Key Takeaways
- The global Gini coefficient for pre-tax income inequality reached 0.72 in 2022, indicating extreme disparity where the top 10% hold 52% of income while bottom 50% hold 8.5%
- In 2021, worldwide wealth inequality saw the richest 1% owning 45.8% of global net worth, up from 42.5% in 2010, per Credit Suisse Global Wealth Report
- Globally, 26 billionaires held more wealth than the poorest 3.8 billion people combined in 2023, according to Oxfam's report on inequality
- US Gini coefficient for household income after taxes and transfers was 0.39 in 2021, Census Bureau data
- In the US, top 1% income share reached 20.2% in 2020, up from 10% in 1980, World Inequality Database
- US wealth inequality: top 10% hold 69% of total wealth in 2022, Federal Reserve SCF
- In EU-27, Gini coefficient for equivalised disposable income was 29.6 in 2021, Eurostat
- Top 10% income share in France was 32.5% in 2021, WID
- UK Gini for income after taxes/transfers rose to 35.6 in 2021/22, ONS
- China's Gini coefficient peaked at 0.49 in 2008 but fell to 0.37 in 2021, NBS data
- India top 10% income share 57.1% in 2022, highest in Asia, WID
- Japan Gini for disposable income 33.4 in 2021, lowest among large Asian economies, Statistics Bureau Japan
- World Gini coefficient declined from 68.7 in 2003 to 64.9 in 2013 due to Asia growth, but stalled since, World Bank PovcalNet 2020 update
- US top 1% income share rose from 10% in 1980 to 19% in 2020, driven by tax cuts, Piketty/Saez 2022
- Global top 10% income share stable at 52% 2000-2020, but within-country rose, WID World Inequality Report 2022
Income inequality shows extreme global wealth concentration at the very top.
Asian Inequality
Asian Inequality Interpretation
European Inequality
European Inequality Interpretation
Global Inequality
Global Inequality Interpretation
Trends and Policy
Trends and Policy Interpretation
US Inequality
US 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.
Megan Gallagher. (2026, February 13). Income Inequality Statistics. Gitnux. https://gitnux.org/income-inequality-statistics
Megan Gallagher. "Income Inequality Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/income-inequality-statistics.
Megan Gallagher. 2026. "Income Inequality Statistics." Gitnux. https://gitnux.org/income-inequality-statistics.
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