SCAN ICT – FINAL REPORT

 

 

Section I

DEFINITIONS OF CONCEPTS AND ACRONYMS

In this section we will define the main concepts discussed in the SCAN framework. In some cases, this exercise must be regarded as an attempt to describe the personal perception and understanding of the project team members in respect to those concepts in the context of the work done on the ground, and not necessarily a scientific definition.

-ICT stands for Information and Communication Technology. This concept is generally used in relation to any computer-based processes in which information and content are developed, shared and transmitted over local, regional or international boundaries.

-ICT Environment describes the country-specific situation with regard to the status of the different elements that influence the development of ICT, such as the telecommunications infrastructure, the regulatory framework and the investment and tax policies.

-ICT Sector defines both the industry and the business structures of the ICT field.

-Teledensity is commonly defined as being the number of existing telephone lines per 100 inhabitants.

-Universal Access is a concept that was adopted to compensate the limitations of another important concept, Universal Service, which refers to the goal of "one telephone line per household". In practice most countries, especially in the less developed world, could not meet that goal and for them a different approach was adopted, where the goal was to ensure that all citizens could have access to a public phone at a reasonable distance from their homes. Generally, "reasonable distance" should mean "walking distance", but in some countries, especially in Africa, this may be up to 5km or more. Universal Access is therefore used to define the average distance or time needed to reach the nearest public phone.

IDRC International Development Research Centre

UNECA United Nations Economic Commission for Africa

TDM Telecommunications of Mozambique (Telecomunicações de Moçambique)

Mcel Mozambique Cellular (Moçambique Celular)

UEM Eduardo Mondlane University (Universidade Eduardo Mondlane)

CIUEM Informatics Centre of the Eduardo Mondlane University (Centro de Informatica da Universidade Eduardo Mondlane)

VSAT Very Small Aperture Terminal

ITU International Telecommunications Union

NGO Non-Governmental Organisation

INCM Instituto Nacional das Comunicações de Moçambique

IX Internet Exchange

ISP Internet Service Provider

CFM Railways of Mozambique (Caminhos de Ferro de Moçambique)

MOZAL Mozambique Aluminium Smelter

LAM Mozambique Airlines (Linhas Aéreas de Moçambique)

RM Radio of Mozambique (Rádio Moçambique)

TVM Television of Mozambique (Televisão de Moçambique)

INE National Institute of Statistics (Instituto Nacional de Estatística)

GDP Gross Domestic Product

FRELIMO Mozambique Liberation Front (Frente de Libertação de Moçambique)

INCM National Institute of Communications of Mozambique (Instituto Nacional das Comunicações de Moçambique)

ISDN Integrated Services Digital Network

DETECON Deutsche Telepost Consulting, GmbH

TMM Mobile Telecommunications of Mozambique (Telecomunicações Móveis de Moçambique)

RTK Klint Radio and Television (Rádio Televisão Klint)

PoPs Points of Presence

MICOA Ministry for Coordination of Environmental Affairs (Ministério para Coordenação da Acção Ambiental)

UNDP United Nations Development Program

MzDG Mozambique Development Gateway

CD-ROM Compact Disc Read Only Memory

RA Regulatory Authority

MICTI Mozambique Information and Communication Technology Institute

BSTM Standard Totta Bank of Mozambique (Banco Standard Totta de Moçambique)

BIM International Bank of Mozambique (Banco Internacional de Moçambique)

UNESCO United Nations Education Science and Culture Organisation

GDOI Global Digital Opportunity Initiative

CPRD Provincial Digital Resource Centre (Centro Provincial de Recursos Digitais)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Section II

BACKGROUND ON THE SCAN-ICT PROCESS

The SCAN ICT process is an initiative of IDRC and the United Nations Economic Commission for Africa (UNECA), and aims at undertaking a baseline study on ICT in African countries.

Mozambique was selected, together with five other countries (Morocco, Ghana, Senegal, Ethiopia and Uganda), to participate in the pilot phase of the project and the Eduardo Mondlane University Informatics Centre (CIUEM) is the collaborating institution.

The SCAN framework was launched during the first Scan-ICT workshop, held in Addis Ababa from 27 to 30 November 2000, with the participation of representatives from all the selected countries.


