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.

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]

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".

Dataset consisting of inequality measures for 46 nation states and a global bibliography of all known household expenditure surveys covering the period roughly 1880-1960. Each entry notes when and where the survey was carried out and salient characteristics of the survey such as number of households, whether income and/or expenditure data are collected etc. These bibliographies are organised by six world regions and then by 118 nation states. For a sub-set of the most useful surveys we have estimated various inequality measures from the published data for 46 nation states, organised by world region.

This project will calculate new estimates of world inequality in the period from the end of the nineteenth century until the 1960s, based on the results of household expenditure surveys. Our investigations have located a vast cache of household expenditure surveys for the period. Thus far, we have identified around 800 household surveys from around the world, carried out between the 1880s and 1960s, of which around half are of sufficient scope as to be potentially useful for the investigation of inequality. We will extract the reported demographic and expenditure data by income group from these reports and use them to estimate parameters of the income distribution. Using these estimates, we will investigate the changing nature of inequality within a number of key nation states, and also investigate the time path and geography of global inequality 1880-1960. In addition, we would use these data to estimate other indicators of living conditions, such as nutritional attainment, which may provide further insights into the impact of industrialisation on inequality.

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 Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles) (WFRBLTP1246) from Q3 1989 to Q4 2024 about net worth, wealth, percentile, Net, and USA.

Bolivia BO: Income Share Held by Lowest 20% data was reported at 5.300 % in 2021. This records an increase from the previous number of 4.700 % for 2020. Bolivia BO: Income Share Held by Lowest 20% data is updated yearly, averaging 3.500 % from Dec 1990 (Median) to 2021, with 24 observations. The data reached an all-time high of 5.600 % in 1990 and a record low of 1.100 % in 2000. Bolivia BO: Income Share Held by Lowest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Social: Poverty and Inequality. 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, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in The Future of Worldwide Income Distribution, PIIE Working Paper 15-7. If you use the data, please cite as: Hellebrandt, Tomas, and Paolo Mauro. (2015). The Future of Worldwide Income Distribution. PIIE Working Paper 15-7. Peterson Institute for International Economics.

The Gini index measures economic inequality in a country. Specifically, it is the extent to which the distribution of income (or, in some cases, consumption expenditure) deviates from a perfectly equal distribution among individuals or households within an economy.

Japan's share of global wealth stood at approximately five percent in 2022, down from around 7.8 percent in 2013. The total wealth held by adults in Japan amounted to approximately 27 trillion U.S. dollars in 2022.

Turkey Annual Disposable Income Distribution: HH: W Anatolia: Qntls: 4th data was reported at 21.530 % in 2016. This records a decrease from the previous number of 21.870 % for 2015. Turkey Annual Disposable Income Distribution: HH: W Anatolia: Qntls: 4th data is updated yearly, averaging 21.900 % from Dec 2006 (Median) to 2016, with 11 observations. The data reached an all-time high of 23.210 % in 2010 and a record low of 21.360 % in 2008. Turkey Annual Disposable Income Distribution: HH: W Anatolia: Qntls: 4th data remains active status in CEIC and is reported by Turkish Statistical Institute. The data is categorized under Global Database’s Turkey – Table TR.H033: Annual Household Disposable Income Distribution: by Quintiles.

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]

Data and insights on Wealth Distribution in India - share of wealth, average wealth, HNIs, wealth inequality GINI, and comparison with global peers.

Switzerland Income Share Held by Lowest 10% data was reported at 3.200 % in 2015. This stayed constant from the previous number of 3.200 % for 2014. Switzerland Income Share Held by Lowest 10% data is updated yearly, averaging 3.150 % from Dec 2006 (Median) to 2015, with 10 observations. The data reached an all-time high of 3.300 % in 2013 and a record low of 2.900 % in 2007. Switzerland Income Share Held by Lowest 10% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Switzerland – Table CH.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.; ; 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.

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in World on the Move: The Changing Global Income Distribution and Its Implications for Consumption Patterns and Public Policies, PIIE Policy Brief 15-21. If you use the data, please cite as: Hellebrandt, Tomas, and Paolo Mauro. (2015). World on the Move: The Changing Global Income Distribution and Its Implications for Consumption Patterns and Public Policies. PIIE Policy Brief 15-21. Peterson Institute for International Economics.

