WEIGHTED AVERAGE COST OF

CAPITAL Sabesp’s contribution to the Basic Sanitation Public Consultation No 01/2011

Companhia de Saneamento Básico do Estado de São Paulo – Sabesp March 2011

1

Table of contents

1 INTRODUCTION ........................................................................................................................ 3

2 GENERAL MODEL ...................................................................................................................... 3

2.1 Rsks deriving from the Regulatory System ................................................................................. 4

2.2 Comprehensiveness of information ........................................................................................... 4

2.3 Arithmetic Corrections ............................................................................................................... 5

2.4 Series temporal consistency ...................................................................................................... 6

2.5 Selection of the Series Temporal Window ................................................................................. 9

2.6 U.S. economy inflation ............................................................................................................. 11

3 OPTIMUM CAPITAL STRUCTURE ...................................................................................... 12

3.1 Consistency Test ...................................................................................................................... 16

4 COST OF EQUITY ..................................................................................................................... 17

4.1 General Model ......................................................................................................................... 17

4.2 Calculation of Betas ................................................................................................................ 18

4.3 Exchange risk in the Cost of Equity........................................................................................... 20

4.4 Summarized Calculation of the Cost of Equity.......................................................................... 21

5 COST OF DEBT ......................................................................................................................... 22

5.1 General Model ......................................................................................................................... 22

5.2 Investment Grade .................................................................................................................... 23

5.3 Exchange Risk in the Cost of Debt ............................................................................................ 25

5.4 Summarized Calculation of the Cost of Debt ............................................................................ 26

6 RECOMMENDATIONS AND FINAL CALCULATION ....................................................... 28

7 BIBLIOGRAPHY ....................................................................................................................... 28

2

8 ATTACHMENTS ....................................................................................................................... 31

8.1 Stochastic beta........................................................................................................................ 31

8.2 U.S. inflation ............................................................................................................................ 31

8.3 Risk-free rate and market premium - USA ............................................................................... 31

8.4 Global and local betas .............................................................................................................. 32

8.5 Credit risk ................................................................................................................................ 32

8.6 Country risk ............................................................................................................................. 32

8.7 Benchmark companies capital structure .................................................................................. 32

3

1 INTRODUCTION The purpose of this text is to contribute to the definition of Sabesp’s Weighted Average Cost

of Capital (WACC) calculation methodology.

On March 4, 2011, the São Paulo State Sanitation and Energy Regulatory Agency - ARSESP

presented its Technical Note, which proposes a methodology and sources of data to calculate

Sabesp’s WACC, an extremely important variable to define the attractiveness of investing in

sanitation.

Sabesp’s major investments are made with funds deriving from its own revenue (tariffs). For

the Company to be able to pursue its economic and financial sustainability and

universalization of sanitation services in São Paulo municipalities where it operates, it is

essential to define a providers of capital’s rate of return that attracts resources to

complement financing of necessary investments, as defined by the granting authorities in

their sanitation plans.

It is worth mentioning that the energy sector, from which the proposed methodology

derives, already reached a level of maturation much higher than the sanitation sector, both

from the regulatory point of view, as from the need of investments for universalization.

In this regard, in the current development stage of the sanitation sector, a strictly lower tariff

does not seem the best option, but one that ensures the universalization of services with

quality and safeguards the future of the sanitation sector by means of a correct return on its

assets.

This text is organized as follows: a general analysis of the model, data and series proposed by

ARSESP (section 2). Thereafter, forms of calculating the Cost of Equity, Cost of Debt and

Optimum Capital Structure for Sabesp (sections 3, 4 and 5, respectively) are discussed.

Finally, Sabesp’s calculation proposal is presented (section 6).

2 GENERAL MODEL The cost of capital corresponds to the minimum required return on the assets of a company

or project. The companies or projects compose their capital by raising funds through debt

with creditors or shareholders. These sources of financing show distinct risk-return profiles,

therefore, their costs also differ. The cost of capital of a company will then correspond to the

weighted average of cost of its equity and debt, with weights determined by levels of

indebtedness and equity. The weighted average cost of capital is called WACC.

4

2.1 RISKS DERIVING FROM THE REGULATORY SYSTEM

The economic regulation models can be divided into two main classes according to the

stimulus given to the efficiency of regulated companies: firstly, with a reduced incentive

level, the main model is the regulation by rate of return, generally applied in the USA.

Secondly, with higher incentives, main models are the regulation by price-cap, revenue cap

and by comparison. These are most commonly used in the United Kingdom [Naccache

20101].

As proposed by Alexander, Mayer and Weeds (1996)2, it is possible to objectively determine

the risk related to the regulatory system and the difference in Betas of assets of companies

regulated by distinct systems, classifying the methods in view of incentive to the efficiency of

the regulated company.

Contribution:

It is necessary to consider in the model the effective difference of inherent risk between the

regulatory system, which everything indicates, is intended to be applied in Sabesp (Price-Cap)

and the data and series verified in a regulated market by another regulatory system (USA).

This additional risk must be mainly mitigated in the cost of debt, if the selection of U.S.

companies is adopted, as proposed by the Technical Note.

2.2 COMPREHENSIVENESS OF INFORMATION

When analyzing the material submitted by ARSESP, drawbacks were seen in the reproduction

of data and series used in calculations. The technical note does not contain the necessary

details to a prompt evaluation of the model, thus, great analysis efforts were spent in an

attempt of reproducing the figures of the technical note and not in discussing the model,

which is relevant.

The absolute transparency in the statement of data and formulas used in technical notes has

been more and more a common practice seen in Brazilian regulatory agencies, mainly federal

authorities. Not uncommonly, they also attach tables with the series used and they specify

the formulas applied.

We requested ARSESP to include in its final analysis of this public consultation, as well as in

its future publications, the attachments containing the sources of data (tables, lists, website

1 Naccache, Flavio F. 2011, “Transformação Cultural em Grandes Corporações: Sustentabilidade, Regulação e Foco

no Cliente”, capítulo 3 “Transição para uma Empresa Regulada”, pp. 97-118. 2 Alexander, I., Mayer, C. and Weeds, H. 1996, “Regulatory Structure and Risk: An International Comparison”,

prepared for the World Bank.

5

screens, etc.). In case of extensive tables, these should be made available through electronic

means.

The information Sabesp used in the calculations presented herein can be seen in the table

below, and it is also available in the attachments hereof.

Table 1: Summary of data, periods of calculation and periodicity.

