By 2030, the middle-class population in Asia-Pacific is expected to increase from **** billion people in 2015 to **** billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from *** million in 2015 to *** million in 2030. Worldwide wealth While the middle-class has been on the rise, there is still a huge disparity in global wealth and income. The United States had the highest number of individuals belonging to the top one percent of wealth holders, and the value of global wealth is only expected to increase over the coming years. Around ** percent of the world’s population had assets valued at less than 10,000 U.S. dollars, while less than *** percent had assets of more than one million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percentage of non-investable assets. The middle-class The middle class is the group of people whose income falls in the middle of the scale. China accounted for over half of the global population for middle-class wealth in 2017. In the United States, the debate about the middle class “disappearing” has been a popular topic due to the increase in wealth among the top billionaires in the nation. Due to this, there have been arguments to increase taxes on the rich to help support the middle class.

This table describes the wealth distribution of the sector households in the national accounts over different household groups. Households are identified by main source of income, living situation, household composition, age classes of the head of the household, income class by 20% groups. Data available from: 2005 up to and including 2014. Status of the figures: The figures of 2005-2014 are final. Changes as of June 22nd 2018: None. This table has been discontinued. Statistics Netherlands has carried out a revision of the national accounts. New statistical sources and estimation methods have been used during the revision. Therefore this table has been replaced by table Wealth distribution of households; National Accounts. For further information see section 3. When will new figures be published? Not applicable anymore.

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.

In 2025, just over 45 percent of American households had an annual income that was less than 75,000 U.S. dollars. On the other hand, some 16 percent had an annual income of 200,000 U.S. dollars or more. The median household income in the country reached almost 84,000 U.S. dollars in 2024. Income and wealth in the United States After the economic recession in 2009, income inequality in the U.S. is more prominent across many metropolitan areas. The Northeast region is regarded as one of the wealthiest in the country. Massachusetts, New Hampshire, and Maryland were among the states with the highest median household income in 2024. In terms of income by race and ethnicity, the average income of Asian households was highest, at over 120,000 U.S. dollars, while the median income among Black households was around half of that figure. What is the U.S. poverty threshold? The U.S. Census Bureau annually updates the poverty threshold based on the income of various household types. As of 2023, the threshold for a single-person household was 15,480 U.S. dollars. For a family of four, the poverty line increased to 31,200 U.S. dollars. There were an estimated 38.9 million people living in poverty across the United States in 2024, which reflects a poverty rate of 10.6 percent.

Over ** million Russians aged 20 years and above, or approximately ** percent of the total adult population of the country, had wealth under 10,000 U.S. dollars in 2022. To compare, on average around the globe, the share of residents belonging to this wealth range was measured at **** percent in the same year. Economic inequality in Russia The latest available data by the World Bank recorded Russia’s Gini index, used as a measurement of income or wealth inequality, at **. The organization classified Russia as an upper-middle-income economy. Over ** percent of Russians considered themselves belonging to the middle class in 2020. HNWIs in Russia Approximately *** percent of Russian adults, or ******* residents, owned over *********** U.S. dollars, or were referred to as high-net-worth individuals (HNWIs). In 2021, the total wealth of the adult population in the country reached nearly *** trillion U.S. dollars. A significant portion of it belonged to roughly ***** ultra-high-net-worth individuals (UHNWIs) whose net worth exceeded ** billion U.S. dollars.

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.

In 2022, the majority of Indian adults had a wealth of 10,000 U.S. dollars or less. On the other hand, about *** percent were worth more than *********** dollars that year. India The Republic of India is one of the world’s largest and most economically powerful states. India gained independence from Great Britain on August 15, 1947, after having been under their power for 200 years. With a population of about *** billion people, it was the second most populous country in the world. Of that *** billion, about **** million lived in New Delhi, the capital. Wealth inequality India suffers from extreme income inequality. It is estimated that the top 10 percent of the population holds ** percent of the national wealth. Billionaire fortune has increase sporadically in the last years whereas minimum wages have remain stunted.

In developed economies, wealth inequality is high, while public capital is underprovided. Here, we study the impact of heterogeneity in saving behavior and income sources on the distributional effects of public investment. A capital tax is levied to finance productive public capital in an economy with two types of households: high income households who save dynastically and middle income households who save for retirement. We find that inequality is reduced the higher the capital tax rate is and that low tax rates are Pareto-improving. There is no clear-cut trade-off between efficiency and equality: middle income households' consumption is maximal at a capital tax rate that is higher than the rate which maximizes high income households' consumption.

