Quality of life indicators - material living conditions


Data extracted in January 2018.

Planned update: February 2019.

Highlights


Almost one quarter of the EU-28 population were living in households that had difficulties to make ends meet in 2016, compared with just over a fifth where it was easy to make ends meet.

In 2016, 16.6 % of the EU-28 population were living in overcrowded households, while more than one third (34.8 %) were living in under-occupied dwellings.


Median equivalised disposable income, 2016

This article is part of a Eurostat online publication that focuses on Quality of life indicators, providing recent statistics for the European Union (EU). The publication presents a detailed analysis of various dimensions that can form the basis for a more profound analysis of the quality of life, complementing gross domestic product (GDP) which has traditionally been used to provide a general overview of economic and social developments.

The focus of this article is the first dimension — material living conditions — of the nine quality of life indicators that form part of a framework endorsed by an expert group on quality of life indicators. Even for those dimensions which extend beyond the material cost of living, an individual’s quality of life is often constrained by economic (monetary) factors, as material resources can often be transformed into well-being in line with each individual’s preferences and capabilities. That said, material living standards should not be viewed exclusively in quantitative monetary terms, as consumption patterns, material deprivation and housing conditions may also play a considerable role in determining an individual’s subjective well-being (life satisfaction, happiness, having a meaning to life).


Full article


General overview

The European economic model of social transfers has been designed to reduce poverty and social exclusion. Nevertheless, there are still wide discrepancies and inequalities in terms of material living standards, both between EU Member States, as well as within them (for example, between different population subcategories, such as an analysis by age or by household type shows). In 2016, almost one in three Bulgarians faced severe material deprivation, while less than 1.0 % of all citizens in Sweden had the same problem. On the other hand, 46.0 % of single parents with dependent children in Luxembourg were at risk of poverty, compared with 16.5 % of the total population.

In general, the risk of poverty and social exclusion is much higher in southern and eastern Europe than it is in most of the western and Nordic Member States, while income inequality is generally much less prevalent in the Nordic and the Benelux countries than it is in most of southern and eastern Europe and the Baltic Member States. However, some exceptions to these general patterns also exist: for example, the lowest risk of poverty was found in the Czech Republic, while inequality in Luxembourg — the richest EU Member State in terms of disposable income — was at a moderate level. Regarding housing conditions, while it was commonplace for much of the population in eastern Europe to be living in overcrowded housing (with the exception of the Czech Republic, Estonia and Slovenia), it was also true that a relatively high proportion of disadvantaged groups in some parts of western Europe were living in low-quality housing (for example, almost a third of single parents in Belgium lived in a dwelling with structural problems).

Income

In 2016, median equivalised disposable income in the EU-28 was 16 452 purchasing power standard (PPS). It varied widely across the EU Member States, from 4 794 PPS in Romania to 28 071 PPS in Luxembourg. As shown in Map 1, there was a relatively clear geographical divide: median levels of equivalised disposable income were over 16 000 PPS in the Nordic and the western Member States; they were also above this level in Malta. By contrast, median equivalised disposable income was below 16 000 PPS in all of the Member States which joined the EU after 2004 except for Malta, as well as in three southern Member States — Greece, Spain and Portugal — each of which saw its level of income fall considerably as a result of the global financial and economic crisis and subsequent sovereign debt crisis.

This geographical pattern was repeated among non-member countries (note the latest data for Iceland, the former Yugoslav Republic of Macedonia and Turkey are for 2015), insofar as Iceland, Norway and Switzerland all recorded median levels of equivalised disposable income that were considerably higher than the EU-28 average, while incomes were much lower (approximately one third of the EU-28 average) in Turkey, Serbia and the former Yugoslav Republic of Macedonia.

Map 1: Median equivalised disposable income, 2016
(PPS)
Source: Eurostat (ilc_di03)

A comparison of median equivalised disposable income levels between 2008 and 2016 is presented in Figure 1. In the vast majority of the EU Member States for which data are available (no comparison available for Croatia), the median level of income rose during the period under consideration. However, there was a marginal reduction in the level of median income in Ireland, as well as larger reductions in the United Kingdom, Cyprus and particularly Greece, where the median income fell by 3 204 PPS; three of these four economies were particularly affected by the crises. Note also that Iceland recorded a reduction in its level of median income between 2008 and 2015.

