GINI index (World Bank estimate) - Country Ranking

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 South Africa 63.00 2014
2 Namibia 59.10 2015
3 Suriname 57.60 1999
4 Zambia 57.10 2015
5 Central African Republic 56.20 2008
6 Lesotho 54.20 2010
7 Mozambique 54.00 2014
8 Belize 53.30 1999
8 Brazil 53.30 2017
8 Botswana 53.30 2015
11 Eswatini 51.50 2009
12 St. Lucia 51.20 2016
13 Guinea-Bissau 50.70 2010
14 Honduras 50.50 2017
15 Panama 49.90 2017
16 Colombia 49.70 2017
17 Congo 48.90 2011
18 Paraguay 48.80 2017
19 Mexico 48.30 2016
19 Guatemala 48.30 2014
19 Costa Rica 48.30 2017
22 Benin 47.80 2015
23 Cabo Verde 47.20 2007
24 Venezuela 46.90 2006
25 Seychelles 46.80 2013
26 Cameroon 46.60 2014
26 Chile 46.60 2017
28 Nicaragua 46.20 2014
29 Dominican Republic 45.70 2016
30 Jamaica 45.50 2004
31 Comoros 45.30 2013
32 Ecuador 44.70 2017
32 Malawi 44.70 2016
34 Guyana 44.60 1998
35 Philippines 44.40 2015
36 Bolivia 44.00 2017
37 Rwanda 43.70 2016
38 Ghana 43.50 2016
39 Chad 43.30 2011
39 Peru 43.30 2017
41 Zimbabwe 43.20 2011
42 Togo 43.10 2015
43 Nigeria 43.00 2009
44 Uganda 42.80 2016
45 Angola 42.70 2008
46 Madagascar 42.60 2012
47 Dem. Rep. Congo 42.10 2012
48 Papua New Guinea 41.90 2009
48 Turkey 41.90 2016
50 Djibouti 41.60 2017
51 Côte d'Ivoire 41.50 2015
51 United States 41.50 2016
53 Argentina 41.20 2017
54 Haiti 41.10 2012
55 Malaysia 41.00 2015
56 Turkmenistan 40.80 1998
56 Kenya 40.80 2015
58 Trinidad and Tobago 40.30 1992
58 Senegal 40.30 2011
60 Iran 40.00 2016
61 Sri Lanka 39.80 2016
62 Serbia 39.60 2015
63 Uruguay 39.50 2017
63 Morocco 39.50 2013
65 Tuvalu 39.10 2010
66 Israel 38.90 2016
67 Samoa 38.70 2013
68 Burundi 38.60 2013
68 China 38.60 2015
70 Mauritius 38.50 2012
71 Indonesia 38.10 2017
71 Myanmar 38.10 2015
73 Gabon 38.00 2017
73 El Salvador 38.00 2017
75 Georgia 37.90 2017
76 Tanzania 37.80 2011
77 Russia 37.70 2015
78 Tonga 37.60 2015
78 Vanuatu 37.60 2010
80 Bhutan 37.40 2017
80 Lithuania 37.40 2015
80 Bulgaria 37.40 2014
83 Solomon Islands 37.10 2013
84 Kiribati 37.00 2006
85 Fiji 36.70 2013
85 Yemen 36.70 2014
87 Thailand 36.50 2017
88 Lao PDR 36.40 2012
89 Spain 36.20 2015
90 Greece 36.00 2015
91 The Gambia 35.90 2015
91 Romania 35.90 2015
93 Australia 35.80 2014
93 Syrian Arab Republic 35.80 2004
95 India 35.70 2011
96 North Macedonia 35.60 2015
97 Portugal 35.50 2015
98 Sudan 35.40 2009
98 Italy 35.40 2015
100 Liberia 35.30 2016
100 Burkina Faso 35.30 2014
100 Vietnam 35.30 2016
100 Uzbekistan 35.30 2003
104 Ethiopia 35.00 2015
105 Niger 34.30 2014
106 Latvia 34.20 2015
107 Sierra Leone 34.00 2011
107 Tajikistan 34.00 2015
107 Canada 34.00 2013
107 Cyprus 34.00 2015
111 Luxembourg 33.80 2015
112 Guinea 33.70 2012
112 Jordan 33.70 2010
114 Armenia 33.60 2017
115 Pakistan 33.50 2015
116 United Kingdom 33.20 2015
117 Mali 33.00 2009
117 Bosnia and Herzegovina 33.00 2011
119 Tunisia 32.80 2015
119 Nepal 32.80 2010
121 Estonia 32.70 2015
121 France 32.70 2015
123 Mauritania 32.60 2014
124 Bangladesh 32.40 2016
125 Mongolia 32.30 2016
125 Switzerland 32.30 2015
127 Japan 32.10 2008
128 Montenegro 31.90 2014
129 Ireland 31.80 2015
129 Egypt 31.80 2015
129 Poland 31.80 2015
129 Lebanon 31.80 2011
133 Germany 31.70 2015
134 Korea 31.60 2012
135 Croatia 31.10 2015
136 São Tomé and Principe 30.80 2010
137 Austria 30.50 2015
138 Hungary 30.40 2015
139 Iraq 29.50 2012
140 Malta 29.40 2015
141 Sweden 29.20 2015
142 Albania 29.00 2012
143 Timor-Leste 28.70 2014
144 Netherlands 28.20 2015
144 Denmark 28.20 2015
146 Iceland 27.80 2014
147 Belgium 27.70 2015
148 Algeria 27.60 2011
149 Norway 27.50 2015
149 Kazakhstan 27.50 2017
151 Kyrgyz Republic 27.30 2017
152 Finland 27.10 2015
153 Azerbaijan 26.60 2005
154 Slovak Republic 26.50 2015
155 Moldova 25.90 2017
155 Czech Republic 25.90 2015
157 Belarus 25.40 2017
157 Slovenia 25.40 2015
159 Ukraine 25.00 2016

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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.

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