This statistic shows the results of a survey among young adults in the United States on how they rank their own living standards compared to those of their parents at the same age. ** percent think their own living standards nowadays are better than those of their parents when they were the same age.

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.

This paper revisits the assessment of living standards in the United States from its founding to the present, challenging the conventional portrayal of economic well-being during wartime periods. Reflecting multiple criticisms made of the quality of national accounts which include defense spending during times of both peace and war, we employ the methodological framework established by Higgs (1992) and extended by Geloso and Pender (2023) to correct national accounts by subtracting military expenditures from GDP and GNP data. This rectifies the overstatement of living standards attributed to defense spending. Our analysis uses comprehensive data from the Historical Statistics of the United States and the Measuring Worth database, adjusting for price controls during World Wars I and II, the Korean War, and the Vietnam War using a corrected price deflator based on a regression model of economic indicators. The study finds that traditional measures significantly overstate living standards during the Civil War, World War I, and World War II. Post-World War II analysis reveals a persistent overestimation of living standards, particularly pronounced during the Vietnam War years. More importantly, our results provide nuanced insights into certain stylized facts of trends in American improvements of living standards (notably inequality and the Great Depression).

West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

In 2024, the U.S. GDP increased from the previous year to about 29.18 trillion U.S. dollars. Gross domestic product (GDP) refers to the market value of all goods and services produced within a country. In 2024, the United States has the largest economy in the world. What is GDP? Gross domestic product is one of the most important indicators used to analyze the health of an economy. GDP is defined by the BEA as the market value of goods and services produced by labor and property in the United States, regardless of nationality. It is the primary measure of U.S. production. The OECD defines GDP as an aggregate measure of production equal to the sum of the gross values added of all resident, institutional units engaged in production (plus any taxes, and minus any subsidies, on products not included in the value of their outputs). GDP and national debt Although the United States had the highest Gross Domestic Product (GDP) in the world in 2022, this does not tell us much about the quality of life in any given country. GDP per capita at purchasing power parity (PPP) is an economic measurement that is thought to be a better method for comparing living standards across countries because it accounts for domestic inflation and variations in the cost of living. While the United States might have the largest economy, the country that ranked highest in terms of GDP at PPP was Luxembourg, amounting to around 141,333 international dollars per capita. Singapore, Ireland, and Qatar also ranked highly on the GDP PPP list, and the United States ranked 9th in 2022.

Judgement on economic and social conditions in the USA in comparison to the FRG. Topics: Development of personal economic conditions and the standard of living in the FRG; reasons for the so-called economic miracle and share of the USA in the economic recovery; perceived linking of German economic development with other countries; attitude to a European Common Market; reasons for the high American standard of living; comparison between the USA and the FRG regarding working conditions, productivity, social security and job security of workers; image of Americans; knowledge of economic data of the USA; investment inclination; attitude to the competitive economy; assumed ownership of various branches of the economy in the FRG and in the USA, differences according to government and private; expected influence of the American government on the economy and vice versa; estimated proportion of members of the middle classes; image of American agriculture; judgement on the ideological influence of the USA on the FRG; sources of information about America; membership in clubs and organizations and offices taken on; party preference; self-assessment of social class; local residency. Demography: age (classified); marital status; religious denomination; school education; occupation; employment; household income; state; refugee status. Interviewer rating: social class and willingness of respondent to cooperate; number of contact attempts. Also encoded were: age of interviewer and sex of interviewer; city size. Beurteilung der wirtschaftlichen und sozialen Verhältnisse in den USA im Vergleich zur BRD. Themen: Entwicklung der persönlichen wirtschaftlichen Verhältnisse und des Lebensstandards in der BRD; Gründe für das sogenannte Wirtschaftswunder und Anteil der USA am wirtschaftlichen Aufschwung; wahrgenommene Verknüpfung der deutschen Wirtschaftsentwicklung mit anderen Ländern; Einstellung zu einem europäischen gemeinsamen Markt; Gründe für den hohen amerikanischen Lebensstandard; Vergleich zwischen USA und BRD bezüglich der Arbeitsbedingungen, Produktivität, Leistungsfähigkeit, Sozialversicherung und Arbeitsplatzsicherheit von Arbeitern; Image von Amerikanern; Kenntnis wirtschaftlicher Daten der USA; Investitionsneigung; Einstellung zur Wettbewerbswirtschaft; vermutete Eignerschaft verschiedener Wirtschaftszweig in der BRD und in den USA, unterschieden nach staatlich und privat; vermuteter Einfluß der amerikanischen Regierung auf die Wirtschaft und umgekehrt; geschätzter Anteil von Zugehörigen zum Mittelstand; Image der amerikanischen Landwirtschaft; Beurteilung des ideologischen Einflusses der USA auf die BRD; Informationsquellen über Amerika; Mitgliedschaft in Vereinen und Organisationen und übernommene Ämter; Parteipräferenz; Selbsteinschätzung der Schichtzugehörigkeit; Ortsansässigkeit. Demographie: Alter (klassiert); Familienstand; Konfession; Schulbildung; Beruf; Berufstätigkeit; Haushaltseinkommen; Bundesland; Flüchtlingsstatus. Interviewerrating: Schichtzugehörigkeit und Kooperationsbereitschaft des Befragten; Anzahl der Kontaktversuche. Zusätzlich verkodet wurden: Intervieweralter und Interviewergeschlecht; Ortsgröße.

