gearing of the fixed and mobile operators inUganda is difficult because only one of the comparable companies, MTN Group, is quoted andacquisition and disposal transactions in their equity are infrequent.

We have therefore used the gearing ratios of the listed mobile and fixed operators in Africa and otheremerging markets in Asia and South America as a proxy for the gearing levels of the mobile andfixed operators in Uganda. We found that the median 5 year gearing ratio for fixed operators was31.7% and 13.0% for mobile operators.

For benchmarking purposes, the charts below present the distribution of gearing for telecomscompanies.

Chart 1: Gearing ratios for fixed-line operators

0

2

4

6

8

10

12

14

0%-10% 10%-20% 20%-30% 30%-40% 40%-50%

Gearing (D/V)

Africa Asia Latin America

Source: Bloomberg, December 2008, PwC Analysis



Chart 2: Gearing ratios for mobile operators

0

2

4

6

8

10

12

0%-10% 10%-20% 20%-30% 30%-40% 40%-50%

Gearing (D/V)

Africa Asia Latin America

Source: Bloomberg, December 2008, PwC analysis

An international regulatory benchmark is the 30% gearing assumption used in setting the cost of

capital for BT by Ofcom in June 20043 and this is in line with the fixed gearing levels we haveobserved from our analysis.

3 Office of Communications. "Partial Private Circuits Charge Control", Consultation document, 24 June 2004.



5 Cost of Equity

5.1 Risk-free Rate

There are two possible approaches to estimating the risk-free rate in Uganda. The first approach (thedirect approach) uses the gross redemption yield (“GRY”) to maturity on traded Ugandangovernment bonds, issued in the same currency as required for the cost of capital. The syntheticapproach applies a Ugandan Country Risk Premium (“CRP”) to the GRY of a benchmark USgovernment bond, and also adjusts for the average expected inflation differential between the USAand Uganda.

Whichever approach (direct or synthetic) is used, it is necessary to match the maturity of the bond tothe length of the investments made by the regulated entities. The typical average asset life for fixed-line and mobile companies is between 7 and 10 years.

Many practitioners use a degree of averaging to smooth out fluctuations in capital markets, and donot rely unduly upon the risk-free rate on any one specific day. This is especially the case whenyields are around historic highs or lows.

5.2 Direct approach

For the direct approach we would ideally use a government bond that has a maturity of close to 10years.

The yield to maturity on the longest term (10 year) UGX bond issued by the Ugandan Government is13.48%.

A Ugandan Government bond with a three year maturity was issued in September 2008 and its yieldto maturity is estimated to be 14.1%.

The drawback of this approach is that it relies upon a few bond instruments which may not be asliquid as other bond instruments.

For benchmarking purposes, an analysis of non traded 10 year bonds from a range of other Africancountries was carried out and these have coupon rates which range from 10.% to 11.5% and theseare summarised in the table below:

Maturity Country Coupon Issue date Expiry date Run time (years)

10 year Kenya 10.75% Sep-08 Sep-18 9.7

10 year Tanzania 11.44% Apr-07 Sep-17 8.7

10 year Tanzania 10.08% Feb-08 Feb-15 6.1

10 year Nigeria 10.70% May-08 May-18 9.4

10 year Botswana 10.00% May-08 Sep-18 9.7

8 year Egypt 10.95% Jun-08 Jun-16 7.5

5.3 Synthetic approach

Due to the liquidity issues in the Ugandan government bond market we prefer to supplement thedirect approach with a synthetic approach that includes information from assets from liquid markets.For this approach we start with the benchmark yield on an index-linked 10 year US government bondas a proxy for the real risk-free rate. This is currently yielding 2.1%. We then inflate this by the



expected 10 year average rate of inflation, the country risk premium that investors require in order toinvest in Uganda and the inflation differential between Uganda and the USA.

Typically, the CRP is measured by observing the additional return investors in the bond marketrequire to compensate for the additional risk associated with the bonds issued by certain countries.This can be due to higher risk associated with macroeconomic, political and institutional factors, suchas financial distress, economic policy inconsistencies and political intervention. A further descriptionof the PwC CRP methodology is provided in Appendix 1.

