Cross-national research on the causes and consequences of income inequality has been hindered by the limitations of existing inequality datasets: greater coverage across countries and over time is 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 overcome these limitations. A custom missing-data algorithm was used to standardize the United Nations University's World Income Inequality Database and data from other sources; data collected by the Luxembourg Income Study served as the standard. The SWIID provides comparable Gini indices of gross and net income inequality for 192 countries for as many years as possible from 1960 to the present along with estimates of uncertainty in these statistics. By maximizing comparability for the largest possible sample of countries and years, the SWIID is better suited to broadly cross-national research on income inequality than previously available sources: it offers coverage double that of the next largest income inequality dataset, and its record of comparability is three to eight times better than those of alternate datasets.

Source: https://www.wider.unu.edu/database/wiid User Guide: https://www.wider.unu.edu/sites/default/files/WIID/PDF/WIID-User_Guide_06MAY2020.pdf

The World Income Inequality Database (WIID) contains information on income inequality in various countries and is maintained by the United Nations University-World Institute for Development Economics Research (UNU-WIDER). The database was originally compiled during 1997-99 for the research project Rising Income Inequality and Poverty Reduction, directed by Giovanni Andrea Corina. A revised and updated version of the database was published in June 2005 as part of the project Global Trends in Inequality and Poverty, directed by Tony Shorrocks and Guang Hua Wan. The database was revised in 2007 and a new version was launched in May 2008.

The database contains data on inequality in the distribution of income in various countries. The central variable in the dataset is the Gini index, a measure of income distribution in a society. In addition, the dataset contains information on income shares by quintile or decile. The database contains data for 159 countries, including some historical entities. The temporal coverage varies substantially across countries. For some countries there is only one data entry; in other cases there are over 100 data points. The earliest entry is from 1867 (United Kingdom), the latest from 2003. The majority of the data (65%) cover the years from 1980 onwards. The 2008 update (version WIID2c) includes some major updates and quality improvements, in fact leading to a reduced number of variables in the new version. The new version has 334 new observations and several revisions/ corrections made in 2007 and 2008.

Since 2000, the share of the world's total labor income before tax earned by women fluctuated between 27.91 percent to 28.25 percent. This is significantly less than their male counterparts. There are also differences between the world regions.

The UNU-WIDER World Income Inequality Database (WIID) collects and stores information on income inequality for developed, developing, and transition countries.

Comparing the 130 selected regions regarding the gini index , South Africa is leading the ranking (0.63 points) and is followed by Namibia with 0.58 points. At the other end of the spectrum is Slovakia with 0.23 points, indicating a difference of 0.4 points to South Africa. The Gini coefficient here measures the degree of income inequality on a scale from 0 (=total equality of incomes) to one (=total inequality).The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

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 Global Database of Light-based Geospatial Income Inequality (LGII) Measures, Version 1 data set contains Gini-coefficients of inequality for 234 countries and territories from 1992 to 2013. The measurement Unit is the Gini-Coefficient (Range: 0-1), with higher values representing higher inequality. These measures are constructed using worldwide geospatial satellite data on nighttime lights emission as a proxy for economic prosperity, matched with varying sources of data on geo-located population counts. The nighttime lights data were supplied by the National Oceanic and Atmospheric Administration (NOAA), National Centers for Environmental Information (NCEI), Earth Observation Group (EOG), and Operational Linescan System (OLS) instruments. The population data used consisted of CIESIN's Gridded Population of the World (GPW) collection, and the Oak Ridge National Laboratory (ORNL) LandScan (LSC) data set. The nighttime lights and population data were combined to produce an array of geospatially-informed Gini-coefficients, which were then weighted to optimize their correlation with a benchmark - specifically, the Standardized World Income Inequality Database (SWIID), to generate a parsimonious composite inequality metric.

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]

Graph and download economic data for Gross National Income for Low Income Countries (NYGNPMKTPCDLIC) from 1960 to 2023 about GNI and income.

Graph and download economic data for Current receipts from the rest of the world: Income receipts (B645RC1Q027SBEA) from Q1 1947 to Q1 2025 about receipts, income, and GDP.

Tunisia TN: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 35.800 % in 2010. This records a decrease from the previous number of 37.700 % for 2005. Tunisia TN: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 40.500 % from Dec 1985 (Median) to 2010, with 6 observations. The data reached an all-time high of 43.400 % in 1985 and a record low of 35.800 % in 2010. Tunisia TN: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tunisia – Table TN.World Bank.WDI: Poverty. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. 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.

Norway NO: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 27.500 % in 2015. This records an increase from the previous number of 26.800 % for 2014. Norway NO: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 26.800 % from Dec 2003 (Median) to 2015, with 13 observations. The data reached an all-time high of 31.600 % in 2004 and a record low of 25.300 % in 2011. Norway NO: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Norway – Table NO.World Bank.WDI: Poverty. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. 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.

BR: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 22.000 % in 2022. This records a decrease from the previous number of 22.200 % for 2021. BR: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 24.500 % from Dec 1981 (Median) to 2022, with 38 observations. The data reached an all-time high of 26.500 % in 1989 and a record low of 18.200 % in 2020. BR: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;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).

United States - Current payments to the rest of the world: Income payments on assets: Interest was 862.94600 Bil. of $ in January of 2025, according to the United States Federal Reserve. Historically, United States - Current payments to the rest of the world: Income payments on assets: Interest reached a record high of 885.12300 in July of 2024 and a record low of 80.49200 in July of 1986. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Current payments to the rest of the world: Income payments on assets: Interest - last updated from the United States Federal Reserve on July of 2025.

Net national incomes have grown globally, growing from 694 U.S. dollars in 1970 to 9,750 in 2021. Much of this growth can be attributed to improvements in overall global development, as economies in developing countries have grown rapidly. Net national incomes grew steadily from the 1970s to the 2000s, and then experienced a sharper increase during the 2000s until the Great Recession, falling slightly in 2008.

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 followsFormat: 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 levelProduct 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

Greece GR: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 36.000 % in 2015. This records an increase from the previous number of 35.800 % for 2014. Greece GR: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 34.600 % from Dec 2003 (Median) to 2015, with 13 observations. The data reached an all-time high of 36.200 % in 2012 and a record low of 32.800 % in 2003. Greece GR: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Greece – Table GR.World Bank.WDI: Poverty. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. 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.

Graph and download economic data for Current payments to the rest of the world: Income payments: Wage and salary payments (NA000274Q) from Q1 2002 to Q1 2025 about payments, salaries, wages, income, and GDP.

With only 1,100 euros after accounting for purchasing power parity (PPP), Yemen had the lowest average income per adult worldwide in 2022. However, most of the countries on the list are located in Sub-Saharan Africa.

Graph and download economic data for Rest of the World; Income Receipts from the U.S., Transactions (BOGZ1FU266904101Q) from Q4 1946 to Q1 2025 about receipts, transactions, income, and USA.