At the other end of the scale, the highest increases in median equivalised disposable incomes — in both relative and absolute terms — were recorded in Estonia and Poland. Median equivalised disposable income rose by more than 4 000 PPS in both of these EU Member States between 2008 and 2016, which was also the case for Belgium. In relative terms, the median income in Poland rose overall by 61.2 % during the period under consideration, while the corresponding growth in Estonia was 56.8 %; in Romania and Slovakia there were also growth rates in excess of 50 %.

Figure 1: Median equivalised disposable income, 2008 and 2016
(PPS)
Source: Eurostat (ilc_di03)

Income distribution and inequality

How do we measure income inequality?

While median disposable income is a useful indicator for analysing the purchasing power of an average citizen (and therefore indicative of their overall material living standards), it is the distribution of income and wealth that determines by which extent individuals have equal access to the goods and services produced within an economy. Alongside the allocation of resources (in other words, the distribution of income between different groups), individuals may also be concerned by subjective perceptions of inequality as an evaluation of ‘social fairness’. This is usually measured as a relative concept, as individuals compare their own situation with that of their peers, therefore relative income measures are also important in a quality of life framework.

The income quintile share ratio, often referred to as the ‘S80/S20 ratio’, is a basic measure of income distribution. It is defined as the ratio of the total income received by the top quintile (in other words, the 20 % of the population with the highest incomes) to that received by the bottom quintile (in other words, the 20 % of the population with the lowest incomes). For example, an S80/S20 ratio of six means that people at the top of the income scale earn on average six times more than those at the bottom. While it does not convey information on the distribution of income across all economic groups, this indicator provides a convenient means of comparing income inequalities over time and/or across countries.

In 2016, the income quintile share ratio in the EU-28 was 5.2 (see Map 2). The Czech Republic, Finland, Slovakia, Slovenia, Belgium and the Netherlands were the most egalitarian EU Member States (on the basis of this measure), each with a ratio in the range of 3.5 to 3.9. Income inequalities were much higher in the Baltic and Balkan Member States, as well as in southern Europe, with this ratio peaking at more than 7.0 in Bulgaria, Romania and Lithuania.

It is interesting to note a general pattern whereby the EU Member States in the top income distribution quintile that recorded the highest levels of median equivalised disposable income tended to have relatively low levels of income inequality. There were however some exceptions to these patterns, for example, Luxembourg — the EU Member State with the highest disposable income per inhabitant — registered a medium level of inequality, while income inequality was lowest in the Czech Republic, a country with modest levels of disposable income compared with some of the other Member States.

Map 2: Inequality of income distribution, 2016
(income quintile share ratio)
Source: Eurostat (ilc_di11)

Evolution of income inequality in the European Union over time

An analysis for the period 2008 to 2016 reveals that income inequalities fell during this period in 11 of the 27 EU Member States for which data are available (no comparison available for Croatia). The largest falls were recorded in Latvia, where recent years have seen minimum wages as a share of median income increase. The next largest falls were recorded in the United Kingdom, where a national minimum wage was first introduced in 1999, followed by a series of progressive changes that led to a widening of the age groups covered by the scheme and the introduction of a national living wage. By contrast, there was a widening of income inequalities in a majority of the Member States between 2008 and 2016 and this was most apparent in Bulgaria, Italy, Spain and Lithuania, which, by 2016, had some of the highest levels of income inequality in the EU (see Figure 2).