The CRP is already included in the borrowing costs of individual governments (so, for example, thedirect approach figure quoted above already includes country risk), but the CRP needs to beincluded in the synthetic approach. Based on the PwC Country Risk Model, the CRP for Uganda isestimated to be 5% by based on an average of each quarter in 2008.

We have adjusted the benchmark yield on the 10 year US government bond by the CRP of Ugandaand the inflation differential between the USA and Uganda to derive an overall figure of 12.8%.

The benefit of the synthetic approach is that it is likely to deliver a more stable figure than the directapproach, as it uses data from highly liquid international bond markets.

The following table summarises our range and midpoint estimate of the risk free rate, where theminimum is based on the synthetic approach and the maximum is based on the Ugandan 10 yearbond yield:

Min Max Midpoint

Risk fee rate 12.8% 13.5% 13.2%

5.4 Equity Market Risk Premium (EMRP)

The EMRP represents the minimum return expected by an average investor investing in an equity ofaverage risk. Arithmetically, it is the expected return provided by all the assets in the market, Rm,minus the risk-free rate, Rf. Strictly speaking, the EMRP in which we are interested is that forUganda.

Estimating the EMRP is an uncertain exercise and there is much disagreement over theinterpretation of figures. The most thorough studies of the EMRP have taken place in the USA,where there is a long enough period of data from which to deduce the premium required by equityinvestors.

A highly respected source is the work carried out by Ibbotson which calculated the historic marketrisk premium for the whole market over the period 1926 to 2002 at 7.0%. This was supported by thework of Dimson, Marsh and Staunton in 2004, who calculated a figure of 6.9% for the USA over theperiod 1901 to 2001. There is no comparable study available for Uganda given the infancy of itscapital markets, and therefore we have to rely on studies such as these.

Ibbotson, in its analysis, makes a strong emphasis on the variation of the EMRP according to thedifferent size of companies under consideration. Higher equity market risk premia for smallercompanies were also supported by the findings of Fama and French who suggested that the CAPMmay be misspecified with respect to size (they also found a misspecification with respect to highbook to market ratios). Higher equity market risk premia for smaller companies have been adopted

4 Source: Dimson, Elroy, Marsh, Paul and Staunton, Mike. “ Triumph of the Optimists: 101 Years of Global Investment

Returns”, Princeton University Press, 2001.



by UK regulators in setting prices (e.g. the water regulator OFWAT and the main competitionauthority, the Competition Commission).

More recent academic studies of the EMRP tend to use forward-looking approaches which deliverlower figures than the historic data. A good summary of the various sources of information on theEMRP was provided by the UK communications regulator Ofcom in its recent cost of capitalconsultation. This is extracted below

Table 1: Summary of EMRP findings

Source: Ofcom: http://www.ofcom.org.uk/consult/condocs/cost_capital2/statement/final.pdf

PwC’s assumption of the EMRP for developed economies such as the UK and the USA is 4.5%. Weassume a higher EMRP of 7% for Uganda, reflecting the higher risks and thus, higher rate of returnrequired by investors for investing in the equity markets of Uganda. Surveys carried out by PwChave suggested that the EMRP is higher in emerging markets than in developed economies.

5.5 Beta

A key characteristic of the CAPM is that the only risks for which equity investors require a return arethose which cannot be eliminated by holding a diversified portfolio of different equity investments.

Modern portfolio theory suggests that while returns on equity investments fluctuate for a wide rangeof reasons, those risks that are specific to individual investments can be successfully eliminated byholding a portfolio of different investments. In other words, over a period of time, poor returns onsome investments are offset by strong returns on others so that overall returns do not fluctuate inreaction to changes in such factors.

On the other hand, there are a range of risk factors, associated with general economic conditions,which affect virtually all equity investments to a greater or lesser extent. Thus, if interest rates rise orGDP growth slows, all equity investments are likely to perform less well than had been expected.This means even a diversified portfolio of equities is vulnerable to such risks. It is for taking the risk



associated with such systematic factors that equity investors require a higher return than thatavailable on risk-free instruments such as US Government bonds.

