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.worldbank.org/PovcalNet/index.htm).

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 South Africa 63.38 2011
2 Namibia 60.97 2009
3 Botswana 60.46 2009
4 Central African Republic 56.24 2008
5 Comoros 55.93 2004
6 Zambia 55.62 2010
7 Lesotho 54.18 2010
8 Swaziland 51.45 2009
9 Rwanda 51.34 2010
10 Guinea-Bissau 50.66 2010
11 Kenya 48.51 2005
12 The Gambia 47.33 2003
13 Cabo Verde 47.19 2007
14 Malawi 46.12 2010
15 Togo 46.02 2011
16 Mozambique 45.58 2008
17 Djibouti 45.13 2012
18 Benin 43.44 2011
19 Chad 43.32 2011
20 Côte d'Ivoire 43.18 2008
21 Nigeria 42.97 2009
22 Cameroon 42.82 2007
23 Ghana 42.77 2005
23 Seychelles 42.77 2006
25 Angola 42.72 2008
26 Uganda 42.37 2012
27 Gabon 42.18 2005
28 Dem. Rep. Congo 42.10 2012
29 Morocco 40.72 2007
30 Madagascar 40.63 2010
31 Senegal 40.28 2011
32 Congo 40.16 2011
33 Burkina Faso 39.76 2009
34 Tanzania 37.78 2011
35 Mauritania 37.48 2008
36 Liberia 36.48 2007
37 Mauritius 35.84 2012
38 Tunisia 35.81 2010
39 Sudan 35.39 2009
40 Algeria 35.33 1995
41 Sierra Leone 33.99 2011
42 Guinea 33.73 2012
43 Burundi 33.36 2006
44 Ethiopia 33.17 2010
45 Mali 33.04 2009
46 Niger 31.45 2011
47 São Tomé and Principe 30.82 2010
48 Egypt 30.75 2008

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.

Periodicity: Annual