Figure 2: Inequality of income distribution, 2008 and 2016
(income quintile share ratio)
Source: Eurostat (ilc_di11)

Income inequalities are lower among the elderly than among younger people: in the EU-28 in 2016, the income share ratio was 5.4 for people aged less than 65, and 4.1 for people aged 65 years and over (see Figure 3). This might be expected insofar as most individuals face a reduction in their overall level of income once they have retired and in some countries state pensions are capped. This pattern of less inequality among the elderly was observed in most of the EU Member States, with the only exceptions in 2016 being France and Slovenia; for both of these, the difference between the ratios for the two age groups was negligible. The discrepancy between income quintile share ratios for these two age groups was much wider in Bulgaria, Greece and Romania (where the inequality of income distribution was approximately twice as high among those aged less than 65 years as it was for the subpopulation aged 65 and over; a similar pattern, although less marked, was also witnessed in Spain, Italy, and all three of the Baltic Member States.

Figure 3: Inequality of income distribution, by age group, 2016
(income quintile share ratio)
Source: Eurostat (ilc_di11)

Risk of poverty

A relative measure of poverty

While poverty is an intuitively familiar concept, its statistical measurement raises methodological difficulties, especially when examined as a dimension in relation to the quality of life. Poverty may be simply defined as the practical difficulty to satisfy basic needs and achieve a decent living standard. However, as inferred above, poverty has both a multi-dimensional nature and is a relative concept, as individuals strive to achieve a minimum standard of living through the interplay between income distribution, consumption patterns and wealth. The issue of poverty measurement is a complex one, not only because of the difficulties in defining it unambiguously. Ideally all three dimensions (income, consumption and wealth) should be measured using the same data source, in order to identify vulnerable populations better. Moreover, in a statistical sense, poverty can be measured either in absolute terms (against a predefined set of basic needs) or in relative terms (against an average level that varies from one economy to another). Indeed, both objective and subjective measures should ideally be used: for example, the share of the population that is at risk of poverty is a relative and objective indicator, the severe material deprivation rate is an absolute and objective measure, whereas the ability to face unexpected financial expenses is a subjective measure.

Within the EU, policymakers have tended to adopt a relative approach based on income (after social transfers) so as to reflect the notion that poverty is related to social exclusion. By doing so, the risk of poverty can be measured in economic terms as persistent conditions under which a person cannot afford to participate fully in the society in which they live. According to this approach, a person’s risk-of-poverty is conventionally set at 60 % of the national median equivalised disposable income; as such, this poverty threshold is different in each country. Since it is directly related to median equivalised disposable income, the monetary value for the at-risk-of-poverty threshold not only varies between countries, but also over time.

Counter-intuitive effects of using a relative poverty measure

Note that a country that demonstrates a higher percentage of its population at risk of poverty may nevertheless have considerably higher overall levels of disposable income, even for the part of the population lying below the risk of poverty threshold. For example, in 2016 the Czech Republic had a very low at-risk-of-poverty rate, at 9.7 %, based on a poverty threshold of 7 508 PPS for a single person household. At the same time, Luxembourg had a higher at-risk-of-poverty rate of 16.5 %, but with a poverty threshold that was more than double that recorded in the Czech Republic, at 16 843 PPS. As such, while relative poverty is about the number or share of people who have low incomes relative to those in the middle of the income distribution, income inequality measures are concerned with differences in income levels across the whole of the income distribution. Note that there is no arithmetic reason why there should be a share of people living in relative poverty below 60 % of the national median equivalised income level (after social transfers).

Other counter-intuitive effects may occur over time, especially in periods of rapid economic change, such as those witnessed during the global financial and economic crisis. For example, the risk of poverty threshold in Greece peaked at 7 559 PPS in 2010, after which it fell back to 5 166 PPS by 2014. The effect of this economic change (a considerable downturn in economic activity) on the risk of poverty, as statistically defined, depends on the distribution of changes in income across the different sections of society. With no major change in population numbers, a fall in the overall (aggregate) level of income, will lead to a reduction in the median level of equivalised disposable income and therefore a lowering of the poverty threshold. Consequently, and perhaps counter-intuitively, this may lead to a lower risk-of-poverty rate (in relative terms), even though there could be an increase in the number of people finding it difficult to make ends meet. Similarly, an increase in median disposable income may lead to a rise in poverty rates, if this increase is not uniformly shared across different socioeconomic groups. For this reason, comparisons over time may be based on anchoring the poverty threshold at a specific point in time (for example, the height of an economic crisis). By contrast, the main advantage of the at-risk-of-poverty rate is that it takes into account the fact that, even in periods of growth, some parts of the population may find themselves increasingly in difficulties or left behind, when compared with the rest of society.

