In 2023, the percentage of income held by the richest 20 percent of the population in Colombia amounted to 58.7 percent. Between 1980 and 2023, the figure dropped by 0.3 percentage points, though the decline followed an uneven course rather than a steady trajectory.

The percentage of income held by the richest 20 percent of the population in Argentina amounted to 47.8 percent in 2023. Between 1980 and 2023, the percentage of income held rose by 1.2 percentage points, though the increase followed an uneven trajectory rather than a consistent upward trend.

Graph and download economic data for GINI Index for the United States (SIPOVGINIUSA) from 1963 to 2023 about gini, indexes, and USA.

Abstract

This file contains data on Gini coefficients, cumulative quintile shares, explanations regarding the basis on which the Gini coefficient was computed, and the source of the information. There are two data-sets, one containing the "high quality" sample and the other one including all the information (of lower quality) that had been collected.

The database was constructed for the production of the following paper:

Deininger, Klaus and Lyn Squire, "A New Data Set Measuring Income Inequality", The World Bank Economic Review, 10(3): 565-91, 1996.

This article presents a new data set on inequality in the distribution of income. The authors explain the criteria they applied in selecting data on Gini coefficients and on individual quintile groups’ income shares. Comparison of the new data set with existing compilations reveals that the data assembled here represent an improvement in quality and a significant expansion in coverage, although differences in the definition of the underlying data might still affect intertemporal and international comparability. Based on this new data set, the authors do not find a systematic link between growth and changes in aggregate inequality. They do find a strong positive relationship between growth and reduction of poverty.

Geographic coverage

In what follows, we provide brief descriptions of main features for individual countries that are included in the data-base. Without being comprehensive, these notes are intended to indicate some of the considerations underlying our decision to include or exclude certain observations.

Argentina Various permanent household surveys, all covering urban centers only, have been regularly conducted since 1972 and are quoted in a wide variety of sources and years, e.g., for 1980 (World Bank 1992), 1985 (Altimir 1994), and 1989 (World Bank 1992). Estimates for 1963, 1965, 1969/70, 1970/71, 1974, 1975, 1980, and 1981 (Altimir 1987) are based only on Greater Buenos Aires. Estimates for 1961, 1963, 1970 (Jain 1975) and for 1970 (van Ginneken 1984) have only limited geographic coverage and do not satisfy our minimum criteria.

Despite the many urban surveys, there are no income distribution data that are representative of the population as a whole. References to national income distribution for the years 1953, 1959, and 1961(CEPAL 1968 in Altimir 1986 ) are based on extrapolation from national accounts and have therefore not been included. Data for 1953 and 1961 from Weisskoff (1970) , from Lecaillon (1984) , and from Cromwell (1977) are also excluded.

Australia Household surveys, the result of which is reported in the statistical yearbook, have been conducted in 1968/9, 1975/6, 1978/9, 1981, 1985, 1986, 1989, and 1990.

Data for 1962 (Cromwell, 1977) and 1966/67 (Sawyer 1976) were excluded as they covered only tax payers. Jain's data for 1970 was excluded because it covered income recipients only. Data from Podder (1972) for 1967/68, from Jain (1975) for the same year, from UN (1985) for 78/79, from Sunders and Hobbes (1993) for 1986 and for 1989 were excluded given the availability of the primary sources. Data from Bishop (1991) for 1981/82, from Buhman (1988) for 1981/82, from Kakwani (1986) for 1975/76, and from Sunders and Hobbes (1993) for 1986 were utilized to test for the effect of different definitions. The values for 1967 used by Persson and Tabellini and Alesina and Rodrik (based on Paukert and Jain) are close to the ones reported in the Statistical Yearbook for 1969.

Austria: In addition to data referring to the employed population (Guger 1989), national household surveys for 1987 and 1991 are included in the LIS data base. As these data do not include income from self-employment, we do not report them in our high quality data-set.

Bahamas Data for Ginis and shares are available for 1973, 1977, 1979, 1986, 1988, 1989, 1991, 1992, and 1993 in government reports on population censuses and household budget surveys, and for 1973 and 1975 from UN (1981). Estimates for 1970 (Jain 1975), 1973, 1975, 1977, and 1979 (Fields 1989) have been excluded given the availability of primary sources.

