As of January 2022, the largest share of Chinese middle-class families had an annual income of between *** thousand and *** thousand yuan per year. According to the same survey, almost ** percent of respondents have at least one child. Many middle-class families in China face significant financial burdens because not only do living costs continuously increase but they also often have to support their parents. In that case, one family has to care for four elders and least one kid.

Graph and download economic data for Median Personal Income in the United States (MEPAINUSA646N) from 1974 to 2023 about personal income, personal, median, income, and USA.

In 2023, just over 50 percent of Americans had an annual household income that was less than 75,000 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023. 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. Maryland, New Jersey, and Massachusetts were among the states with the highest median household income in 2020. In terms of income by race and ethnicity, the average income of Asian households was 94,903 U.S. dollars in 2020, while the median income for Black households was around half of that figure. What is the U.S. poverty threshold? The U.S. Census Bureau annually updates its list of poverty levels. Preliminary estimates show that the average poverty threshold for a family of four people was 26,500 U.S. dollars in 2021, which is around 100 U.S. dollars less than the previous year. There were an estimated 37.9 million people in poverty across the United States in 2021, which was around 11.6 percent of the population. Approximately 19.5 percent of those in poverty were Black, while 8.2 percent were white.

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.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Economy. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Economy. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Economy, the median household income stands at $68,750 for householders within the 25 to 44 years age group, followed by $53,542 for the 65 years and over age group. Notably, householders within the 45 to 64 years age group, had the lowest median household income at $41,111.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Economy median household income by age. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in New Port Richey: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 114(1.42%) households where the householder is under 25 years old, 1,617(20.07%) households with a householder aged between 25 and 44 years, 3,385(42.02%) households with a householder aged between 45 and 64 years, and 2,940(36.49%) households where the householder is over 65 years old.
• The age group of under 25 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the city of New Port Richey, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Port Richey median household income by age. You can refer the same here

In 2023, about 26.9 percent of Asian private households in the U.S. had an annual income of 200,000 U.S. dollars and more. Comparatively, around 13.9 percent of Black households had an annual income under 15,000 U.S. dollars.

Income and income and expenditure of households (current economic accounts): Germany, years, household net income classes

Average Family Income: Philippines: All Income Classes data was reported at 267,000.000 PHP in 2015. This records an increase from the previous number of 235,000.000 PHP for 2012. Average Family Income: Philippines: All Income Classes data is updated yearly, averaging 146,019.500 PHP from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 267,000.000 PHP in 2015 and a record low of 40,408.000 PHP in 1988. Average Family Income: Philippines: All Income Classes data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H021: Family Income and Expenditure Survey: Average Annual Income: By Family Size and Income Group.

Korea Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data was reported at 2.673 % in 2016. This records an increase from the previous number of 2.543 % for 2015. Korea Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data is updated yearly, averaging 1.896 % from Dec 1961 (Median) to 2016, with 56 observations. The data reached an all-time high of 5.491 % in 1985 and a record low of 0.012 % in 1972. Korea Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Korea – Table KR.World Bank: Imports. Merchandise imports from low- and middle-income economies in Latin America and the Caribbean are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Latin America and the Caribbean region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

1) Data Introduction • The Income Classification dataset provides data extracted from the U.S. Census Bureau database, aimed at predicting whether an individual's income exceeds $50,000 per year. This dataset is commonly known as the "Adult" dataset and includes features such as age, work class, education, marital status, occupation, race, gender, native-country, and others.

2) Data Utilization (1) Income data has characteristics that: • It includes both continuous and categorical data, enabling various types of analysis to understand the economic demographics of the U.S. • The dataset is often used in predictive modeling to forecast income levels based on demographic and employment information. (2) Income data can be used to: • Economic Research: Analysts use this dataset to study income distribution and the factors affecting economic disparities. • Policy Making: Helps policymakers design more effective social welfare programs targeting low-income families.