The pilot phase of the Mozambique SCAN Project covered the following priority areas:

Education,

Health,

Infrastructure,

Public Sector,

Private Sector and

E-Commerce.

 

PROJECT OBJECTIVES

The main goal of this project is to contribute to building ICT capacity and development in Mozambique and in the Region. Specifically SCAN ICT aims at the following objectives:

Collect and disseminate ICT related information in Mozambique

Create statistical databases containing national information, aimed at:

1. Providing useful and reliable information for the Government and other IT actors (funding agencies, private investors, NGO's, educational and research institutions);
2. Helping to promote coordinated and harmonized efforts in IT development;
3. Sharing existing knowledge, expertise and resources;
4. Facilitating the implementation of appropriate technologies in the country;
5. Providing useful information for regional collaboration and integration in IT;
6. Promoting effective use of national capacity; and
7. Creating public awareness about the importance of ICT for development.

ABOUT THE REPORT

This report presents the outcomes of the Mozambique baseline study carried out in the framework of the SCAN ICT initiative.

The report includes the following components:

-The Scan Methodology,

-Scan Country Profile/Baseline Data, and

-Scan Country Profile/Analysis.

The layout follows the outline suggested by the SCAN ICT framework for the study. The Scan country profile and baseline data are presented in a table format for maximum clarity. Most of the indicators are presented graphically (in tables and charts) and referred to as annexes for the analysis.

The Section on Methodology explains in detailed form, how the study was conducted, discusses the suggested framework in regard to the indicators and provides recommendations for further studies.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Section III

THE METHODOLOGY

A team consisting of a Project Supervisor, Project Co-ordinator and two Project Assistants had the responsibility for organising and co-ordinating the entire process including planning, monitoring, evaluating and reporting.

The project also contracted temporary staff for the survey, database design, data input and analysis, web design and translation of used bibliography and documents into English. This group mainly consisted of university students and some IT professionals.

Following the recommendations of the SCAN framework, the project team decided to use a combination of the following methodologies for this study:

Desk research,

Interviews, and

Questionnaires.

 

THE STRATEGY

Our strategy for the study included the following aspects:

a) Awareness Campaign

Having recognised that the success of the project would greatly benefit from the level of awareness and commitment of all stakeholders, we defined that one of the first priorities of the project was to organise a workshop aiming at creating awareness. All ministries, other public institutions and the private sector were invited to participate.

During the workshop the project objectives and the work plan were presented and discussed. The participants committed themselves to collaborate with the project team and act as focal points for SCAN within their institutions. Those belonging to the public sector even helped to identify focal points at provincial level.

About 50 people attended the workshop.

b) Piloting in Maputo

Given the size of the country and the complexity of the SCAN framework, we decided to pilot the process in Maputo City, before extending the activities to the rest of the territory. The objective was to test the validity of the working instruments and create confidence among the project team members.

In this process we interviewed mainly top-level managers from both the private sector and the public sector. In most cases, the interviews were extended to cover the local IT experts.

There are two reasons why we chose Maputo for piloting: firstly because almost all institutions listed for the SCAN study are based in the capital city, and secondly, because the UEM is also in Maputo, so there would be no extra logistical requirements.

For the pilot phase we selected institutions from the public and private sectors such as the Ministries of Education, Labour and Health, the National Telecommunications Company (TDM), the National Television (TVM), the National Broadcasting Company (RM), the Railway Company (CFM), Mozambique Airlines (LAM) and the Mozambique Aluminium Smelter Plant (MOZAL).

The results of the pilot study were decisive for the success of the following phases. Through the piloting process we were able, for instance, to detect the weaknesses of our questionnaires and sharpen them accordingly.

c) Working with Students

For the purpose of the study it was very important to select the right people to build the team for the fieldwork. We needed intelligent, enthusiastic and inexpensive people, and we thought that students would be the best choice. We therefore recruited about 30 students from our university and trained them on how to work with the questionnaires, in particular ensuring understanding of the meaning of each indicator and teaching how to go about the interviews. After the training, we selected 20 out of the 30 students and contracted them for the survey.

In addition to the students, we built a core team of 5 people, including both Project Assistants, to organise and co-ordinate the logistics, as well as to support the students in any other problems that might arise.

