Income inequality statistics
Income inequality: nearly 40 per cent of total income goes to people belonging to highest (fifth) quintile
Statistics in focus 12/2014; Author: Emanuela DI FALCO
ISSN:2314-9647 Catalogue number:KS-SF-14-012-EN-N
This article presents data on income inequality, measured by the Gini coefficient, across the EU-28 and three EFTA countries. Income inequality is a complex phenomenon, the result of interaction between several factors. It can be related to employment patterns, income sources, individual characteristics (education level, age, gender, etc.) or household features (number of earners in the household, family size, etc.). Inequality is a broader concept than poverty; while poverty mainly relates to the lowest part of the income distribution, inequality takes into account the living conditions of all people in a society.
The analysis showed that Norway and Slovenia had the lowest level of inequality (as measured by the Gini coefficient) in Europe in 2012, and that Spain and Latvia had the highest level. Overall, twelve countries had a level of inequality higher than the EU-28 average in 2012. In Europe, nearly 40 % of total equivalised income goes on average to people belonging to the highest (fifth) income quintile, and less than 10 % to people in the first quintile. This distribution of income explains the income discrepancies among people. It should be noted that inequality decreased in 12 EU countries in 2008-12, mainly due to the income losses seen in the upper part of the income distribution during the financial and economic crisis.
- 1 Main statistical findings
- 2 Data sources and availability
- 3 Further Eurostat information
- 4 Notes
Main statistical findings
The Gini coefficient across the EU in 2012
The Gini coefficient reveals differences of approximately 10 points across the EU in 2012
Income inequality measured by the Gini coefficient varied by approximately 10 points across Europe in 2012, with the lowest levels of inequality seen in Norway and Slovenia and the highest in Spain and Latvia. Only two countries (France and Croatia) had an income inequality level around the EU-28 average (30.6). In twelve countries, income discrepancies were above the EU-28 average, ranging from 31 in Cyprus to 35 or more in Spain and Latvia.
In the remaining countries, the income disparities were below the EU-28 average, ranging from 29.9 in Ireland to less than 24 in Slovenia and Norway. To summarise, the analysis showed high levels of inequality across southern Europe, as seen in Figure 1, but there is no dominant pattern in central- and northern-European countries.
Social transfers and inequality
Social transfers (excluding pensions) played an important role in reducing inequality in 2012
Figure 1 shows the Gini coefficients based on total equivalised disposable household income (see methodological note in Data sources and availability section). These were calculated without including social transfers among the income sources, to measure the impact of these social transfers in reducing inequality.
As expected, income inequality would have been greater in all countries if social transfers were not included, with the highest values seen in Ireland, the United Kingdom and Spain and the lowest in Czech Republic, Slovakia and Slovenia. Finally, social transfers played a crucial role in Ireland, where including them reduced inequality by around 35 %. Finally they did not significantly affect inequality in eight countries where their inclusion among the income sources reduced inequality by less than 10 %.
Evolution of inequality over time
Income disparities increased in Denmark and decreased in Iceland and Norway in 2008-2012
Although inequality in the EU-27 on average remained almost at the same level in 2008-12, a different pattern is seen for individual countries. Income discrepancies decreased in 12 EU Member States and the three EFTA countries included in the analysis, and increased in the remaining countries. Despite their high levels of inequality in 2012, Romania, Bulgaria and Lithuania managed to reduce inequality by about 5 % or more over the period analysed.
In contrast, despite low inequality levels in 2012, all countries included in the blue circle in Figure 2 saw an increase in inequality since 2008, up to 5 % and more in Slovakia, Hungary and Denmark. Denmark and Iceland saw the biggest changes in 2008-2012: a 12 % increase in inequality in Denmark and a 12 % decrease in Iceland.
Income discrepancies across quintiles
On average in Europe in 2012, people in the highest (fifth) income quintile earned nearly 40 % of total income, and people in the lowest (first) quintile earned less than 10 %
The distribution of income among quintiles follows the same pattern in all countries. In the EU-28 on average, 8 % of total income goes to the first quintile, 39 % to the fifth quintile and 13 %, 17 % and 23 % goes to the second, third and fourth quintile, respectively. In the Czech Republic, Iceland and Norway, people in the first quintile earn around 10 % of total income (Figure 3).
