Luxembourg stands out as the European leader in quality of life for 2025, achieving a score of 220 on the Quality of Life Index. The Netherlands follows closely behind with 211 points, while Albania and Ukraine rank at the bottom with scores of 104 and 115 respectively. This index provides a thorough assessment of living conditions across Europe, reflecting various factors that shape the overall well-being of populations and extending beyond purely economic metrics. Understanding the quality of life index The quality of life index is a multifaceted measure that incorporates factors such as purchasing power, pollution levels, housing affordability, cost of living, safety, healthcare quality, traffic conditions, and climate, to measure the overall quality of life of a Country. Higher overall index scores indicate better living conditions. However, in subindexes such as pollution, cost of living, and traffic commute time, lower values correspond to improved quality of life. Challenges affecting life satisfaction Despite the fact that European countries register high levels of life quality by for example leading the ranking of happiest countries in the world, life satisfaction across the European Union has been on a downward trend since 2018. The EU's overall life satisfaction score dropped from 7.3 out of 10 in 2018 to 7.1 in 2022. This decline can be attributed to various factors, including the COVID-19 pandemic and economic challenges such as high inflation. Rising housing costs, in particular, have emerged as a critical concern, significantly affecting quality of life. This issue has played a central role in shaping voter priorities for the European Parliamentary Elections in 2024 and becoming one of the most pressing challenges for Europeans, profoundly influencing both daily experiences and long-term well-being.

Quality of Life Index (higher is better) is an estimation of overall quality of life by using an empirical formula which takes into account purchasing power index (higher is better), pollution index (lower is better), house price to income ratio (lower is better), cost of living index (lower is better), safety index (higher is better), health care index (higher is better), traffic commute time index (lower is better) and climate index (higher is better).

Current formula (written in Java programming language):

index.main = Math.max(0, 100 + purchasingPowerInclRentIndex / 2.5 - (housePriceToIncomeRatio * 1.0) - costOfLivingIndex / 10 + safetyIndex / 2.0 + healthIndex / 2.5 - trafficTimeIndex / 2.0 - pollutionIndex * 2.0 / 3.0 + climateIndex / 3.0);

For details how purchasing power (including rent) index, pollution index, property price to income ratios, cost of living index, safety index, climate index, health index and traffic index are calculated please look up their respective pages.

Formulas used in the past

Formula used between June 2017 and Decembar 2017

We decided to decrease weight from costOfLivingIndex in this formula:

index.main = Math.max(0, 100 + purchasingPowerInclRentIndex / 2.5 - (housePriceToIncomeRatio * 1.0) - costOfLivingIndex / 5 + safetyIndex / 2.0 + healthIndex / 2.5 - trafficTimeIndex / 2.0 - pollutionIndex * 2.0 / 3.0 + climateIndex / 3.0);

The World Happiness 2017, which ranks 155 countries by their happiness levels, was released at the United Nations at an event celebrating International Day of Happiness on March 20th. The report continues to gain global recognition as governments, organizations and civil society increasingly use happiness indicators to inform their policy-making decisions. Leading experts across fields – economics, psychology, survey analysis, national statistics, health, public policy and more – describe how measurements of well-being can be used effectively to assess the progress of nations. The reports review the state of happiness in the world today and show how the new science of happiness explains personal and national variations in happiness.

The scores are based on answers to the main life evaluation question asked in the poll. This question, known as the Cantril ladder, asks respondents to think of a ladder with the best possible life for them being a 10 and the worst possible life being a 0 and to rate their own current lives on that scale. The scores are from nationally representative samples for 2017 and use the Gallup weights to make the estimates representative. The columns following the happiness score estimate the extent to which each of six factors – economic production, social support, life expectancy, freedom, absence of corruption, and generosity – contribute to making life evaluations higher in each country than they are in Dystopia, a hypothetical country that has values equal to the world’s lowest national averages for each of the six factors. They have no impact on the total score reported for each country, but they do explain why some countries rank higher than others.

