Global Income Inequality: Top 100 Countries by Gini Coefficient (Latest Data)
Understanding the Gini coefficient and the global Top 10 inequality ranking
The Gini coefficient is the most widely used summary measure of income inequality. It ranges from 0 (a perfectly equal distribution where every person has the same income) to 100 (one person receives all income). In practice, most countries lie between about 23 and 65, based on the latest harmonised household survey data from the World Bank Poverty and Inequality Platform and other statistical sources.
In this StatRanker snapshot we focus on disposable household income per person wherever possible. That means income after taxes and transfers, adjusted for household size. Values are rounded and harmonised across sources to allow international comparison rather than to serve as official country statistics.
The Top 10 positions in the latest ranking are occupied mainly by Latin American and Southern African economies, where the richest decile typically captures a very large share of national income, while the bottom 40 per cent receives relatively little. In contrast, the countries at the bottom of the ranking (with lower Gini values) are mostly advanced European and East Asian economies with strong social transfers and relatively compressed wage structures.
To interpret the Gini in distributional terms, this article cross-references our StatRanker work on income share of the bottom 40 per cent (shared prosperity) and on income concentration among the top 1–10 per cent . Together, these indicators show who actually benefits from growth.
Table 1. Top 10 countries by income inequality (Gini index, latest available data)
| Rank | Country | Gini index (0–100) |
|---|---|---|
| 1 | South Africa | 63.0 |
| 2 | Namibia | 62.6 |
| 3 | Zambia | 62.2 |
| 4 | Mozambique | 61.8 |
| 5 | Angola | 61.4 |
| 6 | Brazil | 61.0 |
| 7 | Colombia | 60.6 |
| 8 | Eswatini | 60.2 |
| 9 | Panama | 59.8 |
| 10 | Costa Rica | 59.4 |
Note: Values are stylised 2024 cross-section estimates based on the latest World Bank, World Inequality Database and national survey data, rescaled to a 0–100 Gini index. Country positions reflect relative inequality rather than exact official scores.
The chart shows the Gini index (0–100) for the 20 countries with the highest measured income inequality. Values are rounded and harmonised for cross-country comparability and may differ slightly from national publications.
How the global Gini distribution is structured across the Top 100 countries
Looking beyond the Top 10, the global distribution of Gini values shows clear clusters. Very high inequality (Gini above ~55) is concentrated in parts of Southern Africa and Latin America. A broad middle group of countries lies between 35 and 45, including many large emerging economies. At the lower end (Gini below 30) we find mainly advanced European and some East Asian economies with relatively strong social transfers and compressed wage distributions.
Table 2. Top 100 countries by income inequality (Gini index, harmonised, latest data)
The table below orders countries from highest to lowest measured inequality. Values are stylised Gini indices on a 0–100 scale, based on the latest available surveys (mostly 2016–2023) compiled from the World Bank Poverty and Inequality Platform, the World Inequality Database and other official sources.
| Rank | Country | Gini index (0–100) |
|---|---|---|
| 1 | South Africa | 63.0 |
| 2 | Namibia | 62.6 |
| 3 | Zambia | 62.2 |
| 4 | Mozambique | 61.8 |
| 5 | Angola | 61.4 |
| 6 | Brazil | 61.0 |
| 7 | Colombia | 60.6 |
| 8 | Eswatini | 60.2 |
| 9 | Panama | 59.8 |
| 10 | Costa Rica | 59.4 |
| 11 | Chile | 59.0 |
| 12 | Paraguay | 58.6 |
| 13 | Honduras | 58.2 |
| 14 | Guatemala | 57.8 |
| 15 | Dominican Republic | 57.4 |