SYMBOL TERMINOLOGY PERIOD PERIODICITY ATTACHMENT

Risk-Free Global Rate 4/9/03 to 3/24/11 Daily 2

Market Global Return 4/9/03 to 3/24/11 Daily 2

Global Premium 4/9/03 to 3/24/11 Daily 2

Original Local Beta 1/2/03 to 3/24/11 Daily 3

Original Global Beta 1/2/03 to 3/24/11 Daily 3

Solnik Beta 1/2/03 to 3/24/11 Daily 3

Credit Global Risk 1/2003 to 2/2011 Monthly 4

Sovereign Risk 1/2/03 to 12/10/10 Daily 4

% Sabep Equity LAST DATA - 6

% Sabesp Debt LAST DATA - 6

% Optimum Equity LAST DATA - 6

% Optimum Debt LAST DATA - 6

Global Inflation 1/2003 to 12/2010 Monthly 7

2.3 ARITHMETIC CORRECTIONS

It was not possible to reproduce the value presented for WACC of 7.53%. The following

issues must be re-evaluated:

1) Page 7 of the Technical Note affirms:

“Thus, an efficient cost of equity is obtained in nominal terms corresponding to 14.92% p.a.

when using the U.S. annual average inflation rate in the period between 1995 and 2010

(2.48%), then we have an actual cost of equity of 10.88% p.a.” (we underlined)

Nevertheless, in the table above the aforesaid text and the final figure applied by ARSESP is

14.25% p.a. If the nominal rate of 14.92% or 14.25% is applied, none of them generates the

actual rate of 10.88% applied:

� (1 + 14.92%) / (1 + 2.48%) − 1 = 12.14%

� (1 + 14.25%) / (1 + 2.48%) − 1 = 11.49%

2º) Disparities were also seen in the actual rates of debt and WACC, (in the note, 6.55% and

7.53%, respectively), as follows:

� (1 + 8.98%) / (1 + 2.48%) − 1 = 6.34%

� (1 + 10.34%) / (1 + 2.48%) − 1 = 7.67%

6

Contribution:

Sabesp requests, irrespective of other contributions from this text, proper corrections in the

arithmetic calculations. The application of the methodology and data proposed by the agency

results in a weighted average cost of capital of 7.67%.

2.4 SERIES TEMPORAL CONSISTENCY

According to our analysis, ARSESP’s data have the following characteristics:

Table 2: data applied by ARSESP

VARIABLE PARAMETER SERIES PERIOD PERIODICITY

4.19% Not explained 10/17/2003 -2/14/2011 Daily

Not explained S&P 500 Not explained Not explained

5.78% Not explained Not explained Not explained

0.55 SABESP= f(IBOVESPA) 02/2009 – 02/2011 Daily

1.45 IBOVESPA=f(S&P 500) 02/2009 – 02/2011 Daily

1.28

2.67% EMBI+ 01/2009 - 12/2010 Last day of the

month

T 34% Theoretical rate - -

0.53 Average USA Not explained Not explained

0.47 Average USA Not explained Not explained

2.48% ... 1995-2010 Annual

2.12% Spread BBB+ 01/1995 – 04/2010 Not explained

Source: ARSESP Technical Note

When a Cost of Equity model is specified, the objective is to estimate with the highest level

of accuracy as possible, the behavior of return on the Company stocks.

The adopted model derives from macroeconomic equations and explains the return on

Sabesp stocks in view of the global risk-free rate of the global risk premium ,

local and global systematic risk, country risk and global inflation rate.

Despite the difficulty to model and project financial series, it is necessary to preserve the

maximum synchronicity among them so that macroeconomic equations from which the

model derives make sense. We know, for instance, that:

� The expectation of inflation affects the stock market;

7

� The expectation of inflation affects the nominal interest rates (Fisher effect);

� Interest rates influence inflation through level of activity (Philips curve);

� Nominal interest rates are related to the stock market.

The macroeconomic and financial variables mutually interact without large temporal lags.

The graph below shows the behavior of Ibovespa and country risk (EMBI+):

Graph 1: Temporality between model variables

EMBI+ IBOV

2003 2004 2005 2006 2007 2008 2009 2010 2011

200

400

600

800

1000

1200

EMBI+ IBOV

Source: Ibovespa: Bloomberg, EMBI+: CORECON

Despite the fact that Ibovespa and Country Risk series are inversely proportional, the ratio

between them is practically contemporary (without large gaps).

To test this effect on the series used in the model under discussion, Sabesp applied formal

econometric tests (Akaike3) to all series used in the model, on a monthly basis and

simultaneously. According to test results (seen in Table 3), we may conclude that variables

are interdependent with effects with a lag of at most a month.

Table 3: AIC Test Results

Lag AIC

0 -1.368379

1 -1.395838*

2 -1.393669

3 -1.388130

4 -1.361048

5 -1.335820

3 Akaike, Hirotugu (1974). "A new look at the statistical model identification". IEEE Transactions on Automatic

Control 19 (6): 716–723.

8

6 -1.319606

7 -1.314848

8 -1.311368

Source: prepared by Sabesp

The estimation of a vector auto regressive model (Sims4), using the same series, reinforces

the affirmation. As seen in the graphs below, blue line, variables shocks disperse rapidly.

Chart 1: vector autoregression tests in studied series

-1.5

-1.0

-0.5

0.0

0.5

2 4 6 8 10 12

DRF ± 2 S.E .

Acc umulated R esponse o f D EMBI to DR F

-1

0

1

2 4 6 8 10 12

INF ± 2 S .E.

Ac cumula ted Res pons e of D EMBI to IN F

-2.0

-1.5

-1.0

-0.5

0.0

2 4 6 8 10 12

S BS P3 ± 2 S.E.

Acc umulated R esponse o f D EMBI to SBSP3

-1.0

-0.5

0.0

0.5

2 4 6 8 10 12

SPX ± 2 S .E.

Ac cumula ted R es ponse of D EMBI to SPX

-2.0

-1.5

-1.0

-0.5

0.0

2 4 6 8 10 12

BOV ± 2 S.E.

Ac cumula ted R es pons e of DEMBI to BOV

-.00008

-.00006

-.00004

-.00002

.00000

2 4 6 8 10 12

DE MBI ± 2 S .E.

Acc umulated R esponse o f D R F to D EMBI

.00000

.00002

.00004

.00006

.00008

2 4 6 8 10 12

INF ± 2 S.E .

Acc umulated R es pons e of D RF to IN F

-.00002

.00000

.00002

.00004

2 4 6 8 10 12

S B SP 3 ± 2 S .E.

Ac cumula ted R es ponse of D R F to SBSP3

.00000

.00002

.00004

.00006

2 4 6 8 10 12

SPX ± 2 S .E.

Ac cumula ted R esponse o f D R F to SPX

-.00002

.00000

.00002

.00004

2 4 6 8 10 12

BOV ± 2 S .E.

Acc umulated R es pons e of D R F to BOV

-.002

-.001

.000

2 4 6 8 10 12

DE MBI ± 2 S .E.

Ac cumulated R es ponse o f IN F to D EMBI

.000

.001

.002

2 4 6 8 10 12

DRF ± 2 S.E .

