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

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 Zambia 57.10 2015
4 Central African Republic 56.20 2008
5 Lesotho 54.20 2010
6 Mozambique 54.00 2014
7 Botswana 53.30 2015
8 Eswatini 51.50 2009
9 Guinea-Bissau 50.70 2010
10 Congo 48.90 2011
11 Benin 47.80 2015
12 Cabo Verde 47.20 2007
13 Seychelles 46.80 2013
14 Cameroon 46.60 2014
15 Comoros 45.30 2013
16 Malawi 44.70 2016
17 Rwanda 43.70 2016
18 Ghana 43.50 2016
19 Chad 43.30 2011
20 Zimbabwe 43.20 2011
21 Togo 43.10 2015
22 Nigeria 43.00 2009
23 Uganda 42.80 2016
24 Angola 42.70 2008
25 Madagascar 42.60 2012
26 Dem. Rep. Congo 42.10 2012
27 Djibouti 41.60 2017
28 Côte d'Ivoire 41.50 2015
29 Kenya 40.80 2015
30 Senegal 40.30 2011
31 Morocco 39.50 2013
32 Burundi 38.60 2013
33 Mauritius 38.50 2012
34 Gabon 38.00 2017
35 Tanzania 37.80 2011
36 The Gambia 35.90 2015
37 Sudan 35.40 2009
38 Liberia 35.30 2016
38 Burkina Faso 35.30 2014
40 Ethiopia 35.00 2015
41 Niger 34.30 2014
42 Sierra Leone 34.00 2011
43 Guinea 33.70 2012
44 Mali 33.00 2009
45 Tunisia 32.80 2015
46 Mauritania 32.60 2014
47 Egypt 31.80 2015
48 São Tomé and Principe 30.80 2010
49 Algeria 27.60 2011

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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