We analyze how median real incomes in the United States have changed since 1980 under a definition of the middle class that adjusts for changes in demographics. We find that failing to adjust for demographic shifts in the population relating to age, race, and education can indicate a more positive outlook than is truly the case. We also find that the real median incomes of today’s middle class are somewhat higher than they used to be, particularly for households headed by two adults. We find, as in prior research, that prices for housing, healthcare, and education have risen more than middle-class incomes, while prices for transportation, food, and recreation have risen less than middle-class incomes.

Inequality remains woven into America’s economic fabric, fuelling public debate and shaping politics. In 2024, the richest fifth of U.S. households captured more than half of national income, while the poorest secured a just 3.1 percent. This stark contrast highlights the concentration of wealth among high-income households. Measuring income inequality The Gini coefficient, a standard measure of income inequality, has steadily risen over the past three decades. In 1990, the Gini coefficient for households in the United States stood at 0.43, but by 2024 it had increased to 0.49. This upward trend indicates a growing gap between the rich and poor. Among state, the District of Columbia and New York exhibited the greatest income inequality. Utah, on the other hand, recorded the smallest wealth gap. Income inequality across demographics Income disparities are also drawn along ethnic and racial lines. In 2024, Asian households in the United States had the highest median annual income, followed by White households. Black Americans and American Indian and Alaska Native families had comparatively lower household incomes. The overall median income for U.S. households reached nearly 84,000 U.S. dollars that year. These figures highlight the persistent economic gaps among various racial and ethnic groups in America.

Additional file 1: Stata do-file to generate WIR and TWIR figures.

This dataset is about books. It has 1 row and is filtered where the book is Money, wealth and class. It features 7 columns including author, publication date, language, and book publisher.

This Commentary investigates whether there has been a growing divergence in the consumption of luxury and necessity goods across income classes. The analysis shows that while necessities represent a majority of the consumption basket for lower and middle income quintiles, their consumption of necessities in inflation-adjusted dollars has been declining in the face of higher prices of such goods and stagnant income growth. Higher income quintiles have seen increases in their consumption of luxuries, simultaneous with a decline in their consumption of necessities.

Part A. Heinz Müller: The income structure in several German states, 1874-1913. The entire material of this study was developed by the institute for regional politics and transportation science at the University of Freiburg. The first part of the study deals with an analysis of the income structure (=personnel income distribution) in chosen German states for the period from 1873 to 1913. Analysis of income structures can be planned and realized with different aims and with the use of different methods. The following structuring of income recipients is most commonly used: a) By sources of income b) By the income of sociologically important recipient groups c) By income level The structuring by income sources addresses a registration of the functional income distribution. This is instructive but difficult to carry out. For example it is hardly possible to subdivide the income resulting from entrepreneurial activity in the structural components as this term includes employer´s salary, basic pension for entrepreneurs, enterprise interests and entrepreneurial profit. Even theoretically it is difficult to subdivide income resulting from entrepreneurial activity in these components but in the practical implementation this division faces insurmountable difficulties. On the other hand such a structuring is an important perquisite for a proper analysis of income sources especially in the area of agriculture. Another criteria used for classification is the division by sociologically important recipient groups. The aim of such an analysis could be to estimate the share of specific groups of persons in the national income and the changes that are taking place in the process of economic development. Alternatively such an analysis can be based on a division in economic sectors; one could estimate for example the share of agriculture or services in the national income and its changes over time. Also this procedure allows interesting conclusions on social and economic development of the national economy. The third and particularly important criterion consists in the division by income level. This type of investigation serves to generate important findings on the social and economic situation and development of different income groups. Development of wealth within a national economy can be assessed looking at the economic situation of the lower income classes in relation to the higher classes and on how fast one class integrates into another. These three different types of structuring of income recipients can be combined with each other. Doings so one can generate more insights on the development of the industrialization process co pared to using only one classification type (Müller, Heinz/Geisenberger, Siegfried, 1972: Die Einkommensstruktur in verschiedenen deutschen Ländern 1874-1913. Berlin: Duncker & Humblot, S. 13f). The first part of the study exclusively deals with the investigation of the income size structure. These are the summarized results for the investigation on the temporal development of distribution coefficients:

(1) Differentiated according to the different states The share of the very highest incomes in the total income is increasing in all states (Besides Hesse) during the investigation period.

(2) Differentiated according to the surveyed areas According to the distribution coefficient and its development over time one can say that developments differ a lot between rural and industrial areas.

