Graph and download economic data for Median Family Income in the United States (MEFAINUSA646N) from 1953 to 2023 about family, median, income, and USA.

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.

About 50.4 percent of the household income of private households in the U.S. were earned by the highest quintile in 2023, which are the upper 20 percent of the workers. In contrast to that, in the same year, only 3.5 percent of the household income was earned by the lowest quintile. This relation between the quintiles is indicative of the level of income inequality in the United States. Income inequalityIncome inequality is a big topic for public discussion in the United States. About 65 percent of U.S. Americans think that the gap between the rich and the poor has gotten larger in the past ten years. This impression is backed up by U.S. census data showing that the Gini-coefficient for income distribution in the United States has been increasing constantly over the past decades for individuals and households. The Gini coefficient for individual earnings of full-time, year round workers has increased between 1990 and 2020 from 0.36 to 0.42, for example. This indicates an increase in concentration of income. In general, 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. Income distribution is also affected by region. The state of New York had the widest gap between rich and poor people in the United States, with a Gini coefficient of 0.51, as of 2019. In global comparison, South Africa led the ranking of the 20 countries with the biggest inequality in income distribution in 2018. South Africa had a score of 63 points, based on the Gini coefficient. On the other hand, the Gini coefficient stood at 16.6 in Azerbaijan, indicating that income is widely spread among the population and not concentrated on a few rich individuals or families. Slovenia led the ranking of the 20 countries with the greatest income distribution equality in 2018.

Graph and download economic data for Real Median Personal Income in the United States (MEPAINUSA672N) from 1974 to 2023 about personal income, personal, median, income, real, and USA.

Graph and download economic data for Real Median Household Income in New York (MEHOINUSNYA672N) from 1984 to 2023 about NY, households, median, income, real, and USA.

In the U.S., median household income rose from 51,570 U.S. dollars in 1967 to 80,610 dollars in 2023. In terms of broad ethnic groups, Black Americans have consistently had the lowest median income in the given years, while Asian Americans have the highest; median income in Asian American households has typically been around double that of Black Americans.

This statistic shows the change in the median household income per decade in the United States from 1970 to 2014, by income tier. Between 1990 and 2000, the median household income for the middle class increased by 12 percent.

This study defined middle class income households as those with an income between 67 and 200 percent of the U.S. median household income, after adjustment for household size. In 2014, the middle class income ranged from about 42,000 U.S. dollars to about 126,000 U.S. dollars per year for a three-person household.

Key information about China Household Income per Capita

• China Annual Household Income per Capita reached 4,805.935 USD in Dec 2013, compared with the previous value of 4,273.467 USD in Dec 2012.
• China Annual Household Income per Capita data is updated yearly, available from Dec 1985 to Dec 2013, with an averaged value of 711.353 USD.
• The data reached an all-time high of 4,805.935 USD in Dec 2013 and a record low of 262.918 USD in Dec 1986.
• In the latest reports, Retail Sales of China grew 12.700 % YoY in May 2023.

CEIC converts Annual Household Income per Capita into USD. The National Bureau of Statistics provides Average Household Income per Capita in local currency. Federal Reserve Board average market exchange rate is used for currency conversions. Household Income covers urban area only.

VITAL SIGNS INDICATOR
Income (EC4)

FULL MEASURE NAME
Household income by place of residence

LAST UPDATED
January 2023

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

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

U.S. Census Bureau: American Community Survey - https://data.census.gov/
Form B19001 (2005-2021; household income by place of residence)
Form B19013 (2005-2021; median household income by place of residence)
Form B08521 (2005-2021; median worker earnings by place of employment)

Bureau of Labor Statistics: Consumer Price Index - https://www.bls.gov/data/
1970-2021

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Income derived from the decennial Census data reflects the income earned in the prior calendar year, whereas income derived from the American Community Survey (ACS) data reflects the prior 12 month period; note that this inconsistency has a minor effect on historical comparisons (see Income and Earnings Data section of the ACS General Handbook - https://www.census.gov/content/dam/Census/library/publications/2020/acs/acs_general_handbook_2020_ch09.pdf). ACS 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

Quintile income for 1970-2000 is imputed from decennial Census data using methodology from the California Department of Finance. Bay Area income is the population weighted average of county-level income.

Income has been inflated using the Consumer Price Index (CPI) for 2021 specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data uses national CPI for 1970. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Rutland: 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 184(2.47%) households where the householder is under 25 years old, 1,970(26.48%) households with a householder aged between 25 and 44 years, 2,830(38.04%) households with a householder aged between 45 and 64 years, and 2,456(33.01%) households where the householder is over 65 years old.
• In Rutland, the age group of 45 to 64 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

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 Rutland 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 Nantucket County: 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 27(0.53%) households where the householder is under 25 years old, 1,785(35.36%) households with a householder aged between 25 and 44 years, 1,970(39.03%) households with a householder aged between 45 and 64 years, and 1,266(25.08%) households where the householder is over 65 years old.
• In Nantucket County, the age group of 45 to 64 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

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 Nantucket County median household income by age. You can refer the same here

Since 1970, net national incomes per capita have grown in each region of the world. North America has experienced the largest increase, growing from nearly 4,500 U.S. dollars per capita in 1970 to $57,300 per capita in 2021. Europe and Central Asia follow behind North America, growing from 1,200 dollars per capita in 1970 to 22,000 in 2021. Other regions such as Sub-Saharan Africa, the Middle East and North Africa, Latin America and the Caribbean, and South Asia have not grown as high, but their growth is still significant, with net national incomes per capita in 2021 growing to between 10 and 20 times their 1970 levels.