The degree of such systematic risk to which any individual investment exposes an equity investordepends on the correlation between movements in the returns on that investment and returns on themarket as a whole. The stronger the correlation, and the greater the amplitude of any movement inreturns, the higher the risk associated with an investment. A company’s beta measures thiscorrelation. It can be observed by looking at the actual relationship between past movements in thecompany’s returns and those for the stock market as a whole.

Again, because the Ugandan telecommunications companies are not quoted, with the exception ofMTN, it is appropriate to examine the betas of quoted companies that have similar riskcharacteristics. To this extent, we have analysed different samples of comparator companies. Toassist with the applicability of comparator companies in the samples, we have looked at a number ofcriteria. These are:

Income per capita. The comparator companies should operate in countries with similar incomelevels. This is important because the risks of fixed-line telephone businesses are likely to be differentdepending on the income levels of the country in which they operate. For countries with higherincome levels, the use of a fixed-line phone is likely to be insensitive to changes in income, whereasin countries with lower income levels, fixed-line telephone services are likely to have a higher incomeelasticity. Greater sensitivity to the economy should lead to a higher beta for telecommunicationscompanies in countries with a lower income levels, and so comparator companies should also beselected from countries of similar income per capita levels. We therefore analysed comparatorcompanies that operate in similar emerging markets, including Africa and also Asia and LatinAmerica, particularly as the number of listed telecommunications companies in Africa is limited.

Gearing. Beta estimation of companies with high gearing is difficult, because the assumption that thedebt beta is zero does not hold in distressed situations. We therefore typically remove allcomparators with a debt to equity ratio over 100%.

A PwC sample of quoted mobile and fixed operators, based upon information from Bloomberg andselected on the basis of our criteria presented above. We have kept the sample as broad as possibleso that the beta estimate is not unduly influenced by any one comparator.

To reflect the higher risks faced by the fixed-line operators in Uganda compared to those in otheremerging markets, we also selected a sample of alternative network operators (‘altnets’) fromdeveloped markets. These companies mostly provide business communications solutions tocorporations as an alternative to the incumbent fixed network operators, and therefore face a higherlevel of risk compared to fixed incumbents. Since the fixed operators in Uganda face a low marketpenetration compared to the mobile operators, we believe that the ‘altnets’ provide a goodbenchmark for the risks faced by the fixed-line operators.

It should be noted that the betas calculated from historical market data are equity betas. They give ameasure of the risk that equity providers were exposed to as a result of investing in the companiesexamined given the particular level of gearing of those companies in the historical period examined.The existence of debt finance in companies increases the risk to equity investors as debt has firstcall on available cash for investors. Equity betas are thus higher than the underlying ‘asset’ betas(which are the betas that would be appropriate were the company financed by equity only, and therewas no additional financial risk to equity providers associated with the inclusion of debt).

Asset betas have been derived from the observable equity betas by employing a simple adjustmentformula:



E

Dae 1

A discussion on the use of this formula is provided in Appendix 3.

Based on our sample comparators, we calculate an asset beta of 0.68 for mobile operators and fixedoperators.

Based on a gearing figure of 13% for mobile operators and 31.7% for fixed operators, we estimatean equity beta of 0.7 for mobile operators and 0.6 for fixed-line operators. Full details of thecomparator companies and their corresponding gearing and beta values can be found in Appendix 2.



6 Cost of Debt

The cost of debt can be assessed by considering the following:

The yield on traded debt for African countries by comparing the long-term debt margins (i.e.the additional premium over and above the risk-free rate or the return on government bonds)which banks and other debt providers require for lending money to companies similar toUgandan telecommunications companies.

The Ugandan telecommunications companies’ cost of debt from their borrowing facilities andthe interest expenses in their financial accounts.

The Ugandan fixed-line operators have no traded debt and rely on bank loans for their debt fundingand there was no traded debt found in the African listed Telecom companies.

We have obtained the accounts from Telkom South Africa, a listed fixed operator, and fromVodafone Egypt, a listed mobile operator.

