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.

ABSTRACT This is a historical reading of economic ideas about the problem of inequality and poverty. Based on the reflections of David Ricardo, the trajectory of economists’ concerns with the topic is explored, in an attempt to demarcate the phases in which the profession’s attention focused on one aspect of the problem of social justice, as well as its causes. and its effects on the behavior of individuals and the economy. In particular, attention is paid to the sensitivity of the research agenda to the various historical contexts, as well as to methodological and technological innovations. The research agenda is predominantly marked by a focus on functional income distribution until the 1980s, when poverty became the center of attention, motivating the development of methods of personal income distribution (size distribution). It offers a panoramic and non-linear reinterpretation of economic ideas about inequality and poverty, a theme that has been gaining increasing importance in the analytical developments of the economy in the last 15 years, in which the problem of concentration of wealth has gained more elaborate outlines, opening a new front of investigations on social justice and the role of public policy.

Using kernel density estimation we describe the distribution of household size-adjusted real income and how it changed over the business cycle of the 1980s in the United States and the United Kingdom. We confirm previous studies that show income inequality increased in the two countries and the middle of the distribution was squashed down. Using a series of statistical tests, however, we find that while the mass in both tails of the distribution increased significantly in both countries over the period, by far the greatest gains were in the upper tail.

Prior research on trends in educational inequality has focused chiefly on changing gaps in educational attainment by family income or parental occupation. In contrast, this contribution provides the first assessment of trends in educational attainment by family wealth and suggests that we should be at least as much concerned about growing wealth gaps in education. Despite overall growth in educational attainment and some signs of decreasing wealth gaps in high school attainment and college access, I find a large and rapidly increasing wealth gap in college attainment between cohorts born in the 1970 and 1980s, respectively. This growing wealth gap in higher educational attainment co-occurred with a rise in inequality in children's wealth backgrounds, though the analyses also suggest that the latter does not fully account for the former. Nevertheless, the results reported here raise concerns about the distribution of educational opportunity among today's children who grow up in a context of particularly extreme wealth inequality.

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.

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 Q1 2025 about net worth, wealth, percentile, Net, and USA.

The purpose of this study was to describe and test hypotheses about Americans' beliefs regarding inequality. The survey investigated beliefs about causes of wealth and poverty, opportunity, and inequality, plus perceptions of fairness and the necessity of income inequality. Included in the survey were questions on self-perceived social class (poor, working, middle, upper-middle, upper), beliefs about differences between social classes, attitudes toward different social classes, and beliefs about discrimination against Blacks, other minorities, and women. The survey also collected information on political preferences, employment, marital status, educational attainment, religion, religiosity, age, sex, income, and satisfaction with life in general.

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.

This paper discusses how the issue of income distribution has resumed its importance in recent decades, showing the evolution of income inequality from the post-Second World War to the present, based on data from studies elaborated by researchers who work in internationally renowned academic centers. Income inequality starts to increase with the rise of neoliberalism in the 1980s, becoming greater in the 2000s, concentrated in the richest 1% of capitalist countries. This reality has demanded new interpretations by scholars, bringing to the debate contributions from Sociology, Political Science and Political Economy. Authors have shown how changes in the international order and its consequences on the pattern of capitalist accumulation in favor of rentier capitalism – a predominantly financial accumulation of capital – have altered the functioning of representative Democracies and affected economic inequality in capitalist countries, contrasting what happened in the “Golden Age” of capitalism (1945-1980) with what has been happening since the 1980s and especially in the 2000s.

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.

The rising share of national income taken by the top one percent of earners is a common thread amongst almost all European countries over the past half century. As economic globalization took hold throughout the 1980s and 1990s, European countries experienced de-industrialization due to the emergence of international competitors, mostly in East Asia. At the same time, information technology and finance became much more important for most European economies, while growth in these sectors tends to favor high earners. This rise in inequality is also often also attributed to the ascendence of 'neoliberal' economic and political ideas which prioritized free markets and the privatization of government-owned businesses. Russia: the explosion of inequality after the fall of communismAmong the largest European economies, the Russian Federation stands out as the country which experienced the sharpest increase in inequality, as a small number of 'oligarchs' took control of the major industries after the collapse of the Soviet Union and the end of communist rule in 1991. The top one percent in Russia increased their share of national income five-fold over the 20 years from 1987 to 2007, when inequality in the country reached its peak as the oligarchs took home over a quarter of the country's income. Turkey: falling share of national income taken by top earners****** has bucked the trend of the rising income share for the richest over this period, as its extremely concentrated income distribution has in fact become somewhat more equitable. The highest earners in Turkey saw their share of national income drop from almost ** percent in the early *****, to a low of ** percent in 2007, after which it has stabilized between ** and ** percent. Western Europe: gradually rising share of national income for the richThe five western European democracies, Germany, France, Italy, Spain, and the United Kingdom, have all seen increases in their top earners' shares of national income over this period. The United Kingdom, Italy, and Germany have in particular seen their shares increase sharply, while Spain and France have experienced a more gradual increase.

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.

This dataset contains replication files for "The Fading American Dream: Trends in Absolute Income Mobility Since 1940" by Raj Chetty, David Grusky, Maximilian Hell, Nathaniel Hendren, Robert Manduca, and Jimmy Narang. For more information, see https://opportunityinsights.org/paper/the-fading-american-dream/. A summary of the related publication follows. One of the defining features of the “American Dream” is the ideal that children have a higher standard of living than their parents. We assess whether the U.S. is living up to this ideal by estimating rates of “absolute income mobility” – the fraction of children who earn more than their parents – since 1940. We measure absolute mobility by comparing children’s household incomes at age 30 (adjusted for inflation using the Consumer Price Index) with their parents’ household incomes at age 30. We find that rates of absolute mobility have fallen from approximately 90% for children born in 1940 to 50% for children born in the 1980s. Absolute income mobility has fallen across the entire income distribution, with the largest declines for families in the middle class. These findings are unaffected by using alternative price indices to adjust for inflation, accounting for taxes and transfers, measuring income at later ages, and adjusting for changes in household size. Absolute mobility fell in all 50 states, although the rate of decline varied, with the largest declines concentrated in states in the industrial Midwest, such as Michigan and Illinois. The decline in absolute mobility is especially steep – from 95% for children born in 1940 to 41% for children born in 1984 – when we compare the sons’ earnings to their fathers’ earnings. Why have rates of upward income mobility fallen so sharply over the past half-century? There have been two important trends that have affected the incomes of children born in the 1980s relative to those born in the 1940s and 1950s: lower Gross Domestic Product (GDP) growth rates and greater inequality in the distribution of growth. We find that most of the decline in absolute mobility is driven by the more unequal distribution of economic growth rather than the slowdown in aggregate growth rates. When we simulate an economy that restores GDP growth to the levels experienced in the 1940s and 1950s but distributes that growth across income groups as it is distributed today, absolute mobility only increases to 62%. In contrast, maintaining GDP at its current level but distributing it more broadly across income groups – at it was distributed for children born in the 1940s – would increase absolute mobility to 80%, thereby reversing more than two-thirds of the decline in absolute mobility. These findings show that higher growth rates alone are insufficient to restore absolute mobility to the levels experienced in mid-century America. Under the current distribution of GDP, we would need real GDP growth rates above 6% per year to return to rates of absolute mobility in the 1940s. Intuitively, because a large fraction of GDP goes to a small fraction of high-income households today, higher GDP growth does not substantially increase the number of children who earn more than their parents. Of course, this does not mean that GDP growth does not matter: changing the distribution of growth naturally has smaller effects on absolute mobility when there is very little growth to be distributed. The key point is that increasing absolute mobility substantially would require more broad-based economic growth. We conclude that absolute mobility has declined sharply in America over the past half-century primarily because of the growth in inequality. If one wants to revive the “American Dream” of high rates of absolute mobility, one must have an interest in growth that is shared more broadly across the income distribution.

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

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

This statistic shows the Gini's concentration coefficient in Taiwan from 1980 to 2023. In 2023, the Gini index in Taiwan was 33.9 points, ranging at roughly the same level as in 2010. 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 46.7 points in 2022.

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

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. 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. 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 is the replication package for Astorga, Pablo. 2024. Revealing the diversity and complexity of long-term income inequality in Latin America: 1920-2011. Journal of Economic History, 84(4).This paper analyses and documents new long-term income inequality series for Argentina, Brazil, Chile, Colombia, Mexico and Venezuela based on dynamic social tables with four occupational groups. This enables the calculation of comparable Overall (4 groups) and Labor Ginis (3 groups) with their between- and within-groups components. The main findings are: the absence of a unique inequality pattern over time; country outcomes characterized by trajectory diversity and level divergence during industrialization, and by commonality and convergence post 1980; the occurrence of inequality-levelling episodes with different timing and length; and significant changes in trends, but also evidence indicating persistence.

In the first quarter of 2024, 51.8 percent of the total wealth in the United States was owned by members of the baby boomer generation. In comparison, millennials own around 9.4 percent of total wealth in the U.S. In terms of population distribution, there is almost an equal share of millennials and baby boomers in the United States.