Quality of life index, link: https://www.numbeo.com/quality-of-life/indices_explained.jsp

Happiness store, link: https://www.kaggle.com/unsdsn/world-happiness/home

In 2025, Luxembourg was the country with the highest gross domestic product per capita in the world. Of the 20 listed countries, 13 are in Europe and five are in Asia, alongside the U.S. and Australia. There are no African or Latin American countries among the top 20. Correlation with high living standards While GDP is a useful indicator for measuring the size or strength of an economy, GDP per capita is much more reflective of living standards. For example, when compared to life expectancy or indices such as the Human Development Index or the World Happiness Report, there is a strong overlap - 14 of the 20 countries on this list are also ranked among the 20 happiest countries in 2024, and all 20 have "very high" HDIs. Misleading metrics? GDP per capita figures, however, can be misleading, and to paint a fuller picture of a country's living standards then one must look at multiple metrics. GDP per capita figures can be skewed by inequalities in wealth distribution, and in countries such as those in the Middle East, a relatively large share of the population lives in poverty while a smaller number live affluent lifestyles.

The average for 2021 based on 165 countries was 79.81 index points. The highest value was in Bermuda: 212.7 index points and the lowest value was in Syria: 33.25 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

As of 2022, Israel had the highest price level index among listed countries, amounting to 138, with 100 being the average of OECD countries. Switzerland and Iceland followed on the places behind. On the other hand, Turkey and India had the lowest price levels compared to the OECD average. This price index shows differences in price levels in different countries. Another very popular index indicating the value of money is the Big Mac index, showing how much a Big Mac costs in different countries. This list was also topped by Switzerland in 2023.

According to the survey, as of February 2023, four out of the six countries in the Gulf Cooperation Council ranked amongst the top ** in the world for expatriate quality of life. Qatar and the United Arab Emirates topped the list for quality of life, whereas Saudi Arabia and Kuwait came last in the region. Quality of life; an amalgamation of many metrics Since quality of life is dependent on many indicators, it can give us a good insight into many aspects of state welfare policies and services. Saudi Arabia, where the number of foreign workers in the private sector topped *** million, also ranked as having one of the region's lowest quality of life for expatriates. Qatar, which had the second-highest quality of life for expatriates living in the GCC, was ranked as one of the most challenging countries in the region for ease of settling in. The UAE and Qatar, both of which ranked the highest in the survey, also have the highest average salaries and living standards in the region. Foreign workers are a key pillar of the GCC economy Countries in the GCC all have sizable expatriate populations for which their economies are heavily reliant. Roughly ********** of the workforce in the GCC is foreign. Although the share of foreign workers in the GCC has slightly decreased in recent years, they still considerably outweigh the local workforce. Most of these workers comprise the unskilled portion of the occupational category in the GCC. However, with diversifying investments and programs such as Vision 2030, countries have seen a rise in the number of skilled foreign workers.

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

The average for 2024 based on 138 countries was 5.56 points. The highest value was in Finland: 7.74 points and the lowest value was in Afghanistan: 1.72 points. The indicator is available from 2013 to 2024. Below is a chart for all countries where data are available.

The DACH region in Europe comprises the countries of Germany (D), Austria (A), and Switzerland (CH). In 2024, the gross domestic product (GDP) of all DACH countries amounted to approximately **** trillion U.S. dollars. Just under ** percent of this was from Germany, while ** percent came from Switzerland, and * percent from Austria. In comparison to population distribution across the region, Switzerland's GDP per capita was much higher than the other two countries. Germany’s economy Germany’s economy is the largest in Europe, with the majority of the country’s GDP coming from its service sector. The country’s service sector encompasses tourism, financial services, real estate, and other industries. This reflects Germany’s standing as a central financial and political pillar of the European Union, and its position as a popular tourist destination. Grouping the DACH countries The DACH countries are closely associated both geographically and culturally, primarily through shared use of the German language. The region hosts over 100 million inhabitants, with a life expectancy at birth of around 82 years, ten years more than global life expectancy. The DACH countries enjoy a high standard of living, which is reflected in a large GDP per capita in each country.

