This survey illustrates the differences in satisfaction of the upper, middle and lower class in the United States as of August 2012. 62 percent of upper class respondents stated they feel more financially secure now than they did ten years ago. 44 percent of middle class Americans and 29 percent of lower class Americans agree.

This statistic shows the median household income in the United States from 1970 to 2020, by income tier. In 2020, the median household income for the middle class stood at 90,131 U.S. dollars, which was approximately a 50 percent increase from 1970. However, the median income of upper income households in the U.S. increased by almost 70 percent compared to 1970.

Disposable Income per Capita: Urban: Middle Income data was reported at 48,508.000 RMB in 2024. This records an increase from the previous number of 46,276.000 RMB for 2023. Disposable Income per Capita: Urban: Middle Income data is updated yearly, averaging 8,678.295 RMB from Dec 1985 (Median) to 2024, with 40 observations. The data reached an all-time high of 48,508.000 RMB in 2024 and a record low of 737.280 RMB in 1985. Disposable Income per Capita: Urban: Middle Income data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HD: Income by Income Level. Since 2013, All households in the sample are grouped, by per capita disposable income of the household, into groups of low income, lower middle income, middle income, upper middle income, and high income, each group consisting of 20%, 20%, 20%, 20%, and 20% of all households respectively.

Middle-income trap refers to the economic growth strategies that transition low-income countries into middle-income ones but fail to transition the middle-income countries into high-income countries. We observe the existence of a middle-income trap for upper-middle- and lower middle-income countries. We examine the reasons for the middle-income trap using the Bayesian model averaging (BMA) and generalized method of moments (GMM). We also explore the transformation of middle-income economies into high-income economies using logistic, probit and Limited Information Maximum Likelihood (LIML) regression analyses. Random forest analysis is also used to check the robustness of the findings. BMA analysis shows that education plays an enabling role in high-income countries in determining economic growth, whereas the full poten tial of education is not fully utilized in middle-income countries. GMM estimations show that the education coefficient is positive and significant for high-income and middle-income countries. This implies that education plays a decisive positive role in achieving economic growth and gives a path to escape from the middle-income trap. However, the education coefficient for middle-income countries is approximately half that of high-income countries. Therefore, the findings of this study call for additional investment and focused strategies relating to human capital endowments

China Disposable Income per Capita: Urban: Upper Middle Income data was reported at 68,151.000 RMB in 2024. This records an increase from the previous number of 65,430.000 RMB for 2023. China Disposable Income per Capita: Urban: Upper Middle Income data is updated yearly, averaging 11,827.130 RMB from Dec 1985 (Median) to 2024, with 40 observations. The data reached an all-time high of 68,151.000 RMB in 2024 and a record low of 861.960 RMB in 1985. China Disposable Income per Capita: Urban: Upper Middle Income data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HD: Income by Income Level. Since 2013, All households in the sample are grouped, by per capita disposable income of the household, into groups of low income, lower middle income, middle income, upper middle income, and high income, each group consisting of 20%, 20%, 20%, 20%, and 20% of all households respectively.

About **** of the Polish population belonged to the middle class in April 2019. Nearly ******* were lower-class, and the minority were upper-class. When considering only income, a larger share of the population was upper- and middle-class, whereas when considering the only occupation, a larger share was lower class.

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.

United States US: Income Share Held by Highest 20% data was reported at 46.900 % in 2016. This records an increase from the previous number of 46.400 % for 2013. United States US: Income Share Held by Highest 20% data is updated yearly, averaging 46.000 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 46.900 % in 2016 and a record low of 41.200 % in 1979. United States US: Income Share Held by Highest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

By 2030, the middle-class population in Asia-Pacific is expected to increase from 1.38 billion people in 2015 to 3.49 billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from 114 million in 2015 to 212 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 57 percent of the world’s population had assets valued at less than 10,000 U.S. dollars; while less than one percent had assets of more than million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percent 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 to 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.

Graph and download economic data for Real Median Family Income in the United States (MEFAINUSA672N) from 1953 to 2023 about family, median, income, real, and USA.

Data of lower middle-income countries between 1980 and 2018 to study whether indigenous or foreign innovation efforts are more important for the transition of lower middle-income economies to the upper middle-income rank. Data are designed for discrete-time hazard models.

China Disposable Income per Capita: Urban: Lower Middle Income data was reported at 33,351.000 RMB in 2024. This records an increase from the previous number of 32,202.000 RMB for 2023. China Disposable Income per Capita: Urban: Lower Middle Income data is updated yearly, averaging 6,367.340 RMB from Dec 1985 (Median) to 2024, with 40 observations. The data reached an all-time high of 33,351.000 RMB in 2024 and a record low of 632.880 RMB in 1985. China Disposable Income per Capita: Urban: Lower Middle Income data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HD: Income by Income Level. Since 2013, All households in the sample are grouped, by per capita disposable income of the household, into groups of low income, lower middle income, middle income, upper middle income, and high income, each group consisting of 20%, 20%, 20%, 20%, and 20% of all households respectively.

In 2022, less than eight percent of the population in Latin America had either a high or upper-middle income level. Slightly over a fifth of the population fell in the non-poor with low incomes' stratum.