This fileset contains the supplement, the data and the replication code for the paper "Coastal Proximity and Individual Living Standards: Econometric Evidence from Geo-Referenced Household Surveys in Sub-Saharan Africa"

Abstract: We investigate geo-referenced household-level data consisting of up to 128,609 individuals living in 11,261 localities across 17 coastal sub-Saharan African countries over 20 years. We analyze the relevance of coastal proximity, measured by geographic distance to harbors, as a predictor of individual economic living standards. Our setting allows us to account for country-time fixed effects as well as individual-specific controls. Results reveal that individuals living further away from the coast are significantly poorer measured along an array of welfare indicators. Our findings are robust to the inclusion of other geographic covariates of development such as climate (e.g. temperature, precipitation) or terrain conditions (e.g. ruggedness, land suitability). We also explore mechanisms through which coastal proximity may matter for individual welfare and decompose the estimated effect of coastal proximity via formal mediation analysis. Our results highlight the role of human capital, urbanization as well as infrastructural endowments in explaining within-country differences in individual economic welfare.

Data SourcesAmerican Community Survey (ACS):Conducted by: U.S. Census BureauDescription: The ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.Content: The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.Frequency: The ACS offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.Purpose: ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by: ATSDR’s Geospatial Research, Analysis & Services Program (GRASP)Utilized by: CDCDescription: The SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.Content: SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themes. Each tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability.Purpose: SVI data provides insights into the social vulnerability of communities at both the tract and county levels, helping public health officials and emergency response planners allocate resources effectively.Utilization and IntegrationBy integrating data from both the ACS and the SVI, this dataset enables an in-depth analysis and understanding of various socio-economic and demographic indicators at the census tract level. This integrated data is valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United States.ApplicationsPolicy Development: Helps policymakers develop targeted interventions to address the needs of vulnerable populations.Resource Allocation: Assists emergency response planners in allocating resources more effectively based on community vulnerability.Research: Provides a robust foundation for academic and applied research in socio-economic and demographic studies.Community Planning: Aids in the planning and development of community programs and initiatives aimed at improving living conditions and reducing vulnerabilities.Note: Due to limitations in the ArcGIS Pro environment, the data variable names may be truncated. Refer to the provided table for a clear understanding of the variables.CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2013-2017 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2013-2017 ACSEP_PCIEP_PCIPer capita income estimate, 2013-2017 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2013-2017 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2013-2017 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2013-2017 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2013-2017 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2013-2017 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computer

GDP per capita (current US$) is an economic indicator that measures the average economic output per person in a country. It is calculated by dividing the total Gross Domestic Product (GDP) of a country by its population, both measured in current US dollars. GDP per capita provides a useful metric for comparing the economic well-being and living standards between different countries.

There are various sources where you can find GDP per capita data, including international organizations, government agencies, and financial institutions. Some prominent sources for GDP per capita data include:

1. World Bank: The World Bank provides comprehensive data on GDP per capita for countries around the world. They maintain the World Development Indicators (WDI) database, which includes GDP per capita figures for different years.

2. International Monetary Fund (IMF): The IMF also offers GDP per capita data through their World Economic Outlook (WEO) database. It provides economic indicators and forecasts, including GDP per capita figures for various countries.