Norway NO: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Outside Region data was reported at 21.300 % in 2016. This records a decrease from the previous number of 22.255 % for 2015. Norway NO: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Outside Region data is updated yearly, averaging 8.473 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 22.255 % in 2015 and a record low of 3.710 % in 1986. Norway NO: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Outside Region data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Norway – Table NO.World Bank: Imports. Merchandise imports from low- and middle-income economies outside region are the sum of merchandise imports by the reporting economy from other low- and middle-income economies in other World Bank regions according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

This statistic shows the median household income in the United States from 1990 to 2023 in 2023 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023, an increase from the previous year. Household incomeThe median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varies from state to state. In 2020, the median household income was 86,725 U.S. dollars in Massachusetts, while the median household income in Mississippi was approximately 44,966 U.S. dollars at that time. Household income is also used to determine the poverty line in the United States. In 2021, about 11.6 percent of the U.S. population was living in poverty. The child poverty rate, which represents people under the age of 18 living in poverty, has been growing steadily over the first decade since the turn of the century, from 16.2 percent of the children living below the poverty line in year 2000 to 22 percent in 2010. In 2021, it had lowered to 15.3 percent. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.51 in 2019. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing.

Switzerland Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Outside Region data was reported at 20.848 % in 2016. This records an increase from the previous number of 20.596 % for 2015. Switzerland Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Outside Region data is updated yearly, averaging 7.159 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 20.848 % in 2016 and a record low of 4.651 % in 1990. Switzerland Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Outside Region data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Switzerland – Table CH.World Bank: Imports. Merchandise imports from low- and middle-income economies outside region are the sum of merchandise imports by the reporting economy from other low- and middle-income economies in other World Bank regions according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

Graph and download economic data for Real Disposable Personal Income (DSPIC96) from Jan 1959 to May 2025 about disposable, personal income, personal, income, real, and USA.

US Census American Community Survey (ACS) 2016, 5-year estimates of the key economic characteristics of Secondary School Districts geographic level in Orange County, California. The data contains 397 fields for the variable groups E01: Employment status (universe: population 16 years and over, table X23, 7 fields); E02: Work status by age of worker (universe: population 16 years and over, table X23, 36 fields); E03: Commuting to work (universe: workers 16 years and over, table X8, 8 fields); E04: Travel time to work (universe: workers 16 years and over who did not work at home, table X8, 14 fields); E05: Number of vehicles available for workers (universe: workers 16 years and over in households, table X8, 8 fields); E06: Median age by means of transportation to work (universe: median age, workers 16 years and over, table X8, 7 fields); E07: Means of transportation to work by race (universe: workers 16 years and over, table X8, 64 fields); E08: Occupation (universe: civilian employed population 16 years and over, table X24, 53 fields); E09: Industry (universe: civilian employed population 16 years and over, table X24, 43 fields); E10: Class of worker (universe: civilian employed population 16 years and over, table X24, 19 fields); E11: Household income and earnings in the past 12 months (universe: total households, table X19, 37 fields); E12: Income and earnings in dollars (universe: inflation-adjusted dollars, tables X19-X20, 31 fields); E13: Family income in dollars (universe: total families, table X19, 17 fields); E14: Health insurance coverage (universe: total families, table X19, 17 fields); E15: Ratio of income to Poverty level (universe: total population for whom Poverty level is determined, table X17, 8 fields); E16: Poverty in population in the past 12 months (universe: total population for whom Poverty level is determined, table X17, 7 fields); E17: Poverty in households in the past 12 months (universe: total households, table X17, 9 fields); E18: Percentage of families and people whose income in the past 12 months is below the poverty level (universe: families, population, table X17, 8 fields), and; X19: Poverty and income deficit (dollars) in the past 12 months for families (universe: families with income below Poverty level in the past 12 months, table X17, 4 fields). The US Census geodemographic data are based on the 2016 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project github page (https://github.com/ktalexan/OCACS-Geodemographics).