Part B. Siegfried Geisenberger: Important determinants for changes in the income structure. An attempt of an economic interpretation of the development in Prussia 1874-1913. The results from the first part of the investigation gave the impulse for further investigations at the institute of regional politics and transportation science (University of Freiburg). They wanted to investigate the development of the distribution situation for further regions and to control for different income tax laws in several states. The typical differences in the development of income distribution between rural and industrial areas could also be detected for the Prussian governmental districts. The second part of the investigation aims to explain this phenomenon using theoretical economic and statistical instruments.

Register of tables in HISTAT: A. Data on income structure in Prussia and in chosen Prussian governmental districts A.1 Data on income structure in Prussia (1874-1913) A.2 Data on income structure in Prussia, governme...

In the first quarter of 2025, 51.4 percent of the total wealth in the United States was owned by members of the baby boomer generation. In comparison, millennials own around 10.3 percent of total wealth in the U.S. In terms of population distribution, there was almost an equal share of millennials and baby boomers in the United States in 2024.

The Distributional Financial Accounts (DFAs) provide a quarterly measure of the distribution of U.S. household wealth since 1989, based on a comprehensive integration of disaggregated household-level wealth data with official aggregate wealth measures. The data set contains the level and share of each balance sheet item on the Financial Accounts' household wealth table (Table B.101.h), for various sub-populations in the United States. In our core data set, aggregate household wealth is allocated to each of four percentile groups of wealth: the top 1 percent, the next 9 percent (i.e., 90th to 99th percentile), the next 40 percent (50th to 90th percentile), and the bottom half (below the 50th percentile). Additionally, the data set contains the level and share of aggregate household wealth by income, age, generation, education, and race. The quarterly frequency makes the data useful for studying the business cycle dynamics of wealth concentration--which are typically difficult to observe in lower-frequency data because peaks and troughs often fall between times of measurement. These data will be updated about 10 or 11 weeks after the end of each quarter, making them a timely measure of the distribution of wealth.

ABSTRACT The article presents a panorama of socioeconomic hierarchies in late Nineteenth-century Brazil. Income analysis of social classes underpins these echelons. Within a theoretical and historical approach focused on social class, the article reckons that the Brazilian Empire was relatively egalitarian in terms of wages. A broad expressiveness of the lower classes, rather than a hypothetical robustness of the middle or the upper classes, explains this equality. The analysis of purchasing power and patterns of consumption made it possible to identify the degree of precariousness of the popular classes, as well as the existence of mainly urban middle classes. Lastly, salary data on the upper classes should not hide concentration of wealth, a main characteristic of the Empire’s decay, which was largely due to a polarized structure of slave property.

This table contains statistics regarding income and capital of self-employed persons in the Netherlands. A distinction is made between, on the one hand, persons for whom self-employment provides for the main source of income, and on the other hand all persons with income from self-employed work. The figures in this table are broken down by type of self-employed person, sector, gender, age, migration background, position in the household, and by income and wealth decile groups.

All statistics in this table are at the individual level, this includes capital; (corporate) assets are summed per household and then assigned to all household members, thus serving as a measure of personal prosperity. The sample date for both population and capital is the first of January of the reporting year. For the older years 2007 up to and including 2010, capital is sampled on the first of January of the year following the reporting year.

The General Business Register (ABR) is used to determine the sector (SBI) of self-employed persons. The ABR has been subject to various trend breaks in the period 2007-2011. This leads to a sharp decrease in the number of self-employed persons in the financial services (sector K) in 2010. Therefore caution is advised when consulting sector trends or comparing numbers across sectors.

Data available from: 2007.

Status of the figures: The figures for 2006 to 2022 are final. The figures for 2023 are preliminary.

Changes as of November 1 2024: Figures for 2022 have been finalized. Figures for 2023 have been added.

Changes as of March 2022: Figures on the wealth of the self-employed in 2010 were incorrect, and have been removed. For this year the wealth of 2011 applies, as 2011 marks a shift in sample date from December 31 to January 1. Missing wealth figures for 2013 have been supplemented.

Changes as of July 2021: Revised data for 2006 to 2019 have been added. Due to the availability of new sources and improvements in the methodology, wealth figures have changed. Additionally everyone with personnel is now classified as self-employed with employee (formerly this distinction was based solely on the enterprise constituting the main source of income).

When will new figures be published? New figures for 2024 will be published in December 2025.