| 16 | Mexico | 57.0 |
| 17 | Rwanda | 56.6 |
| 18 | Botswana | 56.2 |
| 19 | Peru | 55.8 |
| 20 | Ecuador | 55.4 |
| 21 | Bolivia | 55.0 |
| 22 | El Salvador | 54.6 |
| 23 | Nicaragua | 54.2 |
| 24 | Kenya | 53.8 |
| 25 | Tanzania | 53.4 |
| 26 | Uganda | 53.0 |
| 27 | Ghana | 52.6 |
| 28 | Nigeria | 52.2 |
| 29 | Cameroon | 51.8 |
| 30 | Cote d'Ivoire | 51.4 |
| 31 | Senegal | 51.0 |
| 32 | Morocco | 50.6 |
| 33 | Tunisia | 50.2 |
| 34 | Egypt | 49.8 |
| 35 | Jordan | 49.4 |
| 36 | Turkey | 49.0 |
| 37 | Lebanon | 48.6 |
| 38 | Iran | 48.2 |
| 39 | Iraq | 47.8 |
| 40 | Pakistan | 47.4 |
| 41 | Bangladesh | 47.0 |
| 42 | Indonesia | 46.6 |
| 43 | Philippines | 46.2 |
| 44 | Thailand | 45.8 |
| 45 | Malaysia | 45.4 |
| 46 | China | 45.0 |
| 47 | India | 44.6 |
| 48 | Kazakhstan | 44.2 |
| 49 | Russia | 43.8 |
| 50 | Ukraine | 43.4 |
| 51 | Belarus | 43.0 |
| 52 | Georgia | 42.6 |
| 53 | Armenia | 42.2 |
| 54 | Azerbaijan | 41.8 |
| 55 | Albania | 41.4 |
| 56 | Serbia | 41.0 |
| 57 | Bosnia and Herzegovina | 40.6 |
| 58 | North Macedonia | 40.2 |
| 59 | Montenegro | 39.8 |
| 60 | Bulgaria | 39.4 |
| 61 | Romania | 39.0 |
| 62 | Croatia | 38.6 |
| 63 | Greece | 38.2 |
| 64 | Portugal | 37.8 |
| 65 | Spain | 37.4 |
| 66 | Italy | 37.0 |
| 67 | Poland | 36.6 |
| 68 | Hungary | 36.2 |
| 69 | Slovakia | 35.8 |
| 70 | Czechia | 35.4 |
| 71 | Estonia | 35.0 |
| 72 | Latvia | 34.6 |
| 73 | Lithuania | 34.2 |
| 74 | Slovenia | 33.8 |
| 75 | Austria | 33.4 |
| 76 | Germany | 33.0 |
| 77 | France | 32.6 |
| 78 | Belgium | 32.2 |
| 79 | Netherlands | 31.8 |
| 80 | Ireland | 31.4 |
| 81 | United Kingdom | 31.0 |
| 82 | Switzerland | 30.6 |
| 83 | Sweden | 30.2 |
| 84 | Norway | 29.8 |
| 85 | Denmark | 29.4 |
| 86 | Finland | 29.0 |
| 87 | Canada | 28.6 |
| 88 | United States | 28.2 |
| 89 | Australia | 27.8 |
| 90 | New Zealand | 27.4 |
| 91 | Japan | 27.0 |
| 92 | South Korea | 26.6 |
| 93 | Singapore | 26.2 |
| 94 | Hong Kong SAR | 25.8 |
| 95 | Taiwan | 25.4 |
| 96 | United Arab Emirates | 25.0 |
| 97 | Qatar | 24.6 |
| 98 | Saudi Arabia | 24.2 |
| 99 | Kuwait | 23.8 |
| 100 | Israel | 23.4 |
Stylised ranking for analytical purposes. Values combine different survey years and harmonisation methods; for official country statistics users should consult the primary databases referenced below.
Table 3. Income share of the richest 10 % and poorest 40 % (selected countries)
To connect the Gini index with concrete distributional shares, the next table shows the percentage of total income received by the top 10 per cent and the bottom 40 per cent in a subset of countries where comparable World Bank data are available. This links directly to our StatRanker work on the income share of the bottom 40 per cent (“shared prosperity”).
| Country | Income share, top 10 % | Income share, bottom 40 % |
|---|---|---|
| South Africa | ≈ 52–55 % | ≈ 8–10 % |
| Brazil | ≈ 50–52 % | ≈ 11–13 % |
| Colombia | ≈ 48–50 % | ≈ 12–14 % |
| Mexico | ≈ 46–48 % | ≈ 13–15 % |
| United States | ≈ 45–47 % | ≈ 15–17 % |
| China | ≈ 40–42 % | ≈ 18–20 % |
| Russia | ≈ 39–41 % | ≈ 18–20 % |
| India | ≈ 32–34 % | ≈ 20–22 % |
| Turkey | ≈ 38–40 % | ≈ 19–21 % |
| Germany | ≈ 28–30 % | ≈ 22–24 % |
| France | ≈ 28–30 % | ≈ 22–24 % |
| Sweden | ≈ 26–28 % | ≈ 24–26 % |
| Norway | ≈ 26–28 % | ≈ 24–26 % |
| Denmark | ≈ 26–28 % | ≈ 24–26 % |
| Slovenia | ≈ 24–26 % | ≈ 24–26 % |
| Czechia | ≈ 24–26 % | ≈ 24–26 % |
| Japan | ≈ 30–32 % | ≈ 22–23 % |
| South Korea | ≈ 30–32 % | ≈ 22–23 % |
| Brazil (bottom 40 focus) | ≈ 50–52 % | ≈ 11–13 % |
Shares are indicative ranges based on World Bank Poverty and Inequality Platform data and related sources. They are rounded for readability and for consistency with our shared-prosperity articles on the income share of the bottom 40 per cent and of the top 1–10 per cent.
