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.

Cost of Living Index (Excl. Rent) is a relative indicator of consumer goods prices, including groceries, restaurants, transportation and utilities. Cost of Living Index does not include accommodation expenses such as rent or mortgage. If a city has a Cost of Living Index of 120, it means Numbeo has estimated it is 20% more expensive than New York (excluding rent).

Please refer further to: https://www.numbeo.com/cost-of-living/cpi_explained.jsp for motivation and methodology.

All credits to https://www.numbeo.com .

This dataset would surely help socio-economic researchers to analyse and get deeper insights regarding the life of people country-wise.

Thanks to @andradaolteanu for the motivation! Upwards and onwards...

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.

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.

A table comparing the cost of living in various European Union countries, including expenses for rent, utilities, food, and transportation in major cities

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.

In 2023, Uruguay and Chile had the highest Digital Quality of Life index in Latin America and the Caribbean region, at **** and **** points on a scale from zero to one, respectively. In comparison, Venezuela and Honduras scored the lowest index among the presented countries. The index ranks the quality of digital wellbeing in a country.

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,

Abstract

The Tajik Living Standards Survey (TLSS) was conducted jointly by the State Statistical Agency and the Center for Strategic Studies under the Office of the President in collaboration with the sponsors, the United Nations Development Programme (UNDP) and the World Bank (WB). International technical assistance was provided by a team from the London School of Economics (LSE). The purpose of the survey is to provide quantitative data at the individual, household and community level that will facilitate purposeful policy design on issues of welfare and living standards of the population of the Republic of Tajikistan in 1999.

Geographic coverage

National coverage. The TLSS sample was designed to represent the population of the country as a whole as well as the strata. The sample was stratified by oblast and by urban and rural areas.

The country is divided into 4 oblasts, or regions; Leninabad in the northwest of the country, Khatlon in the southwest, Rayons of Republican Subordination (RRS) in the middle and to the west of the country, and Gorno-Badakhshan Autonomous Oblast (GBAO) in the east. The capital, Dushanbe, in the RRS oblast, is a separately administrated area. Oblasts are divided into rayons (districts). Rayons are further subdivided into Mahallas (committees) in urban areas, and Jamoats (villages) in rural areas.

Analysis unit

• Households
• Individuals
• Communites

Kind of data

Sample survey data [ssd]

Sampling procedure

The TLSS sample was designed to represent the population of the country as a whole as well as the strata. The sample was stratified by oblast and by urban and rural areas.

In common with standard LSMS practice a two-stage sample was used. In the first stage 125 primary sample units (PSU) were selected with the probability of selection within strata being proportional to size. At the second stage, 16 households were selected within each PSU, with each household in the area having the same probability of being chosen. [Note: In addition to the main sample, the TLSS also included a secondary sample of 15 extra PSU (containing 400 households) in Dangara and Varzob. Data in the oversampled areas were collected for the sole purpose of providing baseline data for the World Bank Health Project in these areas. The sampling for these additional units was carried out separately after the main sampling procedure in order to allow for their exclusion in nationally representative analysis.] The twostage procedure has the advantage that it provides a self-weighted sample. It also simplified the fieldwork operation as a one-field team could be assigned to cover a number of PSU.

A critical problem in the sample selection with Tajikistan was the absence of an up to date national sample frame from which to select the PSU. As a result lists of the towns, rayons and jamoats (villages) within rayons were prepared manually. Current data on population size according to village and town registers was then supplied to the regional offices of Goskomstat and conveyed to the center. This allowed the construction of a sample frame of enumeration units by sample size from which to draw the PSU.

This procedure worked well in establishing a sample frame for the rural population. However administrative units in some of the larger towns and in the cities of Dushanbe, Khojand and Kurgan-Tubbe were too large and had to be sub-divided into smaller enumeration units. Fortuitously the survey team was able to make use of information available as a result of the mapping exercise carried out earlier in the year as preparation for the 2000 Census in order to subdivide these larger areas into enumeration units of roughly similar size.

The survey team was also able to use the household listings prepared for the Census for the second stage of the sampling in urban areas. In rural areas the selection of households was made using the village registers – a complete listing of all households in the village which is (purported to be) regularly updated by the local administration. When selecting the target households a few extra households (4 in addition to the 16) were also randomly selected and were to be used if replacements were needed. In actuality non-response and refusals from households were very rare and use of replacement households was low. There was never the case that the refusal rate was so high that there were not enough households on the reserve list and this enabled a full sample of 2000 randomly selected households to be interviewed.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was based on the standard LSMS for the CIS countries, and adapted and abridged for Tajikistan. In particular the health section was extended to allow for more in depth information to be collected and a section on food security was also added. The employment section was reduced and excludes information on searching for employment.

