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 75 percent of the total wealth. On the other hand, in Europe, the richest ten percent held around 60 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 five percent, underlining the high levels of wealth inequalities worldwide.

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.

This feature shows the global wealth distribution for the years 1995, 2000, and 2005. Feature 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".

In 2023, 18 of the 3,323 billionaires worldwide had assets amounting to more than 50 billion U.S. dollars. On the other hand, almost 1,700 had a fortune between one and two billion dollars. As of March 2025, Elon Musk was the richest person in the world.

In the first quarter of 2024, almost two-thirds percent of the total wealth in the United States was owned by the top 10 percent of earners. In comparison, the lowest 50 percent of earners only owned 2.5 percent of the total wealth. Income inequality in the U.S. Despite the idea that the United States is a country where hard work and pulling yourself up by your bootstraps will inevitably lead to success, this is often not the case. In 2023, 7.4 percent of U.S. households had an annual income under 15,000 U.S. dollars. With such a small percentage of people in the United States owning such a vast majority of the country’s wealth, the gap between the rich and poor in America remains stark. The top one percent The United States follows closely behind China as the country with the most billionaires in the world. Elon Musk alone held around 219 billion U.S. dollars in 2022. Over the past 50 years, the CEO-to-worker compensation ratio has exploded, causing the gap between rich and poor to grow, with some economists theorizing that this gap is the largest it has been since right before the Great Depression.

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 Q4 2024 about net worth, wealth, percentile, Net, and USA.

The massive wealth inequality in the world is underpinned by this chart: While just above one percent of the world's population had fortunes of more than one million U.S. dollars in 2022, more than half 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

The World Top Incomes Database provides statistical information on the shares of top income groups for 30 countries. The construction of this database was possible thanks to the research of over thirty contributing authors.

There has been a marked revival of interest in the study of the distribution of top incomes using tax data. Beginning with the research by Thomas Piketty of the long-run distribution of top incomes in France, a succession of studies has constructed top income share time series over the long-run for more than twenty countries to date. These projects have generated a large volume of data, which are intended as a research resource for further analysis.

In using data from income tax records, these studies use similar sources and methods as the pioneering work by Kuznets for the United States.The findings of recent research are of added interest, since the new data provide estimates covering nearly all of the twentieth century -a length of time series unusual in economics. In contrast to existing international databases, generally restricted to the post-1970 or post-1980 period, the top income data cover a much longer period, which is important because structural changes in income and wealth distributions often span several decades.

The data series is fairly homogenous across countries, annual, long-run, and broken down by income source for several cases. Users should be aware also about their limitations. Firstly, the series measure only top income shares and hence are silent on how inequality evolves elsewhere in the distribution. Secondly, the series are largely concerned with gross incomes before tax. Thirdly, the definition of income and the unit of observation (the individual vs. the family) vary across countries making comparability of levels across countries more difficult. Even within a country, there are breaks in comparability that arise because of changes in tax legislation affecting the definition of income, although most studies try to correct for such changes to create homogenous series. Finally and perhaps most important, the series might be biased because of tax avoidance and tax evasion.

The first theme of the research programme is the assembly and analysis of historical evidence from fiscal records on the long-run development of economic inequality. “Long run” is a relative term, and here it means evidence dating back before the Second World War, and extending where possible back into the nineteenth century. The time span is determined by the sources used, which are based on taxes on incomes, earnings, wealth and estates. Perspective on current concerns is provided by the past, but also by comparison with other countries. The second theme of the research programme is that of cross-country comparisons. The research is not limited to OECD countries and will draw on evidence globally. In order to understand the drivers of inequality, it is necessary to consider the sources of economic advantage. The third theme is the analysis of the sources of income, considering separately the roles of earned incomes and property income, and examining the historical and comparative evolution of earned and property income, and their joint distribution. The fourth theme is the long-run trend in the distribution of wealth and its transmission through inheritance. Here again there are rich fiscal data on the passing of estates at death.

