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Final Statistical Abstract:
Timor-Leste Survey of Living Standards 2007
Direcção Nacional de Estatística Ministério de Finanças
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Published in July 2008 Direcção Nacional de Estatística Ministério de Finanças Timor-Leste Ph: +670 333 9527 dne.mopf.gov.tl Front cover design by DNE Research Core Team Printed by: Gráfica Nacional, Dili, Timor-Leste
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Timor-Leste Survey of Living Standards 2007
Table of contents
Foreword x Preface 1 Acknowledgments 3 Introduction 5 1. Demographics
1.a. Concepts and Definitions 15 1.b. Tables: Demographics 16
2. Housing
2.a. Concepts and Definitions 41 2.b. Tables: Housing 42
3. Access to Facilities
3.a. Concepts and Definitions 51 3.b. Tables: Access to Facilities 52
4. Durable Goods
4.a. Concepts and Definitions 59 4.b. Tables: Durable Goods 60
5. Education
5.a. Concepts and Definitions 63 5.b. Tables: Education 65
6. Health
6.a. Concepts and Definitions 107 6.b. Tables: Health 109
7. Employment
7.a. Concepts and Definitions 196 7.b. Tables: Employment 197
8. Social Capital
8.a. Concepts and Definitions 223 8.b. Tables: Social Capital 224
9. Subjective Well Being
9.a. Concepts and Definitions 231 9.b. Tables: Subjective Well Being 232
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Tables Demographics
Table 1.1 Population structure by rural and urban areas and regions, according to gender and age groups
16
Table 1.2 Population structure by regional rural and urban areas, according to gender and age groups
17
Table 1.3 Population structure by district, according to gender and age groups 18
Table 1.4 Mother tongue by rural and urban areas and regions, according to gender 19
Table 1.5 Mother tongue by regional rural and urban areas, according to gender 20
Table 1.6 Mother tongue by district, according to gender 21
Table 1.7 Main languages spoken by rural and urban areas and regions, according to gender 22
Table 1.8 Main languages spoken by regional rural and urban areas, according to gender 23
Table 1.9 Main languages spoken by district, according to gender 24
Table 1.10 Marital status by rural and urban areas and regions, according to gender 25
Table 1.11 Marital status by regional rural and urban areas, according to gender 26
Table 1.12 Marital status by district, according to gender 27
Table 1.13 Main occupation by rural and urban areas and regions, according to gender 28
Table 1.14 Main occupation by regional rural and urban areas, according to gender 29
Table 1.15 Main occupation by district, according to gender 30
Table 1.16 Place of birth by rural and urban areas and regions, according to gender 31
Table 1.17 Place of birth by regional rural and urban areas, according to gender 32
Table 1.18 Place of birth by district, according to gender 33
Table 1.19 Prevalence of orphans by rural and urban areas and regions, according to gender 34
Table 1.20 Prevalence of orphans by regional rural and urban areas, according to gender 35
Table 1.21 Prevalence of orphans by district, according to gender 36
Table 1.22 Living arrangements of children by rural and urban areas and regions, according to gender
37
Table 1.23 Living arrangements of children by regional rural and urban areas, according to gender 38
Table 1.24 Living arrangements of children by district, according to gender 39
Table 1.25 Population away from the household for more than one month in the last year by rural and urban areas and regions
40
Housing
Table 2.1 Main characteristics of the dwelling by rural and urban areas and regions 42
Table 2.2 Main characteristics of the dwelling by regional rural and urban areas 43
Table 2.3 Main characteristics of the dwelling by district 44
Table 2.4 Main infrastructure services of the dwelling by rural and urban areas and regions 45
Table 2.5 Main infrastructure services of the dwelling by regional rural and urban areas 46
Table 2.6 Main infrastructure services of the dwelling by district 47
Table 2.7 Ownership status of the dwelling by rural and urban areas and regions 48
Table 2.8 Ownership status of the dwelling by regional rural and urban areas 49
Table 2.9 Ownership status of the dwelling by district 50
Access to Facilities
Table 3.1 Access to facilities by rural and urban areas and regions 52
Table 3.2 Access to facilities by regional rural and urban areas 53
Table 3.3 Access to facilities by district 54
Table 3.4 Access to roads by rural and urban areas and regions 55
Table 3.5 Access to roads by regional rural and urban areas 56
Table 3.6 Access to roads by district 57
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Durable Goods
Table 4.1 Ownership of durable goods by rural and urban areas and regions 60
Table 4.2 Ownership of durable goods by regional rural and urban areas 61
Table 4.3 Ownership of durable goods by district 62
Education
Table 5.1 Highest educational attainment of the adult population by rural and urban areas and regions, according to gender
65
Table 5.2 Highest educational attainment of the adult population by regional rural and urban areas, according to gender
66
Table 5.3 Highest educational attainment of the adult population by district, according to gender 67
Table 5.4 Highest educational attainment of the youth by rural and urban areas and regions, according to gender
68
Table 5.5 Highest educational attainment of the youth by regional rural and urban areas, according to gender
69
Table 5.6 Highest educational attainment of the youth by district, according to gender 70
Table 5.7 Completion rates of primary, pre secondary and secondary by rural and urban areas and regions, according to gender
71
Table 5.8 Completion rates of primary, pre secondary and secondary by regional rural and urban areas, according to gender
72
Table 5.9 Completion rates of primary, pre secondary and secondary by district, according to gender
73
Table 5.10 Ability to read and write a letter among the adult population by rural and urban areas and regions, according to gender
74
Table 5.11 Ability to read and write a letter among the adult population by regional rural and urban areas, according to gender
75
Table 5.12 Ability to read and write a letter among the adult population by district, according to gender
76
Table 5.13 Enrolment rates for academic year 2004/05 by rural and urban areas and regions, according to gender
77
Table 5.14 Enrolment rates for academic year 2004/05 by regional rural and urban areas, according to gender
78
Table 5.15 Enrolment rates for academic year 2004/05 by district, according to gender 79
Table 5.16 School participation for academic year 2004/05 by rural and urban areas and regions, according to gender
80
Table 5.17 School participation for academic year 2004/05 by regional rural and urban areas, according to gender
81
Table 5.18 School participation for academic year 2004/05 by district, according to gender 82
Table 5.19 Profile of students that attended the 2004/05 academic year by rural and urban areas and regions, according to gender
83
Table 5.20 Profile of students that attended the 2004/05 academic year by regional rural and urban areas, according to gender
84
Table 5.21 Profile of students that attended the 2004/05 academic year by district, according to gender
85
Table 5.22 Population that never attended school by rural and urban areas and regions, according to gender and age groups
86
Table 5.23 Population that never attended school by regional rural and urban areas, according to gender and age groups
87
Table 5.24 Population that never attended school by district, according to gender and age groups 88
Table 5.25 Reasons why never attended school by rural and urban areas and regions, according to gender
89
Table 5.26 Reasons why never attended school by regional rural and urban areas, according to gender
90
Table 5.27 Reasons why never attended school by district, according to gender 91
Table 5.28 Reasons why never attended school among the youth by rural and urban areas and regions, according to gender
92
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Table 5.29 Reasons why never attended school among the youth by regional rural and urban areas, according to gender
93
Table 5.30 Reasons why never attended school among the youth by district, according to gender 94
Table 5.31 Enrolment rates for academic year 2006/07 by rural and urban areas and regions, according to gender
95
Table 5.32 Enrolment rates for academic year 2006/07 by regional rural and urban areas, according to gender
96
Table 5.33 Enrolment rates for academic year 2006/07 by district, according to gender 97
Table 5.34 School participation for academic year 2006/07 by rural and urban areas and regions, according to gender
98
Table 5.35 School participation for academic year 2006/07 by regional rural and urban areas, according to gender
99
Table 5.36 School participation for academic year 2006/07 by district, according to gender 100
Table 5.37 Distribution of students in academic year 2006/07 by rural and urban areas and regions, according to level of schooling and gender
101
Table 5.38 Distribution of students in academic year 2006/07 by regional rural and urban areas, according to level of schooling and gender
102
Table 5.39 Distribution of students in academic year 2006/07 by district, according to level of schooling and gender
103
Table 5.40 Distribution of out‐of‐school population in academic year 2006/07 by rural and urban areas and regions, by gender and age groups
104
Table 5.41 Distribution of out‐of‐school population in academic year 2006/07 by regional rural and urban areas, by gender and age groups
105
Table 5.42 Distribution of out‐of‐school population in academic year 2006/07 by district by gender and age groups
106
Health
Table 6.1 Use and treatment of mosquito nets by rural and urban areas and regions, according to age groups
109
Table 6.2 Use and treatment of mosquito nets by regional rural and urban areas, according to age groups
110
Table 6.3 Use and treatment of mosquito nets by district, according to age groups 111
Table 6.4 Population reporting health complaints in the last month by rural and urban areas and regions
112
Table 6.5 Population reporting health complaints in the last month by regional rural and urban areas
113