Reducing the number of people at risk-of-poverty: An EU goal

Within the EU, policymakers have focused on reducing the number of people at risk of poverty or social exclusion by at least 20 million between 2008 and 2020. Note that this overall indicator covers the situation of people who are at-risk-of-poverty but also includes people who are severely materially deprived and/or people living in a household with very low work intensity; the first two of these three indicators are analysed in this article, as they form part of the most recent quality of life framework.

In 2016, there were 118.0 million persons at risk of poverty or social exclusion in the EU-28, equivalent to 23.5 % of the total population, compared with 23.7 % in 2008 (excluding Croatia for which the figures are not available before 2010). During the period from 2008 to 2016, there was initially a relatively sharp increase in the number of people who were at-risk-of-poverty or social exclusion, due largely to the impact of the global financial and economic crisis. However, since 2012 there have been modest reductions in both the absolute number and the proportion of the EU-28 population facing such risks, and by 2016 the cumulative difference (compared with 2008) was an additional 806 thousand persons at risk of poverty or social exclusion.

Figure 4 shows information pertaining to people who were exclusively at risk of poverty. In 2016, 17.3 % of the EU-28 population faced such a risk — in other words, they had a level of income that was less than 60 % of the national median for the country where they lived. There were eight EU Member States in 2016 which reported that more than one fifth of their population was at-risk-of-poverty: Romania (which had the highest rate, 25.2 %), Bulgaria, the Baltic Member States, Spain, Greece and Italy. By contrast, the lowest relative risk of poverty was recorded in the Czech Republic (9.7 %), the only Member State to record a single-digit share, with relatively low shares also recorded in Finland (11.6 %) and Denmark (11.9 %).

Proportion of people earning at least 130 % of median income

This relative poverty measure may be contrasted with information on those people at the upper end of the income distribution, as measured by the proportion of the population having an income level that was at least 130 % of median income (see also Figure 4). This is of particular relevance as it allows an analysis of those EU Member States which had a relatively high (or low) share of their population close to the middle of the income distribution.

On average, almost three tenths (29.7 %) of the EU-28 population had a level of income that was at least 30 % higher than the median. Income inequalities (using this measure) were generally quite large in the Baltic, Balkan and several Mediterranean Member States, mirroring the results for the risk of poverty — in other words, they displayed a polarised situation with both high shares of people at risk of poverty and high proportions of people earning considerably more than the median level of income. Ireland and the United Kingdom were also characterised by having quite large shares of their populations having incomes that were at least 30 % higher than the national median. By contrast, income inequalities were less marked in the Netherlands, Finland, Slovenia, Denmark, Slovakia and the Czech Republic. In all six of these EU Member States, a relatively high share of the population — more than 60 % — had a level of income that was close to the national median. This was particularly true in the Czech Republic, where almost two thirds (64.8 %) of the population had an income level that was between 60 % and 130 % of the national median.

Figure 4: At-risk-of-poverty rate and proportion of the population having a relatively high income, 2016
(%)
Source: Eurostat (ilc_li03) and (ilc_di20)

At risk of poverty rates were systematically much higher for single-parent households than they were for the overall population

An analysis of the risk of poverty by household type (see Table 1) provides an example of the type of information that may be used to identify the most vulnerable groups in society in order to target them with appropriate, supportive policies. For example, at risk of poverty rates were systematically much higher for single-parent households than they were for the overall population: in 2016, the risk of poverty among people living in single-parent households in the EU-28 was 34.0 % (compared with an average of 17.3 % for the total population). This pattern was repeated in each of the EU Member States and it is interesting to note that the risk of poverty remained high for people living in single-parent households even among Member States where the overall risk of poverty was low. For example, the risk of poverty for single-parent households in the Czech Republic was (at 37.0 %) almost four times as high as the risk experienced by the whole population (9.7 %), the biggest relative difference among any of the Member States.

