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.worldban

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 Turkey 41.20 2014
2 Lithuania 37.70 2014
3 Bulgaria 37.40 2014
4 Spain 36.00 2014
5 Greece 35.80 2014
6 Cyprus 35.60 2014
6 Macedonia 35.60 2015
6 Portugal 35.60 2014
9 Latvia 35.10 2014
10 Italy 34.70 2014
11 Estonia 34.60 2014
12 United Kingdom 34.10 2014
13 Bosnia and Herzegovina 33.80 2011
14 Switzerland 32.50 2013
15 France 32.30 2014
16 Croatia 32.20 2014
17 Poland 32.10 2014
18 Montenegro 31.90 2014
18 Ireland 31.90 2014
20 Germany 31.40 2013
21 Luxembourg 31.20 2014
22 Hungary 30.90 2014
23 Austria 30.50 2014
24 Serbia 29.10 2013
25 Albania 29.00 2012
26 Netherlands 28.60 2014
27 Denmark 28.50 2014
28 Belgium 28.10 2014
29 Romania 27.50 2013
30 Sweden 27.20 2014
31 Moldova 27.00 2015
32 Norway 26.80 2014
32 Finland 26.80 2014
34 Belarus 26.70 2015
35 Slovak Republic 26.10 2014
36 Czech Republic 25.90 2014
37 Slovenia 25.70 2014
38 Iceland 25.60 2014
39 Ukraine 25.50 2015

More rankings: Africa | Asia | Central America & the Caribbean | Europe | Middle East | North America | Oceania | South America | World |

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.

Unit of Measure: %

Periodicity: Annual

General Comments: The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (indu