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 OrganisationGDOI Global Digital Opportunity Initiative
CPRD Provincial Digital Resource Centre (Centro Provincial de Recursos Digitais)
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.
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.
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
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.
Our strategy for the study included the following aspects:
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.
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.
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.
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.
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;
This section is based mainly on desk research information. The tables presented below summarise the demographic, economic, political and cultural data of the country.
According to the National Statistics Institute (INE), Mozambique has a population estimated at around 18 million inhabitants
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, MaputoEDUCATIONAL LEVELS
|
Table 3 |
|
|
Level of Education |
|
|
Category |
Percentage |
|
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
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.
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
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|
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
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 |
|||