Table 6.6 Population reporting health complaints in the last month by district 114
Table 6.7 Population visiting a health care provider or facility in the last month by rural and urban areas and regions
115
Table 6.8 Population visiting a health care provider or facility in the last month by regional rural and urban areas
116
Table 6.9 Population visiting a health care provider or facility in the last month by district 117
Table 6.10 Population buying medicines without prescription in the last month by rural and urban areas and regions, according to gender
118
Table 6.11 Population buying medicines without prescription in the last month by regional rural and urban areas, according to gender
119
Table 6.12 Population buying medicines without prescription in the last month by district, according to gender
120
Table 6.13 Population hospitalized in the last 12 months by rural and urban areas and regions 121
Table 6.14 Population hospitalized in the last 12 months by regional rural and urban areas 122
Table 6.15 Population hospitalized in the last 12 months by district 123
Table 6.16 Immunization against BCG by rural and urban areas and regions, according to age groups
124
Table 6.17 Immunization against BCG by regional rural and urban areas, according to age groups 125
Table 6.18 Immunization against BCG by district, according to age groups 126
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Table 6.19 Immunization against Polio by rural and urban areas and regions, according to age groups
127
Table 6.20 Immunization against Polio by regional rural and urban areas, according to age groups 129
Table 6.21 Immunization against Polio by district, according to age groups 131
Table 6.22 Immunization against DPT by rural and urban areas and regions, according to age groups
133
Table 6.23 Immunization against DPT by regional rural and urban areas, according to age groups 135
Table 6.24 Immunization against DPT by district, according to age groups 137
Table 6.25 Immunization against measles by rural and urban areas and regions, according to age groups
139
Table 6.26 Immunization against measles by regional rural and urban areas, according to age groups
140
Table 6.27 Immunization against measles by district, according to age groups 141
Table 6.28 Full immunization by rural and urban areas and regions, according to age groups 142
Table 6.29 Full immunization by regional rural and urban areas, according to age groups 143
Table 6.30 Full immunization by district, according to age groups 144
Table 6.31 Vitamin A supplementation given to children by rural and urban areas and regions, according to gender and age groups
145
Table 6.32 Vitamin A supplementation given to children by regional rural and urban areas, according to gender and age groups
146
Table 6.33 Vitamin A supplementation given to children by district, according to gender and age 147
Table 6.34 Prevalence of diarrhea in the last 30 days by rural and urban areas and regions, according to gender
148
Table 6.35 Prevalence of diarrhea in the last 30 days by regional rural and urban areas, according to gender
149
Table 6.36 Prevalence of diarrhea in the last 30 days by district, according to gender 150
Table 6.37 Prevalence of malaria or fever in the last 30 days by rural and urban areas and regions, according to gender
151
Table 6.38 Prevalence of malaria or fever in the last 30 days by regional rural and urban areas, according to gender
152
Table 6.39 Prevalence of malaria or fever in the last 30 days by district, according to gender 153
Table 6.40 Use of health care providers in the last 12 months by rural and urban areas and regions 154
Table 6.41 Use of health care providers in the last 12 months by regional rural and urban areas 156
Table 6.42 Use of health care providers in the last 12 months by district 158
Table 6.43 Fertility, antenatal care and assisted deliveries by rural and urban areas and regions 160
Table 6.44 Fertility, antenatal care and assisted deliveries by regional rural and urban areas 161
Table 6.45 Fertility, antenatal care and assisted deliveries by district 162
Table 6.46 Immunization against tetanus toxoid by rural and urban areas and regions 163
Table 6.47 Immunization against tetanus toxoid by regional rural and urban areas 164
Table 6.48 Immunization against tetanus toxoid by district 165
Table 6.49 Birth registration of children by rural and urban areas and regions 166
Table 6.50 Birth registration of children by regional rural and urban areas 167
Table 6.51 Birth registration of children by district 168
Table 6.52 Contraceptive prevalence by rural and urban areas and regions 169
Table 6.53 Contraceptive prevalence by regional rural and urban areas 170
Table 6.54 Contraceptive prevalence by district 171
Table 6.55 Knowledge about AIDS by rural and urban areas and regions 172
Table 6.56 Knowledge about AIDS by regional rural and urban areas 174
Table 6.57 Knowledge about AIDS by district 176
Table 6.58 Knowledge about AIDS among the youth by rural and urban areas and regions 178
Table 6.59 Knowledge about AIDS among the youth by regional rural and urban areas 180
Table 6.60 Knowledge about AIDS among the youth by district 182
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Table 6.61 Weight‐for‐age anthropometric indicators by rural and urban areas and regions, according to gender
184
Table 6.62 Weight‐for‐age anthropometric indicators by regional rural and urban areas, according to gender
185
Table 6.63 Weight‐for‐age anthropometric indicators by district, according to gender 186
Table 6.64 Height‐for‐age anthropometric indicators by rural and urban areas and regions, according to gender
187
Table 6.65 Height‐for‐age anthropometric indicators by regional rural and urban areas, according to gender
188
Table 6.66 Height‐for‐age anthropometric indicators by district, according to gender 189
Table 6.67 Weight‐for‐height anthropometric indicators by rural and urban areas and regions, according to gender
190
Table 6.68 Weight‐for‐height anthropometric indicators by regional rural and urban areas, according to gender
191
Table 6.69 Weight‐for‐height anthropometric indicators by district, according to gender 192
Table 6.70 Iodized salt consumption in the household by rural and urban areas and regions 193
Table 6.71 Iodized salt consumption in the household by regional rural and urban areas 194
Table 6.72 Iodized salt consumption in the household by district 195
Employment
Table 7.1 Labor force participation in the last 7 days by rural and urban areas and regions, according to gender and age groups
197
Table 7.2 Labor force participation in the last 7 days by regional rural and urban areas, according to gender and age groups
198
Table 7.3 Labor force participation in the last 7 days by district, according to gender and age groups
199
Table 7.4 Unemployment rate in the last 7 days by rural and urban areas and regions, according to gender and age groups
200
Table 7.5 Unemployment rate in the last 7 days by regional rural and urban areas, according to gender and age groups
201
Table 7.6 Unemployment rate in the last 7 days by district, according to gender and age groups 202
Table 7.7 Hours worked in all jobs in the last 7 days by rural and urban areas and regions, according to gender and type of job
203
Table 7.8 Hours worked in all jobs in the last 7 days by regional rural and urban areas, according to gender and type of job
204
Table 7.9 Hours worked in all jobs in the last 7 days by district, according to gender and type of job
205
Table 7.10 Industry of main job in the last 7 days by rural and urban areas and regions, according to gender
206
Table 7.11 Industry of main job in the last 7 days by regional rural and urban areas, according to gender
207
Table 7.12 Industry of main job in the last 7 days by district, according to gender 208
Table 7.13 Profile of wage employees by rural and urban areas and regions, according to gender 209
Table 7.14 Profile of wage employees by regional rural and urban areas, according to gender211
Table 7.15 Profile of wage employees by district, according to gender 213
Table 7.16 Use of time by rural and urban areas and regions, according to gender 215
Table 7.17 Use of time by regional rural and urban areas, according to gender 217
Table 7.18 Use of time by district, according to gender 219
Table 7.19 Use of time by age groups, according to gender 220
Employment
Table 8.1 Participation in community groups by rural and urban areas and regions 224
Table 8.2 Participation in community groups by regional rural and urban areas 226
Table 8.3 Participation in community groups by district 228
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Subjective well‐being
Table 9.1 Subjective adequacy of basic needs during the last month by rural and urban areas and regions
232
Table 9.2 Subjective adequacy of basic needs during the last month by regional rural and urban areas
233
Table 9.3 Subjective adequacy of basic needs during the last month by district 234
Table 9.4 Subjective adequacy of household income during the last month by rural and urban areas and regions
235
Table 9.5 Subjective adequacy of household income during the last month by regional rural and urban areas
236
Table 9.6 Subjective adequacy of household income during the last month by district 237
Table 9.7 Subjetive assessment of changes in well‐being since 2001 by rural and urban areas and regions
238
Table 9.8 Subjective assessment of changes in well‐being since 2001 by regional rural and urban areas
239
Table 9.9 Subjective assessment of changes in well‐being since 2001 by district 240
Table 9.10 Food security during the last 12 months by rural and urban areas and regions 241
Table 9.11 Food security during the last 12 months by regional rural and urban areas 242
Table 9.12 Food security during the last 12 months by district 243
Table 9.13 Strategies to cope with the shortage of food during the last 12 months by rural and urban areas and regions
244
Table 9.14 Strategies to cope with the shortage of food during the last 12 months by regional rural and urban areas
245
Table 9.15 Strategies to cope with the shortage of food during the last 12 months by district 246
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Foreword
Statistics can be a pow-erful tool for decision-makers at every level of society. They allow for evidence based planning and evaluation.