A similar, although less pronounced pattern, was often repeated for people living in households composed of two adults with three or more dependent children. Across the whole of the EU-28, their risk of poverty was 26.9 % in 2016, compared with an average of 17.3 % for the total population. There were however three EU Member States where the risk of poverty among people living in households composed of two adults with three or more dependent children was lower than average for the total population: Slovenia, Finland and Denmark. By contrast, the risk of poverty for people living in households composed of two adults with three or more dependent children reached 70.5 % in Bulgaria, which was more than three times as high as the national average.

Table 1: At-risk-of-poverty rate, by type of household, 2016
(%)
Source: Eurostat (ilc_li03)

Severe material deprivation

While the risk of poverty is based on a relative poverty definition, material deprivation provides a complementary view, based on objective and absolute criteria. Material deprivation refers to a state of economic strain, defined as the enforced inability to afford a set of indicative material standards, considered by most people to be desirable or even necessary to lead an adequate life. These include the inability to afford: mortgage or rent payments, utility bills, hire purchase instalments or other loan payments; a one-week annual holiday away from home; a meal involving meat, fish or a protein equivalent every second day; unexpected financial expenses; a telephone (including mobile); a colour television; a washing machine; a car; heating to keep the home adequately warm. The severe material deprivation rate is defined as the share of the population that is unable to afford at least four of the above-mentioned items.

In 2016, the severe material deprivation rate in the EU-28 was 7.5 %; this marked a reduction of 0.9 percentage points compared with the situation in 2008. In a majority (19) of the EU Member States, the severe material deprivation rate was in single digits, with only Slovakia and Portugal recording single-digit rates above the EU-28 average. There were four Member States where the rate was within the range of 2.0-3.0 % — namely, Finland, the Netherlands, Denmark and Austria — with even lower rates in Luxembourg (1.6 %) and most notably Sweden (0.8 %). At the other end of the range, the severe material deprivation rate was within the range of 12.0-14.0 % in Italy, Croatia, Latvia, Lithuania and Cyprus, reaching 16.2 % in Hungary, 22.4 % in Greece, 23.8 % in Romania and a peak of 31.9 % in Bulgaria.

In a majority of the EU Member States there was a relatively small change in the proportion of the population that faced severe material deprivation between 2008 and 2016. However, there was a marked reduction in rates for Poland (-11.0 percentage points), Bulgaria (-9.3 points), Romania (-8.9 points) and Latvia (-6.5 points). By contrast, the severe material deprivation rate doubled in Greece between 2008 and 2016, rising from 11.2 % to 22.4 %, while there were relatively large increases in several other southern Member States, most noticeably Italy (up 4.6 points) and Cyprus (up 4.5 points).

Figure 5: Severe material deprivation rate, 2008 and 2016
(%)
Source: Eurostat (ilc_mddd11)

Making ends meet, a subjective indicator of poverty

Poverty and social exclusion can also be measured in a subjective way. One indicator that may be used to analyse these issues is the difficulty that people experience in making ends meet; this provides a self-reported measure related to poverty. Almost one quarter (24.1 %) of the EU-28 population lived in households that perceived that they had either difficulty or great difficulty to make ends meet in 2016 (see Figure 6). There were wide variations between EU Member States, with more than half the population in Croatia, Cyprus and Bulgaria facing difficulty or great difficulty in making ends meet, a share that rose to more than three quarters (76.8 %) in Greece. By contrast, there were 11 Member States where less than one fifth of the total population was living in a household that faced difficulty or great difficulty in making ends meet; this share was 10.0 % or less in Denmark, Sweden, Germany and Finland. By contrast, just over one fifth of the EU-28 population was living in a household where it was easy or very easy to make ends meet in 2016. This share rose to more than one third of the total population in Belgium and Luxembourg, and was higher still in Denmark, Finland, Germany and Sweden, with more than half (53.1 %) of the population in the Netherlands living in a household that perceived it as easy or very easy to make ends meet.

