Archive:The EU in the world - living conditions
- Data from June - July 2012. Most recent data: Further Eurostat information, Main tables and Database.
This article is part of a set of statistical articles based on Eurostat publication The EU in the world 2013.
The article focuses on the living conditions and social protection in the European Union (EU) and in the 15 non-EU countries from the Group of Twenty (G20). It covers indicators related to income, expenditure, poverty and social protection and gives an insight into the European economy and society in comparison with the major economies in the rest of the world, especially with the EU's counterparts in the so-called Triad, the US and Japan, and with the BRIC countries Brazil, Russia, India and China (or BRICS if South-Africa is also included).
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(% of total)
Source: Eurostat (ilc_lvph03), the United Nations Department of Economic and Social Affairs (Demographic statistics) and national surveys
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(% of total household consumption expenditure)
Source: Eurostat (hbs_str_t211), the United Nations Statistics Division (Economic Statistics Branch) and national household surveys
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(ratio)
Source: Eurostat (ilc_di11), the World Bank (Poverty and Inequality Database) and the OECD (Income Distribution and Poverty)
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(ratio)
Source: Eurostat (ilc_di11), the World Bank (Poverty and Inequality Database) and the OECD (Income Distribution and Poverty)
![](/eurostat/statistics-explained/images/thumb/9/96/EU-G20_Expenditure_on_social_protection%2C_2009_%281%29.png/350px-EU-G20_Expenditure_on_social_protection%2C_2009_%281%29.png)
Source: Eurostat (spr_exp_sum), the OECD (Social Expenditure Database) and the International Labour Organisation (Social Security Department)
Main statistical findings
The growth of cities and urban agglomerations results essentially from migration from rural areas and can be related, among other factors, to industrialisation. In developing economies urban areas may be seen as offering stable employment compared with traditional agricultural practices. Urban and rural areas may offer different opportunities for people, for example, in terms of social mobility and ease of access to diverse economic activities (and related job opportunities), educational possibilities, transport and communication networks, accommodation, as well as leisure and recreational activities. Alongside issues of proximity and choice in terms of the consumption of goods and services, urban and rural areas may also be contrasted in relation to a range of other issues, for example, in terms of living costs, congestion, pollution, crime and poverty.
In recent years Eurostat, with other services of the European Commission, has worked on the development of various territorial typologies based on population size and density. Traditionally, territorial typologies have been based on the classification of administrative units (such as municipalities) according to their population density; this could lead to villages in units with a very small area being classified as urban, whereas large towns in very large administrative units could potentially be considered as rural. A new typology has been introduced that is based on a grid of 1 km² cells which are individually classified according to population size and population density; these standard grids are grouped into clusters which in turn are used to classify administrative units or regions into their degree of urbanisation or into an urban-rural typology. Based on this approach, data for 2006 indicate that 40 % of the EU‑27 population lived in predominantly urban regions, 36 % in intermediate regions, and 24 % in predominantly rural regions.
According to the World Urbanisation Prospects report of the United Nations, globally just over half (52.1 %) of the world’s population lived in urban areas in 2011 and the remainder in rural areas – see Figure 6.1. More than two thirds of the Indian population lived in rural areas in 2011, while in China and Indonesia the urban and rural populations were almost equal in size. In all other G20 members more than half or the population lived in urban areas, ranging from 62.0 % in South Africa, through 73.9 % in the EU‑27 to 92.5 % in Argentina.
Many statistical analyses of social and living conditions focus on households, in other words a person or group of persons living together (but separate from others), regardless of whether they are family members or not. Many factors influence household formation, for example, marriage, divorce, fertility and life expectancy, as well as geographical mobility, and economic and cultural factors. Figure 6.2 shows that more than half of all households in the EU‑27, Japan, the United States, Canada and Australia were one and two person households, whereas the majority of households in India, Turkey, Mexico and Indonesia had four or more persons.
Table 6.1 provides an analysis of the distribution of household consumption expenditure for various purposes. Factors such as culture, income, weather, household composition, economic structure and degree of urbanisation can all influence expenditure patterns. In most G20 members the highest proportion of expenditure was normally devoted to food and nonalcoholic beverages or housing (including also expenditure for water and fuels). A notable exception to this general pattern was the United States where household expenditure on health had the highest share. The share of expenditure on food and non-alcoholic beverages was particularly low in the United States, as it was in Canada and Australia.
Income generally has a major impact on an individual’s living conditions. Figures 6.3 and 6.4 present two commonly used measures for studying income distribution: the income quintile share ratio is calculated as the ratio of the proportion of income received by the 20 % of the population with the highest income (the top quintile) compared with the proportion received by the 20 % of the population with the lowest income; the Gini coefficient measures dispersion (on a range from zero for perfect equality to 1 for maximal inequality) and for income gives a summary measure of income dispersion across all income levels, not just the extremes of the highest and lowest incomes. South Africa, Brazil, Mexico, Argentina and China had the highest income inequality among G20 members according to both of these measures, whereas the EU-27 was among the members with the lowest income inequality.
Figure 6.5 presents a non-monetary indicator for an analysis of the effects of poverty, in this case under-nourishment. For most G20 members the proportion of the population suffering from under-nourishment was around 5 %, with substantially higher proportions in India, Indonesia and China.
Social protection encompasses all interventions from public or private bodies intended to relieve households and individuals from the burden of a defined set of risks or needs. Figure 6.6 shows the level of social protection expenditure in the G20 members relative to GDP and relative to the size of the population; the per capita measure is presented in euro converted at market exchange rates and so does not reflect price level differences in the G20 members.
Data sources and availability
The statistical data were mainly extracted during June and July 2012.
The indicators are often compiled according to international – sometimes global – standards, for example, UN standards for national accounts and the IMF’s standards for balance of payments statistics. Although most data are based on international concepts and definitions there may be certain discrepancies in the methods used to compile the data.
EU‑27 and euro area data
Almost all of the indicators presented for the EU‑27 and EA-17 aggregates have been drawn from Eurobase, Eurostat’s online database. Eurobase is updated regularly, so there may be differences between data appearing in this publication and data that is subsequently downloaded. In exceptional cases some indicators for the EU have been extracted from international sources, for example, when values are expressed in purchasing power parities. Otherwise, European Commission sources have been used.
G20 countries from the rest of the world
For the 15 G20 countries that are not members of the EU, the data presented have generally been extracted from a range of international sources listed in the Introduction. In a few cases the data available from these international sources have been supplemented by data for individual countries from national statistics authorities. For some of the indicators a range of international statistical sources are available, each with their own policies and practices concerning data management (for example, concerning data validation, correction of errors, estimation of missing data, and frequency of updating). In general, attempts have been made to use only one source for each indicator in order to provide a comparable analysis between the countries.
Context
The data on living conditions and social protection shown in this article aims to provide a picture of the social situation covering indicators related to income, expenditure, poverty and social protection. The distribution of income is often used to measure inequalities in society. On the one hand, differences in income may provide an incentive to individuals to improve their situation (for example, through looking for a new job or acquiring new skills). On the other, crime, poverty and social exclusion are often linked to income inequalities.
Further Eurostat information
Publications
- Key data on education in Europe 2012
- The EU in the world 2013
- The European Union and the BRIC countries
Main tables
- Title(s) of second level folder (if any)
- Title(s) of third level folder (if any)
Database
- Title(s) of second level folder (if any)
- Title(s) of third level folder (if any)