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

The 2019 International Social Survey Programme (ISSP) studied economic inequality in Finland. The respondents' attitudes were surveyed on income disparity between social groups, occupations and societies as well as which actors in society should solve these disparities. In addition, the survey charted the respondents' socio-economic situation, Finnish taxation, and conflicts between social groups. The previous ISSP survey regarding inequality was collected in 2009. First, the respondents' opinions were charted concerning the importance of different factors for succeeding in life, such as parents' wealth, ambition, social networks, corruption, or gender. Additionally, views were canvassed on fairness of differences in wealth between rich and poor countries. The respondents were also asked to estimate what persons in different occupations earned (euros/month, gross) and what the respondents thought they ought to be paid. Next, the respondents were presented with a set of statements that they were asked to agree or disagree with on a 5-point Likert scale. The questions concerned, for example, whether income disparity was too great in Finland, who should intervene with income disparity, whether the policies of the government were justified and whether the current level of taxation was justified. The respondents also placed themselves on a 10-point scale according to whether they considered themselves to be at the top or the bottom in society - currently, in childhood home and ten years into the future. Their views were also enquired on which factors they deemed important in deciding one's level of pay. Views on the hierarchical structure of society were examined by showing the respondents five figures representing differently built societies and asking which of the figures corresponded most closely to the situation in the respondent's own country, and which figure corresponded most closely to an optimal situation. The respondents were also asked questions regarding their economic situation at the time of the survey. Background variables included, for instance, gender, year of birth, region of residence (NUTS2), occupation, educational background, religious affiliation, which party the respondent voted for in previous elections, number of children, income, marital status, and statistical grouping of municipalities (urban, semi-urban, rural). The survey also included questions concerning the respondent's spouse/partner and parents' occupations.

US Census American Community Survey (ACS) 2019, 5-year estimates of the key economic characteristics of Block Groups geographic level in Orange County, California. The data contains 397 fields for the variable groups E01: Employment status (universe: population 16 years and over, table X23, 7 fields); E02: Work status by age of worker (universe: population 16 years and over, table X23, 36 fields); E03: Commuting to work (universe: workers 16 years and over, table X8, 8 fields); E04: Travel time to work (universe: workers 16 years and over who did not work at home, table X8, 14 fields); E05: Number of vehicles available for workers (universe: workers 16 years and over in households, table X8, 8 fields); E06: Median age by means of transportation to work (universe: median age, workers 16 years and over, table X8, 7 fields); E07: Means of transportation to work by race (universe: workers 16 years and over, table X8, 64 fields); E08: Occupation (universe: civilian employed population 16 years and over, table X24, 53 fields); E09: Industry (universe: civilian employed population 16 years and over, table X24, 43 fields); E10: Class of worker (universe: civilian employed population 16 years and over, table X24, 19 fields); E11: Household income and earnings in the past 12 months (universe: total households, table X19, 37 fields); E12: Income and earnings in dollars (universe: inflation-adjusted dollars, tables X19-X20, 31 fields); E13: Family income in dollars (universe: total families, table X19, 17 fields); E14: Health insurance coverage (universe: total families, table X19, 17 fields); E15: Ratio of income to Poverty level (universe: total population for whom Poverty level is determined, table X17, 8 fields); E16: Poverty in population in the past 12 months (universe: total population for whom Poverty level is determined, table X17, 7 fields); E17: Poverty in households in the past 12 months (universe: total households, table X17, 9 fields); E18: Percentage of families and people whose income in the past 12 months is below the poverty level (universe: families, population, table X17, 8 fields), and; X19: Poverty and income deficit (dollars) in the past 12 months for families (universe: families with income below Poverty level in the past 12 months, table X17, 4 fields). The US Census geodemographic data are based on the 2019 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project github page (https://github.com/ktalexan/OCACS-Geodemographics).

Philippines Average Family Income: By Income Class (IC): Annual data was reported at 267,000.000 PHP in 2015. This records an increase from the previous number of 235,000.000 PHP for 2012. Philippines Average Family Income: By Income Class (IC): Annual data is updated yearly, averaging 146,019.500 PHP from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 267,000.000 PHP in 2015 and a record low of 40,408.000 PHP in 1988. Philippines Average Family Income: By Income Class (IC): Annual data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H018: Family Income and Expenditure Survey: Average Annual Income and Expenditure: By Income Class.