As we did not have `specific information about the borrowing rates, we calculated an average cost ofdebt by dividing the annual interest charge by the average of the short-term and long-termborrowings throughout the year. Because this is calculated from point values of borrowing levels atthe beginning of the year and the end of the year, it can deviate from the true borrowing cost.

Telkom South Africa’s accounts show that their implied rate for the total cost of debt is 14.4%.Vodafone Egypt’s cost of debt has been estimated in the same way at 15.7%. The drawback to thismethod is that the maturity and terms of the debt is unknown and it includes short term as well aslong term debt.

We have also considered the commercial bank rate quoted on the Bank of Uganda’s website at18.2%. The implied rate of interest derived from the African company accounts is lower and this maybe explained by the fact that Ugandan telecoms rely on significant intercompany loans that may ormay not carry market rates of interest.

The table below summarises the range and mid-point estimate of the cost of debt adopted for ouranalysis:

Min Max Midpoint

Cost of debt 15.0% 18.0% 16.5%

The minimum is based on the implied cost of debt from African company accounts and the maximumis based no the commercial lending rate per the Bank of Uganda’s website.

Compared with the risk-free rate of Uganda, a borrowing cost of 18.2% implies a debt margin of4.1%. The debt margin is calculated as follows: debt margin = cost of borrowing – risk-free rate (Debtmargin = 18.2% - 14.1% = 4.1%).

Whilst a rate of interest (risk-free rate plus debt margin) is charged in the market most businesseseffectively pay a lower corporation rate because they are able to utilise the tax shield advantages ofdebt finance (profits are taxed after interest payments. This is taken into account in the WACCformula by multiplying the cost of debt by [1 - tc].



6.1 Tax wedge uplift

In order to convert a post-tax WACC to a pre-tax WACC, the post-tax WACC should be ‘uplifted’ bythe Ugandan tax rate. For 2009, the Ugandan corporation tax rate for residential companies is 30%.

The uplift is applied as follows: pre-tax WACC = post-tax WACC/(1-corporation tax). The overallcalculation is presented in the following section.



7 WACC

The formula for the WACC is as follows:

Post-tax WACC = Ke * [E/(D+E)]+Kd *(1-tc)*[D/(D+E)]

Pre-tax WACC = (Post-tax WACC)/(1-te)

where: Ke = Cost of equityKd = Cost of debtE = Value of equityD = Value of debttc = Marginal corporation tax rate

te = Effective corporation tax rate

andKe = [(1+Rf)*(1+CRP)-1]+*EMRP+SCP

where: Rf = Risk free rateCRP = Country Risk Premium

= Equity betaEMRP= Equity market risk premium

SCP = Small Company premium

andKd = [(1+Rf)*(1+CRP)–1]+m

where: m = Debt margin

The table below summarises our findings. We have prepared two scenarios - ‘Mobile’ and‘Fixed’ – to reflect the different risk profiles of the two different sectors.



Table 1: Uganda WACC

Component Mobile Fixed-lineoperators

Assumptions

Risk free rate 12.8% - 13.5% 12.8% - 13.5% Based on 10 year Ugandan bond and the syntheticapproach

Tax Shield 30.0% 30.0% Corporate tax rate in Uganda

Debt Margin 2.2% - 4.5% 2.2% - 4.5% Debt margin based on company accountsinformation from listed African fixed and mobileoperators.

Cost of Debt(pre-tax)

15.0% - 18.0% 15.0% - 18.0% (Risk-free + Debt Margin)

Cost of Debt(post-tax shield)

10.5 – 12.6% 10.5 – 12.6% (Risk-free + Debt Margin)*(1-Tax)

Asset beta 0.7 0.6 Mobile companies: average asset betas of mobileoperators in all emerging markets:

Fixed companies: average asset betas of the fixed-line operators in all emerging markets and ‘altnets’from developed markets

Debt-Equity ratio 16.5% 50.8% Based on median gearing of mobile operators andfixed operators in Africa

Equity beta 0.8 0.9 Equity beta is levered using the Miller formula:Equity Beta = Asset Beta * (1+D/E)

Gearing (D/V) 13.0% 31.7% Based on median gearing of mobile operators andfixed operators in Africa.