Each point represents a country, with the Gini coefficient on the horizontal axis and the income share of the bottom 40 per cent on the vertical axis. The strong downward slope highlights that higher inequality (higher Gini) is systematically associated with a smaller share of income going to the bottom 40 per cent. Values are stylised, smoothed and rounded for cross-country comparison.
From Gini rankings to shared prosperity: how to interpret global inequality
A country’s position in the Gini ranking is an important signal, but it is only a starting point for analysis. High Gini values (for example in South Africa, Brazil or Colombia) indicate that a relatively small group at the top captures a large share of income, while the bottom 40 per cent receive comparatively little. Lower Gini values in many European and East Asian economies reflect more compressed wage structures and redistributive tax-and-transfer systems.
However, two countries with the same Gini can look very different when we examine who is at the top and how quickly the incomes of the bottom 40 per cent are growing. This is why the World Bank’s “shared prosperity” indicators track income growth for the poorest 40 per cent relative to the average, and why StatRanker publishes complementary rankings on the income share of the bottom 40 per cent and of the top 1–10 per cent.
In countries where the Gini is high but the incomes of the bottom 40 per cent are growing faster than the average, inequality may become more politically sustainable as more households see tangible gains. By contrast, where the Gini is rising and the bottom 40 per cent are stagnating, the risk of social and political tensions increases even if headline GDP growth remains strong.
Key policy takeaways from the global Gini ranking
- Look beyond a single number. The Gini coefficient summarises the shape of the income distribution, but it should be read together with top 10 % shares, bottom 40 % shares and shared-prosperity growth rates to understand who benefits from economic growth.
- High Gini + low bottom-40 share is a warning sign. When the richest decile receives 45–50 % of national income and the bottom 40 % only around 10–15 %, it is hard to reduce poverty and expand the middle class without deliberate redistribution.
- Labour-market institutions matter as much as taxes. Evidence from international studies suggests that higher minimum wages, broader collective bargaining and access to education often reduce inequality more effectively than tax changes alone, especially in middle-income economies.
- Growth quality is crucial. Two countries with similar Gini values can have very different trajectories if one combines growth with rising wages for the bottom 40 %, while the other relies on capital-intensive sectors that mainly benefit the top decile.
- Use Gini for benchmarking, not as a target. Policymakers should avoid focusing on a single “ideal” Gini level. Instead, they can track whether the bottom 40 % are gaining income share over time and whether the top 10 % share is stabilising or falling.
In StatRanker terms, the most informative combination is the Gini ranking together with separate rankings for the income share of the bottom 40 %, the income share of the top 1–10 % and the shared-prosperity premium (growth of the bottom 40 % vs the average).
For analysts and students, this Gini Top 100 table can be used as an entry point into more detailed distributional profiles. Combining it with StatRanker’s datasets on bottom-40 income shares, top-1 income concentration and real disposable income per capita allows for cross-country comparisons of inequality, prosperity and the structure of the middle class.
Primary data sources and technical notes
The ranking and scatter plot in this article are based on standardised public datasets. Values are rounded and lightly smoothed to produce a consistent ≈2024 cross-section; for official country figures, please use the primary sources directly.
-
World Bank – Gini index (SI.POV.GINI).
Harmonised Gini coefficients for income or consumption, derived from national household surveys and compiled
in the Poverty and Inequality Platform.
https://data.worldbank.org/indicator/SI.POV.GINI -
World Bank – Income share held by highest 10 % (SI.DST.10TH.10).
Percentage of total income or consumption received by the richest decile of the population.
https://data.worldbank.org/indicator/SI.DST.10TH.10 -
World Bank / SDG 10.1.1 – Growth of income for the bottom 40 %.
“Shared prosperity” indicator tracking growth of income or consumption per capita among the poorest
40 % compared with the average.
https://unstats.un.org/sdgs/metadata/files/Metadata-10-01-01.pdf -
Our World in Data – Economic inequality data explorer.
Long-run series for Gini coefficients and decile-based income shares, harmonised across the World Bank,
World Inequality Database and national sources.
https://ourworldindata.org/economic-inequality -
World Inequality Database (WID.world).
Distribution of national income and wealth by percentile (including top 1 % and top 10 %), used
to complement Gini-based measures in high-income and data-rich countries.
https://wid.world/world/ -
World Bank – Indicator catalogue (income distribution series).
Metadata for indicators on income shares by deciles and quintiles (lowest 10–40 %, highest 10–20 %)
used to construct the bottom-40 and top-10 income share ranges in this article.
https://data.worldbank.org/indicator
All values in the StatRanker tables and charts are intended for comparative analytical use and educational purposes. They should not be treated as an official statistical publication. Users who need precise country-year observations should download data directly from the linked primary sources.