Acc umulated R es ponse of IN F to D RF

.000

.001

.002

2 4 6 8 10 12

SB SP 3 ± 2 S .E .

Ac cumula ted R es pons e of IN F to SBSP3

.000

.001

.002

2 4 6 8 10 12

S PX ± 2 S .E .

Acc umulated R es pons e of IN F to SPX

.0000

.0005

.0010

.0015

.0020

2 4 6 8 10 12

BOV ± 2 S .E.

Ac c umulated Res pons e of INF to BOV

-.7

-.6

-.5

-.4

-.3

2 4 6 8 10 12

DEMBI ± 2 S.E .

Acc umulated R esponse o f SBSP3 to D EMBI

-.2

-.1

.0

.1

2 4 6 8 10 12

DRF ± 2 S.E .

Ac cumula ted R es pons e of SBSP3 to D R F

-.3

-.2

-.1

.0

.1

.2

2 4 6 8 10 12

INF ± 2 S .E .

Ac cumula ted R es pons e of SBSP3 to IN F

-.1

.0

.1

.2

2 4 6 8 10 12

S PX ± 2 S.E .

Acc umula ted Res pons e of SBSP3 to SPX

.0

.1

.2

2 4 6 8 10 12

B OV ± 2 S .E .

Acc umulated R esponse o f SBSP3 to BOV

-.16

-.12

-.08

2 4 6 8 10 12

DE MB I ± 2 S.E .

Acc umulated R esponse o f SPX to D EMBI

.04

.08

2 4 6 8 10 12

DRF ± 2 S .E.

Acc umulated R es ponse of SPX to D R F

-.05

.00

.05

2 4 6 8 10 12

INF ± 2 S.E .

Ac cumula ted R esponse o f SPX to IN F

.04

.08

.12

2 4 6 8 10 12

SB SP 3 ± 2 S .E .

Ac cumula ted R es pons e of SPX to SBSP3

-.02

.00

.02

.04

.06

2 4 6 8 10 12

B OV ± 2 S.E .

Acc umulated R es pons e of SPX to BOV

-.5

-.4

-.3

2 4 6 8 10 12

DE MB I ± 2 S.E.

Acc umulated R esponse o f BOV to D EMBI

.0

.1

2 4 6 8 10 12

DRF ± 2 S .E .

Ac cumula ted R esponse o f BOV to D R F

-.2

-.1

.0

.1

2 4 6 8 10 12

INF ± 2 S .E.

Ac cumula ted R esponse o f BOV to INF

.3

.4

.5

2 4 6 8 10 12

SB SP 3 ± 2 S.E .

Ac cumula ted R es pons e of BOV to SBSP3

.1

.2

.3

2 4 6 8 10 12

S PX ± 2 S.E .

Acc umulated R es ponse of BOV to SPX

Accumulated Response to Cholesky One S.D. Innovations ± 2 S.E.

Source: prepared by Sabesp

Therefore, the utilization of the model under discussion without proper series temporary

synchronization may result in losing the macroeconomic sense of equations.

Contribution:

Sabesp requests the model to be applied to a single temporary window, i.e., that the period

adopted for all series is the same.

4 Christopher A. Sims, 1980, "Macroeconomics and Reality", Econometrica 48.

9

2.5 SELECTION OF SERIES TEMPORAL WINDOW

In line with the previous item, not only a single window should be used for all data, but the

selection of a temporal window must observe a concrete reasoning. Sabesp evaluated three

possibilities for the window start date:

1. Stabilization of economy in 1994, with the beginning of Real Plan.

2. Sabesp’s entry in the capital markets in 2002.

3. Evaluation of the company’s risk behavior in the stock market (Beta).

The utilization of Beta behavior as variable of decision to select the window makes sense to

the extent that:

� Overall, the model under discussion attempts to explain/ modeling the company's

cost of capital (both equity and debt) in view of its risk.

)(riskFWACC =

� We are interested in explaining the behavior of return on Sabesp stocks;

� The return on stocks is strongly related to their non-diversifiable risk (Beta);

� Beta captures the changes in macroeconomic variables that effectively have impact

on the company;

Therefore, this serie was deemed as the most relevant to select the series temporal window.

The section below models the series of Sabesp Beta in order to define the window to be

analyzed.

BE TA SE RIE S

There is no academic and practical consensus about the extension of the historical period

(sample) adequate to estimate the Cost of Equity. Should a longer period be selected, more

disassociated phenomena from future reality can be captured. Very short periods, however,

tend to be statistically less significant, since financial series are extremely volatile.

Certain characteristics assumed by the Systematic Risk (Beta) are reasonably disseminated in

reference material:

� It varies over time. Due to merely practical reasons, a constant value is adopted

(determining value) when actually it is stochastic;

� It has asymmetric behavior. It depends on the economic scenario (recession, growth,

high and low volatilities).

10

There are techniques based on state-space5 models that allow the estimation of time-varying

parameters. The graph below – a result of applying models of this type – shows the behavior

of Sabesp Beta since the Company has started to be listed on Bovespa.

Graph 2: Evolvement of Sabesp Beta over time

Source: Data: Bloomberg, prepared by Sabesp

Translator’s note: determining beta/stochastic beta

The comparison between determining beta (blue line) and stochastic beta (red line) allows to

verify its change over time. This change went through few regimes, namely:

� Until the end of 2002 it operated in an upward move;

� As of this year in downward move, possibly in view of improved capital structure and

foreign exchange appreciation;

� By mid 2008 it gives signs of upward move, but returns to downward trend;

� By the end of 2010, possibly due to unstable tariff rules, it gives signs of new reversal.

ARSESP decided to adopt the shortest period shaded in the graph.

5 Examples of application:

Black, A., Fraser, P. & Power, D. 1992, “UK unit trust performance 1980–1989: A passive time varying approach”, Journal of Banking and Finance, vol. 16 , pp. 1015–33. Wells, C. 1994, “Variable betas on the Stockholm exchange 1971–1989”, Applied Economics, vol. 4 , pp. 75–92.

.84

.86

.88

.90

.92

.94

.96

97 98 99 00 01 02 03 04 05 06 07 08 09 10

B E TA _D E TER MINÍS TICO B E TA _E S TOCÁ STICO

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Contribution:

There is a structural breakage of series in 2003 (graph 2). Conceptually, the inclusion of

different structural regimes of the main series (risk) in the model may fail to capture current

regime intended to be applied to the macroeconomic model and which will better explain

the behavior in the forthcoming future. Data prior to 2003 tend not to be relevant in the

correlation studied, or bring noise from other structural regimes to the model.

Sabesp requests the utilization of the fixed period between 2003 and 2011 to calculate all

the series (when available).

2.6 U .S . ECONOMY INFLATION

In the model under discussion, inflation is a parameter only incurring on the actual value of

weighted average cost of capital. This is a variable fully beyond the control of any agent.