Billionaires with a net worth over 50 billion U.S. dollars had a combined net worth of nearly two trillion dollars in 2023. Billionaires with a fortune of two to five billion U.S. dollars had the highest combined total wealth, nearly reaching three trillion U.S. dollars. That year, there were 18 persons with a fortune of over 50 billion dollars.

Coordinated by Facundo Alvaredo, Anthony B. Atkinson, Thomas Piketty, Emmanuel Saez and Gabriel Zucman, the World Wealth and Income Database aims to provide open access to data series on income and wealth worldwide. The goal is to be able to produce Distributional National Accounts: estimates of the distribution of wealth and income using concepts that are consistent with the macroeconomic national accounts. The focus lies not only on the national level, but also on the global and regional level.

There has been a marked revival of interest in the study of the distribution of top incomes using tax data. Beginning with the research by Thomas Piketty (2001, 2003) of the long-run distribution of top incomes in France, a succession of studies has constructed top income share time series over the long-run for more than twenty countries to date. These projects have generated a large volume of data, which are intended as a research resource for further analysis. The world top incomes database aims to providing convenient on line access to all the existent series. This is an ongoing endeavour, and we will progressively update the base with new observations, as authors extend the series forwards and backwards. Despite the database's name, we will also add information on the distribution of earnings and the distribution of wealth. As the map below shows, around forty-five further countries are under study, and will be incorporated at some point (see Work in Progress).

Description:

The "Billionaires_2023_Dataset" is a meticulously curated and up-to-date compilation of data on the world's wealthiest individuals as of the year 2023, sourced directly from Forbes.com. This dataset offers comprehensive insights into the financial, demographic, and professional characteristics of billionaires, making it an invaluable resource for researchers, analysts, journalists, and data enthusiasts. Explore the economic trends, wealth disparities, and entrepreneurial achievements of the globe's most affluent individuals with this dataset.

Contents:

Rank: The ranking of billionaires based on their net Name: The full name of each Net Worth: Estimated net worth in billions of Age: Age of each billionaire at the time of data Country/Territory: The location associated with each billionaire's residence or business Source: The primary source of wealth for each individual . Industry: The specific industry or sector linked to the source of wealth .

How to Use:

• Data Analysis: Perform in-depth analysis to uncover trends and patterns in billionaire demographics, wealth distribution, and industry concentrations.
• Visualizations: Create visualizations such as charts, graphs, and maps to represent the data visually.
• Research: Utilize the dataset for academic research, market analysis, or investigative journalism.
• Comparative Studies: Compare the 2023 dataset with previous years to observe changes in billionaire profiles and wealth distribution.
• Data Enrichment: Enhance your own datasets or research projects with demographic and financial data from this dataset.

Important Notes:

• Data Source: The data has been sourced directly from Forbes.com, a trusted and reputable platform for billionaire rankings and wealth estimates.
• Updates: The dataset may be periodically updated to reflect changes in billionaire rankings and net worth estimates.
• Privacy and Ethical Considerations: Respect privacy and ethical considerations when using the data, and avoid using it for harmful purposes.

Graph and download economic data for Net Worth Held by the Bottom 50% (1st to 50th Wealth Percentiles) (WFRBLB50107) from Q3 1989 to Q4 2024 about net worth, wealth, percentile, Net, and USA.

Abstract

Dataset used in World Bank Policy Research Working Paper #2876, published in World Bank Economic Review, No. 1, 2005, pp. 21-44.

The effects of globalization on income distribution in rich and poor countries are a matter of controversy. While international trade theory in its most abstract formulation implies that increased trade and foreign investment should make income distribution more equal in poor countries and less equal in rich countries, finding these effects has proved elusive. The author presents another attempt to discern the effects of globalization by using data from household budget surveys and looking at the impact of openness and foreign direct investment on relative income shares of low and high deciles. The author finds some evidence that at very low average income levels, it is the rich who benefit from openness. As income levels rise to those of countries such as Chile, Colombia, or Czech Republic, for example, the situation changes, and it is the relative income of the poor and the middle class that rises compared with the rich. It seems that openness makes income distribution worse before making it better-or differently in that the effect of openness on a country's income distribution depends on the country's initial income level.