Today Timor-Leste is able to make use of high level, credible and up to date statistics provided
by the Direccao Nacional de Estatistica from the Ministry of Finance, through its latest publication, the Timor-Leste Survey of Living Standards 2007.
Over the last few months the current government has been implementing a set of national priorities covering:
1. Public Safety and Security 2. Social Protection and Solidarity 3. Addressing the Needs of Youth 4. Employment and Income Generation 5. Improving Social Service Delivery 6. Clean and Effective Government This statistical abstract provides much of the information needed to enable policy makers to address these priorities, but the survey itself provides even more, details which will be of particular use to sectoral experts. I encourage the members of the Government and Parlia-ment and other interested stakeholders to par-ticipate by appointing expertise to delve further into this wealth of statistics.
In 2001, statistics gathered from the Living Standards Timor-Leste gave us the roots for the production of the first National Development Plan of Timor-Leste. The new Government will soon commence work on the next National De-velopment Plan and this process will be no dif-ferent. Already the experts are working on the Poverty Estimates, Profiles and Assessment. These will not only give us the evidence we need to formulate the second National Devel-opment Plan of the country but also the indica-tors which will be used to measure and monitor its success.
This survey is already being used for the MDG Poverty Reduction Report. It will also contribute to the update of the next Human Development Report (UNDP) and the Consumer Price Index (CPI) of the country.
The TLSLS07 provides an objective view of how the Timorese people are fairing in their daily lives. The challenge for this Government now is how to take this statistical information and transform it into a realistic action plan.
This Report allows for comparisons with the same survey taken in 2001, and allows us to measure our progress. The Report shows that we still have a long way to go towards our vision of our coun-try, but there have been improvements.
We call on all our development partners, other development stakeholders, and the society at large, to base their development programs on this official national data. Thus, assuring that all gov-ernment and donor programs alike are based on the same platform of information.
When one looks over the past few years and the next few years to come, one this is certain: it is possible to achieve the best practice plans in Timor-Leste. However, this can only be done if we plan the work, and work the plan, and subse-quently this can only be achieved with official credible national statistics and evidence-based planning.
It is important that policy makers, planners, politi-cal parties and community leaders are aware of the needs and aspirations of the people of their country in order for them to effectively provide for the specific needs of their population. Similarly, we, the Government, need to be aware of our country’s demographic structure and socio-economic characteristics in order to plan for an adequate standard of living, and for the proper provision and distribution of goods and services to the people of Timor-Leste.
Emilia Pires Minister of Finance 8 July 2008
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Timor-Leste Survey of Living Standards 2007
Preface
This initiative was two years in the planning and drafting, putting together the right team and theproper conditions, so that we could in some way measure our development over the first fewyears of nationhood. Fortunately, we now have a reference point. In 2001, the first report on poverty and living standards titled “Poverty in a New Nation: Analysisfor Action” was published. This report was the outcome of three data collection activities: a SucoSurvey, a Participatory Potential Assessment and a Living Standards Measurement Survey (TLSS). This effort was supported by several donors. The TLSS 2001 reached 1,800 households over a period of three months. In 2007, that samehousehold survey was extended to almost 4,500 households over a period of twelve months. The Timor Leste Survey of Living Standards (TLSLS) 2007 is a government-implemented activity with support from the multi-donor Planning and Financial Management Capacity BuildingProgram (PFMCBP) managed by the World Bank. Given the challenges facing us since 2006 due to the conflict, the change in government andthe unsettled situation across all sectors, it became imperative to have an idea of the currentconditions of our people. But this should be from their perspective, from their personal opinion, from their reality. It is hoped that with this report, ahead of the poverty profile report which is expected to bereleased in the coming months, the various sectors of the government, civil society and thedonors at large take a close look at some of the signs contained herein. It is not the job of this report to explain or evaluate the findings from the survey, but merely toilluminate and prepare us all for what is happening in our country, in the urban and ruralenvironments and how our people are being affected by the shifting reality that faces TimorLeste as it develops. Our visiting experts have left behind several edicts to the quality of our work for which our Core Team at the Directorate of National Statistics (DNE) stands to be congratulated. They have stood up to the test and proved their worth and have done an outstanding job. The TLSLS 2007 is considered to be of a high standard and quality comparable with some ofthe best such surveys in other countries. The data were entered in the field and quality controls were actively applied. This procedure saved us months of work and has allowed us to haveaccess to the data for analysis with greater speed and accuracy. Most importantly, this was allpossible through a small DNE Core Team, well-trained, dedicated and motivated to prove that they could do it. They were supported by a visiting team of four experts and one facilitator. Westand and applause our Core Team and continue to support them with our commitment. Manuel Mendonça DNE Director Elias dos Santos Ferreira Project Manager Lourenco Soares Data Manager Advisor Americo Soares Data Manager Silvina Soares Finance Officer
June 2008
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Timor-Leste Survey of Living Standards 2007
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Timor-Leste Survey of Living Standards 2007
Acknowledgments
Government Core Team Manuel Mendonça DNE Director Elias dos Santos Ferreira Project Manager Lourenco Soares Data Manager Advisor Américo Soares Data Manager Silvina Soares Finance Officer Management Facilitator Cristina Dasilva- Cruz Technical Assistance Juan Muñoz Beatriz Godoy Victor Canales World Bank Gaurav Datt Senior Economist Martín Cumpa Analyst World Bank IDF Grant TF 53690 PFMCBP – Muitilateral Fund UNICEF
Listing Operation: Ana Senorina da Silva Correia Aristides Soares Armando da Costa Botavio Joaquim Alves Carlos da Costa Lemos Cristovo tolo Dulce de Deus Eduardo Alves Filman Paulino Inácio de Jesus dos Santos Joanico Horácio Joanina dos Santos Guterres Maria de Fátima Mariano de Fátima Mausilio Marques Napoleáo Vieira soares Olivia da Conceição Paulo Pereira Martins Pedro Bere dos Santos Perpetua Sousa de Carvalho Rosa Maria da Costa Belo Severino Guterres de Jesus Teresa M da Silva Yohanis W Leyn Zulmira Maria Fernandes
Field Operation: Abel Castro Ximenes Afonso Babo Martins Agostinha Petrus Alarico Fernandes Alcino da Silva Amélia da C Fátima Ana Maria Guterres Ananias Ezequiel da Silva Antoninho dos Santos António C Alves Augusto Ximenes da Silva Barbara Araújo Gomes Carlos Correia da Silva Cesaltina Falcão de Araújo Diiva do Rosário F B Costa Domingos de Brito Guterres Domingos Gomes Ferreira Domingos Moniz Emanuela Joaquim Alves Evaristo Guterres Félix Celestinho Fernando Valentim Filipe da Silva Filomeno Baptista Gernamos dos Anjos Marques Graciela Boavida da Costa Jacinto Freitas
