GINI index (World Bank estimate) - Country Ranking - Europe

Definition: Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.

Source: World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 Macedonia 44.05 2008
2 Turkey 40.17 2012
3 Greece 36.68 2012
4 Portugal 36.04 2012
5 Bulgaria 36.01 2012
6 Spain 35.89 2012
7 Latvia 35.48 2012
8 Italy 35.16 2012
9 Lithuania 35.15 2012
10 Luxembourg 34.79 2012
11 Cyprus 34.31 2012
12 Montenegro 33.19 2013
13 Estonia 33.15 2012
14 France 33.10 2012
15 Bosnia and Herzegovina 33.04 2007
16 United Kingdom 32.57 2012
17 Ireland 32.52 2012
18 Poland 32.39 2012
19 Croatia 31.98 2011
20 Switzerland 31.64 2012
21 Hungary 30.55 2012
22 Austria 30.48 2012
23 Germany 30.13 2011
24 Serbia 29.65 2010
25 Denmark 29.08 2012
26 Albania 28.96 2012
27 Moldova 28.53 2013
28 Netherlands 27.99 2012
29 Belgium 27.59 2012
30 Romania 27.33 2012
31 Sweden 27.32 2012
32 Finland 27.12 2012
33 Iceland 26.94 2012
34 Czech Republic 26.13 2012
35 Slovak Republic 26.12 2012
36 Belarus 26.01 2012
37 Norway 25.90 2012
38 Slovenia 25.59 2012
39 Ukraine 24.55 2013

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Limitations and Exceptions: Gini coefficients are not unique. It is possible for two different Lorenz curves to give rise to the same Gini coefficient. Furthermore it is possible for the Gini coefficient of a developing country to rise (due to increasing inequality of income) while the number of people in absolute poverty decreases. This is because the Gini coefficient measures relative, not absolute, wealth. Another limitation of the Gini coefficient is that it is not additive across groups, i.e. the total Gini of a society is not equal to the sum of the Gini's for its sub-groups. Thus, country-level Gini coefficients cannot be aggregated into regional or global Gini's, although a Gini coefficient can be computed for the aggregate. Because the underlying household surveys differ in methods and types of welfare measures collected, data are not strictly comparable across countries or even across years within a country. Two sources of non-comparability should be noted for distributions of income in particular. First, the surveys can differ in many respects, including whether they use income or consumption expenditure as the living standard indicator. The distribution of income is typically more unequal than the distribution of consumption. In addition, the definitions of income used differ more often among surveys. Consumption is usually a much better welfare indicator, particularly in developing countries. Second, households differ in size (number of members) and in the extent of income sharing among members. And individuals differ in age and consumption needs. Differences among countries in these respects may bias comparisons of distribution. World Bank staff have made an effort to ensure that the data are as comparable as possible. Wherever possible, consumption has been used rather than income. Income distribution and Gini indexes for high-income economies are calculated directly from the Luxembourg Income Study database, using an estimation method consistent with that applied for developing countries.

Statistical Concept and Methodology: The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality. The Gini index provides a convenient summary measure of the degree of inequality. Data on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data. The distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption. No adjustment has been made for spatial differences in cost of living within countries, because the data needed for such calculations are generally unavailable. For further details on the estimation method for low- and middle-income economies, see Ravallion and Chen (1996). Survey year is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which most of the data were collected.

Periodicity: Annual