Kind of data

Aggregate data [agg]

Over 21 million individuals residing in the United States belonged to the global top one percent of ultra high net worth individuals worldwide in 2022. China ranked second, with over five million top one percent wealth holders globally. France followed in third.

This activity will no longer be maintained after June 16, 2025. Current lessons are available in the K-12 Classroom Activities Gallery.

This activity uses Map Viewer. ResourcesMapTeacher guide Student worksheetGet startedOpen the map.Use the teacher guide to explore the map with your class or have students work through it on their own with the worksheet.New to GeoInquiriesTM? See Getting to Know GeoInquiries.Science standardsAPES: II – The Living World.APES: III.B – Population. Strategies for sustainability; impacts of population growth.Learning outcomesStudents will determine patterns of wealth distribution globally. Students will identify sustainable suggestions for regions of the world.More activitiesAll Environmental Science GeoInquiriesAll GeoInquiries

Based on the degree of inequality in income distribution measured by the Gini coefficient, Colombia was the most unequal country in Latin America as of 2022. Colombia's Gini coefficient amounted to 54.8. The Dominican Republic recorded the lowest Gini coefficient at 37, even below Uruguay and Chile, which are some of the countries with the highest human development indexes in Latin America. The Gini coefficient explained The Gini coefficient measures the deviation of the distribution of income among individuals or households in a given country from a perfectly equal distribution. A value of 0 represents absolute equality, whereas 100 would be the highest possible degree of inequality. This measurement reflects the degree of wealth inequality at a certain moment in time, though it may fail to capture how average levels of income improve or worsen over time. What affects the Gini coefficient in Latin America? Latin America, as other developing regions in the world, generally records high rates of inequality, with a Gini coefficient ranging between 37 and 55 points according to the latest available data from the reporting period 2010-2023. According to the Human Development Report, wealth redistribution by means of tax transfers improves Latin America's Gini coefficient to a lesser degree than it does in advanced economies. Wider access to education and health services, on the other hand, have been proven to have a greater direct effect in improving Gini coefficient measurements in the region.

Introduction

Millionaire Statistics: A growing number of individuals are becoming millionaires across the globe due to economic growth, an increase in stock markets, and entrepreneurial ventures. Studies show that by the year 2024, the population of millionaires and born and bred individuals across the globe will still grow due to the growing concentration of wealth in certain areas and sectors.

An analysis of the statistics on millionaires paints a clear picture of how wealth is being shared among the general populace and the levels of economic oppression in existence, as well as financial matters in the international arena.

This piece demonstrates the situational picture of millionaire statistics in the world, their wealth, their geographical distribution, and projections of their population in the years to come.

About Datset

Top 10 Billionaires Details Dataset of last 25years from 1987 to 2022.

Key Concepts:

1. The dataset contains information about billionaires across the world from 1987 to 2022.
2. It includes variables such as billionaire's name, age, nationality, net worth, and source of wealth.

The Top 10 Billionaires Details Dataset from 1987 to 2022 is a dataset that provides information on the top 10 billionaires of each year from 1987 to 2022. The dataset includes the names of the billionaires, their age, nationality, net worth, and source of wealth.

This dataset is a valuable resource for researchers, analysts, and enthusiasts who are interested in studying the wealth distribution among the top 1% of the population. The dataset can be used for various data analysis tasks such as exploring the trends in the accumulation of wealth over time, analyzing the sources of wealth of the top 10 billionaires, and comparing the net worth of the top 10 billionaires from different years. This dataset is updated annually, and it is a valuable resource for those who want to keep track of the changes in the top 10 billionaires' list over the years.

Acknowledgements:

The data were collected from the official website of worldbank.org