This data collection consists of modified records from CENSUS OF POPULATION AND HOUSING, 1970 [UNITED STATES]: PUBLIC USE SAMPLES (ICPSR 0018). The original records consisted of 120-character household records and 120-character person records, whereas the new modified records are rectangular (each person record is combined with the corresponding household record) with a length of 188, after the deletion of some items. Additional information was added to the data records, including typical educational requirement for current occupation, occupational prestige score, and group identification code. This version also differs from the original public use census samples in other ways: persons aged 15-75 were included, no majority males were included, but the majority males from CENSUS OF POPULATION AND HOUSING [UNITED STATES], 1970 PUBLIC USE SAMPLE: MODIFIED 1/1000 5% STATE SAMPLES (ICPSR 7922) were included for convenience, 10 percent of the Black population from each file was included, and Mexican Americans (identified by a Spanish surname) from outside the five southwestern states of Arizona, California, Colorado, New Mexico, and Texas were not included in this file. Variables provide information on the housing unit, such as occupancy and vacancy status of house, value of property, commercial use, ratio of rent and property value to family income, availability of plumbing facilities, sewage disposal, complete kitchen facilities, heating facilities, flush toilet, water, television, and telephone. Data are also provided on household characteristics such as household size, family size, and household relationships. Other demographic variables specify age, sex, place of birth, state of residence, Spanish descent, marital status, race, veteran status, income, and ratio of family income to poverty cutoff level. This collection was made available by the National Chicano Research Network of the Institute for Social Research, University of Michigan. See the related collection, CENSUS OF POPULATION AND HOUSING [UNITED STATES], 1970 PUBLIC USE SAMPLE: MODIFIED 1/1000 5% STATE SAMPLES (ICPSR 7922).

VITAL SIGNS INDICATOR Income (EC4)

FULL MEASURE NAME Household income by place of residence

LAST UPDATED May 2019

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

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

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

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

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

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

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

Netherlands Real Households Disposable Income: Volume Changes data was reported at 1.042 % in 2017. This records a decrease from the previous number of 2.016 % for 2016. Netherlands Real Households Disposable Income: Volume Changes data is updated yearly, averaging 1.884 % from Dec 1970 (Median) to 2017, with 48 observations. The data reached an all-time high of 8.087 % in 1990 and a record low of -5.037 % in 1970. Netherlands Real Households Disposable Income: Volume Changes data remains active status in CEIC and is reported by CPB Netherlands Bureau for Economic Policy Analysis. The data is categorized under Global Database’s Netherlands – Table NL.H011: Real Households Disposable Income: Volume Changes.

Netherlands Real Households Disposable Income: Volume Changes: Profits data was reported at 1.690 % in 2017. This records an increase from the previous number of -1.219 % for 2016. Netherlands Real Households Disposable Income: Volume Changes: Profits data is updated yearly, averaging 2.946 % from Dec 1970 (Median) to 2017, with 48 observations. The data reached an all-time high of 10.451 % in 1979 and a record low of -13.064 % in 1971. Netherlands Real Households Disposable Income: Volume Changes: Profits data remains active status in CEIC and is reported by CPB Netherlands Bureau for Economic Policy Analysis. The data is categorized under Global Database’s Netherlands – Table NL.H011: Real Households Disposable Income: Volume Changes.

This data collection contains 132 Public Use Microdata Samples (PUMS) files from the 1970 Census of Population and Housing. Information is provided in these files on the housing unit, such as occupancy and vacancy status of house, tenure, value of property, commercial use, year structure was built, number of rooms, availability of plumbing facilities, sewage disposal, bathtub or shower, complete kitchen facilities, flush toilet, water, telephone, and air conditioning. Data are also provided on household characteristics such as the number of persons aged 18 years and younger in the household, the presence of roomers, boarders, or lodgers, the presence of other nonrelative and of relative other than wife or child of head of household, the number of persons per room, the rent paid for unit, and the number of persons with Spanish surnames. Other demographic variables provide information on age, race, marital status, place of birth, state of birth, Puerto Rican heritage, citizenship, education, occupation, employment status, size of family, farm earnings, and family income. This hierarchical data collection contains approximately 214 variables for the 15-percent sample, 227 variables for the 5-percent sample, and 117 variables for the neighborhood characteristics sample. (Source: downloaded from ICPSR 06/09/2011).