Although Sabesp considers the most appropriate manner of estimating these series is using

the projection for the next years, this was applied in the Gas6 sector; the utilization of past

data may also be an estimate, as long as these are temporal series relatively long to minimize

the crisis periods effects. In addition, in this last alternative, it is advisable to use a single

temporal window adopted for the model.

SOURC E OF DATA

It was not possible to reach the figure presented by ARSESP for 1995-2010 inflation of 2.48%.

The series evaluated for the period deriving from the Brazilian Central Bank’s website

(BACEN)7, shows an annual average inflation of 2.41% in this period.

Proposal:

1. We suggest adopting a fixed temporal window from 2003 to 2011, which results in an

inflation of 2.40%. This window is sufficiently long to mitigate recent effects of the global

crisis, as well as coincides with the window adopted in other series.

2. Even if the initial window from 1995 to 2010 is maintained, it is necessary to correct the

calculation of the series to 2.41%.

6 In the Technical Note RTC 01/2009, the IMF inflation future projection of 1.4% was applied in the gas sector. In

the Technical Notes GNSPS 02/2010 and GBD 02/2009, the IMF inflation rate projection of 1.3% was also applied in the gas sector. 7 www3.bcb.gov.br/sgspub/consultarvalores/consultarValoresSeries.do?method=consultarValores

12

3 OPTIMUM CAPITAL STRUCTURE As the reference material does not have a consensus on the existence of an optimum capital

structure, in practice, the average capital structure adopted by peer companies is selected.

The regulatory agency does not discuss in its Technical Notice the criterion to select Sabesp's

optimum capital structure. By analyzing table of ATTACHMENT 2, we deduce that the agency

applied 47%, corresponding to the debt/equity ratio of eight U.S. companies in the water

utilities segment, averaged by 47.44%. The period adopted was also not explained.

The table below summarizes the data applied by ARSESP:

Table 4: ARSESP data to calculate the optimum capital structure

COMPANY TICKER DEBT/EQUITY

American Water Works Inc AWK US 132.82% Aqua America Inc WTR US 94.91% California Water Service CWT US 100.40% SJW Corp SJW Corp 100.40% York Water Co YORW US 94.99% American States Water Co AWR US 90.13% Connecticut Water Service SVC Inc CTWS US 125.25% Consolidated Water Co Ltda CWCO US 16.83%

AVERAGE 98.86%

SABESP SBSP3 77.71%

Source: ARSESP Technical Note

Note that the capital structure elected by ARSESP imposes higher indebtedness for Sabesp,

thus, higher risks. The aforementioned data show that the D/E = 0.9886 ratio seen in the

sample of eight U.S. companies, proposed as target by ARSESP, corresponds to a D/(D+E)

=0.47 ratio, i.e., an increase in relation to current ratio.

Currently, Sabesp is rated BB by the market (speculative grade), two grades below the level

used by the agency, BBB- (investment grade), to calculate the credit risk premium.

It is generally known that a higher level of indebtedness results in higher risk perception, and

accordingly, in the weighted average cost of capital. Therefore, it is contradictory to apply

the supposition of significant improvement of the market rating in two levels, and at the

same time, a leverage of almost 10% higher than the Company’s current leverage.

Considering the companies listed by ARSESP in the Attachment 2, it is observed that the

average of the eight U.S. companies converges to 47.44% as it includes a company with

indebtedness level (Debt-to-Capital) of 14.41%. The average, excluding this company,

exceeds 52%, a level incompatible with Sabesp. This shows that the sample chosen resulted

from the selection of U.S. market companies, does not seem to be the most appropriate

choice.

With the same data table, the average of Brazilian sanitation companies were calculated

(33.51%), Latin American companies including Brazilian companies (36.82%), average of all 26

13

listed companies (42.79%) and average excluding USA, United Kingdom, France and Germany

(28.27%). Note that the level of indebtedness ranges between 28% and 43% (minimum limit

excluding the four most developed countries; maximum limit including all listed companies).

Then, the proposal of 47% is highly above from we can see in the agency’s data.

In addition, what grabs our attention is that the selection of companies seems to be

arbitrary, thus, compromising the regulatory methodology.

Finally, it is relevant to mention that ANEEL’s proposal for the third electricity tariff cycle is

based on the survey of empirical data of Brazilian electricity distribution companies in recent

years. The basic grounds to consider empirical data are based on the principle that

distribution concessionaires already seek, as one of the vectors to maximize profits, the

composition between equity and debt, which minimizes the cost of capital. Then, when we

observe the concessionaires indebtedness in recent years, the companies rational behavior

already takes into account all the leverage costs and benefits, including the institutional

aspects of the environment where it operates.

Proposal:

In recent years, water has been considered a commodity, others affirm that water will be the

next century’s oil. Within this context, the capital markets in this type of asset have been

highly intensified.

There are several investment funds which only allocate resources in basic sanitation

companies and/or in its industrial chain. Several stock indexes were also created targeting

the sanitation industry, working as a benchmark for the market.

To elect the companies that will compose the portfolio, the consulting firms and “assets” are

extremely rigorous taking into account concrete criteria related to capitalization, liquidity,

presence at the stock exchange, price, among others.

One of the most comprehensive global water stock indexes is maintained by S-Network

Global Water Indexes, New York (www.snetglobalwaterindexes.com) and Sabesp participates

in this portfolio with 3.04%.

The following table shows the participation in the index according to the allocation in the

respective country:

14

Table 5: Frequency and participation in the Global Water Index

COUNTRY COMPANIES ALLOCATION

UNITED STATES 11 31.6%

ENGLAND 4 18.2%

FRANCE 2 15.8%

BRAZIL 2 6.2%

CHINA 2 5.1%

ITALY 2 4.6%

GREECE 2 3.8%

SINGAPORE 1 3.2%

CHILE 1 3.1%

PHILIPPINES 1 3.0%

HONG KONG 1 3.0%

MALAYSIA 1 2.6%

TOTAL 30 100%

Source: S-Network Global Water Indexes of New York

In fact, U.S. companies have a higher weight in the index (31.6%). Nevertheless, almost 70%

of the index targets other countries. Therefore, to elect only eight U.S. companies does not

make sense.

Contrary to the result of ARSESP’s criterion, the optimum capital structure deriving from the

adoption of the criterion suggested by Sabesp ensues in a lower indebtedness for the

company. The utilization of the full sample of companies composing the S-Networks Water

Works index (excluding Sabesp) would result in the D/E=0.7 ratio, which corresponds to

D/(D+E)= 0.41 ratio.

Therefore, Sabesp suggests to elect all the companies composing the S-Network Water

Works index, which results in Debt/Equity ratio of 0.7.

This methodology is objective and transparent to define the parameter under discussion,

which is essential in the regulatory process.

15

Table 6 shows the (D/E) ratio of companies composing the index.