EMRP 7.0% 7.0% EMRP used is PwC estimate for emerging markets

Cost of Equity(post-tax)

18.0% - 17.7% 19.0% - 19.7% CAPM formula = Risk-free rate + Equitybeta*EMRP

Nominal post-taxWACC

17.4%- 18.2% 16.3% - 17.2% WACC = Cost of Equity*(Equity /Debt +Equity) +Cost of Debt*(Debt /Debt +Equity)

Nominal pre-taxWACC

24.2% - 25.6% 23.3% - 24.9% Pre-tax WACC = Post-tax/(1-Tax)



8 Conclusions

We calculate a pre-tax nominal cost of capital (rounded to the nearest whole percentage point) of:

24% to 26% for Uganda’s mobile operators; and

23% to 25% for Uganda’s fixed-line operators.

By way of comparison Ofcom used a pre-tax WACC of 10% for BT’s latest regulatorydetermination in June 2005. It follows that the telecommunications operators in Uganda shouldbe set a significantly higher return on the basis of its less developed business, with highexposure to risky urban and business customers in a country of higher sovereign risk, and thehigher rate of inflation in Uganda compared with the UK.



Appendix 1: Country Risk Premium Methodology

1 What is Country Risk?

Country risk reflects risks inherent to investing in different sovereign territories. It is close to zero formost developed and stable countries, but can be substantially higher in emerging markets. Broadlyspeaking, it can be attributed to variations in the degree of economic, political, financial andinstitutional stability in different countries.

Country Risk Adjustments

Many academics agree that country risk has a material impact on Net Present Value (NPV), butdisagree about how it is best handled. The standard textbook approach assumes it has alreadybeen dealt with by making (downwards) adjustments to cashflows – for factors such as the risk ofcivil unrest, expropriation, exchange controls and so on – when the cashflows were initiallyassessed.

In reality, this is rarely the case. Most financial analysts are not country risk experts, and cashflowsare usually assembled using straightforward public or management account information withoutfurther adjustment.

Financial textbooks are typically silent on this problem, even though the principle of arbitrage statesthat two opportunities of similar risk should have the same required rate of return, and an exposureto a higher risk macroeconomic, political or institutional environment should therefore becompensated by a premium on invested cash.

The PwC approach handles country risk (where it is clear that adjustments to cash flowshave not been made), through adjustments to the discount rate. If such adjustments werenot made, the value ascribed to investments in countries with higher country risk would beoverstated.

2 Quantification of Country Risk

It is possible to quantify country risk premia by measuring the default yield spreads on US dollar–denominated sovereign Eurodollar bonds (issued by various countries) compared with the yields onUS Treasury bonds of the equivalent maturity (US Treasury bonds are usually considered “risk-free”). Because both types of bond will pay both principle and interest in US dollars, the cashflowpayoffs from both are identical; any premia on the yields on the sovereign bonds (compared with theUS Treasuries) can therefore be attributed to the perceived default risk of the sovereign countryrelative to the US.

These premia are derived directly from market prices. They can therefore be seen as representing aconsensus view of the level of country risk.

An in-house PwC model estimates default spreads for over 30 countries where bondinformation is available, by using logarithmic regressions to fit yield curves so that astatistical term structure model can be derived. By way of illustration, the graph belowshows the US Treasury yield curve and a Colombia US dollar yield curve, based onobservations in the Eurobond market. The gap between the two represents the defaultspread associated with Colombia, at different points in time. This varies with duration.



USD Yield Curves

R2 = 0.9152

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

0 50 100 150 200 250 300 350 400

Months to Maturity

Colombia Log. (US Treasury) Log. (Colombia)

From the modelled curves, it is possible to estimate a 10 year Country Risk Premium (CRP) of 3.4%for Colombia.

Where sovereign bond information is unavailable, the PwC model calculates an implied premium bylooking at credit ratings of the country in question. This relies on country credit ratings from Moody’s,S&P, EIU and Euromoney (section four below). The PwC model regresses observed premia forcountries where direct bond market information is available against their corresponding credit rating.This derives a predictive statistical model of country risk.