 

SURVEY COVERAGE

Due to time limitations, the study was only carried out in 10 provinces (out of 11), namely:

-Cabo Delgado,

-Nampula,

-Zambezia,

-Tete,

-Manica,

-Sofala,

-Inhambane,

-Gaza,

-Maputo, and

-Maputo City*

The province of Niassa, in the north of the country, could not be covered for lack of flights. In other words, we would have needed to keep the team there for at least two weeks, waiting for the next flight to return to Maputo.

In general the survey covered the provincial capitals, but 6 districts (Manhiça, Marracuene, Namaacha, Boane, Moamba and Ressano Garcia) were included in Maputo, and Nacala city in Nampula.

About 1500 people in 780 institutions were interviewed all over the country. Table 1 shows the distribution of interviewees by province. However, the list containing full personal details by sector is presented as an annex to this report.

For personal reasons some of the people who answered the questionnaire did so under conditions of anonymity. Thus the total numbers by province and by sector/institution may not necessarily always match the information in tables 1 and 2 below.

 

 

 

 

 

 

Distribution of interviewees by province (Summary)

Table 1

PROVINCE

Interviewees

Cabo Delgado

146

Nampula

220

Zambezia

65

Tete

62

Manica

10

Sofala

55

Inhambane

58

Gaza

322

Maputo

228

Maputo City*

302

Total

1468

(*) Maputo City has the status of a province.

 

Type and number of institutions (Summary)

Table 2

Type of Institution

Number of Institutions Visited

Education

134

Health

82

Public Sector

121

Private Sector

63

Total

400

Obviously, the number of interviewees and institutions visited differs from province to province according to the local environment and conditions. Maputo City, as the "host" of the project, is clearly far ahead in comparison, for instance, with Manica province.

Another important factor in the good results was the commitment and enthusiasm of the local people, who agreed to join the project teams (even with no payment of any kind), especially in Education. The provinces of Nampula and Gaza are good examples.

According to our initial planning and predictions, the project should have interviewed about 3000 people in about 1000 institutions. The main reasons for not reaching these targets were related to major time limitations for the fieldwork (only one month) and the fact that by the time the survey was conducted (August), most of the schools were closed for vacation. This situation obviously affected the results in education considerably.

The full lists of interviewees and institutions inquired are presented as annexes to this report. However, the number of respondents in the list is lower than the one indicated in the summary above, because some people only accepted to be interviewed under anonymity conditions.

 

 

 

 

 

 

 

THE QUESTIONNAIRES

Two different questionnaires were designed for each specific area, namely one for the institutions themselves and another for the individuals belonging to those institutions. It was important for us to separate the purely institutional information from the individual aspects, because our understanding was that the impact of ICT development in an organisation might affect staff members in differing ways.

Basically the questionnaires were designed in accordance with the SCAN framework, but in some cases the suggested indicators and/or the respective methods of measurement were not applicable for Mozambique. Another related problem was the lack of up to date information and statistical data about the country in general and the visited institutions in particular. This situation resulted in missing indicators in this report or the use of different indicators.

Samples of all the questionnaires used are presented as annexes to this report.

RECOMMENDATIONS ON THE METHODOLOGY

Based on the experience of the pilot phase, we would like to recommend the following measures on the methodology for the coming phases:

-Establishment of permanent focal points in each province, preferably at institutional level rather than individual to ensure the continuous character of the Scan process;

-Involve the National Institute for Statistics (INE) in the process in order to give the survey a mandatory character at least for the Government and public institutions, to increase the number of respondents and accuracy of data;

-Promote awareness among the groups to be interviewed to stimulate more participation. In this regard, the involvement of local authorities will be determinant, especially in the rural areas;

-Plan more time for the fieldwork to increase the coverage of the survey;

-Revise the questionnaires in order to create more realistic, suitable and measurable indicators and to include more area specific aspects rather than general;

 

 

 

 

 

 

 

 

 

 

 

 

 

Section IV

GENERAL COUNTRY PROFILE

This section is based mainly on desk research information. The tables presented below summarise the demographic, economic, political and cultural data of the country.

POPULATION

According to the National Statistics Institute (INE), Mozambique has a population estimated at around 18 million inhabitants

POPULATION GROWTH

The Population growth from 2001 to 2002 is estimated at 426,370, a rate of 2.3%.