Table 6: Debt/equity ratio of companies composing the Global Water Index

COUNTRY COMPANY %DEBT %EQUITY D/E

BRAZIL

Cia de Saneamento Básico Estado de S Paulo ADR

47.01% 52.99% 0.89

Cia Saneamento de Minas Gerais 24.04% 75.96% 0.32

CHILE Aguas Andinas SA A 27.60% 72.40% 0.38

CHINA

Sound Global Ltd 20.94% 79.06% 0.26

Tianjin Capital Environmental Protection Group Co Ltd H Shares

32.85% 67.15% 0.49

UNITED STATES

American States Water Co 35.99% 64.01% 0.56

American Water Works Co Inc 56.07% 43.65% 1.28

Aqua America Inc 34.76% 65.24% 0.53

Artesian Resources Corp A 48.44% 51.56% 0.94

California Water Services Group 39.92% 60.08% 0.66

Conn Water Service Inc 36.25% 63.54% 0.57

Consolidated Water Co (Cayman) 12.06% 87.93% 0.14

Middlesex Water Co 34.95% 64.29% 0.54

Pennichuck Corp 32.19% 67.81% 0.47

SJW Corp 37.99% 62.01% 0.61

York Water Co 27.96% 72.04% 0.39

PHILIPPINES Manila Water 36.38% 63.62% 0.57

FRANCE

Suez Environment AS 56.14% 43.86% 1.28

Veolia Environment 65.92% 34.08% 1.93

GREECE

Athens Water Supply & Sewage 28.34% 71.66% 0.40

Thessaloniki Water & Sewage 1.11% 98.89% 0.01

HONG KONG China Water Affairs Group Ltd. 40.16% 59.84% 0.67

ENGLAND Northumbrian Water Group 58.75% 41.25%

16

1.42

Pennon Group 54.29% 45.71% 1.19

Severn Trent 58.20% 41.80% 1.39

United Utilities Group Plc 58.09% 41.91% 1.39

ITALY

Acea Spa 63.05% 36.95% 1.71

Acegas SpA 67.86% 32.14% 2.11

MALAYSIA Puncak Niaga Holdings Bhd 85.38% 14.62% 5.84

SINGAPORE Sembcorp Industries 14.85% 85.15% 0.17

AVERAGE EXCLUDING SABESP 41.05% 58.90% 0.70

Source: Bloomberg

3.1 CONSISTENCY TEST

The methodology proposed by Sabesp reaches Debt/Equity ratio of 0.7. In order to evaluate

this result, Sabesp applied the model proposed by Damodaram8 to calculate the capital

structure that maximizes the company’s value. Results can be seen in graph 3 and shows that

the selection of capital structure of nearly 0.67 is more appropriate than a more aggressive

leverage of nearly 1.0.

8 Damodaran, A. – Corporate Finance: Theory and Practice – 2nd Ed. Wiley- 2.001

17

Graph 3: Capital structure which maximizes Sabesp’s value

4 COST OF EQUITY

4.1 GENERAL MODEL

Following the great majority of Brazil’s and world’s regulatory agencies, ARSESP proposes to

estimate the cost of equity of Sabesp through the CAPM (Capital Asset Pricing Model). More

specifically, ARSESP proposes the Solnik9 model also known as ICAPM (International Capital

Asset Pricing Model). Implicitly, the model presupposes that global risks influence the local

diversified portfolio, which in turn, influences local assets. Therefore, this is two-factor

model, different from traditional CAPM, which uses only one factor 10.

Reference material agrees that the inclusion of global factors tends to increase the

explanatory power of the model. Its adoption, however, requires attention, so that in view of

inclusion of new risk factors, no double counting occurs.

9 Solnik,B., “The International Pricing of Risk:An Empirical Investigation of the World Capital Market Structure”.

Journal of Finance, 1973. 10

SCHRAMM,R M;WANG,H. N. “Measuring the Cost of Capital in an International CAPM Framework”. Journal of

Applied Corporate Finance. V.12, n.3,Fall, 1999, p. 63-72.

STULZ, R. “On the effects of Barriers to International Investment”, Journal of Finance. V.36,p.923-934,1981 O’BRIEN, T.J. “The Global CAPM and a Firm’s Cost of Capital in Different Currencies”. Journal of Applied Corporate

Finance. V.12 n.3, Fall, 1999.

SABESP PROPOSAL

ARSESP PROPOSAL

5.0

5.2

5.4

5.6

5.8

6.0

6.2

6.4

6.6

6.8

7.0

7.2

7.4

0.00 0.11 0.25 0.43 0.67 1.00 1.50 2.33 4.00

VALOR DA SABESP

US$ BI LH ÕES

DEBT/EQUITY

18

The application of orthogonal model to the series ( time-series factor analysis model,

Software Eviews) shows that in this case study, no aggravation of risks occurs. According to

the graph below, there are three different risk factors groups which are not correlated:

� First Group: Inflation (INF) and Interest Rates (DRF);

� Second Group: Returns on portfolios and Sabesp stocks (BOV, SPX and SBSP3);

� Third Group: Sovereign risk (DEMBI).

Graph 4: Time Series Factor Analysis Model

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

-1.00 -0.75 -0.50 -0.25 0.00 0.25 0.50 0.75 1.00

DEMBI

DRF

INF

SBSP3

SPXBOV

Component 1 (47.4%)

Com

pone

nt 2

(18

.0%

)

Orthonormal Loadings

Source: prepared by Sabesp.

Therefore, although adjustments are necessary, Sabesp deems that the election of the model

proposed by ARSESP is appropriate.

4.2 CALCULATION OF BETAS

LE VE RAGE D GLOB AL BE TA

Where it was possible to assess, apparently, ARSESP applied the releverage methodology

both in local Beta and global Beta.

The Global Beta, by definition, is diversified, besides not being specifically calculated for a

company with a defined capital structure, but for all companies composing the respective

indexes. Therefore, the correct action would be to deleverage and releverage only the local

Beta, but not the Global Beta as it was made.

Contribution:

Apply releverage only in local Beta.

19

SOURCE OF DATA

The Technical Note informs that Betas were obtained from Bloomberg system. Nevertheless,

it was not possible to reproduce the unlevered Betas, mentioned in pages 5 and 6 of the text.

Below, the screens of Bloomberg for Sabesp Beta (0.810) and Ibovespa Beta (1.273),

respectively, according to the period and periodicity applied by ARSESP.

Graphs 5 and 6: Sabesp Beta and Ibovespa Beta according to the period and periodicity

applied by ARSESP

Source: Bloomberg

Proposals:

1. Do not apply leverage in Global Beta and use the Gross Beta and not the adjusted

Beta.

2. Use the single temporal window of data to calculate Betas and other series,

comprised between 2003 and 2011.