Field Operation (cont’d) Januário Ximenes Joana Aparício Guterres Joaquim dos Reis Joaquim Gonçalces Júlio Anaceto Lay Júlio da Conceição Lourenço da Costa Luís Valentim JMS dos Santos Martinha C P Neto Martinho Ximenes Mateus Potto Miguel Pereira Paulino R Ximenes Paul C Mesquita Paulo Rodrigues Guterres Rogério Castro Soares Roménia Gomes Ferreira Saul do Carmo Sónia N M Fernandes Thomas Dias Q Simões Thomas Ximenes Yohana Soi Bere Pedro Paul António Sergio Abel Pinto Mondego da Conceição Almicar Soares da Cruz
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Introduction
This Final Statistical Abstract presents key tabulations from the 2007 Timor-Leste Survey of Living Standards (TLSLS) that concluded its field operations in January 2008. The Final Abstract follows an Interim Statistical Abstract of September 2007 which presented early findings from the TLSLS based on a little over half of the full sample representing data from households who were surveyed up to the end of June 2007. TLSLS The TLSLS is the second national survey of living standards for Timor-Leste. The first national sur-vey, the Timor-Leste Living Standards Survey (TLSS), was undertaken in 2001 during the months of August to November. The 2001 TLSS had a modest, though nationally representative, sample of 1800 households from 100 sucos covering one percent of the population. Being the first national living standards survey of its kind following the independence referendum of August 1999, the TLSS provided a wealth of information on living conditions in the country as an input into the first National Development Plan. The second national living standards survey, the TLSLS, has been undertaken to update this information and is also expected to provide an input into the development of the sec-ond National Development Plan. It is notable that the TLSLS is a comprehensive multi-module survey. The scope of topics covered by the survey is very broad, and encompasses most of those that would be covered under more specialized surveys such as the Demographic and Health Survey, the Multiple Cluster Indicators Survey and a typical labor force survey. The TLSLS was launched on 27 March, 2006. Unlike its predecessor, this survey was designed to run over a period of a full year in order to better account for any seasonal variation in different indi-cators. However, after about eight weeks of fieldwork, the survey had to be suspended due to the outbreak of conflict in the country. The survey was resumed on January 9, 2007, and survey opera-tions have progressed without interruption since then. Fieldwork for the survey concluded on Janu-ary 22, 2008. At the time of the resumption of the survey, a decision was made to revisit the house-holds who were interviewed in 2006 prior to the interruption of the survey. In particular, 351 house-holds had been visited in 2006. Of these, 317 households were revisited during December 2007-January 2008. The remaining 34 households could not be found at the time of the revisits, and in-stead an additional 41 new households were interviewed as replacement households. In order to maintain a sample for a continuous period of a year, the final TLSLS sample thus excludes the 351 households interviewed in 2006 and instead includes the 358 revisited or replaced households. The TLSLS sample was designed to have two components: (i) a cross-sectional component of 4500 households selected with the intention of representing the current population of Timor-Leste, and (ii) a panel component of 900 households, where half of the 2001 TLSS sample of 1800 households are randomly selected and re-interviewed. The main purpose of the panel component is to evaluate changes in the living conditions for the same set of households between the two surveys. The cross-sectional component is expected to provide independent estimates for rural and urban areas of each of five recently defined groups of districts or Regions (see Figure 1):
• Region 1: Baucau, Lautem and Viqueque; • Region 2: Ainaro, Manufahi and Manatuto; • Region 3: Aileu, Dili and Ermera; • Region 4: Bobonaro, Cova Lima and Liquiçá; and • Region 5: Oecussi.
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Timor-Leste Survey of Living Standards 2007
TLSLS sample design The cross-sectional sample is selected in two stages:
• In the first stage, 300 Census Enumeration Areas (EAs) are selected as the primary sampling units (PSUs).
• In the second stage, 15 households are selected in each EA. The design recognizes ten explicit strata – the Urban and Rural areas in each of the five regions. Table 1 shows the allocation of the 300 cross-sectional PSUs among them.
Figure 1: The districts of Timor-Leste
Table 1: Distribution of enumeration areas for the TLSLS cross-section sample
Rural Urban Total
Region 1: Baucau, Lautem and Viqueque 35 25 60
Region 2: Ainaro, Manatutao and Manufahi 35 25 60
Region 3: Aileu, Dili and Ermera 35 37 72
Region 4: Bobonaro, Cova Lima and Liquica 35 25 60
Region 5: Oecussi 28 20 48
Timor-Leste 168 132 300
Number of enumeration areas
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Timor-Leste Survey of Living Standards 2007
This particular allocation resulted from the following line of reasoning:
• In spite of their different populations and total number of households, sampling the-ory dictates that a sample of the roughly the same size (60 EAs) should be allo-cated to each region in order to produce estimates of similar quality for each of them.
• A similar case could have been made for allocating a sample of the same size (30
EAs) to urban and rural areas within each region, but since the definition of urban and rural areas outside Dili was still a matter of discussion, it was decided to opt for an allocation closer to proportional: 25 EAs in Urban areas and 35 EAs to Rural ar-eas.
• Region 5 represents a special case. It is composed of a single district of difficult ac-
cess (Oecussi, see Figure 1) that ought to be the responsibility of a dedicated team. This imposed a total sample size of 50 EAs for this region, of which only 48 can be allocated to the cross-sectional component since the panel component contains two EAs in Oecussi.
• The capacity thus liberated to visit an additional 12 EAs in the rest of the country
was devoted to reinforce the urban sample in Region 3, where Dili is located. The first sampling stage used the list of 1,163 Census Enumeration Areas (EAs) generated by the 2004 Census as a sample frame. Within each stratum, the allocated number of EAs was selected with probability proportional to size (pps) using the number of households re-ported by the census as a measure of size. No efforts were made to append the smaller EAs to neighboring EAs, or to segment the larger EAs in order to make the size of the pri-mary sampling units (PSUs) more uniform. The second sampling stage used an exhaustive household listing operation in all selected EAs as its sample frame. Sample households in each EA were selected from the list by systematic equal probability sampling. As a result of the relatively large sampling fraction in some of the strata, certain large EAs were selected more than once by the pps procedure adopted at the first sampling stage. In fact, the cross-sectional sample only consists of only 269 (rather than 300) different EAs. This necessitated selecting a multiple of 15 households (rather than just 15 households) in the EAs that were selected more than once.
Definition of urban and rural areas At the time of the 2001 TLSS, 71 of Timor-Leste’s 498 sucos were conventionally qualified as urban, of which 31 sucos in the Dili and Baucau districts were qualified as major urban centers. By the time of preparation of the sample design for the 2007 TLSLS, 60 of the 498 sucos defined by the 2001 Suco Survey were conventionally qualified as urban. The partition of the country into sucos was also modified in September 2004. With the amalga-mation of several sucos, the original 498 sucos were now collapsed into 442. Many of the rearrangements took place in urban areas with the result that the 60 “old” sucos are now considered urban only constitute 38 “new” sucos. Table 2 gives a list of the 60 sucos that are now considered urban.