Analysis of ‘ Decomposing World Income Distribution Database’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://datacatalog.worldbank.org/search/dataset/0041692/ on 21 November 2021.

--- Dataset description provided by original source is as follows ---

Using national income and expenditure distribution data from 119 countries, the authors decompose total income inequality between the individuals in the world, by continent and by "region" (countries grouped by income level). They use a Gini decomposition that allows for an exact breakdown (without a residual term) of the overall Gini by recipients. Looking first at income inequality in income between countries is more important than inequality within countries. Africa, Latin America, and Western Europe and North America are quite homogeneous continent, with small differences between countries (so that most of the inequality on these continents is explained by inequality within countries). Next the authors divide the world into three groups: the rich G7 countries (and those with similar income levels), the less developed countries (those with per capita income less than or equal to Brazil's), and the middle-income countries (those with per capita income between Brazil's and Italy's). They find little overlap between such groups - very few people in developing countries have incomes in the range of those in the rich countries.

--- Original source retains full ownership of the source dataset ---

This dataset provides a gridded subnational datasets for

• Income inequality (Gini coefficient) at admin 1 level
• Gross national income (GNI) per capita PPP at admin 1 level

The datasets are based on reported subnational admin data and spans three decades from 1990 to 2021.

The dataset is presented in details in the following publication. Please cite this paper when using data.

Chrisendo D, Niva V, Hoffman R, Sayyar SM, Rocha J, Sandström V, Solt F, Kummu M. 2024. Income inequality has increased for over two-thirds of the global population. Preprint. doi: https://doi.org/10.21203/rs.3.rs-5548291/v1

Code is available at following repositories:

• Gini coefficient data creation: https://github.com/mattikummu/subnatGini
• GNI per capita data creation: https://github.com/mattikummu/subnatGNI
• analyses for the article: https://github.com/mattikummu/gini_gni_analyses

The following data is given (formats in brackets)

• Income inequality (Gini coefficient) at admin 0 level (national) (GeoTIFF, gpkg, csv)
• Income inequality (Gini coefficient) at admin 1 level (subnational) (GeoTIFF, gpkg, csv)
• Gross national income (GNI) per capita PPP at admin 0 level (national) (GeoTIFF, gpkg, csv)
• Gross national income (GNI) per capita PPP at admin 1 level (subnational) (GeoTIFF, gpkg, csv)
• Slope for Gini coefficient at admin 1 level (GeoTIFF; slope is given also in gpk and csv files)
• Slope for GNI per capita at admin 1 level (GeoTIFF; slope is given also in gpk and csv files)
• Input data for the script that was used to generate the Gini coefficient (input_data_gini.zip)
• Input data for the script that was used to generate the GNI per capita PPP (input_data_GNI.zip)

Files are named as follows
Format: raster data (GeoTIFF) starts with rast_*, polygon data (gpkg) with polyg_*, and tabulated with tabulated_*.
Admin levels: adm0 for admin 0 level, adm1 for admin 1 level
Product type:

• _gini_disp_ for gini coefficient based on disposable income
• _gni_perCapita_ for GNI per capita PPP

Metadata

Grids

Resolution: 5 arc-min (0.083333333 degrees)

Spatial extent: Lon: -180, 180; -90, 90 (xmin, xmax, ymin, ymax)

Coordinate ref system: EPSG:4326 - WGS 84

Format: Multiband geotiff; one band for each year over 1990-2021

Unit: no unit for Gini coefficient and PPP USD in 2017 international dollars for GNI per capita

Geospatial polygon (gpkg) files:

Spatial extent: -180, 180; -90, 83.67 (xmin, xmax, ymin, ymax)

Temporal extent: annual over 1990-2021

Coordinate ref system: EPSG:4326 - WGS 84

Format: gkpk

Unit: no unit for Gini coefficient and PPP USD in 2017 international dollars for GNI per capita

This statistic shows the distribution of income worldwide in 2035 by region. By 2035, roughly 215 million people in India are projected to earn between zero and 1,144 U.S. dollars annually.

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.