POPULATION DISTRIBUTION BY GEOGRAPHICAL AREA

The table below shows the population distribution by province and region (North, Central and South).

Table 1

Region/Province

Total

NORTH

5,601,935

Niassa

870,544

Cabo Delgado

1,465,537

Nampula

3,265,854

CENTRAL

7,227,983

Zambézia

3,316,703

Tete

1,319,904

Manica

1,137,448

Sofala

1,453,928

SOUTH

4,412,322

Inhambane

1,256,139

Gaza

1,203,294

Maputo Province

933,951

Maputo

1,018,938

Grand Total

17,242,240

Source: National Human Development Report 2001, UNDP, Maputo

 

 

 

 

 

 

 

 

 

POPULATION DISTRIBUTION BY AGE

Table 2

AGE

Province

0

1-4

5-9

10-14

15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

55-59

60-64

65-69

70-74

75-79

80+

Niassa

35416

121710

141874

116879

84889

74344

67444

54993

42790

34127

26830

21221

16249

12152

8601

5476

2924

2625

Cabo Delgado

53451

175927

214030

188882

138549

127670

122186

102684

81188

65910

52770

43102

34337

26119

18511

11478

5450

3293

Nampula

126945

428091

510820

425133

314156

283482

264234

216775

169365

136697

108305

86294

67011

50609

35953

22560

11375

8049

Zambézia

141333

468616

517504

404928

335419

290937

270415

222030

170093

134188

103792

81175

61452

45804

32161

19941

9759

7156

Tete

55570

189130

213894

179017

127053

110919

101390

81243

60762

49062

39625

31673

24833

19703

14983

9962

5674

5411

Manica

47209

160796

170468

150385

118460

103589

91509

72192

53928

42909

33893

26908

21073

15982

11566

7648

4339

4594

Sofala

55673

191165

211595

178880

151313

136067

122401

97855

75310

61831

49626

37767

27775

20927

15244

9722

5283

5494

Inhamb.

47915

163298

164150

159943

139148

111910

88251

70690

54675

47622

43196

39320

35574

30987

25547

17422

9346

7145

Gaza

42660

150187

159295

159062

142553

111641

83019

66547

52600

45827

41406

36028

31059

26651

21955

15367

8900

8537

Maputo Prov.

31214

108019

119899

118343

109943

96255

74915

59161

48350

39234

31134

25502

21153

17311

13919

9621

5256

4722

Maputo city

33618

115972

118634

125716

128355

116399

92870

72432

58584

47017

35074

25092

17194

12587

9046

4996

2587

2765

Source: National Human Development Report 2001, UNDP, Maputo

EDUCATIONAL LEVELS

Table 3

Level of Education

 Category

Percentage

Adult Education

1.5

Primary

86.4

Secondary

9.1

Technical

1.7

Higher

0.7

Other

0.6

Total

100.0

Source: http://www.ine.gov.mz

 

ECONOMY

The political stability in the country is certainly one of the most decisive factors in its economic success. With a double digit growth rate before the floods in 2000, Mozambique was considered one of the countries with the fastest economic growth in the world. The economic growth trends continued after the floods, but the country will need some time to reestablish its previous levels of development.

To illustrate the statement above, some of the most import indicators are presented in this section. In some cases, updated data were not available, thus we used the most recent, we could find.

BALANCE OF PAYMENTS

Mozambique Balance of Payments (in USD millions)

2002-03-31

Table 4

2002Q1

Prov.