The median income in 2023 was at 56,490 U.S. dollars for Black households. In 1990, the median income among Black households was 38,360 U.S. dollars (In 2023 U.S. dollars).

Abstract copyright UK Data Service and data collection copyright owner.

The Family Expenditure Survey (FES), which closed in 2001, was a continuous survey with an annual sample of around 10,000 households. They provided information on household and personal incomes, certain payments that recurred regularly (e.g. rent, gas and electricity bills, telephone accounts, insurances, season tickets and hire purchase payments), and maintained a detailed expenditure record for 14 consecutive days.

The original purpose of the FES was to provide information on spending patterns for the United Kingdom Retail Price Index (RPI). The survey was a cost-efficient way of collecting a variety of related data that the government departments required to correlate with income and expenditure at the household, tax unit and person levels. The annual FES began in 1957 (with an earlier large scale survey conducted in 1953/54) and was one of the first Department of Employment (DE) systems to be computerised in the early 1960s. The UKDA holds FES data from 1961-2001. The Northern Ireland Family Expenditure Survey (NIFES), which ran from 1967-1998, was identical to the UK FES and therefore used the same questionnaires and documentation. However, starting in 1988, a voluntary question on religious denomination was asked of those aged 16 and over in Northern Ireland. The UKDA holds NIFES data from 1968-1998, under GN 33240.

Significant FES developments over time include:

• 1968: the survey was extended to include a sample drawn from the Northern Ireland FES and a new computer system was introduced which was used until 1985
• 1986: DE and the Office of Population Censuses and Surveys (OPCS) converted the FES into a new database system using the SIR package
• 1989: the Central Statistical Office (CSO) took over responsibility for the survey
• 1994: in April, computerised personal interviewing was introduced using lap-top computers, the database system changed to INGRES and the survey changed from a calendar year to financial year basis
• 1996: in April, OPCS and CSO were amalgamated into the Office for National Statistics (ONS), who assumed responsibility for the FES
• 1998: from April onwards information from expenditure diaries kept by children aged 7 to 15 was included in data, and grossing factors were made available on the database

From 2001, the both the FES and the National Food Survey (NFS) (held at the UKDA under GN 33071) were completely replaced by a new survey, the Expenditure and Food Survey (EFS). Prior to the advent of the EFS, there had previously been considerable overlap between the FES and NFS, with both surveys asking respondents to keep a diary of expenditure. Thus, the 2000-2001 FES was the final one in the series. The design of the new EFS was based on the previous FES; further background to its development may be found in the 1999-2000 and 2000-2001 Family Spending reports. From 2008, the EFS became the Living Costs and Food Survey (LCF) (see under GN 33334).


Main Topics:
Household Schedule:
This schedule was taken at the main interview. Information for most of the questions was obtained from the head of household or housewife, but certain questions of a more individual character were put to every spender aged 15 or over (or 16 or over from 1973 onwards). Until the introduction of the community charge, information on rateable value and rate poundage was obtained from the appropriate local authority, as was information on whether the address was within a smokeless zone. Information was collected about the household, the sex and age of each member, and also details about the type and size of the household accommodation. The main part of the questionnaire related to expenditure both of a household and individual nature, but the questions were mainly confined to expenses of a recurring nature, e.g.:

• Household: housing costs, payment to Gas and Electricity Boards or companies, telephone charges, licences and television rental
• Individual: motor vehicles, season tickets for transport, life and accident insurances, payments through a bank, instalments, refund of expenses by employer, expenditure claimed by self-employed persons as business expenses for tax purposes, welfare foods, education grants and fees

Income Schedule:
Data were collected for each household spender. The schedule was concerned with income, national insurance contributions and income tax. Income of a child not classed as a spender was obtained from one or other of his parents and entered on the parent's questionnaire. Information collected included: employment status and recent absences from work, earnings of an employee, self-employed earnings, National Insurance contributions, pensions and other regular allowances, occasional benefits - social security benefits and other...

This data collection contains 132 Public Use Microdata Samples (PUMS) files from the 1970 Census of Population and Housing. Information is provided in these files on the housing unit, such as occupancy and vacancy status of house, tenure, value of property, commercial use, year structure was built, number of rooms, availability of plumbing facilities, sewage disposal, bathtub or shower, complete kitchen facilities, flush toilet, water, telephone, and air conditioning. Data are also provided on household characteristics such as the number of persons aged 18 years and younger in the household, the presence of roomers, boarders, or lodgers, the presence of other nonrelative and of relative other than wife or child of head of household, the number of persons per room, the rent paid for unit, and the number of persons with Spanish surnames. Other demographic variables provide information on age, race, marital status, place of birth, state of birth, Puerto Rican heritage, citizenship, education, occupation, employment status, size of family, farm earnings, and family income. This hierarchical data collection contains approximately 214 variables for the 15-percent sample, 227 variables for the 5-percent sample, and 117 variables for the neighborhood characteristics sample. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR00018.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.