-
8
Timor-Leste Survey of Living Standards 2007
Table 2: Names of the 60 urban sucos in 2006
District: Aileu _______________________________________________________________ Posto: Aileu010110 .............................Seloi 010113 ..................... Hurairaco (the last two now collapsed into a single suco called Seloi Manere)
District: Ainaro_____________________________________________________________Posto: Ainaro020101 .......................... Ainaro 020408 ..................... Maubisse
District: Baucau ___________________________________________________________Posto: Baucau030201 ........................Tiri Lolo 030208 .........................Caicido (the last two now collapsed into a single suco called Tiri Lolo) 030202 ............................ Bahu
District: Bobonaro _________________________________________________________Posto: Maliana040603 ........................ Ritabou 040605 ............................Holsa
District: Covalima _______________________________________________________ Posto: Suai Kota050502 ....................... Laconac 050508 .......................... Debos 050509 ...............................Vila(the last three now collapsed into a single suco called Debos)
District: Dili ____________________________________________________________Posto: Cristo Rei060201 ...................... Culuhum 060202 ........Centro Benemauk 060204 ......................... Becora 060207 ............................. Ailok(the last three now collapsed into a single suco called Becora) 060203 .........................Fatuahi 060208 ......................... Camea (the last two now collapsed into a single suco called Camea) 060205 .............................Hera 060210 ............. Bidau Santana
District: Dili __________________________________________________________ Posto: Dom Aleixo060301 ................... Loscabubu 060304 .......................... Suleur 060306 ....................Malinamoc060310 .............Rai Naca Doco (the last four now collapsed into a single suco called Comoro) 060303 ......................... Nazare 060307 ............... 12 Novembro 060606 ...................... Naroman060608 ............. Isolado060611 Moris Dame (the last five now collapsed into a single suco called Bairo Pite) 060302 ..................... Beira Mar (now called Fatuhada) 060308 ................. 7 Decembro (now called Kampung Alor)
District: Dili ____________________________________________________________ Posto: Nein Feto060501 ..................Monumento (now called Bidau Lecidere)` 060507 ................... Talera Hun (now called Acadiru Hun) 060502 ............ Asucai Lorosae 060503 ..............................Solo 060504 ................... Santa Cruz(the last three now collapsed into a single suco called Santa Cruz) 060506 .......................Inur Fuik 060509 ........... Lahane Oriental (the last two now collapsed into a single suco called Gricenfor) 060505 ............................Meira 060508 ......................... Bemori (the last two now collapsed into a single suco called Bemori)
District: Dili ____________________________________________________________ Posto: Vera Cruz060604 ................ Mascarinhas 060605 ........................ Rumbia (now called Caicoli) 060602 ...............Hanso Hatora 060607 ...................... Haksolok (the last two now collapsed into a single suco called Vila Verde) 060305 ............... 28 Novembro (now called Colmera) 060309 ........................20 Maio (now called Motael) 060601 .................Alto Hospital 060603 ..................... Bairo Alto (the last two now collapsed into a single suco called Lahane Occidental)
District: Ermera _______________________________________________________Posto: Ermera Kota070201 ........................ Poetete 070206 .......................Talimoro
District: Liquiça ___________________________________________________________ Posto: Liquiça080201 ............................. Dato
District: Lautem _________________________________________________________ Posto: Lospalos090301 ..........................Fuiluro
District: Manufahi __________________________________________________________ Posto: Same100301 .......................Letefoho 100302 ..........................Babulu
Note: Each suco is identified by a geocode with 2 digits for the district, 2 digits for the posto within the dis-trict and 2 digits for the suco within the posto.
-
9
Timor-Leste Survey of Living Standards 2007
Scope of the Abstract This Final Statistical Abstract is based on tabulations of data from the full cross-sectional component of TLSLS. The final cross-sectional sample consists of 4,477 households. Table 3 shows the distri-bution of the total TLSLS sample across the rural and urban areas of the five main regions in the country. The sample s can be considered representative at national level as well as at the level of the ten domains represented by the rural and urban areas of the five regions.
The fieldwork was designed to be more or less evenly spread throughout the country over the year. Given the challenges of the turbulent political and security situation during some periods in 2007, the fieldwork schedule had on occasion to be modified a bit to accommodate concerns of security and feasibility of fieldwork. Despite this, as seen in Table 4, the distribution of the sample by month of interview and by region and rural and urban areas indicates a sample that is well-spread through the year, which should allay any concerns of intra-year seasonality.
Table 3: The distribution of the TLSLS full sample by region and rural/urban areas
Rural Urban Total
Region 1 : Baucau, Lautem, Viqueque 524 375 899Region 2 : Ainaro, Manatuto and Manufahi 517 374 891Region 3 : Aileu, Dili and Ermera 522 552 1,074Region 4 : Bobonaro, Cova Lima and Liquiçá 520 375 895Region 5 : Oecussi 419 299 718
Timor-Leste 2,502 1,975 4,477
Table 4: The distribution of the TLSLS sample by month of interview and by region and rural/urban areas
Region 1: Region 2: Region 3: Region 4: Region 5: Timor-LesteBaucau, Ainaro, Aileu, Bobonaro, OecussiLautem Manatuto Dili Cova Lima
and Viqueque and Manufahi and Ermera and Liquiçá
January 2007 60 90 75 87 58 370February 91 60 75 90 45 361March 75 59 105 45 60 344April 58 45 45 60 45 253May 75 132 90 135 75 507June 60 74 105 88 60 387July 60 74 164 60 60 418August 45 119 58 60 60 342September 60 88 90 45 60 343October 120 30 89 75 76 390November 105 60 90 45 59 359December 2007 60 45 45 60 30 240January 2008 30 15 43 45 30 163
Total 899 891 1,074 895 718 4,477
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10
Timor-Leste Survey of Living Standards 2007
This Statistical Abstract presents tabulations on nine main topics drawn from the corresponding sec-tions of the TLSLS questionnaire. The topics covered include: demographics, housing, access to facilities, durable goods, education, health, employment, social capital and subjective well-being. A set of key tables are presented for each topic. The Abstract however does not aim to present an exhaustive tabulation of the all the data for any topic. Moreover, besides these topics, there are many others; Three variants of each key table are presented: • The first presents estimates at the national level, for rural and urban areas, and for each of the
five regions. • The second presents separate estimates for rural and urban areas within each of the five re-
gions. • The third presents estimates for each of the 13 districts. A special feature of the Abstract is that it exploits the similarity of the 2001 TLSS and 2007 TLSLS survey instruments to also present comparative estimates for 2001 at the national level. Exactly the same methodology is applied in computing the 2001 numbers as used for the 2007 estimates. The 2001 estimates are intended to provide some notion of the change in various indicators over the last six years. However, no attempt is made in this Abstract to explain the observed changes. An expla-nation of these changes requires deeper and a more complex level of analysis that is beyond the limited scope of this Abstract. It is hoped that the findings presented in this Abstract will spur more detailed analysis. Further care should be taken in comparing the 2001 and 2007 estimates. While the questionnaire for the 2007 TLSLS mirrors that for the 2001 TLSS for the most part, there are some differences in particular instances due to the adaptation of the survey instrument to the new realities which may influence the comparability of results. The notes to the tables also alert the readers to some varia-tions in survey instruments where relevant.
Selection probabilities and raising factors For the cross-sectional sample of TLSLS, the selection probabilities and raising factors are deter-mined in accordance with the sample design described above. The probability of selecting Census Enumeration Area ij in stratum i is
(1) where nij is the number of households in the EA (as reported by the 2004 Census), ni is the total number of households in the stratum (also as per the 2004 Census) and mi is the number of EAs selected in the stratum. The probability of selecting household ijk in EA ij of stratum i is
(2) where n’ij is the number of households in the EA, as per the household listing operation.
i
ijiij n
nmp =
ijijijk n
pp′
=15
-
11
Timor-Leste Survey of Living Standards 2007
The raising factor or weight wijk for household ijk is the inverse of the selection probability pijk. If the number n’ij of households found at the time of the listing operation were equal to the number nij re-corded by the census in all EAs, the sample would be self-weighted in each stratum, with a constant raising factor equal to ni/15mi. In practice the numbers nij and n’ij will seldom be equal but often close to each other, meaning that the samples will not be exactly self-weighted, but quite approximately so. 1 The household weights are further adjusted such that the population totals as estimated from the full sample match the demographic projections for mid-2007 for each stratum. This corresponds to a mid-2007 total population for Timor-Leste of 1,047, 632 persons. 2
Standard errors and confidence intervals The statistics presented in this Abstract are based on a sample of the population and thus have sampling errors associated with them. For reasons of space, the Abstract does not report any stan-dard errors or confidence intervals for the statistics. However, to illustrate the margin of error asso-ciated with the reported statistics, Table 5 shows the standard errors and 95% confidence intervals for the net primary enrolment rates for the academic year 2006/7, which is one set of the tables pre-sented in the Education section of the Abstract. In computing these standard errors and confidence intervals, the particular features of the TLSLS sample design have been taken into account. As discussed above, the TLSLS is not a simple ran-dom sample of the population in Timor-Leste, but follows a stratified two-stage sampling design. In particular, the sample design involved defining ten strata, selecting a number of primary sampling units (PSUs) within each stratum at the first stage, and then selecting households from each PSU at the second stage. Thus, the computation of standard errors and confidence intervals takes into ac-count three key features of the survey design: strata, primary sampling units and sampling weights. These design features imply that the standard errors of TLSLS-based statistics will be different to those that can be expected from a simple random sample. ( see table overleaf)
1 Strictly speaking, the above formulae are valid only when the size of the EA is such that it can be selected at most once by the pps procedure. However, the artifact of selecting 15t households in the second stage whenever an EA is selected t times in the first stage has the effect of making them applicable to compute raising factors even for the large EAs where that may not be the case. Formula (2) may be inadequate if the actual size n’ij of EA ij happens to be less than 15. In that (quite unlikely) case, all households in the EA will need to be visited, and pijk simplifies to pij. 2 This population total relates to the medium-level projection in DNE (2007), Population Projections 2004-2050: Analy-sis of Census Results, Report 1, General Population Census of Timor-Leste 2004.
-
12
Timor-Leste Survey of Living Standards 2007
The standard errors and confidence intervals in Table 5 have the standard interpretation. While the statistics on net enrolment rates are unbiased, the standard errors give a measure of the dispersion for the statistic in question. The lower and upper bound of the 95% confi-dence intervals give the range within which the statistic in question can be expected to lie with a 95% probability. A particular feature of the estimates in Table 5 is worth highlighting, namely, the standard errors and confidence intervals become larger for statistics at succes-sively lower levels of disaggregation. Thus, standard errors are lowest and the confidence intervals are narrowest for the national primary net enrolment rate indicating that national-level indicators (which are based on the entire sample) are the most precisely estimated. However, as we move from national to rural-urban to regional and stratum level net enrol-ment rates the standard errors and confidence intervals become larger. In particular, the confidence intervals are largest at the district level, which carries the important implication that district-level statistics reported in this Abstract should be interpreted cautiously in view of their relatively lower degree of statistical precision.
Table 5: Standard errors and confidence intervals of net primary enrolment rate for the academic year 2006/7
Net Standard [95% confidence interval]enrolment error Lower Upper
rate bound bound
National 65.62 1.86 61.96 69.29
Rural 62.26 2.41 57.51 67.00Urban 74.28 2.79 68.79 79.77
Region 1: Baucau, Lautem, Viqueque 71.42 3.13 65.26 77.59Region 2: Ainaro, Manufahi, Manatuto 72.17 3.56 65.16 79.18Region 3: Aileu, Dili, Ermera 61.77 3.59 54.70 68.83Region 4: Bobonaro, Cova Lima, Liquiçá 64.01 4.05 56.04 71.99Region 5: Oecussi 52.48 3.11 46.35 58.61
Region 1 rural 71.42 3.46 64.61 78.22Region 1 urban 71.50 2.64 66.31 76.69Region 2 rural 72.82 4.18 64.59 81.05Region 2 urban 69.00 4.11 60.91 77.10Region 3 rural 38.30 5.11 28.24 48.37Region 3 urban 76.61 3.88 68.98 84.24Region 4 rural 63.79 4.55 54.84 72.74Region 4 urban 65.46 7.09 51.50 79.42Region 5 rural 50.14 3.44 43.38 56.91Region 5 urban 76.13 4.20 67.87 84.39
Aileu 39.72 7.92 24.14 55.31Ainaro 70.51 4.44 61.76 79.25Baucau 67.96 3.33 61.41 74.51Bobonaro 72.35 4.81 62.89 81.81Cova Lima 77.37 5.62 66.30 88.44Dili 79.84 3.05 73.84 85.85Ermera 33.12 4.40 24.45 41.78Lautem 77.52 5.32 67.04 88.00Liquiçá 44.01 4.84 34.49 53.53Manufahi 65.88 9.06 48.06 83.70Manatuto 79.55 5.92 67.89 91.21Oecussi 52.48 3.11 46.35 58.61Viqueque 67.62 3.95 59.85 75.39
-
13
Timor-Leste Survey of Living Standards 2007
Future uses of TLSLS data Notwithstanding the larger number of tabulations presented in this Abstract, it only scratches the surface of the wealth of information that the TLSLS contains. Some of the anticipated uses of the TLSLS data include: the monitoring of several of the Millennium De-velopment Goals, an assessment of poverty in the country, information for components of National Accounts, and updating of the weighting diagram for the Consumer Price Index, just to name a few. Beyond these, the data from the TLSLS will also enable further detailed analysis of sectoral issues, and indeed provide an important input for the Second National Development Plan, and evidence-based policy making for Timor-Leste more generally.
-
14
Timor-Leste Survey of Living Standards 2007
-
15
Timor-Leste Survey of Living Standards 2007
Demographics
1. Demographics
Concepts and definitions
This section describes selected characteristics of the population of Timor-Leste. The demo-graphic profile includes the population structure by gender and age groups as well as the distribution of the population by marital status, mother tongue, languages spoken and main occupations. Tabulations of the population that has been away from their household for more than a month in the last year are also included. The prevalence of orphans and living arrangements of children are reported for all children under 15 years old. The prevalence of orphans refers to the proportion of children that have lost one or both parents. The living arrangements of children indicate whether a child is liv-ing with none of his or her biological parents, with only one or with both of them. The TLSLS captures the population living in private households. A household is a group of persons (or a single person) who usually live together and have a common arrangement for food, such as using a common kitchen or a common food budget. The persons may be re-lated to each other or may be non-relatives, including servants or other employees, staying with the employer. Students and employees residing in and having a common food arrange-ment with the household are considered members of the household if they have been in the household for the last year and absent for no more than one month. If absent for longer than nine months, only infants less than three months old, newly weds or a bride who has joined her husband’s family are considered household members. However, this does not include boarders/lodgers or boarding houses operated by the household. Boarding houses with more than five persons are considered to be institutional households. Institutional households are not covered by the survey. They are defined as a group of five or more unrelated persons living together, for example, those living in boarding houses, military barracks, prisons, or student dormitories.
-
Dem
o gr a
p hi c
s 1 6
T1.1
PO
PU
LA
TIO
N S
TR
UC
TU
RE
BY
RU
RA
L A
ND
UR
BA
N A
RE
AS
AN
D R
EG
ION
S,
AC
CO
RD
ING
TO
GE
ND
ER
AN
D A
GE
GR
OU
PS
(% o
f popula
tion)
2001
2007
Natio
nal
Natio
nal
Rura
lU
rban
Bauca
u,
Ain
aro
,A
ileu,
Bobonaro
,O
ecu
ssi
Laute
m,
Manatu
to,
Dili
,C
ova
Lim
a,
Viq
ueque
Manufa
hi
Erm
era
Liq
uiç
á
Tota
l100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
<5
16.8
15.6
15.8
14.9
14.9
15.9
15.8
15.0
18.0
5-9
16.5
15.2
15.6
14.0
16.6
14.6
15.2
14.0
14.9
10-1
412.1
12.6
12.7
12.1
12.7
13.1
12.7
12.5
10.4
15-1
99.0
10.6
10.0
12.3
10.4
9.4
11.2
11.1
9.6
20-2
45.6
8.2
7.2
10.9
7.1
7.4
9.7
8.2
5.8
25-2
98.1
5.7
5.4
6.8
4.9
5.9
6.7
4.9
6.0
30-3
46.7
5.8
5.4
6.9
5.8
6.1
5.9
5.2
7.1
35-3
95.7
5.6
5.8
5.0
5.6
5.6
5.4
5.7
6.5
40-4
44.7
4.7
4.8
4.3
4.6
4.7
4.5
4.8
5.8
45-4
93.5
4.0
4.1
3.6
3.8
4.1
3.7
4.4
4.8
50+
11.3
12.1
13.0
9.3
13.7
13.3
9.4
14.1
11.2
Male
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
<5
16.9
15.7
16.0
14.8
16.0
16.7
15.0
14.8
19.2
5-9
17.4
15.6
16.2
13.7
16.5
14.8
15.3
15.3
16.0
10-1
412.4
12.1
12.2
11.9
11.8
11.7
13.1
11.5
10.5
15-1
99.2
11.0
10.7
12.0
11.2
10.5
11.0
11.8
9.2
20-2
45.3
8.4
7.2
11.5
7.4
7.5
10.2
7.9
5.8
25-2
97.4
5.4
4.9
6.8
4.5
5.1
6.5
5.1
4.6
30-3
46.6
5.6
5.1
6.9
5.2
6.2
5.8
4.7
7.4
35-3
95.4
5.9
6.1
5.2
6.5
6.0
5.5
5.7
5.9
40-4
44.7
4.6
4.7
4.5
4.5
4.8
4.4
4.6
6.0
45-4
93.4
4.0
4.2
3.5
3.3
3.8
3.9
4.8
5.1
50+
11.3
11.7
12.6
9.2
13.1
12.9
9.3
13.8
10.3
Fem
ale
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
<5
16.8
15.4
15.6
15.0
13.9
15.0
16.6
15.1
16.8
5-9
15.5
14.7
14.9
14.2
16.6
14.3
15.0
12.6
13.7
10-1
411.8
13.1
13.3
12.4
13.6
14.6
12.3
13.6
10.3
15-1
98.8
10.2
9.4
12.5
9.5
8.3
11.4
10.4
10.0
20-2
45.9
8.0
7.2
10.2
6.8
7.2
9.1
8.6
5.8
25-2
98.8
6.0
5.8
6.7
5.3
6.7
6.9
4.6
7.5
30-3
46.7
6.1
5.8
6.8
6.4
5.9
5.9
5.8
6.8
35-3
96.0
5.3
5.5
4.9
4.7
5.2
5.3
5.7
7.0
40-4
44.8
4.8
5.0
4.2
4.6
4.7
4.6
5.1
5.6
45-4
93.5
3.9
4.1
3.6
4.3
4.4
3.4
3.9
4.4
50+
11.3
12.4
13.5
9.5
14.3
13.7
9.4
14.5
12.1
Sourc
e:
2001 T
LS
S a
nd 2
007 T
LS
LS
.
-
Dem
ogra
phic
s 17
T1.
2P
OP
ULA
TIO
N S
TRU
CTU
RE
BY
RE
GIO
NA
L R
UR
AL
AN
D U
RB
AN
AR
EA
S, A
CC
OR
DIN
G T
O G
EN
DE
R A
ND
AG
E G
RO
UP
S(%
of p
opul
atio
n)
2007
Nat
iona
l
Rur
alU
rban
Rur
alU
rban
Rur
alU
rban
Rur
alU
rban
Rur
alU
rban
Tot
al10
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
-
Dem
o gr a
p hi c
s 1 8
T1.3
POPU
LATI
ON
STR
UC
TUR
E B
Y D
ISTR
ICT,
AC
CO
RD
ING
TO
GEN
DER
AN
D A
GE
GR
OU
PS(%
of p
opul
atio
n)
2007
Nat
iona
lA
ileu
Ain
aro
Bau
cau
Bob
onar
oC
ova
Lim
aD
iliE
rmer
aLa
utem
Liqu
içá
Man
ufah
iM
anat
uto
Oec
ussi
Viq
uequ
e
Tota
l10
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
0
-
Dem
ogra
phic
s 19
T1.
4M
OTH
ER
TO
NG
UE
BY
RU
RA
L A
ND
UR
BA
N A
RE
AS
AN
D R
EG
ION
S, A
CC
OR
DIN
G T
O G
EN
DE
R(%
of p
opul
atio
n)
2001
2007
Nat
iona
lR
ural
Urb
anB
auca
u,A
inar
o,A
ileu,
Bob
onar
o,O
ecus
siLa
utem
,M
anat
uto,
Dili
,C
ova
Lim
a,V
ique
que
Man
ufah
iE
rmer
aLi
quiç
á
Tot
al10
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
Tet
um11
.317
.44.
453
.92.
010
.239
.18.
50.
5B
aequ
eno
4.4
6.2
7.3
3.3
0.0
0.0
0.1
0.1
98.6
Bun
ak11
.15.
76.
53.
70.
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90.
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7.4
6.3
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0.0
0.4
4.4
22.6
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Mac
asae
11.5
11.7
13.9
5.7
45.9
0.1
2.6
0.0
0.0
Mam
bae
25.8
24.6
27.2
17.5
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51.5
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46.
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313
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514
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4.6
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010
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4.0
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ak10
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53.
50.
04.
50.
523
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emak
7.7
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0.0
0.4
4.2
23.3
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Mac
asae
11.7
11.8
13.8
6.4
45.8
0.2
2.9
0.0
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bae
26.1
24.6
27.3
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76.
17.
91.
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4.5
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446
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33.
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4
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ale
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
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etum
11.3
17.5
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39.4
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Bae
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86.
47.
53.
20.
00.
00.
10.
099
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11.5
5.8
6.5
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ak7.
16.
27.
42.
90.
00.
44.
621
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acas
ae11
.211
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10.
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e25
.624
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152
.246
.73.
40.
1T
etum
terik
6.0
6.5
8.1
1.8
5.3
12.9
0.8
14.8
0.0
Tok
odet
e4.
65.
05.
73.
10.
00.
10.
423
.40.
0O
ther
17.8
16.5
19.5
8.2
46.5
19.3
5.4
4.3
0.6
Sou
rce:
200
1 T
LSS
and
200
7 T
LSLS
.
-
Dem
o gr a
p hi c
s 2 0
T1.5
MO
THER
TO
NG
UE
BY
REG
ION
AL R
UR
AL A
ND
UR
BAN
AR
EAS,
AC
CO
RD
ING
TO
GEN
DER
(% o
f pop
ulat
ion)
2007
Nat
iona
l
Rur
alU
rban
Rur
alU
rban
Rur
alU
rban
Rur
alU
rban
Rur
alU
rban
Tota
l10
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
Tetu
m17
.41.
39.
27.
623
.83.
970
.27.
416
.80.
12.
5B
aequ
eno
6.2
0.1
0.0
0.0
0.0
0.0
0.2
0.0
0.4
99.1
95.5
Bun
ak5.
70.
00.
05.
70.
90.
01.
022
.130
.50.
10.
1K
emak
6.3
0.0
0.1
0.2
1.3
8.0
1.3
22.8
21.0
0.0
0.0
Mac
asae
11.7
47.8
27.6
0.1
0.2
0.0
4.9
0.0
0.0
0.0
0.1
Mam
bae
24.6
0.0
0.4
48.7
66.2
81.4
16.5
4.0
0.2
0.2
0.2
Tetu
m te
rik6.
35.
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615
.70.
00.
20.
815
.52.
70.
00.
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kode
te5.
20.
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10.
10.
00.