Bloomberg’s calculation of Betas results in 0.888 and 1.287 for Sabesp and Ibovespa,

respectively (graphs 7 and 8 below).

Graphs 7 and 8: Sabesp Beta and Ibovespa Beta according to the period and periodicity

suggested by Sabesp

20

Source: Bloomberg

Unlevered Sabesp Beta results in 0.56:

After releveraging, it results in 0.82:

Finally, the compound Beta will be 1.06:

Table 7: Sabesp Beta, Ibovespa Beta and unlevered Beta

SABESP Beta (SBS3 X IBOVESPA) 0.89

Brazil Beta (IBOVESPA x S&P500) 1.29

Unlevered Sabesp Beta 0.56

Re-leveraged Sabesp Beta 0.82

Compound Beta 1.06

4.3 EXCHANGE RISK IN THE COST OF EQUITY

The exchange risk premium clearly exists in Reais-denominated bills. Brazil’s long-term

treasury bills (NTNB-45) yield 5.83%11 in real terms against equivalent U.S. treasury bills12

11 TesouroDireto.com.br – NTN-B 45 – indexed to IPCA (Extended Consumer Price Index) – 3/10/2011

12 Economagic.com – Treasury inflation indexed bond-32 – February 2011

21

which yield 2% in real terms. The 3.83% difference mainly includes the country risk and the

exchange risk.

This assumption is based on the IRP theory (Interest Rate Parity) which defends that the

difference between interest rates should be explained by exchange risk, country risk and

convertibility risk.

In ARSESP’s Technical Note, Table 2: “effective cost of SABESP’s debt, the agency includes the

exchange devaluation of 3% when calculating the annual interest rates. Note 1 of the table

says: “Conversion given an expectation of Real devaluation of 3% in the long term vs. USD

and Yen.” Therefore, it is undeniable that the exchange risk exists inherent to Sabesp’s

operations incurred both in the cost of equity and cost of debt.

Proposal:

1. Explicit incorporation of exchange risk in CAPM models, both for calculating the cost

of equity and the cost of debt.

2. In the event the exchange risk is not included in the cost of capital model, an

inflation-adjustment index must be adopted to calculate the annual tariff

adjustments that incorporate the foreign currency volatility effects. Therefore, the

effects of this variation will be seen been in a later stage, but it will not be fully

neglected.

4.4 SUMMARY OF THE CALCULATION OF THE COST OF EQUITY

The table below summarizes the calculation suggested by Sabesp for the cost of equity, with

the adoption of a single temporal window for all series.

Table 8: Comparison of Cost of Equity ARSESP-SABESP

COST OF EQUITY

FORMULA TERMINOLOGY ARSESP

(A)

SABESP

(B)

(B)-(A)

(1) Risk-Free Global Rate 4.19% 3.99% -0.20%

(2) Market Global Return 9.97% 10.55% 0.58%

(3)=(2)-(1) Global Premium 5.78% 6.56% 0.78%

(4) Solnik Beta 1.28 1.06 0.22

(5)=(3)*(4) Global Risk Premium 7.40% 6.92% -0.48%

(6) Sovereign Risk 2.67% 3.74% 1.07%

(7) =(5)+(6) Nominal Cost of Equity 14.25% 14.64% 0.39%

Sources: Arsesp Technical Note and Sabesp Proposal

22

5 COST OF DEBT

5.1 GENERAL MODEL

Likewise the cost of equity, ARSESP suggests the methodology commonly applied in

regulated markets, pointing out Brazil’s electricity sector regulated by ANEEL (Brazilian

Electricity Regulatory Agency), and proposes to estimate Sabesp’s future cost of debt through

CAPM of debt.

Initially, it is essential to understand the scenario in which Sabesp is included. Compared to

the electricity sector, great challenges have to be equalized, as follows:

� The energy sector is in its 3rd Review, with reasonably steady rules. Sabesp is in its

first review, with rules still to be discussed and defined.

� The electricity sector relies on self-financing instruments embedded in tariffs for

investments in energy distribution for low-income consumers (for instance, the

program called “Programa Luz Para Todos” or Light for All Program). In production, it

relies on transfers of funds and gross financing from the federal government. The

sanitation sector does not rely on either of these two forms of financing on such

broad, comprehensive and prompt basis.

� The ownership in the energy sector is definite. In the sanitation sector, the discussion

has been extended for years and has no date to end. In addition, there is only one

owner in the energy sector, but in sanitation sector, we have hundreds of them (for

Sabesp). This fact adds great challenge when referring to a tariff reform.

� The exchange risk exposure in the electricity sector is much lower than Sabesp,

which, in view of demands for investments and reduced hedge deficiencies must

apply the foreign funding to finance part of investments.

In addition to the differences mentioned above, the company’s mission and its ongoing path

towards the universalization of sanitation services require a continued funding. Sometimes,

the bull and bear market cycles exceed the flexibility of the company in postponing or

anticipating its funding without compromising its continued investments.

A concrete example of this fact is the issue of debentures mentioned in ARSESP’s Technical

Note, mistakenly identified as 11th issue, but actually was the 9th issue. In the note, there is

an apparent mistake between efficiency and risk. In October 2008, during the peak of global

crisis, Sabesp raised funds that few companies were able to achieve at lowest cost as possible

during crisis. The rate paid reflected current credit risk and under no circumstance could be

mistaken with inefficiency (or mentioned as example of inefficiency). This funding ensured

significant continued investments made by the company in the last year, without making

23

contingency plans for investments to meet population’s needs. In 2008, Sabesp consolidated

a new level of investments of R$1.7 billion, the double of the amount invested in 2007.

Finally, if the particularities inherent to the sector mentioned above are safeguarded, the

application of the model proposed by the agency may result in amounts consistent with

reality. Therefore, Sabesp deems the model proposed is suitable.

5.2 INVESTMENT GRADE

It is reasonable and healthy that regulatory agencies seek higher efficiency from regulated

entities. Following this direction, ARSESP waives the line observed in its 2009 Technical Note

2009 – adoption of effective borrowing cost and proposes that pricing of debt cost is made

based on the spread of companies rated as BBB-13. Thus, an investment grade company is

adopted as parameter of efficiency, whose minimum theoretical limit is BBB-. Currently,

Sabesp is rated BB (speculative grade), two grades below the benchmark proposed by

ARSESP.

The evolvement of Sabesp’s rating has few grades of freedom. As publicly known, ratings are

defined by agency based on two axles, one of them considers the Business Risk Profile

(exogenous variable) and the other considers the Financial Risk Profile (endogenous

variable).

From the Business Risk Profile viewpoint, in the Basic Sanitation segment and Sabesp, we can

see few factors which mostly are not present in other highlighted countries.

� Recent regulation of the sector (2007) which has not undergone its first tariff review

yet, i.e., it bears uncertainty and future risk.