The graph below shows the relationship between observed 10-year default spreads and creditratings supplied by Moody’s. The credit ratings are linearised into percentages to facilitate thisprocess (see section four below).

Premium as a Function of Rating (Moody)

y = 0.005e3.3073x

R2 = 0.7678

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Risk Rating

Ris

kP

rem

ium

Market Spreads Moody Model

We use four credit rating agencies to derive four separate predictive models. By a process ofresidual analysis, we are able to rank them in order of preference. For the third quarter in 2004 wecontinue to use an average of all four credit rating variables as the best predictor for yield spreads inour sample.

For countries where no credit rating is supplied by one or more of the rating agencies, the modeluses those that are available. As a consequence, as long as a country has a credit rating supplied byone or more agencies from our sample, it is possible to estimate a country risk premium for thatcountry.



3 Credit Ratings

There are numerous organisations that rate the political, social, institutional and macroeconomicrisks faced by particular countries. For example, EIU and Euromoney grade individual countriesbetween 0% and 100%, - where 0% is zero risk and 100% is maximum risk – using a system offactors considered of importance. These include the risk of social unrest, the impact of crime andmore economic factors such as debt service as a percentage of GDP.

Moody’s and Standard and Poor’s also provide credit ratings for sovereign states, reflecting the riskof default on government bonds. These ratings consist of twenty bands ranging from AAA (minimalrisk of default) to D (default). For the purpose of our regression analysis, we have linearised theseratings into percentages – where 0% represents no risk of default and 100% represents maximumrisk – in order to derive our predictive statistical models.

Sovereign credit ratings are largely determined by the markets’ perception of country risk. Theratings are therefore intended to be forward-looking, assessing the prospects of different countries inrelation to their future ability to repay debt.



Appendix 2: Comparator information

Table 2: Mobile companies

Sector Company Country Equity Market Cap. Total Debt 5 year D/E ratio 5 year D/ V AssetBeta GBP£ mils. GBP£ mils. Beta

Africa MobiNil Egypt 0.7 14500 6368 21% 16% 0.6

MTN Group Limited South Africa 0.9 196864 70300 16% 13% 0.8Asia (excluding Japan) China United Telecommunications Ltd China 0.9 105771 1408 33% 21% 0.7

China Mobile Limited China 1.1 1347618 35388 4% 4% 1.1New World Mobile Holdings Ltd China 1.1 225 n/a 483% 37% 0.2

Hutchison Telecommunications Int Ltd China 0.7 9581 11269 57% 34% 0.5Partner Communications Ltd Israel 0.8 9299 388 17% 12% 0.7

Digi.com Berhad Malaysia 1.0 16716 200 5% 5% 0.9Pilipino Telephone Corp Philippines 1.0 81205 43 21% 8% 0.8

Mobile TeleSystems Russia 0.8 7468 3312 22% 17% 0.7MobileOne Ltd Singapore 0.7 1342 250 15% 13% 0.6Far EasTone Telecommunications Ltd Taiwan 0.6 121216 5409 5% 4% 0.6

Taiwan Mobile Ltd Taiwan 0.6 184915 25243 15% 13% 0.5Advanced Info Service Ltd Thailand 0.8 235458 33042 11% 10% 0.7

South America Tim Participacoes SA Brazil 0.9 8597 2942 38% 20% 0.6Telemig Cellular Participacoes SA Brazil 0.6 1260 181 13% 11% 0.6

Telemig Cellular SA Brazil 0.7 2576 181 15% 12% 0.6Vivo Participacoes SA Brazil 0.9 10704 5953 50% 32% 0.6

Tele Norte Celular Participacoes SA Brazil 0.7 351 77 108% 47% 0.3Median Excluding Outliers 16% 13% 0.6Arithmetic Mean Excluding Outliers 26% 16% 0.7

Table 3: Fixed-line companies

Company Country Equity Market Cap. Total Debt 5 year D/E ratio 5 year D/ V AssetBeta GBP£ mils. GBP£ mils. Beta