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

Abstract

The principal objective of this survey is to collect basic data reflecting the actual living conditions of the population in Tajikistan. These data will then be used for evaluating socio-economic development and formulating policies to improve living conditions.

The first assessment of living standards in Tajikistan was conducted in 1999. This assessment is bringing about data in order to update the 1999 assessment.

The survey collects information on education, health, employment and other productive activities, demographic characteristics, migration, housing conditions, expenditures and assets.

The information gathered is intended to improve economic and social policy in Tajikistan. It should enable decision-makers to 1) identify target groups for government assistance, 2) inform programs of socio-economic development, and 3) analyse the impact of decisions already made and the current economic conditions on households.

Geographic coverage

National coverage. The 2003 data are representative at the regional level (4 regions) and urban/rural.

Analysis unit

• Households
• Individuals
• Communites

Kind of data

Sample survey data [ssd]

Sampling procedure

The Tajikistan Living Standards Survey (TLSS) for 2003 was based on a stratified random probability sample, with the sample stratified according to oblast and urban/rural settlements and with the share of each strata in the overall sample being in proportion to its share in the total number of households as recorded in the 2000 Census. The same approach was used in the TLSS 1999 although there were some differences in the sampling. First the share of each strata in the overall sample in 1999 was determined according to ‘best estimates’, as it was conducted prior to the 2000 Census. Second the TLSS 2003 over-sampled by 40 percent in Dushanbe, 300 percent in rural Gorno-Badakhshan Administrative Oblast (GBAO) and 600 percent in urban GBAO. Third the sample size was increased in 2003 in comparison with 1999 in order to reduce sampling error. In 2003, the overall sample size was 4,156 households compared with 2,000 households in 1999. [Note: Taken from “Republic of Tajikistan: Poverty Assessment Update”, Report No. 30853, Human Development Sector Unit, Central Asia Country Unit, Europe and Central Asia Region, World Bank, January 2005.]

In addition to the capital city of Dushanbe, the country has several oblasts (regions): (i) Khatlon (comprising Kurban-Tube and Khulyab), which is an agricultural area with most of the country’s cotton growing districts; (ii) the Rayons of Republican Subordination (RRS) with the massive aluminum smelter in the west and agricultural valleys in the east growing crops other than cotton; (iii) Sugd which is the most industrialized oblast; and (iv) Gorno-Badakhshan Administrative Oblast which is mountainous and remote with a small population.

The 2003 data are representative at the regional level (4 regions) and urban/rural.

Mode of data collection

Face-to-face [f2f]

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

Questions on security policy. Attitude to the Common Market. East-West comparison and preferred economic system.

Topics: Attitude to selected countries; preferred political position of one´s own country; judgement on American and Soviet foreign policy; agreement in principle of the interests of one´s own country with the interests of the USA and the USSR; confidence in the ability of the USA to solve international problems; judgement on the peace efforts of the USA and the USSR; alliance loyalty of the USA to Western Europe; attitude to nuclear tests and to a test-ban treaty even without a surveillance system; judgement on one´s own standard of living in the past, at present, and in future; country with the highest standard of living; superiority of the communist or anti-communist countries in military, economic and scientific areas as well as in the area of space flight; attitude to use of nuclear weapons in case of attack on one´s own country; judgement on the American peace corps program; attitude to a possible peace corps program of one´s own country, to a united Western Europe and to the membership of one´s own country in the Common Market; assumed effect of the Common Market on the standard of living, on the political unification of Western Europe and on the influence of the USA on European affairs; approval for a change of American influence on Europe; judgement on American trade policy; supposed attitude of the USA and the USSR to the Common Market and effect of the Common Market on US imports; attitude to socialism, communism and capitalism as well as to a nationalization of industrial establishments; outstanding characteristics of a social, capitalist or communist economic system; preferred economic system; classification of the economic systems of selected countries as more socialist or capitalist and attitude to the economic systems of these countries; judgement on American capitalism (scale); TV viewing; attitude to American television programs and films; judgement on American films, books, newspapers, music and television programs as agent of American life-style; trips to the movies; film preferences relative to individual countries; frequency of viewing American films; judgement on American, British, French and Italian films as an image of life in these countries; impression of different aspects of American life mediated by American films.

In France the following questions were also asked: income, employment of household help; ownership of automobile, radio and real estate.

Interviewer rating: duration of interview (Great Britain only); location of interview (Italy only); respondent´s willingness to cooperate (FRG only).

The Social Progress Index ranks countries based on the well-being and quality of life of their citizens, considering factors such as access to education, healthcare, human rights, and environmental sustainability.

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

Abstract

Timor-Leste experienced a fundamental social and economic upheaval after its people voted for independence from Indonesia in a referendum in August 1999. Population was displaced, and public and private infrastructure was destroyed or rendered inoperable. Soon after the violence ceased, the country began rebuilding itself with the support from UN agencies, the international donor community and NGOs. The government laid out a National Development Plan (NDP) with two central goals: to promote rapid, equitable and sustainable economic growth and to reduce poverty.

Formulating a national plan and poverty reduction strategy required data on poverty and living standards, and given the profound changes experienced, new data collection had to be undertaken to accurately assess the living conditions in the country. The Planning Commission of the Timor-Leste Transitional Authority undertook a Poverty Assessment Project along with the World Bank, the Asian Development Bank, the United Nations Development Programme and the Japanese International Cooperation Agency (JICA).

This project comprised three data collection activities on different aspects of living standards, which taken together, provide a comprehensive picture of well-being in Timor-Leste. The first component was the Suco Survey, which is a census of all 498 sucos (villages) in the country. It provides an inventory of existing social and physical infrastructure and of the economic characteristics of each suco, in addition to aldeia (hamlet) level population figures. It was carried out between February and April 2001.

A second element was the Timor-Leste Living Standards Measurement Survey (TLSS). This is a household survey with a nationally representative sample of 1,800 families from 100 sucos. It was designed to diagnose the extent, nature and causes of poverty, and to analyze policy options facing the country. It assembles comprehensive information on household demographics, housing and assets, household expenditures and some components of income, agriculture, labor market data, basic health and education, subjective perceptions of poverty and social capital.

Data collection was undertaken between end August and November 2001.

The final component was the Participatory Potential Assessment (PPA), which is a qualitative community survey in 48 aldeias in the 13 districts of the country to take stock of their assets, skills and strengths, identify the main challenges and priorities, and formulate strategies for tackling these within their communities. It was completed between November 2001 and January 2002.

Geographic coverage

National coverage. Domains: Urban/rural; Agro-ecological zones (Highlands, Lowlands, Western Region, Eastern Region, Central Region)

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE SIZE AND ANALYTIC DOMAINS

A survey relies on identifying a subgroup of a population that is representative both for the underlying population and for specific analytical domains of interest. The main objective of the TLSS is to derive a poverty profile for the country and salient population groups. The fundamental analytic domains identified are the Major Urban Centers (Dili and Baucau), the Other Urban Centers and the Rural Areas. The survey represents certain important sub-divisions of the Rural Areas, namely two major agro-ecologic zones (Lowlands and Highlands) and three broad geographic regions (West, Center and East). In addition to these domains, we can separate landlocked sucos (Inland) from those with sea access (Coast), and generate categories merging rural and urban strata along the geographic, altitude, and sea access dimensions. However, the TLSS does not provide detailed indicators for narrow geographic areas, such as postos or even districts. [Note: Timor-Leste is divided into 13 major units called districts. These are further subdivided into 67 postos (subdistricts), 498 sucos (villages) and 2,336 aldeias (sub-villages). The administrative structure is uniform throughout the country, including rural and urban areas.]

The survey has a sample size of 1,800 households, or about one percent of the total number of households in Timor-Leste. The experience of Living Standards Measurement Surveys in many countries - most of them substantially larger than Timor-Leste - has shown that samples of that size are sufficient for the requirements of a poverty assessment.