Looking at the distribution across EU Member States, a very low share (28.5 %) of the population in Estonia faced either difficulty/great difficulty or found it easy/very easy to make ends meet in 2016; as such, the vast majority of its population (71.5 %) was concentrated in the middle of the distribution. This pattern was repeated, to a lesser degree, in Lithuania, France, the Czech Republic and Malta, where a relatively small share of the population was at either end of the distribution. By contrast, the difficulty of making ends meet was more polarised in Greece, Bulgaria, Cyprus and the Netherlands. For the first three of these, the vast majority of the population faced difficulty/great difficulty in making ends meet, whereas in the Netherlands the opposite situation arose, namely, that a high share of the population found it easy/very easy to make ends meet.

Figure 6: Proportion of the population living in households, by difficulty of making ends meet, 2016
(%)
Source: Eurostat (ilc_mdes09)

Housing conditions

Overcrowding rate and under-occupied dwellings

Housing conditions have an important impact on the quality of life. Low quality housing may be associated with reduced well-being and increased levels of psychological stress [1] and it is therefore of interest to analyse these aspects as a complement to information on material deprivation. There are several aspects of an objective nature that may form the basis for an evaluation of housing conditions in the EU, for example, structural problems within dwellings (such as damp walls or a leaking roof), overcrowding, or the lack of basic amenities (such as a toilet, shower or bath). For the purpose of this article, information is presented for the overcrowding rate and the share of the population living in dwellings with a leaking roof, damp walls, floors, foundation, or rot in window frames or floor.

As already mentioned, when analysing quality of life statistics, it is beneficial to also consider information in relation to the distribution of living conditions within each country, for example, is a large share of the population living in a situation that is close to average, or do many people live at the extremes at each end of the range (in other words, are there large numbers of people living in very poor or very good conditions). Therefore, Figure 7 contrasts the share of the population living in overcrowded housing with the share of the population living in under-occupied dwellings. In 2016, approximately one sixth (16.6 %) of the EU-28 population was living in an overcrowded household, while more than one third (34.8 %) of the population was living in under-occupied dwellings. Some of these differences between EU Member States reflect social developments and in particular the relative importance of family units, for example, the increasing likelihood that people live alone (as between 2005 and 2013 the share of EU-28 households that were composed of one or two persons rose from 59.2 % to 63.2 %), which may be contrasted with the situation particularly in rural areas of eastern Europe where it is more likely that extended families continue to live together under the same roofSee for example the publication People in the EU, who are we and how do we live?, page 48. Across 12 of the EU Member States, less than one tenth of the population was living in an overcrowded household in 2016, with shares of less than 4.0 % recorded in Cyprus, Malta, Ireland and Belgium. At the other end of the range, overcrowding impacted upon 40-43 % of the population in Hungary, Slovakia, Poland, Croatia, Bulgaria and Latvia, rising to a peak of 48.4 % in Romania. More than two thirds of the population in Ireland, Cyprus, Malta and Belgium was living in under-occupied housing in 2016, while this share was also more than half in Spain, Luxembourg, the United Kingdom and the Netherlands. At the other end of the range, the proportion of the population living in under-occupied housing was less than 10.0 % in Latvia, Hungary and Romania.

As may be expected, EU Member States that displayed a high share of their population living in overcrowded dwellings tended to record some of the lowest proportions of their population living in under-occupied housing and the reverse was also true; this pattern held across each of the Member States. The development of an increasing share of the population living in under-occupied housing may be linked, at least in part, to increasing longevity and a growing share of the elderly choosing to remain in their own house long after their children have left home (rather than downsizing), but may also reflect local or national imbalances in the housing stock and consequently a lack of specific types of housing that prevent some people from moving.

Figure 7: Overcrowding rate and proportion of the population living in under occupied housing, 2016
(%)
Source: Eurostat (ilc_lvho05a) and (ilc_lvho50a)

Proportion of the dwellings having structural problems

In 2016, some 15.4 % of the EU-28 population was living in low-quality housing (defined here as a dwelling with a leaking roof, damp walls, floors, foundation, or rot in its window frames or floor). The existence of such problems was particularly acute for vulnerable groups within society. For example, more than a fifth (22.0 %) of the population in single-parent households lived in a dwelling with these issues, whereas the share for the population living in households composed of two adults (at least one of which was aged 65 years or over) was less than half that recorded for single-parent households, at 10.9 % (see Figure 8).