Africa Sonatel Senegal n/a 1300000 23174 6% 6% n/a

Asia China Telecom Corporation Ltd China 1.1 202001 99806 46% 31% 0.7PCCW Ltd China 0.7 23364 27443 99% 49% 0.4Tata Communications Ltd India 1.0 144025 33466 17% 14% 0.8Mahanagar Telephone Nigam Ltd India 1.1 50369 106 0% 0% 1.1Tata Teleservices Maharashtra Ltd India 1.1 39746 26269 55% 36% 0.7Pakistan Telecommunications Co. Ltd Pakistan 0.9 91239 10907 7% 7% 0.8Starhub Ltd Singapore 0.6 3354 914 16% 13% 0.5KT Corporation South Korea 0.6 10257590 5867138 67% 40% 0.4

South America Telefonica del Peru S.A.A. Peru 0.7 6649 3770 63% 38% 0.4Compania de Telecomunicaciones de Chile Chile 0.8 1042893 428381 42% 30% 0.5Compania Nacional de Telefonos Telefonica del Sur Chile 0.5 63015 67067 67% 39% 0.3Telesp Brazil 0.5 21433 2764 12% 10% 0.5Tele Norte Leste Participacoes SA Brazil 0.6 13534 17724 75% 42% 0.3Brasil Telecom SA Brazil 0.8 17638 4266 49% 32% 0.5Brasil Telecom Participcoes SA Brazil 0.8 11853 4266 51% 33% 0.5Telefonica de Argentina SA Argentina 1.7 3562 1327 295% 48% 0.4

Alternative Thus Group Plc UK 0.6 218 102 28% 21% 0.5

Networks Colt Telecom Group SA UK 1.4 424 262 57% 33% 0.9FiberNet Telecom Group Inc US 1.5 74 14 54% 29% 1.0Tele2 Netherlands Holding NV Netherlands 0.9 754 167 34% 24% 0.7

Median Excluding Outliers 51% 32% 0.5

Arithmetic Mean Excluding Outliers 58% 29% 0.6



Appendix 3: Unlevering formulae

Summary

In choosing a beta de-levering/re-levering formula to use in estimating the Weighted Average Cost ofCapital (“WACC”) an assumption must be made about the degree of certainty around future debt taxshields. Treating companies’ future debt tax shields as certain is generally not a realistic assumptionto make. A more reasonable assumption is that future debt tax shields are uncertain, consistent withcompanies having active debt management policies (although the first year’s debt tax shields might,perhaps, be considered as certain).

This assumption points to the Harris and Pringle beta de-levering/re-levering formula, being theappropriate formula to use in all beta de-levering/re-levering calculations. The formula is as follows:

E

Dae 1 (1)

where:

e is the company’s equity beta;

a is the company’s asset beta;

D is the market value of the company’s debt; andE is the market value of the company’s equity.

It is noted that provided the same formula is used for de-levering the comparable company betas asis used for re-levering the target company beta, and that the comparable companies have similargearing and tax rates as the target company, the target company equity beta estimate should not beparticularly sensitive to the choice of beta de-levering/re-levering formula.

Background

The beta input required for the CAPM is an equity beta ( e ). Equity betas reflect the "riskiness" of

shareholder returns that arises as a result of fixed debt servicing commitments (i.e. the effects offinancial leverage or gearing) and the underlying riskiness of the firm’s assets. The latter is

measured as an asset beta ( a ). Only equity betas are “observed” in the market place, through

statistical analysis of share price behaviour for companies whose shares are actively traded. Sincefinancial leverage varies between companies the preferred, and indeed conventional, approach toestimating the equity beta for the firm being valued is as follows:

Obtain equity beta estimates for a sample of listed companies that are considered comparableto the company being valued (“compcos”);

Obtain financial leverage details for the compcos;

“De-lever” the compco equity betas to arrive at asset beta estimates for the compcos(formulae for doing this are discussed below). This step removes the influence on beta arisingfrom variations in compco financial leverage;

Having regard to the compco asset betas, make an assessment of the asset beta appropriatefor the “target” company being valued; and



“Re-lever” the assessed asset beta for the level of gearing being assumed for the targetcompany, to arrive at an assessed equity beta for that company (the formula used is generallythe reverse of that applied in the “de-levering” process).