Another inequality measure that tells the same story
Figure 3 shows another tool to measure inequality, the S80/S20 index. This index supports the picture shown by the Gini coefficient in Figure 1, but ranks countries in a slightly different order. Here, Spain and Greece had the highest levels of inequality, Latvia had the 3rd highest level, and Norway and Slovenia once again had the lowest inequality levels. This shows that high levels of inequality are caused by significant income discrepancies between the lower and upper parts of the income distribution scale.
Figure 4 shows the level of inequality measured by the S80/S20 index, for two groups of people categorised based on age. The main conclusion is that people aged under 65 experience more inequality than elderly people do, in all countries except for Ireland, Slovenia, France and Switzerland. There was no difference in Cyprus. The biggest difference was seen in Latvia and Spain.
Different living conditions across countries
In 2012, the biggest income gap between the upper and lower part of the income distribution was seen in Luxembourg, and the smallest in Romania
Looking at income distribution in more detail, Figure 5 plots the income levels (with the top cut-off points expressed in Purchasing power standard (PPS)) related to each quintile. As expected, there were big differences between countries in 2012, reflecting differences in living standards. For example, belonging to the first quintile basically meant living in a household that earned less than 2 000 PPS in Romania, and less than 4 000 PPS in Bulgaria and Latvia. However, it meant living in a household that earned less than 16 000 PPS in Switzerland, less than 17 300 PPS in Luxembourg and less than 18 700 PPS in Norway.
The highest quintile included households that earned more than 39 500 PPS in Luxembourg, more than 35 600 PPS in Switzerland and more than 34 400 PPS in Norway, but it also included households that earned more than 5 900 PPS in Romania and more than 8 800 in Bulgaria (Figure 5).
Figure 6 shows the change for different points on the income distribution (the top cut-off points for each quintile are in euros), in real terms, in 2008-12 (income reference period 2007-11). It shows the sensitivity of different points on the income distribution scale to changes over time in each country.
A decrease in each part of the income distribution scale is seen in nine countries among which a consistent decrease in Greece and Iceland. In the remaining countries, the incomes related to each top-cut off points were higher in 2012 than in 2008, with the biggest increases seen in Slovakia, Poland and Bulgaria.
Income mobility in 2008-2011
At least 30 % of the population stayed in the same decile in 2010-2011
The longitudinal component of the EU-SILC instrument allows users to monitor income mobility issues. People can change their position on the income distribution scale over time, and can belong to different quintiles. This can be related also to how the financial situation of the other people living in the same country changes over time.
Looking at the income transitions in 2010-11, at least 30 % of the population stayed in their original group, in all countries, with the biggest percentage observed in Romania. This high percentage of people for whom income did not change is not surprising since the period for which the transition was computed was very short.
In contrast, a lot of change meaning that a high mobility (around 64 % of the population) was seen in Austria, Lithuania, Greece, Croatia, the United Kingdom and Spain (Figure 7). Of the people whose income position changed, nearly 50 % saw an increase in income, and nearly 50 % saw a decrease.
When the transition period was increased to two or three years, income mobility increased everywhere. Moving from a one-year to two-year transition, the percentage of the population that remained in the same decile of income distribution decreased in all countries. Furthermore, when the transition period was extended to three years, 30 % or more of the population saw no change in fifteen countries (from 30.3 in Austria to 41.7 in Finland).
Data sources and availability
EU-SILC income reference period
The income reference period is a fixed 12-month period (such as the previous calendar or tax year) for all countries except the UK, for which it is the current year, and Ireland, for which the survey is continuous and income information is collected for the last twelve months. The data used in this publication comes from the EU-SILC 2012 report. With the exception of the UK and Ireland, the income reference period is therefore 1 January 2011 to 31 December 2011.
Gross income includes income from market sources and cash benefits. Market sources include: employee cash or near-cash income; non-cash employee income; cash benefits from self-employment; income from rental of property or land; regular inter-household cash transfers received; interest; dividends; profit from capital investments in unincorporated businesses; income received by people aged under 16; and pensions from individual private plans. Cash benefits are the sum of: all unemployment, old-age, survivor’s, sickness and disability benefits; education-related, family/children-related and housing allowances; and benefits for social exclusion or those not included elsewhere. Direct taxes and regular inter-household cash transfers paid are deducted from gross income to give disposable income. The current definition of total household disposable income used for calculating the indicators presented excludes imputed rent — i.e. money that the household saves on full (market) rent by living in its own accommodation or in accommodation it rents at a price that is lower than the market price. The definition of income used also excludes non-monetary income components, in particular the value of goods produced for own consumption, social transfers in-kind, and non-cash employee income, except for company cars.