Bangladesh Data from household surveys for 1973/74, 1976/77, 1977/78, 1981/82, and 1985/86 are available from the Statistical Yearbook, complemented by household-survey based information from Chen (1995) and the World Development Report. Household surveys with rural coverage for 1959, 1960, 1963/64, 1965, 1966/67 and 1968/69, and with urban coverage for 1963/64, 1965, 1966/67, and 1968/69 are also available from the Statistical yearbook. Data for 1963/64 ,1964 and 1966/67, (Jain 1975) are not included due to limited geographic coverage, We also excluded secondary sources for 1973/74, 1976/77, 1981/82 (Fields 1989), 1977 (UN 1981), 1983 (Milanovic 1994), and 1985/86 due to availability of the primary source.

Barbados National household surveys have been conducted in 1951/52 and 1978/79 (Downs, 1988). Estimates based on personal tax returns, reported consistently for 1951-1981 (Holder and Prescott, 1989), had to be excluded as they exclude the non-wage earning population. Jain's figure (used by Alesina and Rodrik) is based on the same source.

Belgium Household surveys with national coverage are available for 1978/79 (UN 1985), and for 1985, 1988, and 1992 (LIS 1995). Earlier data for 1969, 1973, 1975, 1976 and 1977 (UN 1981) refer to taxable households only and are not included.

Bolivia The only survey with national coverage is the 1990 LSMS (World Development Report). Surveys for 1986 and 1989 cover the main cities only (Psacharopoulos et al. 1992) and are therefore not included. Data for 1968 (Cromwell 1977) do not refer to a clear definition and is therefore excluded.

Botswana The only survey with national coverage was conducted in 1985-1986 (Chen et al 1993); surveys in 74/75 and 85/86 included rural areas only (UN 1981). We excluded Gini estimates for 1971/72 that refer to the economically active population only (Jain 1975), as well as 1974/75 and 1985/86 (Valentine 1993) due to lack of national coverage or consistency in definition.

Brazil Data from 1960, 1970, 1974/75, 1976, 1977, 1978, 1980, 1982, 1983, 1985, 1987 and 1989 are available from the statistical yearbook, in addition to data for 1978 (Fields 1987) and for 1979 (Psacharopoulos et al. 1992). Other sources have been excluded as they were either not of national coverage, based on wage earners only, or because a more consistent source was available.

Bulgaria: Data from household surveys are available for 1963-69 (in two year intervals), for 1970-90 (on an annual basis) from the Statistical yearbook and for 1991 - 93 from household surveys by the World Bank (Milanovic and Ying).

Burkina Faso A priority survey has been undertaken in 1995.

Central African Republic: Except for a household survey conducted in 1992, no information was available.

Cameroon The only data are from a 1983/4 household budget survey (World Bank Poverty Assessment).

Canada Gini- and share data for the 1950-61 (in irregular intervals), 1961-81 (biennially), and 1981-91 (annually) are available from official sources (Statistical Yearbook for years before 1971 and Income Distributions by Size in Canada for years since 1973, various issues). All other references seem to be based on these primary sources.

Chad: An estimate for 1958 is available in the literature, and used by Alesina and Rodrik and Persson and Tabellini but was not included due to lack of primary sources.

Chile The first nation-wide survey that included not only employment income was carried out in 1968 (UN 1981). This is complemented by household survey-based data for 1971 (Fields 1989), 1989, and 1994. Other data that refer either only to part of the population or -as in the case of a long series available from World Bank country operations- are not clearly based on primary sources, are excluded.

China Annual household surveys from 1980 to 1992, conducted separately in rural and urban areas, were consolidated by Ying (1995), based on the statistical yearbook. Data from other secondary sources are excluded due to limited geographic and population coverage and data from Chen et al (1993) for 1985 and 1990 have not been included, to maintain consistency of sources..

Colombia The first household survey with national coverage was conducted in 1970 (DANE 1970). In addition, there are data for 1971, 1972, 1974 CEPAL (1986), and for 1978, 1988/89, and 1991 (World Bank Poverty Assessment 1992 and Chen et al. 1995). Data referring to years before 1970 -including the 1964 estimate used in Persson and Tabellini were excluded, as were estimates for the wage earning population only.

Costa Rica Data on Gini coefficients and quintile shares are available for 1961, 1971 (Cespedes 1973),1977 (OPNPE 1982), 1979 (Fields 1989), 1981 (Chen et al 1993), 1983 (Bourguignon and Morrison 1989), 1986 (Sauma-Fiatt 1990), and 1989 (Chen et al 1993). Gini coefficients for 1971 (Gonzalez-Vega and Cespedes in Rottenberg 1993), 1973 and 1985 (Bourguignon and Morrison 1989) cover urban areas only and were excluded.

