Between December 2019 and 2021, the top one percent of earners accumulated 63 percent of all new wealth worldwide. This is more than six times more wealth than accumulated by the bottom 90 percent over the same time period.

Global wealth distribution Newly generated wealth landing in the hands of the few is not a new story and has been the focus of international development policy for many years. Looking at a regional level, Latin America was the region with the starkest distribution of wealth. In this region, 77 percent of the wealth was held by the richest 10 percent in 2021, and only 0.5 percent held by the poorest 50 percent. At an individual level, around 2.82 billion adults worldwide had a net worth of less than 10,000 U.S. dollars in 2021.

Billionaires In 2021, the highest concentration of billionaires could be found in North America. However, China had the largest number of billionaires in its population in 2022, with most living in Beijing. Looking at wealth distribution amongst billionaires themselves, 20 people had fortunes of 50 billion U.S. dollars or more, but the majority of billionaires had a personal fortune between two and five billion U.S. dollars.

In December 2022, Elon Musk slipped from the top spot of richest people on Earth. The number one spot was taken by French magnate, Bernard Arnault of Moët Hennessy Louis Vuitton.

Graph and download economic data for Share of Net Worth Held by the Top 1% (99th to 100th Wealth Percentiles) (WFRBST01134) from Q3 1989 to Q2 2025 about net worth, wealth, percentile, Net, and USA.

The massive wealth inequality in the world is underpinned by this chart: while *** percent of the world's population had fortunes of more than one million U.S. dollars in 2025, over ** percent of the global population had a total wealth of less than 10,000 U.S. dollars.

The OECD Income Distribution database (IDD) has been developed to benchmark and monitor countries' performance in the field of income inequality and poverty. It contains a number of standardised indicators based on the central concept of "equivalised household disposable income", i.e. the total income received by the households less the current taxes and transfers they pay, adjusted for household size with an equivalence scale. While household income is only one of the factors shaping people's economic well-being, it is also the one for which comparable data for all OECD countries are most common. Income distribution has a long-standing tradition among household-level statistics, with regular data collections going back to the 1980s (and sometimes earlier) in many OECD countries.

Achieving comparability in this field is a challenge, as national practices differ widely in terms of concepts, measures, and statistical sources. In order to maximise international comparability as well as inter-temporal consistency of data, the IDD data collection and compilation process is based on a common set of statistical conventions (e.g. on income concepts and components). The information obtained by the OECD through a network of national data providers, via a standardized questionnaire, is based on national sources that are deemed to be most representative for each country.

Small changes in estimates between years should be treated with caution as they may not be statistically significant.

Fore more details, please refer to: https://www.oecd.org/els/soc/IDD-Metadata.pdf and https://www.oecd.org/social/income-distribution-database.htm

Cross-national research on the causes and consequences of income inequality has been hindered by the limitations of the existing inequality datasets: greater coverage across countries and over time has been available from these sources only at the cost of significantly reduced comparability across observations. The goal of the Standardized World Income Inequality Database (SWIID) is to meet the needs of those engaged in broadly cross-national research by maximizing the comparability of income inequality data while maintaining the widest possible coverage across countries and over time. The SWIID’s income inequality estimates are based on thousands of reported Gini indices from hundreds of published sources, including the OECD Income Distribution Database, the Socio-Economic Database for Latin America and the Caribbean generated by CEDLAS and the World Bank, Eurostat, the World Bank’s PovcalNet, the UN Economic Commission for Latin America and the Caribbean, national statistical offices around the world, and academic studies while minimizing reliance on problematic assumptions by using as much information as possible from proximate years within the same country. The data collected and harmonized by the Luxembourg Income Study is employed as the standard. The SWIID currently incorporates comparable Gini indices of disposable and market income inequality for 199 countries for as many years as possible from 1960 to the present; it also includes information on absolute and relative redistribution.

This statistic shows the distribution of income worldwide in 2035 by region. By 2035, roughly *** million people in India are projected to earn between zero and ***** U.S. dollars annually.

Graph and download economic data for Minimum Wealth Cutoff for the Top 0.1% (99.9th to 100th Wealth Percentiles) (WFRBLTP1311) from Q3 1989 to Q3 2022 about wealth, percentile, and USA.

Global Income Inequality Dataset (2000–2023)

Overview

This dataset provides a comprehensive look at global income inequality from the year 2000 to 2023. It includes key indicators such as Gini index, average income, income distribution across different population percentiles, and income group classifications for 30 countries worldwide. The dataset offers insights into how income is distributed within nations and highlights disparities across different economic groups.

Data Features

• Country: The name of the country.
• Year: The year of the data point (2000–2023).
• Population: The estimated population for the given year.
• Gini Index: A measure of income inequality, where 0 represents perfect equality and 1 represents maximum inequality.
• Average Income (USD): The average income in USD for the country in the given year.
• Top 10% Income Share (%): The percentage of total income held by the top 10% of the population.
• Bottom 10% Income Share (%): The percentage of total income held by the bottom 10% of the population.
• Income Group: Categorization of the country’s income group (Low Income, Lower Middle Income, Upper Middle Income, High Income).

Potential Uses

• Economic Analysis: Understand global income inequality trends and how they vary by country and region.
• Predictive Modeling: Use the dataset to build machine learning models predicting future income inequality based on historical data.
• Policy Research: Study the impact of income distribution on policy decisions and economic growth in different nations.
• Visualization: Create heatmaps, time series charts, and more to visualize the income inequality across various countries and years.

Source

The data has been generated to simulate realistic income inequality patterns based on publicly available data on global economic trends.