I. Current Account

-135.9

A. Goods and services

-177.6

1. Goods

-112.5

1.1. Exports (FOB)

152.5

1.1.1. Of which: Large Projects

115.0

1.2. Imports (FOB)

-265.0

1.2.1. Of which: Large Projects

-68.5

2. Services

-65.1

2.1. Transportation

-33.8

2.1.1. Credit

17.7

2.1.2. Debit

-51.5

2.2. Travel

-13.0

2.2.1. Credit

9.9

2.2.2. Debit

-22.9

2.3. Communications services

-0.1

2.3.1. Credit

0.1

2.3.2. Debit

-0.2

2.4. Construction services

-17.7

2.4.1. Credit

1.9

2.4.2. Debit

-19.7

2.5. Insurance services

-3.2

2.5.1. Credit

0.0

2.5.2. Debit

-3.2

2.6. Financial services

0.3

2.6.1. Credit

1.0

2.6.2. Debit

-0.7

2.7. Computer and information services

0.0

2.7.1. Credit

0.0

2.7.2. Debit

0.0

2.8. Royalties and license fees

0.0

2.8.1. Credit

0.0

2.8.2. Debit

0.0

2.9. Government services (n.i.e.)

0.9

2.9.1. Credit

2.3

2.9.2. Debit

-1.4

2.10.Other services

1.5

2.10.1. Credit

22.3

2.10.2. Debit

-20.8

B. Income

-49.2

3. Compensation of employees

-21.3

3.1.1. Credit

7.1

3.1.2. Debit

-28.4

4. Direct Investment

0.0

4.1.1. Credit

0.0

4.1.2. Debit

0.0

5. Portfolio Investment

0.0

5.1.1. Credit

0.0

5.1.2. Debit

0.0

6. Other Investment

-27.9

6.1. Interest on public sector external debt

-30.3

6.2. Interest on private sector external debt

-0.5

6.3. Interest on deposits abroad

3.4

6.4. Other interest

-0.5

C. Current transfers

91.0

7. General government

82.1

8. Other sectors

8.9

8.1. Worker's remittances

2.0

8.2. Other transfers

6.9

II. Capital and Financial Account

126.2

D. Capital account

45.9

9. General government

45.9

9.1. Debt forgiveness

0.0

9.2. Other (grants for investment)

45.9

10. Other sectors

0.0

10.1. Migrant's transfers

0.0

10.2. Other transfers

0.0

E. Financial Account

80.3

11. Direct investment abroad

0.0

12. Direct investment in reporting economy

43.3

13. Portfolio investment

0.0

14. Other investment - Assets

31.2

14.1. Trade credits

0.0

14.2. Loans

0.0

14.3. Currency and deposits

31.2

a. Monetary authorities

0.0

b. General government

0.0

c. Banks

31.2

d. Other sectors

0.0

14.4. Other Assets

0.0

a. Monetary authorities

0.0

b. General government

0.0

c. Banks

0.0

d. Other sectors

0.0

15. Other investment - Liabilities

5.8

15.1. Trade credits

-4.6

a. Other sectors

-4.6

15.2. Loans

50.5

a. Monetary authorities

0.0

b. General government

-55.3

Drawing on new loans

18.2

Repayments

-73.5

c. Banks

0.0

d. Other sectors

105.8

15.3. Currency and deposits

-39.5

a. Monetary authorities

0.0

b. Banks

-39.5

15.4. Other liabilities

-0.7

a. Monetary authorities

-0.7

b. General government

0.0

c. Banks

0.0

d. Other sectors

0.0

F. Financing

70.5

16. Reserve assets

-14.8

16.1. Monetary gold

0.3

16.2. Special drawing rights

0.5

16.3. Reserve position in the Fund

8.9

16.4. Foreign exchange

-12.0

a. Currency and deposits

-12.0

b. Securities

0.0

16.5. Other assets

-12.6

17. Use of IMF credit

-13.5

18. Exceptional financing transactions

98.8

III. Net Errors and Omissions

-60.8

Source: Banco de Moçambique

 

GROSS DOMESTIC PRODUCT - EXPENDITURE ON GDP - GROWTH RATE

2001-12-31

Table 5

Type of Expenditure

2001

Overall Demand

9.3

Domestic Demand

2.5

Total Consumption

6.4

Private Consumption

5.2

Government Consumption

15.2

Gross Capital Formation

-8.6

Exports of Goods and Services

68.2

Imports of Goods and Services

-3.2

GROSS DOMESTIC PRODUCT (mp)

13.8

Source: Banco de Moçambique

 

GDP BY SECTORAL DISTRIBUTION

Mozambique’s Gross Domestic Product (GDP) Percentage structure, 1999

Table 6

GDP

Niassa

C. Delg.

Namp.

Zamb.

Tete

Manica

Sofala

I´bane

Gaza

Map. Prov.