The survey domains were defined as follows. The Urban Area is divided into the Major Urban Centers (the 31 sucos in Dili and the 6 sucos in Baucau) and the Other Urban Centers (the remaining 34 urban sucos outside Dili and Baucau). The rest of the country (427 sucos in total) comprises the Rural Area. The grouping of sucos into urban and rural areas is based on the Indonesian classification. In addition, we separated rural sucos both by agro-ecological zones and geographic areas. With the help of the Geographic Information System developed at the Department of Agriculture, sucos were subsequently qualified as belonging to the Highlands or the Lowlands depending on the share of their surface above and below the 500 m level curve. The three westernmost districts (Oecussi, Bobonaro and Cova Lima) constitute the Western Region, the three easternmost districts (Baucau, Lautem and Viqueque) the Eastern Region, and the remaining seven districts (Aileu, Ainaro, Dili, Ermera, Liquica, Manufahi and Manatuto) belong to the Central Region.

SAMPLING STRATA AND SAMPLE ALLOCATION

Our next step was to ensure that each analytical domain contained a sufficient number of households. Assuming a uniform sampling fraction of approximately 1/100, a non-stratified 1,800-household sample would contain around 240 Major Urban households and 170 Other Urban households -too few to sustain representative and significant analyses. We therefore stratified the sample to separate the two urban areas from the rural areas. The rural strata were large enough so that its implicit stratification along agro-ecological and geographical dimensions was sufficient to ensure that these dimensions were represented proportionally to their share of the population. The final sample design by strata was as follows: 450 households in the Major Urban Centers (378 in Dili and 72 in Baucau), 252 households in the Other Urban Centers and 1,098 households in the Rural Areas.

SAMPLING STRATEGY

The sampling of households in each stratum, with the exception of Urban Dili, followed a 3-stage procedure. In the first stage, a certain number of sucos were selected with probability proportional to size (PPS). Hence 4 sucos were selected in Urban Baucau, 14 in Other Urban Centers and 61 in the Rural Areas. In the second stage, 3 aldeias in each suco were selected, again with probability proportional to size (PPS). In the third stage, 6 households were selected in each aldeia with equal probability (EP). This implies that the sample is approximately selfweighted within the stratum: all households in the stratum had the same chance of being visited by the survey.

A simpler and more efficient 2-stage process was used for Urban Dili. In the first stage, 63 aldeias were selected with PPS and in the second stage 6 households with equal probability in each aldeia (for a total sample of 378 households). This procedure reduces sampling errors since the sample will be spread more than with the standard 3-stage process, but it can only be applied to Urban Dili as only there it was possible to sort the selected aldeias into groups of 3 aldeias located in close proximity of each other.

HOUSEHOLD LISTING

The final sampling stage requires choosing a certain number of households at random with equal probability in each of the aldeias selected by the previous sampling stages. This requires establishing the complete inventory of all households in these aldeias - a field task known as the household listing operation. The household listing operation also acquires importance as a benchmark for assessing the quality of the population data collected by the Suco Survey, which was conducted in February-March 2001. At that time, the number of households currently living in each aldeia was asked from the suco and aldeia chiefs, but there are reasons to suspect that these figures are biased. Specifically, certain suco and aldeia chiefs may have answered about households belonging, rather than currently living, in the aldeias, whereas others may have faced perverse incentives to report figures different from the actual ones. These biases are believed to be more serious in Dili than in the rest of the country.

Two operational approaches were considered for the household listing. One is the classical doorto-door (DTD) method that is generally used in most countries for this kind of operations. The second approach - which is specific of Timor-Leste - depends on the lists of families that are kept by most suco and aldeia chiefs in their offices. The prior-list-dependent (PLD) method is much faster, since it can be completed by a single enumerator in each aldeia, working most of the time in the premises of the suco or aldeia chief; however, it can be prone to biases depending on the accuracy and timeliness of the family lists.

After extensive empirical testing of the weaknesses and strengths of the two alternatives, we decided to use the DTD method in Dili and an improved version of the PLD method elsewhere. The improvements introduced to the PLD consisted in clarifying the concept of a household "currently living in the aldeia", both by intensive training and supervision of the enumerators and by making its meaning explicit in the form's wording (it means that the household members are regularly eating and sleeping in the aldeia at the time of the operation). In addition,

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The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

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