The questionnaires were translated into Tajik, Russian and Uzbek.

The TLSS consists of three parts: a household questionnaire, a community level questionnaire and a price questionnaire.

Household questionnaire: the Household questionnaire is comprised of 10 sections covering both household and individual aspects.

Community/Population point Questionnaire: the Community level or Population Point Questionnaire consists of 8 sections. The community level questionnaire provides information on differences in demographic and economic infrastructure. Open-ended questions in the questionnaire were not coded and hence information on the responses to these qualitative questions is not provided in the data sets.

Summary of Section contents

The brief descriptions below provide a summary of the information found in each section. The descriptions are by no means exhaustive of the information covered by the survey and users of the survey need to refer to each particular section of the questionnaire for a complete picture of the information gathered.

Household information/roster This includes individual level information of all individuals in the household. It establishes who belongs to the household at the time of the interview. Information on gender, age, relation to household head and marital status are included. In the question relating to family status, question 7, “Nekared” means married where nekar is the Islamic (arabic) term for marriage contract. Under Islamic law a man may marry more than once (up-to four wives at any one time). Although during the Soviet period it was illegal to be married to more than one woman this practice did go on. There may be households where the household head is not present but the wife is married or nekared, or in the same household a respondent may answer married and another nekared to the household head.

Dwelling This section includes information covering the type of dwelling, availability of utilities and water supply as well as questions pertaining to dwelling expenses, rents, and the payment of utilities and other household expenses. Information is at the household level.

Education This section includes all individuals aged 7 years and older and looks at educational attainment of individuals and reasons for not continuing education for those who are not currently studying. Questions related to educational expenditures at the household level are also covered. Schooling in Tajikistan is compulsory for grades (classes) 1-9. Primary level education refers to grades 1 - 4 for children aged 7 to 11 years old. General secondary level education refers to grades 5-9, corresponding to the age group 12-16 year olds. Post-compulsory schooling can be divided into three types of school: - Upper secondary education covers the grades 10 and 11. - Vocational and Technical schools can start after grade 9 and last around 4 years. These schools can also start after grade 11 and then last only two years. Technical institutions provide medical and technical (e.g. engineering) education as well as in the field of the arts while vocational schools provide training for employment in specialized occupation. - Tertiary or University education can be entered after completing all 11 grades. - Kindergarten schools offer pre-compulsory education for children aged 3 – 6 years old and information on this type of schooling is not covered in this section.

Health This section examines individual health status and the nature of any illness over the recent months. Additional questions relate to more detailed information on the use of health care services and hospitals, including expenses incurred due to ill health. Section 4B includes a few terms, abbreviations and acronyms that need further clarification. A feldscher is an assistant to a physician. Mediniski dom or FAPs are clinics staffed by physical assistants and/or midwifes and a SUB is a local clinic. CRH is a local hospital while an oblast hospital is a regional hospital based in the oblast administrative centre, and the Repub. Hospital is a national hospital based in the capital, Dushanbe. The latter two are both public hospitals.

Employment This section covers individuals aged 11 years and over. The first part of this section looks at the different activities in which individuals are involved in order to determine if a person is engaged in an income generating activity. Those who are engaged in such activities are required to answer questions in Part B. This part relates to the nature of the work and the organization the individual is attached to as well as questions relating to income, cash income and in-kind payments. There are also a few questions relating to additional income generating activities in addition to the main activity. Part C examines employment

Household furnishings, consumer habits, evaluation of country image and general attitude to the EEC.

Topics: 1. consumption and furnishing questions: assessment of personal as well as national economic situation in the last 5 years; relative assessment of the standard of living in one´s country, compared with the other countries; detailed recording of type, age and repeated acquisition of durable economic goods; country image regarding product, price and fashion; judgement on quantitative product selection from abroad; residential furnishings; having a yard; type of film used for camera and film use in the last year; flash pictures.

1. questions on car: possession of delivery vehicle and car, organized according to number, brand, model, form of vehicle, displacement and year of manufacture; new purchase or used car; car radio possession und kilometers driven annually; getting gas self-service; personally conducting vehicle maintenance and use of car cleansers as well as car wax; possession of bicycle.

2. detailed recording of drinking habits with softdrinks, beer, wine and schnapps.