Map. City

Total

Agriculture

48.1

52.4

52.8

55.4

25.7

34.1

15.5

34.2

26.5

13.9

1.0

24.6

Livestock

0.8

5.6

2.2

1.5

3.2

1.6

2.1

3.0

6.1

1.9

0.2

1.8

Forestry

4.6

5.2

3.1

6.5

4.1

5.3

3.1

3.2

3.3

2.6

0.5

2.8

Fisheries

0.4

1.9

2.7

3.1

1.3

0

2.1

2.8

2.9

2.4

3.4

2.6

Mining

0.3

1.9

0.1

0.2

0.1

0.2

0.1

0.1

0.1

1.7

0

0.3

Manufacturing industry

6.2

2.6

6.4

7.9

6.4

12.8

9.4

3.7

3.3

12.6

18.4

11.3

Electricity and water

0.7

0.7

1.3

0.8

1.3

3.2

2.1

0.6

1.7

0.5

4.6

2.5

Construction

4.4

1.2

0.7

0.8

4.1

2.8

3.6

2.8

5.9

23.1

20.1

9.6

Transport and communications

4.6

6.5

5.7

2.6

7.4

8.1

13.5

7.8

9.8

14.5

11.5

9.2

Commerce

14.1

12.2

13.5

9.9

24.1

17.9

29.8

24.6

21.7

15.3

30.2

22.5

Restaurants and hotels

0.6

0.2

0.1

0.4

0.8

0.3

0.3

0.2

0.2

0.1

1.9

0.9

Public admin. and defence services

5.3

3.9

2.1

3.1

3.9

3.0

2.5

3.3

3.8

3.6

0.9

2.3

Financial and insurance services

1.3

1.0

1.4

1.3

2.3

1.2

3.7

1.6

1.9

1.1

3.5

2.4

Real estate, renting and business activities

3.0

2.9

3.3

2.4

2.9

3.7

4.3

4.5

4.7

1.9

1.9

2.9

Education services

2.4

1.8

1.5

2.7

2.3

1.5

0.9

2.4

2.7

2.4

0.5

1.4

Health services

0.6

0.4

0.4

0.5

0.7

0.6

0.5

0.8

0.9

0.6

0.3

0.5

Other services

1.7

-1.1

1.8

0

8.5

2.6

5.5

3.5

3.6

0.9

0.3

1.8

Adjustment by customs duties and SIFIM

0.9

0.9

0.9

0.9

0.9

0.9

0.9

0.9

0.9

0.9

0.9

0.9

Source: National Human Resources Development 2001

UNEMPLOYMENT RATE

Table 6

 

Rural

Urban

Total Mozambique

 

Absolutely poor

Poor

Non poor

All

Absolutely poor

Poor

Non poor

All

Absolutely poor

Poor

Non poor

All

Unemployed

0.2

0.3

0.3

0.3

1.2

1.2

1.4

1.3

0.4

0.4

0.6

0.5

Error

(0.06)

(0.05)

(0.08)

(0.04)

(0.33)

(0.23)

(0.38)

(0.2)

(0.07)

(0.06)

(0.12)

(0.05)

Note: The errors standardised in brackets have been corrected to give uniformity to the survey.

Source: National Human Development Report 2001

INFLATION

Consumer Price Index

Table 7

1998=100

 

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

General Index a)

1995

52.9

52.5

54.1

55.6

57.2

59.3

62.2

63.4

65.4

69.8

73.6

79.7

 

1996

83.1

90.3

92.7

93.5

91.1

92.4

92.9

93.5

93.6

93.9

95.2

95.1

 

1997

98.3

100.4

100.2

99.4

98

98.1

97.9

98.7

98.3

98.9

99.7

101

 

1998

102.4

104.1

103.2

102.2

101.7

100.4

99.1

98.8

98

97.7

98.9

100

 

1999

102.7

105

103.9

104.7

104.1

103.8

103.4

102.7

102.4

101.2

100.9

106.2

 

2000

105.8

113.9

116.5

118.4

119.3

117.8

118.6

117.2

118

118.2

116.8

118.4

 

2001

117.2

116.9

117.7

119

121.8

124.4

127.4

129.6

130.9

135.9

140.4

144.3

 

2002

144.1

146

145

145.4

145.6

147.1

148.6

149.4

149.6

150.2

153

157.5

Monthly growth rate b)

 

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep