Final Statistical Abstract: Timor-Leste Survey of Living ...€¦ · Final Statistical Abstract: Timor-Leste Survey of Living Standards 2007 Direcção Nacional de Estatística Ministério

Final Statistical Abstract:

Timor-Leste Survey of Living Standards 2007

Direcção Nacional de Estatística Ministério de Finanças

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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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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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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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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5


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.

6


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

7


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


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


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

10


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


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


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


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


15


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.

04.

90.

523

.10.

1K

emak

7.4

6.3

7.5

3.0

0.0

0.4

4.4

22.6

0.0

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

0.1

51.5

47.0

3.5

0.2

Tet

um te

rik6.

46.

38.

01.

55.

313

.20.

514

.00.

1T

okod

ete

4.6

5.2

5.9

3.2

0.0

0.1

0.4

24.0

0.1

Oth

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Documents

Final Statistical Abstract: Timor-Leste Survey of Living ...€¦ · Final Statistical Abstract: Timor-Leste Survey of Living Standards 2007 Direcção Nacional de Estatística Ministério