3. attitude to the EEC: knowledge about the member countries of the EEC; countries that should join the EEC; countries that have drawn the greatest or the least benefit from the EEC; EEC membership for the benefit of the country and to raise the standard of living; most important political goals of the EEC.

4. socio-cultural attitudes: attitude to law-breakers; social justice; social and ethnic tolerance; general attitude to young people and older people.

5. attitude to advertising: purchase of a watch during the last five years and price paid for it; activities and jobs conducted oneself in the household; attitude to fashion (scale); social prestige of selected occupations; church attendance on Christmas Day; desire for a life 50 years from now; number of rooms with carpeting.

6. leisure time and further education: knowledge of a foreign language; television habits and reading habits with magazines; total reading times and whereabouts of the magazines; number of books read and bought in the last year; book price; manner of book purchase (mail-order or bookstore); pet possession and manner as well as extent of obtaining feed; participation in further education courses and motives for this; vacation behavior; vacation destinations abroad; package tours; relatives and friends traveling along; trip duration; trip costs; means of transport used; trips by airplane; scheduled or charter flight; frequency of trips to the hairdresser; (among women: use of toiletries and cosmetics); (among men: use of washing and shaving utensils; custom-made or off-the-shelf suit; type of store and price of the last suit purchased); use or provisions of nutrition and semi-luxury foods, tobacco and alcohol; use of dish-washing liquids and household cleansers or cleaning products; use of communal washing machines or use of a laundry; age of one´s own washing machine; forms of assets and bank account possession; second home; Readers´ Digest subscriber.

Demography: age; sex; marital status; religious denomination; occupational position; employment; company size; household income; possession of durable economic goods; composition of household; respondent is head of household; characteristics of head of household; housing situation; residential status; degree of urbanization.

Interviewer rating: social class of respondent; weekday of interview.

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'.

Household furnishings, consumer habits, evaluation of country image and general attitude to the EEC.

Topics: 1. consumption and furnishing questions: assessment of personal as well as national economic situation in the last 5 years; relative assessment of the standard of living in one´s country, compared with the other countries; detailed recording of type, age and repeated acquisition of durable economic goods; country image regarding product, price and fashion; judgement on the quantitative product selection from abroad; residential furnishings; having a yard; film used for camera and film use in the last year; flash pictures.

1. questions on car: possession of delivery vehicle and car, organized according to number, brand, model, form of vehicle, displacement and year of manufacture; new purchase or used car; car radio possession and kilometers driven annually; getting gas self-service; personally conducting vehicle maintenance and use of car cleanser as well as car wax; possession of bicycle.

2. detailed recording of drinking habits with softdrinks, beer, wine and schnapps.

3. attitude to the EEC: knowledge about the member countries of the EEC; countries that should join the EEC; countries that have drawn the greatest or the least benefit from the EEC; EEC membership for the benefit of the country and to raise the standard of living; most important political goals of the EEC.

4. socio-cultural attitudes: attitude to law-breakers; social justice; social and ethnic tolerance; general attitude to young people and older people.

5. attitude to advertising: purchase of a watch during the last five years and price paid for it; activities and jobs conducted oneself in the household; attitude to fashion (scale); social prestige of selected occupations; church visit on Christmas Day; desire for a life 50 years from now; number of rooms with carpeting.

6. leisure time and further education: knowledge of a foreign language; television habits and reading habits with magazines; total reading times and whereabouts of the magazines; number of books read and bought in the last year; book price; manner of book purchase (mail-order or bookstore); pet possession and manner as well as extent of obtaining feed; participation in further education courses and motives for this; vacation behavior; vacation destinations abroad; package tours; relatives and friends traveling along; trip duration; trip costs; means of transport used; trips by airplane; scheduled or charter flight; frequency of trips to the hairdresser; (among women: use of toiletries and cosmetics); (among men: use of washing and shaving utensils; custom-made or off-the-shelf suit; type of store and price of suit last purchased); use or provisions of nutrition and semi-luxury foods, tobacco and alcohol; use of dish-washing liquids and household cleansers or cleaning products; use of communal washing machines or use of a laundry; age of one´s own washing machine; forms of assets and bank account possession; second home; Readers´ Digest subscriber.

Demography: age; sex; marital status; religious denomination; occupational position; employment; company size; household income; possession of durable economic goods; composition of household; respondent is head of household; characteristics of head of household; housing situation; residential status; degree of urbanization.

Interviewer rating: social class of respondent; weekday of interview.