Formulae for De-levering/Re-levering Betas

Fundamentally the asset beta of a company is a weighted average of that company’s equity beta and

its debt beta ( d ). Estimation of debt betas is problematic, so current practice among most

practitioners and many academics is to assume that companies’ debt betas have a value of zero.This simplifies the relationship between equity beta and asset beta, but three issues still need to beconsidered in determining the appropriate formula to use. These issues are:

The company’s effective corporate tax rate ( CT );

The effect of investors’ taxes on the value (if any) of the tax shield arising from the use of debt;and

The effect of the company’s debt management policy on the value of the debt tax shield.

The Hamada Formula

Under a classical tax system (i.e. one where dividends are paid from company earnings aftercorporate tax, and are then subject to personal taxes at the investor level) and where the companyadopts a passive debt management policy (i.e. the future debt servicing schedule is assumed to beknown with certainty at the valuation date), then the appropriate formula for relating equity and assetbetas is:

E

DTCae 11 (2)

where:

D is the market value of the company’s debt; and

E is the market value of the company’s equity.

The above formula is known as the “Hamada” formula5 and is widely used by practitioners andacademics. However, the assumption that the company’s future debt servicing schedule is knownwith certainty is questionable. For example, in the face of changes to its enterprise value a companyis likely to adjust its level of debt – to maintain a target leverage ratio. Furthermore, features of thepersonal tax regime may significantly reduce the value of the tax shield attributable to the use of debtfinancing.

5 Hamada (1969).



The Harris and Pringle Formula

Where all of the company’s future debt tax shields, including those arising in the first period, aretreated as uncertain or risky then analysis by Harris and Pringle (1985) provides the followingrelationship between equity beta and asset beta:

E

Dae 1 (3)

The above formula is known as the “Harris and Pringle” formula and is derived from differentassumptions to the Hamada formula. If the company is expected to maintain a target leverage ratiothrough time (i.e. it has an active debt management policy), but with total firm value evolving withuncertainty, then it follows that the future debt servicing schedule is uncertain. Typically thisassumption is more realistic than the alternative of assuming that the future debt servicing scheduleis known with certainty. This means that in most circumstances the Harris and Pringle formula willbe more appropriate than the Hamada formula.

The Miles and Ezzell Formula

Miles and Ezzell (1985) derive a beta de-levering/re-levering formula that assumes that the tax shieldon debt is certain for the first period (i.e. the first year), but thereafter is uncertain. Theseassumptions fall between those of Hamada and of Harris and Pringle so, as to be expected, theresulting formula falls between formulae (2) and (3) above. The Miles and Ezzell formula is:

E

D

r

Tr

f

Cf

ae1

11 (4)

where:

fr is the risk free rate of return.



References

Graham, J.R., 2000, “How Big Are the Tax Benefits of Debt?”, Journal of Finance, vol. 55(5), pp.1901-41.

Hamada, R.S., 1969, “The Effect of the Firm’s Capital Structure on the Systematic Risk of CommonStocks”, Journal of Finance, vol. 27, pp. 435-52.

Harris, R.S. and J.J. Pringle, 1985, “Risk-adjusted Discount Rates – Extensions from the Average-risk Case”, Journal of Financial Research, vol. 8(3), pp. 237-44.

Miles, J.A. and J.R. Ezzell, 1985, “Reformulating Tax Shield Valuation: A Note”, Journal of Finance,vol. 40(5), pp. 1485-92.

Taggart, R.A.,Jr., 1991, “Consistent Valuation and Cost of Capital Expressions With Corporate andPersonal Taxes”, Financial Management, vol. 20(3), pp. 8-20.



© 2009 PricewaterhouseCoopers. PricewaterhouseCoopers refers to the network of memberfirms of PricewaterhouseCoopers International Limited, each of which is a separate andindependent legal entity. All rights reserved.

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