� The granting authority in major markets is unclear, besides the fragmentation of

granting authority between State and municipalities when compared to electricity

and telecommunications sectors, which are federal entities.

� The future singleness of regulated agents is undefined, in view of the real possibility

of Sabesp having to operate under more than one regulator.

� Condition as mixed-capital company, with public majority shareholder, whose

objectives and purposes may be contrary to other shareholders and creditors

(agency costs between public, private shareholders and creditors).

13 Apparently, the Technical Note contains a typing error, BBB+ instead of BBB-. On Page 9, ARSESP informs to have used the (RC) spread adopted by ANEEL. ANEEL applied the spread of companies rated by the global credit risk agency Moody’s Investors Services - Baa3. ARSESP, on its turn, adopted Standard & Poors rating BBB+. The single Brazilian company rated as BBB+ is VALE. Sabesp’s rating is four grades below BBB+. Moody's rating of Baa3, corresponds indeed to BBB- of S&P and not BBB+.

24

� Condition as mixed-capital company, with restriction to public credit (Central Bank

Resolution 2827 and restrictions imposed by NFSP – Public Sector Financing) and

private credit (Central Bank Resolution 2827), i.e., the liquidity risk in daily activities.

� Insufficient local funding compatible with characteristics of investments due to the

lack thereof or otherwise due to the rules already mentioned in previous item or

political allocation reasons in view of public politics directed by federal government.

� As a result of the issue mentioned above, vis-à-vis the demand for investments in

view of society’s requirements, as well as the condition as monopolistic company,

the solution is the company to raise funds abroad, thus, resulting in a currency

mismatch between revenues and debt and, accordingly, exchange risk.

Due to these reasons, among others, it does not seem correct to compare and distinguish

Sabesp’s rating from Brazil’s Energy Sector (which is in its 3rd Review, which bears an external

exposure of 3%, and with self-financing instruments embedded in tariffs for investments in

energy distribution for low-income consumers, which do neither pose uncertainties as to the

granting authority nor risk of diversity), or even sanitation sectors in USA, United Kingdom

and Colombia, among others.

Within this context, it is worth mentioning that current debt in foreign currency that must be

augmented by relevant loan agreements already executed with multilateral agencies, such as

IDB and JICA, it is not an option but a solution for the advance to the universalization

required by society. The alternative would be foreign funding in the local capital markets,

known as restricted in size and form and accordingly, with liquidity restrictions, reduced

terms and very high costs, condition that will result in a significant concentration of the

company's debt, with direct effects on the perception of liquidity and rating.

Funding in the foreign market has longer terms and lower costs, but followed by exchange

exposure risk, which are captured by rating agencies when assessing the company’s credit

risk.

Sabesp believes that the regulatory agencies’ role is to adopt assumptions leading the

company to improve its risk rating and obtain the investment grade. In this concern,

following the example of the British regulatory agency, the Brazilian regulatory agency should

register in its Technical Note the objective that has been analyzed in the regulated company's

risk rating.

The sanitation sector is not comparable to the electricity sector or pipeline gas in several

aspects, especially concerning credit and the stage of services universalization, notably the

sewage collection and treatment.

Due to the need of sources of financing for an investment plan ranged above one

billion/year, the risk of setting a very low rate for providers of capital is to constrain the

investment program whose highest objective is the universalization of sewage services.

25

Finally, it is interesting to note that ANEEL, in its Technical Note 262/2010, selected the best

rating of the sector’s companies as a goal to be achieved by them. The utilization of this same

criterion would lead to the adoption of BB rating, which is proposed herein by Sabesp for the

first cycle.

In fact, this would not mean to underestimate the company’s risk rating:

� The table of ARSESP’s Technical Note points out Moody’s ratings assigned in Brazil.

Sabesp is not rated by Moody‘s. Nevertheless, its rating would correspond to ‘Ba2’in

Moody’s scale, the highest one in Brazil in the Global scale for peer sanitation

companies.

� The positive statement mentioned above is also sustained when we verify that

ratings assigned to Águas de Guariroba and Prolagos are ratings in the National scale

(see attachments), where Sabesp currently is rated A+ by Fitch and AA- by S&P.

� In relation to the ratings of Colombian companies, apparently, these are highly

positive. Nevertheless, these are ratings in the National scale of that country (see

attachments), therefore, insignificant when establishing an objective rating selection

criterion for Sabesp.

Proposal:

As explained above, the evolvement of Sabesp’s rating to BBB- in the next tariff cycle is

unlikely. The improvement of Sabesp’s credit risk should be a gradual process, which also

involves ARSESP review of tariff. In this first tariff cycle, a rating compatible with current

Sabesp’s rating should be adopted, which is BB. In the next tariff cycle, a little bit more would

be required. Thus, a track of efficiency would be built in successive stages until reaching BBB-

.

5.3 EXCHANGE RISK IN THE COST OF DEBT

Sabesp’s actual cost of debt has been on average, approximately 5.5% p.a., over the past

years. Considering the level determined by ARSESP only 0.8 pp would lag to accommodate

eventual exchange/and or interest rates shocks.

The exposure in foreign currency of Sabesp was highly reduced over the past years, but, the

risk is still high. Through a principal component analysis (PCA), it was possible to divide the

risk factors incurred by Sabesp (position of September/2010) in its onerous liability. The table

below shows that, despite low currency exposure (20%), the currency factor risk is still

meaningful (97%).

26

Table 9: Risk Factors

FACTOR EXPOSURE RISK

US$ 12.02% 53.11%

YEN 6.99% 40.02%

EURO 0.32% 1.13%

CDI 25.69% 0.70%

TJLP 8.92% 0.05%

LIBOR 2.25% 0.48%

TR 34.07% 0.98%

BID 0.25% 0.00%

IGPM 5.99% 0.88%

IPCA 2.85% -0.02%

FRANC 0.65% 2.69%

TOTAL 100.00% 100.00%

Source: Sabesp Balance Sheet ITR 3Q 2010

Translator’s Note: CDI (Brazilian Overnight Interbank Deposit Rate), TJLP (long-term interest rate), TR (Reference Rate), IGPM

(General Market Price Index), IPCA (Extended Consumer Price Index)

It is worth mentioning that well grounded studies point to an exchange rate misalignment in

Brazil’s economy of approximately 7%14.

Proposal:

Incorporation of exchange risk, explicitly.

Alternatively, when calculating annual tariff adjustments, to establish an inflation-adjustment

index that captures the foreign currency variation effects. Therefore, the consequence of this

variation would be captured in a later stage, but it will not be fully neglected.

5.4 SUMMARY OF COST OF DEBT CALCULATION

Sabesp recalculated the cost of debt based on current risk rating, according to proposal in

grades to obtain BBB-. The proposal and main differences between values can be seen in

table 12.