Among the EU Member States, the proportion of the population living in a dwelling with a leaking roof, damp walls, floors, foundation, or rot in the window frames or floor in 2016 peaked at 30.5 % in Portugal, while shares above 25 % were also recorded in Cyprus and Hungary. There were five Member States where fewer than 1 in 10 persons experienced living in low-quality housing, namely, Malta, the Czech Republic, Sweden, Slovakia and Finland (where the lowest share was recorded, at 4.7 %).

In most EU Member States, the proportion of the population living in single-parent households that faced low-quality housing in 2016 was higher than the average for the total population, although there were exceptions in Lithuania, Bulgaria, Portugal and Italy. A relatively high share of the population living in single-parent households faced living in such conditions in Hungary, the United Kingdom, Germany, Belgium, Ireland and Slovenia, as each reported a share for this subpopulation that was at least 9.0 percentage points higher than the average for the total population.

In comparison, for most EU Member States a lower than average share of the population in households composed of two adults where at least one of them was aged 65 years or over faced living in low-quality housing; this was particularly true in Denmark, the United Kingdom, Belgium, Hungary and Germany. By contrast, there were seven Member States where a higher proportion of the population living in households composed of two adults where at least one of them was aged 65 years or over faced living in low-quality housing (compared with the total population); this was particularly the case in the Mediterranean countries of Malta, Croatia and Cyprus.

Figure 8: Proportion of the population living in a dwelling with a leaking roof, damp walls, floors, foundation, or rot in window frames or floor, by type of household, 2016
(%)
Source: Eurostat (ilc_mdho01)

Source data for tables, figures and maps(MS Excel)


Data sources

Material living conditions refer to an individual’s standard of living as expressed through three different sub-dimensions: income, consumption and material living conditions. The data used in this section are primarily derived from EU statistics on income and living conditions (EU-SILC). EU-SILC are compiled annually and are the principal European source for measuring income and living conditions, as well as the leading source of information for analysing different aspects related to the quality of life of households and individuals.

Quality of life, even for those dimensions that extend beyond material costs, are often constrained and shaped in a fundamental way by economic (monetary) conditions. Material resources are however only a means for transforming an individual’s well-being according to their own preferences, values, free will and capabilities. Indeed, while material resources do not guarantee happiness, they are clearly beneficial to most individuals who strive to improve their quality of life. In this sense, material living conditions, while not intrinsically reflecting an individual’s quality of life, nevertheless provide a framework to measure the potential of individuals/households to achieve and ensure their own self-defined well-being.

GDP is a measure of economic activity (either from an expenditure, income or output perspective). When divided by the number of inhabitants, GDP per capita has traditionally been used as an indicator to measure economic well-being, or more precisely standards of living for a (sub) population. While an economy’s performance from the macroeconomic perspective is certainly crucial to the overall level of a society’s material well-being, material living standards are more closely associated with real household income and household consumption. Indeed, there is increasing awareness among statisticians that the development of average income and consumption at a national level (as measured within the framework of national accounts) may diverge considerably from the income of a typical household, as its distribution is unevenly shared. By contrast, household-oriented statistical surveys, like EU-SILC facilitate the estimation of median (rather than mean) values, which are less prone to distortions. Furthermore, surveys such as EU-SILC also provide more complete information on distributions within subpopulations, for example, allowing an analysis by income quintile, by sex, by age, and by level of educational attainment, thereby providing a more detailed picture of the actual distribution of material living conditions.

For cross-country comparisons, income expressed in national currency terms is generally misleading (even in the case of a common currency, such as the euro, or after converting different currencies using exchange rates) given there are differences in price levels between economies: for example, a loaf of bread does not cost the same price in Budapest as it does in Copenhagen. To ensure comparability purchasing power parities (PPPs) are calculated and factored in. Accordingly, income estimations in euro terms or national currencies are converted into a common unit, called a purchasing power standard (PPS) — these represent a virtual currency, a unit of which has the same purchasing power regardless of the different price level in each country. Monetary poverty indicators are designed to reveal the share of a (sub) population that is facing difficulties to achieve a minimum standard of living; such indicators are relative in nature and will vary from one country to another reflecting the different price levels in each economy.