Cote d'Ivoire: Data based on national-level household surveys (LSMS) are available for 1985, 1986, 1987, 1988, and 1995. Information for the 1970s (Schneider 1991) is based on national accounting information and therefore excluded

Cuba Official information on income distribution is limited. Data from secondary sources are available for 1953, 1962, 1973, and 1978, relying on personal wage income, i.e. excluding the population that is not economically active (Brundenius 1984).

Czech Republic Household surveys for 1993 and 1994 were obtained from Milanovic and Ying. While it is in principle possible to go back further, splitting national level surveys for the former Czechoslovakia into their independent parts, we decided not to do so as the same argument could be used to

The period from 1980 to 2023 saw an increase in the share of national income in Europe taken by the top 10 percent of earners. This period has generally been categorized by economists as a period of rising income inequality, especially when compared with the postwar period (1945-1970s) in Europe which saw a compression of the income distribution, with the middle classes in particular making large gains. As financial and labor markets were liberalized in the 1980s and as the effects of economic globalization took hold, however, a growing share of income went to the top earners. This European trend mirrors increases in inequality across the globe during this period, with the United States seeing a particularly sharp rise in the share taken by its top one percent. Rising income inequality has been linked to the rise of populism in Europe throughout the 2000s and 2010s, as voters sought to hit back at economic elites.

Abstract Contrary to the huge development of the Brazilian economy from the post-war to the end of the seventies, the eighties signified the rupture of this cycle and the combination of a chronic inflationary process, the economic stagnation and the worsening of income inequality. These factors together have not revealed to be neutral concerning the distributive aspect. Between 1981 and 1989, the income of the 10 per cent richer increased 14,2 per cent, while the income of the 20 per cent poorer decreased 26 per cent. This work presents some international comparisons, even on the functional as well as on the personal distribution of income and concludes that this distribution becomes a fundamental aspect to the stabilization and to the economic-social development recovering.

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.

As of 2023, Spain was the major economy in Europe with the highest share of national income taken home by the bottom 50 percent of earners. The country has seen a gradual increase in the share taken by the poorest 50 percent since the 1990s, with this share increasing from roughly 20 percent to over 21 percent in 2023. In stark contrast, Russia is the country which has seen the greatest decrease in the share of income taken by the bottom half. With the end of communist rule in 1991, the income of the poorest Russians nosedived from around 28 percent of national income, to less than 10 percent in 1996. Since then, the bottom half's share in Russia has increased, being approximately 16 percent in 2023.

I construct an incomplete market model featuring a closed-form expression for optimal consumption. In the model, individual consumption is an isoelastic function of wealth, inclusive of income, yielding partial consumption smoothing based on borrowing and lending in response to income shocks. I show that the model replicates several empirical characteristics of inequality in consumption, income, and wealth and their dynamics at the individual level. Using the model, I show that the rising wealth inequality since the 1980s, induced by an increase in idiosyncratic income risk, has substantially contributed to trend-level changes in real interest rates, capital-to-income ratios, and consumption-to-wealth ratios.

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.

While most Americans appear to acknowledge the large gap between the rich and the poor in the U.S., it is not clear if the public is aware of recent changes in income inequality. Even though economic inequality has grown substantially in recent decades, studies have shown that the public's perception of growing income disparities has remained mostly unchanged since the 1980s. This research offers an alternative approach to evaluating how public perceptions of inequality are developed. Centrally, it conceptualizes the public's response to growing economic disparities by applying theories of macro-political behavior and place-based contextual effects to the formation of aggregate perceptions about income inequality. It is argued that most of the public relies on basic information about the economy to form attitudes about inequality and that geographic context---in this case, the American states---plays a role in how views of income disparities are produced. A new measure of state perceptions of growing economic inequality over a 25-year period is used to examine whether the public is responsive to objective changes in economic inequality. Time-series cross-sectional analyses suggest that the public's perceptions of growing inequality are largely influenced by objective state economic indicators and state political ideology. This research has implications for how knowledgeable the public is of disparities between the rich and the poor, whether state context influences attitudes about inequality, and what role the public will have in determining how expanding income differences are addressed through government policy.

In the third quarter of 2024, the top ten percent of earners in the United States held over ** percent of total wealth. This is fairly consistent with the second quarter of 2024. Comparatively, the wealth of the bottom ** percent of earners has been slowly increasing since the start of the *****, though remains low. Wealth distribution in the United States by generation can be found here.