10.
723
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10.
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ther
16.5
45.9
53.9
21.8
7.5
6.3
4.5
4.6
0.1
0.4
1.2
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e10
0.0
100.
010
0.0
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010
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010
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Tetu
m17
.31.
29.
68.
123
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269
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23.
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6.1
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6.4
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1.7
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23.6
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0.0
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11.8
47.4
29.5
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0.0
5.5
0.0
0.0
0.0
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24.6
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82.4
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Tetu
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724
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ther
16.6
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0.3
0.9
Fem
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100.
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0.0
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0.0
100.
010
0.0
100.
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0.0
100.
010
0.0
100.
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tum
17.5
1.3
8.8
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3.7
71.1
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Bae
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40.
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00.
00.
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10.
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299
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5.8
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6.5
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dete
5.0
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Oth
er16
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64.
34.
90.
10.
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Sou
rce:
200
7 TL
SLS
.
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cau,
Lau
tem
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ique
que
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ussi
Liqu
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Bob
onar
o, C
ova
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a,A
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, Erm
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Man
ufah
iA
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o, M
anat
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-
Dem
ogra
phic
s 21
T1.6
MO
THER
TO
NG
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BY
DIS
TRIC
T, A
CC
OR
DIN
G T
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END
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of p
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n)
2007
Nat
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lAi
leu
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aro
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cau
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a Li
ma
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010
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100.
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100.
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tum
17.4
2.5
6.1
1.5
5.8
17.0
70.7
3.2
2.8
5.5
20.2
5.7
0.5
2.1
Bae
quen
o6.
20.
00.
00.
10.
10.
00.
20.
00.
00.
10.
10.
098
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unak
5.7
0.0
9.3
0.0
33.1
31.7
1.0
0.0
0.0
0.0
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6.3
0.6
0.0
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48.8
0.7
0.0
0.0
0.0
17.5
28.0
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24.9
Toko
dete
5.2
0.0
0.0
0.0
0.0
0.0
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Oth
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17.3
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5.7
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5.3
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317
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6.4
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00.
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50.
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6.2
0.3
0.7
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1.4
0.9
13.8
0.0
0.4
0.3
0.0
0.0
0.0
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asae
11.6
0.0
0.0
70.8
0.2
0.0
4.1
0.1
9.9
0.0
0.0
0.4
0.0
41.8
Mam
bae
24.6
93.4
83.5
0.1
0.0
0.4
11.8
82.3
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48.8
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Tetu
m te
rik6.
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00.
00.
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kode
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10.
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40.
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ther
16.5
2.7
0.0
27.6
9.5
0.0
8.9
0.6
87.1
0.1
9.6
60.2
0.6
31.3
Sou
rce:
200
7 TL
SLS
.
-
Dem
o gr a
p hi c
s 2 2
T1.
7M
AIN
LA
NG
UA
GE
S S
PO
KE
N B
Y R
UR
AL
AN
D U
RB
AN
AR
EA
S A
ND
RE
GIO
NS
, AC
CO
RD
ING
TO
GE
ND
ER
(% o
f pop
ulat
ion)
2001
2007
Nat
iona
lR
ural
Urb
anB
auca
u,A
inar
o,A
ileu,
Bob
onar
o,O
ecus
siLa
utem
,M
anat
uto,
Dili
,C
ova
Lim
a,V
ique
que
Man
ufah
iE
rmer
aLi
quiç
á
Tot
al10
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
Tet
un81
.787
.484
.196
.772
.996
.798
.196
.730
.1In
done
sian
42.6
38.2
33.2
52.3
43.5
29.6
44.4
31.8
25.6
Por
tugu
ese
5.3
15.6
12.1
25.4
16.7
10.6
21.8
10.3
6.7
Eng
lish
2.0
4.3
1.4
12.3
1.9
1.0
9.1
2.1
0.9
Onl
y T
etun
40.2
45.5
47.4
40.0
24.5
64.5
48.8
61.6
7.3
Tet
un a
nd In
done
sian
35.3
26.0
24.5
30.3
31.8
21.4
26.7
24.6
16.5
Tet
un, I
ndon
esia
n an
d P
ortu
gues
e3.
97.
56.
79.
79.
27.
18.
65.
23.
1O
ther
com
bina
tions
3.9
9.1
6.2
17.0
8.5
3.6
14.0
5.3
8.9
Non
e of
the
mai
n fo
ur16
.811
.915
.13.
026
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31.
83.
364
.2
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0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
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Tet
un83
.488
.585
.596
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.196
.698
.296
.537
.2In
done
sian
46.6
42.3
37.5
55.9
47.8
33.2
48.9
34.9
30.6
Por
tugu
ese
7.4
17.8
14.3
27.6
19.7
11.9
24.2
12.0
7.5
Eng
lish
2.7
5.0
1.7
14.1
2.5
1.4
10.3
2.4
1.3
Onl
y T
etun
37.6
42.5
44.5
37.0
22.3
61.1
44.9
58.3
8.6
Tet
un a
nd In
done
sian
37.2
27.8
26.6
31.1
33.0
23.4
28.4
26.0
21.1
Tet
un, I
ndon
esia
n an
d P
ortu
gues
e5.
49.
28.
610
.811
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510
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74.
3O
ther
com
bina
tions
4.7
9.5
6.4
18.2
9.5
3.7
14.7
5.6
7.4
Non
e of
the
mai
n fo
ur15
.211
.013
.92.
923
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41.
73.
558
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Fem
ale
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
0T
etun
80.0
86.3
82.6
96.6
70.5
96.7
97.9
96.8
23.2
Indo
nesi
an38
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.028
.748
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.125
.939
.628
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ortu
gues
e3.
213
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.013
.59.
319
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65.
9E
nglis
h1.
23.
51.
110
.51.
30.
77.
91.
80.
4
Onl
y T
etun
42.9
48.5
50.5
43.1
26.8
67.9
53.0
65.0
6.0
Tet
un a
nd In
done
sian
33.3
24.2
22.4
29.4
30.5
19.4
24.9
23.1
12.0
Tet
un, I
ndon
esia
n an
d P
ortu
gues
e2.
45.
74.
78.
66.
95.
86.
93.
71.
9O
ther
com
bina
tions
3.0
8.6
6.0
15.8
7.5
3.6
13.2
5.0
10.5
Non
e of
the
mai
n fo
ur18
.412
.916
.43.
128
.33.
32.
03.
269
.7
Sou
rce:
200
1 T
LSS
and
200
7 T
LSLS
.
-
Dem
ogra
phic
s 23
T1.8
MAI
N L
ANG
UAG
ES S
POK
EN B
Y R
EGIO
NAL
RU
RAL
AN
D U
RB
AN A
REA
S, A
CC
OR
DIN
G T
O G
END
ER(%
of p
opul
atio
n)
2007
Nat
iona
l
Rur
alU
rban
Rur
alU
rban
Rur
alU
rban
Rur
alU
rban
Rur
alU
rban
Tota
l10
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
Tetu
n87
.471
.982
.896
.498
.296
.999
.196
.498
.323
.272
.6In
done
sian
38.2
42.3
55.6
29.6
29.3
30.8
56.4
30.6
40.2
20.9
53.9
Por
tugu
ese
15.6
16.1
22.4
10.7
9.9
13.4
29.2
9.6
15.8
4.8
18.0
Eng
lish
4.3
1.6
5.0
0.9
1.7
1.6
15.8
1.7
5.1
0.1
5.2
Onl
y Te
tun
45.5
24.7
22.3
63.9
67.7
61.3
37.9
62.7
53.8
5.7
16.8
Tetu
n an
d In
done
sian
26.0
31.2
37.3
21.6
20.1
22.2
30.7
24.1
28.2
13.2
36.6
Tetu
n, In
done
sian
and
Por
tugu
ese
7.5
8.8
13.1
7.1
7.5
7.1
9.9
4.9
7.2
1.9
10.4
Oth
er c
ombi
natio
ns9.
18.
310
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