In order to define the share of the population who are considered to be living below the minimum standard of living, a threshold is generally used, traditionally this has been set to 60 % of the national median equivalised disposable income (after social transfers). Note that this measure does not provide any information on absolute wealth or poverty, but instead identifies people whose income is low in comparison with other residents in the same country; it is important to bear in mind that this does not necessarily imply a low standard of living.

The concept of equivalised disposable income is used to reflect the fact that incomes of individuals are often shared within a household and usually this will help to achieve economies of scale. The equivalised disposable income is the sum of all income from all different sources acquired by all members of a household, divided by an equivalised household size, according to a standard scale, to take into account the composition of the household in terms of the number of adults and children. The median equivalised disposable income of a country (or a region or a demographic or socioeconomic stratum) may therefore be used as a proxy for the standard of living. Since income distributions are often characterised by extreme outliers, in particular in the high income groups, the use of the median — rather than mean — ensures a more representative estimation.

While monetary indicators may be used to analyse the distribution of income across different socioeconomic groups, they should ideally be complemented by indicators on material conditions — such as material deprivation and housing conditions — designed to measure poverty in absolute (rather than relative) terms. In other words, these indicators are based on using the same set of standards for each country or (sub) population, for example, can the population afford to go on holidays, can they keep their homes adequately warm, or are they confronted with arrears when paying their rent, mortgage or utility bills?

Context

People use material resources, according to their own values and priorities, to pursue their own interests and self-defined well-being. An individual’s quality of life is, therefore, fundamentally constrained by their access to material resources, some of which are transformed into well-being. In this perspective, material living conditions, while not intrinsically reflecting the quality of life, may provide a proxy for measuring it.

The importance of having access to material resources is recognised at a political level within the EU. Reducing poverty, by lifting at least 20 million people out of the risk of poverty or social exclusion, is one of the five EU headline targets within the Europe 2020 strategy, which provides the EU’s growth strategy for developing smart, sustainable and inclusive growth through to 2020 [2]. To support this ambitious objective, the European Commission has launched two flagship initiatives ‘Agenda for new skills and jobs’ and the ‘European platform against poverty and social exclusion’ designed to help contribute towards reaching the employment and education targets for 2020. Furthermore, the EU‘s Sustainable Development Strategy identified social inclusion, demography and migration as one of its seven key challenges to assist with the overall objective of ‘creating a socially inclusive society’ and ‘to secure and increase the quality of life of citizens’.

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Income distribution and monetary poverty (t_ilc_ip)  
Monetary poverty (t_ilc_li)
Monetary poverty for elderly people (t_ilc_pn)
In-work poverty (t_ilc_iw)
Distribution of income (t_ilc_di)
Material deprivation (ilc_md)
Material deprivation by dimension (t_ilc_mddd)
Housing deprivation (t_ilc_mdho)
Environment of the dwelling (t_ilc_mddw)


Income distribution and monetary poverty (ilc_ip)
Monetary poverty (ilc_li)
Monetary poverty for elderly people (ilc_pn)
In-work poverty (ilc_iw)
Distribution of income (ilc_di)
Material deprivation (ilc_md)
Material deprivation by dimension (ilc_mddd)
Economic strain (ilc_mdes)
Economic strain linked to dwelling (ilc_mded)
Durables (ilc_mddu)
Housing deprivation (ilc_mdho)
Environment of the dwelling (ilc_mddw)



Notes

  1. Abdallah, S. and Stoll, L. (2012), Review of individual-level drivers of subjective well-being, produced as part of the contract ‘Analysis, implementation and dissemination of well-being indicators’, Eurostat.
  2. European Commission, Taking stock of the Europe 2020 strategy for smart, sustainable and inclusive growth, COM(2014) 130 final, Brussels, 2014