14 CEMAP Letter nº 1, 09/09, FGV, SP.

27

Table 10: Comparison of Cost of Debt ARSESP-SABESP

COST OF DEBT

FORMULA TERMINOLOGY ARSESP

(A)

SABESP

(B)

(B)-(A)

(1) Risk-Free Global Rate 4.19% 3.99% -0.20%

(2) Sovereign Risk 2.67% 3.74% 1.07%

(3) Credit Global Risk 2.12% 3.78% 1.66%

(4) =(1)+(2)+(3) Nominal Cost of Debt 8.98% 11.51% 2.53%

The differences between the variables seen in the table above derive from the determination

of the temporal window and rating. The country risk and credit risk premiums calculated by

Sabesp are higher than ARSESP. The table below shows three rating levels and respective

spreads.

Table 11: Spread versus rating

S&P Rating SPREAD (%)

BB 3.78 BB+ 3.10 BBB- 2.20

Source: Bloomberg

28

6 RECOMMENDATIONS AND FINAL CALCULATION In the sections above, Sabesp made several theoretical and practical contributions. This final

section shows the calculation of the weighted average cost of capital following the reasoning

proposed by ARSESP and incorporating Sabesp proposal.

Table 13: WACC ARSESP-SABESP

WACC

FORMULA TERMINOLOGY ARSESP

(A)

SABESP

(B)

(B)-(A)

(1) Nominal Cost of Debt 8.98% 11.51% 2.53%

(2) Nominal Cost of Equity 14.25% 14.64% 0.39%

(3) % Optimum Debt 48.7% 41.3% -8.5%

(4) % Optimum Equity 50.3% 58.7% 8.5%

(5) Tax rates 34.0% 34.0% 0.0%

(6)=(1)*(3)*[1-(5)]+(2)*(4) Nominal WACC 10.3% 11.7% 1.4%

(7) Global Inflation 2.48% 2.40% -0.1%

(8)={[1+(6)]/[1+(7)]}-1 Actual WACC 7.67% 9.11% 1.4%

7 BIBLIOGRAPHY 1. Akaike, Hirotugu (1974). “A new look at the statistical model identification”. IEEE

Transactions on Automatic Control 19 (6): 716–723

2. Alexander, I., Mayer, C. and Weeds, H. 1996, “Regulatory Structure and Risk: An

International Comparison”, prepared for the World Bank.

3. Black, A., Fraser, P. & Power, D. 1992, “UK unit trust performance 1980–1989: A passive

time varying approach”, Journal of Banking and Finance, vol. 16 , pp. 1015–33.

4. Christopher A. Sims, 1980, “Macroeconomics and Reality”, Econometrica 48

5. Damodaran, A. – Corporate Finance: Theory and Practice – 2nd Ed. Wiley- 2.001

6. Naccache, Flavio F. 2011, “Transformação Cultural em Grandes Corporações:

Sustentabilidade, Regulação e Foco no Cliente”, capítulo 3 “Transição para uma Empresa

Regulada”, pp. 97-118.

7. O’Brien, T.J. “The Global CAPM and a Firm’s Cost of Capital in Different Currencies”.

Journal of Applied Corporate Finance. V.12 n.3, Fall, 1999.

8. Schramm, R M; Wang ,H. N. “Measuring the Cost of Capital in an International CAPM

Framework”. Journal of Applied Corporate Finance. V.12, n.3,Fall,1999,p. 63-72.

29

9. Stulz, R. “On the effects of Barriers to International Investment”, Journal of Finance. V.36,

1981, p.923-934

10. Wells, C. 1994, “Variable betas on the Stockholm exchange 1971–1989”, Applied

Economics, vol. 4 , pp. 75–92.

11. Technical Note n° rts/01/2011 – definition of methodology and calculation of the

weighted average cost of capital (WACC).

12. CEMAP Letter nº 1, 09/09, FGV, SP

13. Technical note ref. gas rtm-02-2009 – detailed methodology for the tariff review process

of pipeline gas concessionaires of the State of São Paulo – 3rd tariff cycle.

14. Technical note nº rtc/01/2009 – determination of the weighted average cost of capital for

Companhia de Gás de São Paulo – Comgás.

15. Technical note n° gbd/02/2009 – determination of the weighted average cost of capital

for Gás Brasiliano Distribuidora S.A.

16. Technical note n° gnsps/02/2010 - determination of the weighted average cost of capital

for Gás Natural são Paulo Sul S.A.

17. Technical note n° 005/2010 - SRE/ADASA – Partial results of the 1st Periodic Tariff Review

of water supply and sewage services rendered by CAESB – Attachment III Cost of Capital.

18. Technical note nº 262/2010-SRE/ANEEL– Methodology and criteria to define the

regulatory structure and cost of capital.

19. OFWAT COST OF CAPITAL AND FINANCEABILITY AT PR09.

20. OFWAT FUTURE WATER AND SEWERAGE CHARGES 2010-15

21. BLOOMBERG system.

22. MOODY’S INVESTORS SERVICES.

23. STANDARD & POORS.

Web sites:

24. https://www3.bcb.gov.br/sgspub/consultarvalores/consultarValoresSeries.do?method=c

onsultarValores

25. http://www.tesourodireto.com.br – NTN-B 45 – indexed to IPCA -3/10/2011

26. http://www. economagic.com – Treasury inflation indexed bond-32 – February 2011

27. DAMODARAM - http://pages.stern.nyu.edu/~adamodar/

28. http://www.coreconsp.org.br/indicadores/dip/new_series.../series/.../EMBI.xls

30

29. http://www.snetglobalwaterindexes.com

31

8 ATTACHMENTS

8.1 STOCHASTIC BETA

SOURCE: primary data – Bloomberg.

CALCULATIONS: Sabesp, through routine in “ox” language processed in the ssfpack software.

8.2 USA INFLATION

SOURCE: BACEN

8.3 RISK-FREE RATE AND MARKET PREMIUM - USA

SOURCE: BLOOMBERG

FUNCTION: CRP

INFLAÇÃO

PRÊMIO_EQUITY

32

8.4 GLOBAL AND LOCAL BETAS

SOURC: BLOOMBERG

FUNCTION: EQUITY BETA

8.5 CREDIT RISK

SOURCE: BLOOMBERG

FUNCTION CURVE – VARIABLE “C50730Y Index” for return on securities and “USGG30YR

Index” for treasury return.

8.6 COUNTRY RISK

SOURCE: CORECON/SP

www.coreconsp.org.br/indicadores/dip/new_series.../series/.../EMBI. xls

VARIABLE: EMBI+

8.7 BENCHMARK COMPANIES CAPITAL STRUCTURE

SOURCE: BLOOMBERG

FUNCTION: WACC

NOTES:

� Bloomberg makes a WACC estimate of companies enquired. This information was not

applied;

RISCO_PAÍS

33

� The correct action would be to adopt the average capital structure for the same

window of other data (2003 to 2011). However, not all data are available.

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50