Colombia CO: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 54.800 % in 2022. This records a decrease from the previous number of 55.100 % for 2021. Colombia CO: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 53.600 % from Dec 1980 (Median) to 2022, with 28 observations. The data reached an all-time high of 59.100 % in 1980 and a record low of 49.700 % in 2017. Colombia CO: 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 Colombia – Table CO.World Bank.WDI: Social: Poverty and Inequality. 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, 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 article tests the empirical relationship between inequality and the protection of personal integrity rights using a cross-national time-series data set for 162 countries for the years 1980–2004. The data comprise measures of land inequality, income inequality, and a combined factor score for personal integrity rights protection, while the analysis controls for additional sets of explanatory variables related to development, political regimes, ethnic composition, and domestic conflict. The analysis shows robust support for the empirical relationship between income inequality and personal integrity rights abuse across the whole sample of countries as well as for distinct subsets, including non-communist countries and non-OECD countries. The hypothesized effect of land inequality is also born out by the data, although its effects are less substantial and less robust across different methods of estimation. Additional variables with explanatory weight include the level of income, democracy, ethnic fragmentation, domestic conflict, and population size. Sensitivity analysis suggests that the results are not due to reverse causation, misspecification or omitted variable bias. The analysis is discussed in the context of inequality and rights abuse in specific country cases and the policy implications of the results are considered in the conclusion.

Growing economic inequality has raised concerns that democratic governments are no longer responsive to popular demands for redistribution, either because the state capacity is eroded by footloose capital, or because the wealthy subvert democracy through the power of money. In this paper we critically assess these assertions against long-standing arguments about redistribution and insurance under democracy. We test the alternatives on a new comprehensive dataset on income inequality from 17 advanced democracies between 1980 and 2019. We find that before taxes and transfers income inequality has risen markedly everywhere, but also that government redistribution has played a critical role in compensating the middle class, and to a perhaps surprising degree also the poor. The United States is a large outlier, however.

This statistic shows the Gini's concentration coefficient in Taiwan from 1980 to 2024. In 2024, the Gini index in Taiwan was 34.1 points, which indicates a slight increase compared to 2023. In the countries having relative equality in their distributions of income, the value of the Gini coefficient usually ranges between the scores of 20 and 35. In comparison, the Gini index in China ranged at around 46.5 points in 2023.

AR: Income Share Held by Lowest 10% data was reported at 2.000 % in 2022. This records an increase from the previous number of 1.800 % for 2021. AR: Income Share Held by Lowest 10% data is updated yearly, averaging 1.550 % from Dec 1980 (Median) to 2022, with 34 observations. The data reached an all-time high of 2.000 % in 2022 and a record low of 0.700 % in 2001. AR: 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 Argentina – Table AR.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.;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).

Madagascar: Gini income inequality index: The latest value from 2012 is 42.6 index points, an increase from 42.4 index points in 2010. In comparison, the world average is 36.29 index points, based on data from 82 countries. Historically, the average for Madagascar from 1980 to 2012 is 42.79 index points. The minimum value, 38.6 index points, was reached in 1999 while the maximum of 47.4 index points was recorded in 2001.

VITAL SIGNS INDICATOR Income (EC4)

FULL MEASURE NAME Household income by place of residence

LAST UPDATED May 2019

DESCRIPTION Income reflects the median earnings of individuals and households from employment, as well as the income distribution by quintile. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis.

DATA SOURCE U.S. Census Bureau: Decennial Census Count 4Pb (1970) Form STF3 (1980-1990) Form SF3a (2000) https://nhgis.org

U.S. Census Bureau: American Community Survey Form B19013 (2006-2017; place of residence) http://api.census.gov

Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1970-2017; specific to each metro area) http://data.bls.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Income data reported in a given year reflects the income earned in the prior year (decennial Census) or in the prior 12 months (American Community Survey); note that this inconsistency has a minor effect on historical comparisons (for more information, go to: http://www.census.gov/acs/www/Downloads/methodology/ASA_nelson.pdf). American Community Survey 1-year data is used for larger geographies – metropolitan areas and counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Quintile income for 1970-2000 is imputed from Decennial Census data using methodology from the California Department of Finance (for more information, go to: http://www.dof.ca.gov/Forecasting/Demographics/Census_Data_Center_Network/documents/How_to_Recalculate_a_Median.pdf). Bay Area income is the population weighted average of county-level income.

Income has been inflated using the Consumer Price Index specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data is unavailable for some historical data points. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.