Equivalised disposable income
In order to reflect differences in household size and composition, income figures are given per equivalent adult. This means that the total household income is divided by its equivalent size using the ‘modified OECD equivalence scale’ and the resulting figure is allocated to each member of the household, whether adult or child. The scale gives a weight of 1.0 to the first adult, 0.5 to any other household member aged 14 and over and 0.3 to each child below the age of 14. The equivalent size of a household that consists of, for example, of two adults and two children below the age of 14 is therefore: 1.0 + 0.5 + (2*0.3) = 2.1. Equivalised disposable income is therefore an indicator of the economic resources available to a standardised household. For a one-person household it is equal to household income. For a household comprising more than one person, it is an indicator of the household income that would be needed by a one-person household to enjoy the same level of economic wellbeing.
Income quintiles and top cut-off points
Quintiles refer to the position in the frequency distribution. Quintiles divide a distribution into five parts so that we find 20 % of total observations in each quintile. The quintile cut-off value is obtained by sorting all income from lowest to highest, and then choosing the value of income under which 20 % (lower limit), 40 % (second limit), 60 % (third), 80 % (fourth) and 100 % (upper limit) of the sample are located. A quintile refers to the segment between the cut-off values of two quintiles. The first segment includes income below the lower quintile cut-off (20 %), the second segment includes income located between the lower cut-off and the second quintile cut-off, and so on.
Income quintile share ratio (S80/S20)
This is the ratio of the total income received by the 20 % of the country’s population with the highest disposable income (top quintile) to that received by the 20 % of the country’s population with the lowest disposable income (bottom quintile). EU and other aggregate values are calculated as the population-weighted averages of national indicators.
This index is the best-known index used to measure the level of income inequality in a particular country at one point in time. It ranges from 0 to 100, where 0 represents perfect equality in a society and 100 represents the maximum level of inequality. The Gini coefficient is based on the equivalised disposable income of each individual.
Social benefits are defined as transfers received by households during the income reference period to relieve them from the financial burden of certain risks or needs. In the analysis, social benefits and pensions include: unemployment benefits (PY090); old-age benefits (PY100); survivor’s benefits (PY110); sickness benefits (PY120); disability benefits (PY130); education-related allowances (PY140); family/children related allowances (HY050); social exclusion not included elsewhere (HY060); and housing allowances (HY070).
In order to take account of inflation in year-to-year income changes, we have used the HICP (Harmonised Index of Consumer Prices). The HICP is the consumer price index as it is calculated in the European Union, according to a harmonised approach and a single set of definitions.
Purchasing power standard Purchasing power standard (PPS) is an artificial currency unit that would allow the purchase of the same basket of goods and services in different countries. PPS offsets differences in price levels between countries and thus allows real income to be compared.
EU average EU aggregates are calculated as the population-weighted averages of national indicators.
- Children at risk of poverty or social exclusion
- European social statistics (online publication)
- Housing conditions
- Living standard statistics
- People at risk of poverty or social exclusion
- Social inclusion statistics
Further Eurostat information
- Income and living conditions (ilc)
- Income distribution and monetary poverty (ilc_ip)
- Distribution of income (ilc_di)
- Income distribution and monetary poverty (ilc_ip)
- Regulation 1177/2003 of 16 June 2003 concerning Community statistics on income and living conditions (EU-SILC)
- Regulation 1980/2003 of 21 October 2003 implementing Regulation 1177/2003 concerning Community statistics on income and living conditions (EU-SILC) as regards definitions and updated definitions
- Evolutions for Austria should not be interpreted in terms of evolutions of inequalities as they are due to the break in the time series for income based indicators following an extensive use of administrative data from 2012 onwards
- This index compares the proportion of total equivalised disposable household income earned by the richest part of the population to the proportion of income earned by the poorest part. High values mean high levels of inequality, see methodological note, in annex.
- A top cut-off point is a segment that divides two consecutive quintiles, see methodological note, in annex.
- Longitudinal data pertaining to individual-level changes over time, observed periodically over a four-year period.