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 health dimension is assessed by life expectancy at birth, the education dimension is measured by mean of years of schooling for adults aged 25 years and more and expected years of schooling for children of school entering age. The standard of living dimension is measured by gross national income per capita. The HDI uses the logarithm of income, to reflect the diminishing importance of income with increasing GNI. The scores for the three HDI dimension indices are then aggregated into a composite index using geometric mean. Refer to Technical notes for more details. The HDI simplifies and captures only part of what human development entails. It does not reflect on inequalities, poverty, human security, empowerment, etc. The HDRO offers the other composite indices as broader proxy on some of the key issues of human development, inequality, gender disparity and poverty. A fuller picture of a country's level of human development requires analysis of other indicators and information presented in the statistical annex of the report.

1199 persons were interviewed in the FRG, 1228 in France, 1178 in Great Britain, 1164 in Italy and 500 in Greece. The study has the USIA-designation XX-17. The USIA-Studies of the XX-Series (international relations) from XX-2 to XX-18 are archived under ZA Study Nos. 1969-1976 as well as 2069-2074 and 2124-2127.

Gross domestic product (GDP) per capita is a crucial economic indicator that represents the average economic output per person in a given country or region. It is calculated by dividing the total GDP by the population size. This metric is often used to compare the economic performance of different countries and assess the relative prosperity of their citizens. Two commonly used versions of this indicator are GDP per capita at current prices and GDP per capita adjusted for purchasing power parity (PPP). GDP per capita at current prices reflects the total economic output of a country divided by its population, using the market prices of goods and services at the time of measurement. This metric provides a snapshot of the economic activity within a country without adjusting for inflation or differences in the cost of living across regions. Global GDP per capita at current prices (PPP) provides a measure of the average economic output per person, adjusted for the differences in the cost of living between countries. This adjustment allows for a more accurate comparison of living standards and economic productivity across different nations.

Vietnam HSS: HS: Quintile 2: Whole Country data was reported at 3.930 Person in 2014. This records a decrease from the previous number of 3.990 Person for 2012. Vietnam HSS: HS: Quintile 2: Whole Country data is updated yearly, averaging 4.300 Person from Dec 2002 (Median) to 2014, with 7 observations. The data reached an all-time high of 4.690 Person in 2002 and a record low of 3.930 Person in 2014. Vietnam HSS: HS: Quintile 2: Whole Country data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.H021: Household Living Standard Survey (HSS): Household Size .

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Effective governments improve people's standard of living by ensuring access to essential services – health, education, water and sanitation, electricity, transport – and the opportunity to live and work in peace and security. Data here includes World Bank staff assessments of country performance in economic management, structural policies, policies for social inclusion and equity, and public sector management and institutions for the poorest countries. Also included are indicators on revenues and expenses from the International Monetary Fund's Government Finance Statistics, and on tax policies from various sources.

Household furnishings, consumer habits, evaluation of country image and general attitude to the EEC.

Topics: 1. consumption and furnishing questions: assessment of personal as well as national economic situation in the last 5 years; relative assessment of the standard of living in one´s country, compared with the other countries; detailed recording of type, age and repeated acquisition of durable economic goods; country image regarding product, price and fashion; judgement on the quantitative product selection from abroad; residential furnishings; having a yard; type of film used for camera and film use in the last year; flash pictures.

1. questions on car: possession of delivery vehicle and car, organized according to number, brand, model, form of vehicle, displacement and year of manufacture; new purchase or used car; car radio possession and kilometers driven annually; getting gas self-service; personally conducting vehicle maintenance and use of car cleansers as well as car wax; possession of bicycle.

2. detailed recording of drinking habits with softdrinks, beer, wine and schnapps.

3. attitude to the EEC: knowledge about the member countries of the EEC; countries that should join the EEC; countries that have drawn the greatest or the least benefit from the EEC; EEC membership for the benefit of the country and to raise the standard of living; most important political goals of the EEC.

4. socio-cultural attitudes: attitude to law-breakers; social justice; social and ethnic tolerance; general attitude to young people and older people.

5. attitude to advertising: purchase of a watch during the last five years and price paid for it; activities and jobs conducted oneself in the household; attitude to fashion (scale); social prestige of selected occupations; church attendance on Christmas Day; desire for a life 50 years from now; number of rooms with carpeting.