Context

Income inequality is a global issue reflecting the uneven distribution of wealth within and between countries. Developed nations exhibit varying income levels due to economic policies and labor dynamics, resulting in Gini coefficients of around 0.3 to 0.4. Conversely, developing nations often experience higher income disparities due to limited access to education, healthcare, and jobs, leading to Gini coefficients exceeding 0.4, exacerbating poverty cycles and social tensions. This inequality hampers economic growth, social cohesion, and upward mobility. Addressing it requires comprehensive policies, including progressive taxation and equitable resource distribution, to promote a more just and inclusive society.

Content

This dataset comprises historical information encompassing various indicators concerning Inequality in Income on a global scale. The dataset prominently features: ISO3, Country, Continent, Hemisphere, Human Development Groups, UNDP Developing Regions, HDI Rank (2021), and Inequality in Income from 2010 to 2021.

Dataset Glossary (Column-wise)

• ISO3 - ISO3 for the Country/Territory
• Country - Name of the Country/Territory
• Continent - Name of the Continent
• Hemisphere - Name of the Hemisphere
• Human Development Groups - Human Development Groups
• UNDP Developing Regions - UNDP Developing Regions
• HDI Rank (2021) - Human Development Index Rank for 2021
• Inequality in Income from 2010 to 2021 - Inequality in Income from year 2010 to 2021

Data Dictionary

• UNDP Developing Regions:
  • SSA - Sub-Saharan Africa
  • LAC - Latin America and the Caribbean
  • EAP - East Asia and the Pacific
  • AS - Arab States
  • ECA - Europe and Central Asia
  • SA - South Asia

Structure of the Dataset

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Acknowledgement

This Dataset is created from Human Development Reports. This Dataset falls under the Creative Commons Attribution 3.0 IGO License. You can check the Terms of Use of this Data. If you want to learn more, visit the Website.

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This data collection is part of a longitudinal survey designed to provide detailed information on the economic situation of households and persons in the United States. These data examine the distribution of income, wealth, and poverty in American society and gauge the effects of federal and state programs on the well-being of families and individuals.

There are three basic elements contained in the survey. The first is a control card that records basic social and demographic characteristics for each person in a household, as well as changes in such characteristics over the course of the interviewing period. These include age, sex, race, ethnic origin, marital status, household relationship, education, and veteran status. Limited data are provided on housing unit characteristics such as units in structure, tenure, access, and complete kitchen facilities. The second element is the core portion of the questionnaire, with questions repeated at each interview on labor force activity, types and amounts of income, and participation in various cash and noncash benefit programs for each month of the four- month reference period. Data for employed persons include number of hours and weeks worked, earnings, and weeks without a job. Nonworkers are classified as unemployed or not in the labor force. In addition to providing income data associated with labor force activity, the core questions cover nearly 50 other types of income. Core data also include postsecondary school attendance, public or private subsidized rental housing, low-income energy assistance, and school breakfast and lunch participation. The third element consists of topical modules, which are a series of supplemental questions asked during selected household visits. Topical modules include some core data to link individuals to the core files.

1. The Wave 1 Topical Module covers recipiency and employment history.

2. The Wave 2 Topical Module includes work disability, education and training, marital, migration, and fertility histories, and household relationships.

3. The Wave 3 Topical Module covers medical expenses and utilization of health care, work-related expenses and child support, assets and liabilities, real estate, shelter costs, dependent care, vehicles, value of business, interest earning accounts, rental properties, stocks and mutual fund shares, mortgages, and other assets.

4. The Wave 4 Topical Module covers work schedule, taxes, child care, and annual income and retirement accounts.

5. Data in the Wave 5 Topical Module describe child support agreements, school enrollment and financing, support for non-household members, adult and child disability, and employer-provided health benefits.

6. The Wave 6 Topical Module covers medical expenses and utilization of health care, work related expenses, child support paid and child care poverty, assets and liabilities, real estate, shelter costs, dependent care, vehicles, value of business, interest earning accounts, rental properties, stock and mutual fund shares, mortgages, and other financial investments.

7. The Wave 7 Topical Module covers informal caregiving, children's well-being, and annual income and retirement accounts.

8. The Wave 8 Topical Module and Wave 8 Welfare Reform Topical Module cover child support agreements, support for nonhousehold members, adult disability, child disability, adult well-being, and welfare reform.

9. The Wave 9 Topical Module covers medical expenses and utilization of heath care (adults and children), work related expenses, child support paid and child care poverty, assets and liabilities, real estate, shelter costs, dependent care, vehicles, value of business, interest earnings accounts, rental properties, stocks and mutual fund shares mortgages, and other financial investments