Key Takeaways
- The World Bank reports that the Gini index for India was 0.36 in 2019 (income inequality measured by Gini).
- In South Africa, the Gini coefficient was 0.60 in 2021 (income inequality measure).
- In Nigeria, the Gini coefficient was 0.43 in 2022 (income inequality measure).
- In France, the S80/S20 income ratio was 4.7 in 2022 (ratio of top to bottom income quintiles).
- In France, the top 10% of households received 31.0% of income in 2022 (top decile share).
- In Canada, the income share of the bottom 20% of households was 7.4% in 2022 (share of total after-tax income).
- In the United States, the top 5% held 35.6% of income in 2022 (pre-tax).
- There were 2,640 billionaires in the Forbes 2024 list (global count of billionaires).
- The World Bank estimated that 30.0% of people in the world lived in poverty in 2017 ($2.15/day, 2017 PPP), highlighting inequality-linked hardship (poverty rate indicator often used alongside inequality).
- In the UK, 12.8% of individuals were in relative poverty in 2023/24 (poverty indicator used alongside inequality).
- In Spain, 26.6% of people were at risk of poverty or social exclusion in 2023 (EU-SILC metric).
- In the US, the median weekly earnings gap in 2023 was $349 between men ($1,001) and women ($652), reflecting persistent gender earnings inequality
- Global wealth ownership: the bottom 50% of adults held 1.1% of global wealth in 2023 (World Wealth Report 2024), highlighting the low-wealth end
- In Japan, income inequality measured by the Gini coefficient for household income was 0.36 in 2022, indicating substantial income dispersion
- In the United States, 15.0% of people were food insecure in 2023, showing deprivation patterns linked to inequality
Inequality remains widespread globally, from high Gini values to major poverty and housing hardship.
Related reading
Income Inequality Metrics
Income Inequality Metrics Interpretation
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Earnings Concentration
Earnings Concentration Interpretation
Wealth Inequality
Wealth Inequality Interpretation
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Labor Market Inequality
Labor Market Inequality Interpretation
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Income Distribution
Income Distribution Interpretation
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Poverty & Deprivation
Poverty & Deprivation Interpretation
Housing Inequality
Housing Inequality Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Min-ji Park. (2026, February 13). Economic Inequality Statistics. Gitnux. https://gitnux.org/economic-inequality-statistics
Min-ji Park. "Economic Inequality Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/economic-inequality-statistics.
Min-ji Park. 2026. "Economic Inequality Statistics." Gitnux. https://gitnux.org/economic-inequality-statistics.
References
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- 2data.worldbank.org/indicator/SI.POV.GINI?locations=ZA
- 3data.worldbank.org/indicator/SI.POV.GINI?locations=NG
- 4data.worldbank.org/indicator/SI.POV.GINI?locations=MX
- 5data.worldbank.org/indicator/SI.POV.GINI?locations=RU
- 6ec.europa.eu/eurostat/databrowser/view/ilc_di12/default/table?lang=en
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- 18ec.europa.eu/eurostat/databrowser/view/t2020_52/default/table?lang=en
- 8ifs.org.uk/publications/23801
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- 10data.oecd.org/inequality/income-inequality.htm
- 11insee.fr/en/statistiques/series/215605
- 12insee.fr/en/statistiques/series/215607
- 13www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1110000901
- 14wid.world/data/
- 15forbes.com/billionaires/
- 16worldbank.org/en/topic/poverty/overview
- 17ons.gov.uk/peoplepopulationandcommunity/educationandchildcare/healthandwellbeing/bulletins/ukpoverty/financialyearending2024
- 19oecd.org/social/society-and-poverty/poverty-income-distribution.htm
- 20oecd.org/pisa/publications/PISA-2022-results-volume-2-education-and-socio-economic-status.pdf
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- 22cdc.gov/nchs/data/nhis/earlyrelease/insur202406.pdf
- 23rand.org/pubs/research_reports/RRA110-2.html
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- 25ubs.com/global/en/wealth-management/insights/global-wealth-report.html
- 26stat.go.jp/english/data/kakei/index.html
- 27ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/
- 28census.gov/library/publications/2024/demo/p60-283.html
- 29huduser.gov/portal/datasets/assth/2023%20Assth/data%20doc.html