6. leisure time and further education: knowledge of a foreign language; television habits and reading habits with magazines; total reading times and whereabouts of the magazines; number of books read and bought in the last year; book price; manner of book purchase (mail-order or bookstore); pet possession and manner as well as extent of obtaining feed; participation in further education courses and motives for this; vacation behavior; vacation destinations abroad; package tours; relatives and friends traveling along; trip duration; trip costs; means of transport used; trips by airplane; scheduled or charter flight; frequency of trips to the hairdresser; (among women: use of toiletries and cosmetics); (among men: use of washing and shaving utensils; custom-made or off-the-shelf suit; type of store and price of suit last purchased); use or provisions of nutrition and semi-luxury foods, tobacco and alcohol; use of dish-washing liquids and household cleansers or cleaning products; use of communal washing machines or use of a laundry; age of one´s own washing machine; forms of assets and bank account possession; second home; Readers´ Digest subscriber.

Demography: age; sex; marital status; religious denomination; occupational position; employment; company size; household income; possession of durable economic goods; composition of household; respondent is head of household; characteristics of head of household; housing situation; residential status; degree of urbanization.

Interviewer rating: social class of respondent; weekday of interview.

Vietnam HSS: LPH: Quintile 2: Whole Country data was reported at 2.400 Person in 2014. This records a decrease from the previous number of 2.500 Person for 2012. Vietnam HSS: LPH: Quintile 2: Whole Country data is updated yearly, averaging 2.600 Person from Dec 2006 (Median) to 2014, with 5 observations. The data reached an all-time high of 2.600 Person in 2010 and a record low of 2.400 Person in 2014. Vietnam HSS: LPH: Quintile 2: Whole Country data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.H022: Household Living Standard Survey (HSS): Laborers Per Household .

The Candidate Countries Eurobarometer (CCEB) series, first conducted in 2001, gathers information from the countries applying to become members of the European Union (EU) in a way that allows direct comparison with the standard Eurobarometer series carried out in the existing EU countries. The CCEB provides decision-makers and the European public with opinion data on the similarities and differences between the EU and candidate countries. The CCEB continuously tracks support for EU membership in each country and records changes in attitudes related to European issues in the candidate countries. This round of the CCEB survey was conducted between March 1 and April 5, 2002, in the candidate countries: Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia, Slovenia, and Turkey. The survey first asked respondents three questions in regard to European Union membership. In addition to these questions, respondents were queried on the following major areas of focus: (1) quality of life indicators and life satisfaction, (2) family and children, (3) elderly people, (4) lifestyle and health , (5) access to and quality of social services, (6) household income and standard of living, (7) social protection, inclusion, and exclusion, (8) social and political participation and integration, (9) employment, unemployment, and quality of work, and (10) regional mobility. For the first major area of focus, quality of life indicators and life satisfaction, respondents were questioned about life satisfaction in the past, present, and near future, and particular factors which contribute to or improve their present quality of life. For the second major area of focus, family and children, respondents provided their views in regard to the ideal number of children for a family, decision-making in having a child, age at birth of first child, parental and family roles, and the role of government in improving life for families with children. For the third major area of focus, elderly people, respondents gave their opinion on who should care for elderly persons, as well as who should pay for their care. The survey also asked respondents whether they cared for an individual who has a long-term illness, or who is handicapped or elderly, in-home or outside the home. For the fourth major area of focus, lifestyle and health, respondents were queried about their current lifestyle and whether they had any long-term illness and/or handicap that limits their activities in any way. For the fifth major area of focus, access to and quality of social services, respondents provided feedback about their distance from a particular service or business, their satisfaction with the health and social services in their country, and whether the local or national government, private companies, or associations should provide certain services. For the sixth major area of focus, household income and standard of living, questions asked of respondents included the lowest net monthly income level their household would need in order to make a living, their appraisal of the current household income situation, whether any household member had difficulties in paying the bills, and their ability to save and invest. The survey also queried respondents about their current standard of living, and whether and how they are improving their standard of living. For the seventh major focus, social protection, inclusion, and exclusion, respondents provided their ideas about necessities of the good life, their opinion as to whether they could rely on anyone outside the home for certain problems, and their views on social exclusion, poverty, and the state of the area in which they live within their country. In addition, the respondents were asked about their response to the poor or socially excluded, which entities provide the most help to these individuals versus who should do so, the reasons why people are poor or socially excluded, as well as the extent of social disparities in their country and government's role in reducing these disparities. For the eighth major area of focus, social and political participation and integration, respondents were asked about their participation in social, community, political, and advocacy groups or organizations. For the ninth major area of focus, employment, unemployment, and quality of work, the survey qu