This is a data record which corresponds to the paper "A consistent dataset for the net income distribution for 184 countries, aggregated to 32 geographical regions and the world from 1958-2015" (Narayan et al. 2023, in prep) https://essd.copernicus.org/preprints/essd-2023-137/

Description/Abstract- Data on the income distribution within and across countries are increasingly becoming important to inform analysis on income inequality and human welfare. While datasets on the income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same income concept and therefore make comparisons across countries and across datasets difficult. Here, we present a consistent dataset on the income distribution across 184 countries which all represent a single income concept namely net-income. We complement the observed values in this dataset with values of the income distribution imputed from summary measures such as the GINI coefficient to generate a consistent time series across countries from 1958 to 2015. For the imputation, we use a recently developed PCA based approach which shows an excellent fit to the latest data on income distributions. We also present another version of this dataset which is aggregated from the country level to 32 geographical regions and the world as a whole. Our aggregation method takes into account both within country and cross- country income inequality when aggregating to the regional level. This dataset will enable more robust analysis of the income distribution at multiple scales.

Abstract

Is global inequality (inequality among world citizens) stable, decreasing or increasing? How high it is? Is it mostly due to inequalities within nations or between nations? Is there a global middle class? See the working papers above: "True world income distribution 1988 and 1993: first calculations based on household surveys alone" no. 2244, and "Decomposing global income distribution: Does the world have a middle class?" no. 2562

Household survey data (1988-2002) used in these papers, and subsequent book "Worlds Apart: Measuring International and Global Inequality", Princeton University Press, 2005. The data are for three benchmark years: 1988, 1993 and 1998

Kind of data

Aggregate data [agg]

Mode of data collection

Other [oth]

In 2023, roughly 1.49 billion adults worldwide had a net worth of less than 10,000 U.S. dollars. By comparison, 58 million adults had a net worth of more than one million U.S. dollars in the same year. Wealth distribution The distribution of wealth is an indicator of economic inequality. The United Nations says that wealth includes the sum of natural, human, and physical assets. Wealth is not synonymous with income, however, because having a large income can be depleted if one has significant expenses. In 2023, nearly 1,700 billionaires had a total wealth between one to two billion U.S. dollars. Wealth worldwide China had the highest number of billionaires in 2023, with the United States following behind. That same year, New York had the most billionaires worldwide.

China % of Household grouped by Annual Income: Urban:RMB65000-70000 data was reported at 4.920 % in 2011. This records an increase from the previous number of 4.420 % for 2010. China % of Household grouped by Annual Income: Urban:RMB65000-70000 data is updated yearly, averaging 3.480 % from Dec 2005 (Median) to 2011, with 7 observations. The data reached an all-time high of 4.920 % in 2011 and a record low of 1.500 % in 2005. China % of Household grouped by Annual Income: Urban:RMB65000-70000 data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HD: Household Income Distribution: Urban.

In 2023, the Middle East and North Africa, and Latin America were the regions with the lowest level of distribution of wealth worldwide, with the richest ten percent holding around ** percent of the total wealth. On the other hand, in Europe, the richest ten percent held around ** percent of the wealth. East and South Asia were the regions where the poorest half of the population held the highest share of the wealth, but still only around **** percent, underlining the high levels of wealth inequalities worldwide.

The OECD Income Distribution Database (IDD) offers data on levels and trends in income inequality and poverty and is updated on a rolling basis, two to three times a year.

Graph and download economic data for Net Worth Held by the Bottom 50% (1st to 50th Wealth Percentiles) (WFRBLB50107) from Q3 1989 to Q2 2025 about net worth, wealth, percentile, Net, and USA.

This Web map shows the global wealth distribution for the years 1995, 2000, and 2005. Web map published and hosted by Esri Canada © 2013. Content Sources: Countries, Esri Maps and DataThe World Bank, The Changing Wealth of Nations: http://data.worldbank.org/data-catalog/wealth-of-nations Coordinate System: Web Mercator Auxiliary Sphere (WKID 102100) Update Frequency: As Required Publication Date: October 2013 OECD stands for Organisation for Economic Co-operation and Development and is a global organization created to "promote policies that will improve the economic and social well-being of people around the world".

The indicator is a measure of the inequality of income distribution. It is calculated as the ratio of total income received by the 20 % of the population with the highest income (the top quintile) to that received by the 20 % of the population with the lowest income (the bottom quintile).

United States US: Income Share Held by Highest 20% data was reported at 46.900 % in 2016. This records an increase from the previous number of 46.400 % for 2013. United States US: Income Share Held by Highest 20% data is updated yearly, averaging 46.000 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 46.900 % in 2016 and a record low of 41.200 % in 1979. United States US: Income Share Held by Highest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; 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 (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Upvote if its helpful for you Thank You Dive into the intricate relationship between happiness and income inequality with our comprehensive dataset sourced from the World Bank. Uncover key insights into how nations' happiness levels may be influenced by economic disparities. Explore the nuances of global well-being and socioeconomic factors, shedding light on the intricate connections between happiness and income distribution on a worldwide scale. Harness the power of data to gain valuable insights into the factors that contribute to societal contentment and address the complexities of global happiness. Columns in dataset are: Column Names: ['country', 'adjusted_satisfaction', 'avg_satisfaction', 'std_satisfaction', 'avg_income', 'median_income', 'income_inequality', 'region', 'happyScore', 'GDP', 'country.1']

This dataset provides a comprehensive overview of global wealth distribution in 2021. It includes data on total wealth, GDP per adult, wealth per adult, and the share of world wealth for various countries. This data can be used for various analyses, such as studying wealth inequality, economic development, and global financial trends.