Content

The World Bank classifies the world's economies into four income groups — high, upper-middle, lower-middle, and low. We base this assignment on Gross National Income (GNI) per capita (current US$) calculated using the Atlas method. The classification is updated each year on July 1st.

The classification of countries is determined by two factors:

A country’s GNI per capita, which can change with economic growth, inflation, exchange rates, and population. Revisions to national accounts methods and data can also influence GNI per capita.
Classification threshold: The thresholds are adjusted for inflation annually using the SDR deflator.

Check this link for more: https://blogs.worldbank.org/opendata/new-country-classifications-income-level-2019-2020

Source

https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups

United States - Gross National Income for Lower Middle Income Countries was 7363999721063.92000 Current $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Gross National Income for Lower Middle Income Countries reached a record high of 7643930159482.68000 in January of 2019 and a record low of 88909419647.05350 in January of 1960. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Gross National Income for Lower Middle Income Countries - last updated from the United States Federal Reserve on July of 2025.

During a 2023 survey, around 35 percent of respondents interviewed in Brazil said they belonged to the middle class. Meanwhile, 24.3 percent of the interviewees defined their social class as "low" and 25.7 percent stated that they were part of the middle class.Furthermore, Brazil's Gini coefficient, an indicator that measures wealth distribution, shows Brazil is one of the most unequal countries in the Latin American region.

The average for 2022 based on 32 countries was 6460.03 million U.S. dollars. The highest value was in Vietnam: 122993.36 million U.S. dollars and the lowest value was in Cape Verde: 0.02 million U.S. dollars. The indicator is available from 2007 to 2022. Below is a chart for all countries where data are available.

Context

This dataset was uploaded as supplemental data for the 2019 Kaggle ML & DS Survey. It allows classification of countries into income groups - low, lower-middle, upper-middle and high - by gross national income (GNI) per capita, in U.S. dollars,.

For details of this calculation see here and here.

Content

The csv file consists of 218 countries listed by name and country code and their corresponding income group and lending category.

Acknowledgements

Thanks to the World Bank for providing the data at "https://datahelpdesk.worldbank.org/knowledgebase/articles/906519">https://datahelpdesk.worldbank.org/knowledgebase/articles/906519

Inspiration

This dataset allows any other data containing country names or codes to be supplemented with income group data.

Research Hypothesis

The research investigates the relationship between economic growth and income inequality, drawing on Kuznets' theory of an inverted U-shaped relationship. The central hypotheses are:

H0: Income inequality is not affected by GDP growth, indicating no relationship between economic growth and income inequality.
H1: GDP growth influences income inequality, which may increase or decrease depending on societal and economic contexts.
H2: GDP growth positively affects income inequality, widening income disparities.
H3: GDP growth negatively affects income inequality, reducing disparities and promoting equitable distribution.
H4: In lower-middle-income countries, GDP growth reduces income inequality.

Description of Data

The study utilizes data from the World Bank for 39 countries spanning the years 2004 to 2019. The dataset includes:

Gross Domestic Product (GDP): Measured in constant local currency units (LOGGDP), used as a proxy for economic growth.
Gini Index: A standardized measure of income inequality, ranging from 0 (perfect equality) to 100 (maximum inequality).
Income Categories: Countries are grouped into high, upper-middle, and lower-middle income categories based on the World Bank’s GNI per capita classification.

Methodology and Data Gathering

Selection Criteria: Countries were selected to represent diverse income groups, ensuring a balanced and comprehensive analysis of varying economic contexts.
Data Source: All data were sourced from the World Bank’s publicly available databases.
Data Analysis:
  Correlation analysis to explore the general relationship between GDP and inequality.
  Linear regression models to identify causal relationships across income categories.
  Group-specific analysis to investigate how GDP impacts inequality within high-, upper-middle-, and lower-middle-income countries.

Notable Findings

Overall Trends:
  Across all countries, a positive correlation was observed between GDP and the Gini index, indicating that GDP growth is generally associated with increasing income inequality.
  The regression model (GINI = 23.931 + 0.937 × LOGGDP) confirmed a statistically significant relationship, with an F-value (p < 0.05) supporting the model’s validity.

Income Group Analysis:
  High-Income Countries: No statistically significant relationship between GDP growth and inequality.
  Upper-Middle-Income Countries: A weak relationship was observed, but it lacked statistical significance.
  Lower-Middle-Income Countries: A significant negative relationship was identified (β = -22.291, p < 0.001), suggesting that in these countries, GDP growth reduces income inequality.

Interpretation and Use of Data: The findings can be interpreted in light of Kuznets' hypothesis, which posits that inequality first rises and then falls as economies develop.

China Disposable Income per Capita: Urban: Low Income data was reported at 18,003.000 RMB in 2024. This records an increase from the previous number of 17,478.000 RMB for 2023. China Disposable Income per Capita: Urban: Low Income data is updated yearly, averaging 3,829.760 RMB from Dec 1985 (Median) to 2024, with 40 observations. The data reached an all-time high of 18,003.000 RMB in 2024 and a record low of 546.720 RMB in 1985. China Disposable Income per Capita: Urban: Low Income data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HD: Income by Income Level. Since 2013, All households in the sample are grouped, by per capita disposable income of the household, into groups of low income, lower middle income, middle income, upper middle income, and high income, each group consisting of 20%, 20%, 20%, 20%, and 20% of all households respectively.