https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States US: Income Share Held by Highest 10% data was reported at 30.600 % in 2016. This records an increase from the previous number of 30.100 % for 2013. United States US: Income Share Held by Highest 10% data is updated yearly, averaging 30.100 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 30.600 % in 2016 and a record low of 25.300 % in 1979. United States US: Income Share Held by Highest 10% 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.; ; 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.
In 2023, the real median household income in the state of Alabama was 60,660 U.S. dollars. The state with the highest median household income was Massachusetts, which was 106,500 U.S. dollars in 2023. The average median household income in the United States was at 80,610 U.S. dollars.
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.
https://www.icpsr.umich.edu/web/ICPSR/studies/27804/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/27804/terms
This special topic poll, fielded September 10, 2009, re-interviewed 648 adults first surveyed August 27-31 2009. This continuing series of monthly surveys solicit public opinion on the presidency and on a range of other political and social issues. The dataset includes their responses to call-back questions as well as to selected questions in the original poll (ICPSR 27803) which asked whether they approved of the way Barack Obama was handling the presidency, the war in Afghanistan, health care, and the economy. Several questions addressed health care, including whether respondents thought the health care system in the United States worked well, whether Medicare worked well, and whether the government would do a better job than private health care companies in keeping health care costs down and providing medical coverage. Respondents were also asked their opinions on whether President Obama's proposals for reform would increase competition in the private insurance market, the health insurance industry, whether they believed in the possibility of expanding health care coverage without increasing budget deficits or taxes on the middle class, whether President Obama or the Republicans in Congress had better ideas about reforming the health care system, and whether they understood the health care reforms that Congress was considering. Whether President Obama's proposals for reform would increase competition in the private insurance market, whether the health care reform proposed by President Obama would make health care better in the United States and would help the respondent personally, and whether respondents favored the ideas of requiring all Americans to buy health insurance and the government offering everyone a government administered health insurance plan. Information was collected on how respondents thought health care reforms under consideration in Congress would effect the middle class, senior citizens, small businesses, the respondent personally, their health care costs, and the quality of health care. Additional topics that were covered included the pullout of troops from Iraq, credit card debt, how the federal government should use taxpayer's money, personal finances, the best way to discourage obesity, terrorist attacks, the war in Afghanistan, the swine flu, and job security. Respondents were re-interviewed on September 10, 2009, and asked whether they approved of the way Barak Obama was handling health care, if they had listened to the president's address of September 9th, the clarity of his explanation in regard to reform, if they agreed with the proposed reforms, whether Congress would pass and President Obama would sign a bill reforming the system. Questions in regard to budget deficit, expanded health care, regulation of the health insurance industry were also asked. Demographic variables include sex, age, race, marital status, education level, household income, political party affiliation, political philosophy, perceived social class, religious preference, and voter registration status and participation history.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Personal Saving Rate (PSAVERT) from Jan 1959 to May 2025 about savings, personal, rate, and USA.
The Global Consumption Database (GCD) contains information on consumption patterns at the national level, by urban/rural area, and by income level (4 categories: lowest, low, middle, higher with thresholds based on a global income distribution), for 92 low and middle-income countries, as of 2010. The data were extracted from national household surveys. The consumption is presented by category of products and services of the International Comparison Program (ICP) 2005, which mostly corresponds to COICOP. For three countries, sub-national data are also available (Brazil, India, and South Africa). Data on population estimates are also included.
The data file can be used for the production of the following tables (by urban/rural and income class/consumption segment):
- Sample Size by Country, Area and Consumption Segment (Number of Households)
- Population 2010 by Country, Area and Consumption Segment
- Population 2010 by Country, Area and Consumption Segment, as a Percentage of the National Population
- Population 2010 by Country, Area and Consumption Segment, as a Percentage of the Area Population
- Population 2010 by Country, Age Group, Sex and Consumption Segment
- Household Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency (Million)
- Household Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP (Million)
- Household Consumption 2010 by Country, Sector, Area and Consumption Segment in US$ (Million)
- Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in Local Currency (Million)
- Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in $PPP (Million)
- Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in US$ (Million)
- Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in Local Currency (Million)
- Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in $PPP (Million)
- Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in US$ (Million)
- Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency
- Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in US$
- Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP
- Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in Local Currency
- Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in US$
- Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in $PPP
- Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in Local Currency
- Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in US$
- Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in $PPP
- Consumption Shares 2010 by Country, Sector, Area and Consumption Segment (Percent)
- Consumption Shares 2010 by Country, Category of Products/Services, Area and Consumption Segment (Percent)
- Consumption Shares 2010 by Country, Product/Service, Area and Consumption Segment (Percent)
- Percentage of Households who Reported Having Consumed the Product or Service by Country, Consumption Segment and Area (as of Survey Year)
For all countries, estimates are provided at the national level and at the urban/rural levels. For Brazil, India, and South Africa, data are also provided at the sub-national level (admin 1): - Brazil: ACR, Alagoas, Amapa, Amazonas, Bahia, Ceara, Distrito Federal, Espirito Santo, Goias, Maranhao, Mato Grosso, Mato Grosso do Sul, Minas Gerais, Para, Paraiba, Parana, Pernambuco, Piaji, Rio de Janeiro, Rio Grande do Norte, Rio Grande do Sul, Rondonia, Roraima, Santa Catarina, Sao Paolo, Sergipe, Tocatins - India: Andaman and Nicobar Islands, Andhra Pradesh, Arinachal Pradesh, Assam, Bihar, Chandigarh, Chattisgarh, Dadra and Nagar Haveli, Daman and Diu, Delhi, Goa, Gujarat, Haryana, Himachal Pradesh, Jammu and Kashmir, Jharkhand, Karnataka, Kerala, Lakshadweep, Madya Pradesh, Maharastra, Manipur, Meghalaya, Mizoram, Nagaland, Orissa, Pondicherry, Punjab, Rajasthan, Sikkim, Tamil Nadu, Tripura, Uttar Pradesh, Uttaranchal, West Bengal - South Africa: Eastern Cape, Free State, Gauteng, Kwazulu Natal, Limpopo, Mpulamanga, Northern Cape, North West, Western Cape
Data derived from survey microdata
https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS
A dataset listing the richest zip codes in New Jersey per the most current US Census data, including information on rank and average income.
https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS
A dataset listing the richest zip codes in Missouri per the most current US Census data, including information on rank and average income.
This dataset contains around 480,000 records of patients data from the NTR Vaidya Seva scheme of the Government of Andhra Pradesh, India. NTR Vaidya Seva is the flagship healthcare scheme of the government in which lower-middle class and low-income citizens of the state of Andhra Pradesh can obtain free healthcare for many major diseases and ailments. A similar program exists in the neighboring state of Telangana as well.
Original dataset can be found on the NTR Vaidya Seva's official website. The dataset has been partially anonymized on the official website. I've further anonymized it.
Also thanks to Unsplash for the cover pic!
A useful beginner level real world dataset. I'm tired of seeing the IRIS and Titanic Datasets for exploratory data analysis!
Dataset owned by the Government of Andhra Pradesh but released freely on official website.
https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS
A dataset listing the richest zip codes in Puerto Rico per the most current US Census data, including information on rank and average income.
Not seeing a result you expected?
Learn how you can add new datasets to our index.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
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.