3. National Statistical Agencies: Many countries have their own national statistical agencies that publish GDP per capita data. These agencies collect and analyze economic data, including GDP and population figures, to calculate GDP per capita.

4. Central Banks: In some cases, central banks may also provide GDP per capita data for their respective countries. They often publish economic indicators and reports that include GDP per capita figures.

When using GDP per capita data, it's important to note that it represents an average measure and does not necessarily reflect the distribution of wealth within a country. Additionally, GDP per capita figures are often adjusted for inflation to provide real GDP per capita, which accounts for changes in the purchasing power of money over time.

To access the most up-to-date and accurate GDP per capita data, it is recommended to refer to reputable sources mentioned above or consult the official websites of international organizations, government agencies, or central banks that specialize in economic data and analysis.

The ACCRA Cost of Living Index (COLI) is a measure of living cost differences among urban areas compiled by the Council for Community and Economic Research. Conducted quarterly, the index compares the price of goods and services among approximately 300 communities in the United States and Canada. This Microsoft Excel file contains the average prices of goods and services published in the ACCRA Cost of Living Index since 1990.

In 2025, Luxembourg was the country with the highest gross domestic product per capita in the world. Of the 20 listed countries, 13 are in Europe and five are in Asia, alongside the U.S. and Australia. There are no African or Latin American countries among the top 20. Correlation with high living standards While GDP is a useful indicator for measuring the size or strength of an economy, GDP per capita is much more reflective of living standards. For example, when compared to life expectancy or indices such as the Human Development Index or the World Happiness Report, there is a strong overlap - 14 of the 20 countries on this list are also ranked among the 20 happiest countries in 2024, and all 20 have "very high" HDIs. Misleading metrics? GDP per capita figures, however, can be misleading, and to paint a fuller picture of a country's living standards then one must look at multiple metrics. GDP per capita figures can be skewed by inequalities in wealth distribution, and in countries such as those in the Middle East, a relatively large share of the population lives in poverty while a smaller number live affluent lifestyles.

Indicators characterizing the distribution of households by income level.

Assessment of economic and social conditions in the USA in comparison to the FRG. Topics: Judgement on development of personal economic situation; evaluation of cooperation between the German and the American economy; evaluation of German and American commercial life, the economic strength of America, the German and American standard of living as well as the influence of American ideas on the FRG; reasons for the economic strength of America and the high standard of living as well as for American aid for European countries; differences between German and American trade unions and assumed political influence of American trade unions; economic strength of European countries; comparison of shopping habits of Germans and Americans; attitude to America and the Americans; use of sources of information about America; assessment of the best form of provision for one´s old age; naming the American film city and automobile city; estimate of quota of vehicle possession in the FRG and the USA. Demography: age (classified); marital status; religious denomination; school education; occupation; employment; household income; party preference; self-assessment of social class; state; refugee status; present and past offices held; membership. Interviewer rating: social class and willingness of respondent to cooperate; number of contact attempts. Also encoded were: age of interviewer and sex of interviewer; city size. Einschätzung der wirtschaftlichen und gesellschaftlichen Verhältnisse in den USA im Vergleich zur BRD. Themen: Beurteilung der Entwicklung der eigenen wirtschaftlichen Lage; Bewertung der Zusammenarbeit zwischen der deutschen und der amerikanischen Wirtschaft; Bewertung des deutschen und amerikanischen Geschäftslebens, der wirtschaftlichen Stärke Amerikas, des deutschen und amerikanischen Lebensstandards sowie des Einflusses amerikanischer Ideen auf die BRD; Gründe für die wirtschaftliche Stärke Amerikas und den hohen Lebensstandard sowie für die amerikanische Hilfe an europäischen Staaten; Unterschiede zwischen deutschen und amerikanischen Gewerkschaften und vermuteter politischer Einfluß der amerikanischen Gewerkschaften; wirtschaftliche Stärke europäischer Länder; Vergleich der Kaufgewohnheiten von Deutschen und Amerikanern; Einstellung zu Amerika und den Amerikanern; Nutzung von Informationsquellen über Amerika; Einschätzung der besten Form der Altersversorgung; Nennung der amerikanischen Filmstadt und Autostadt; Schätzung der Kfz-Besitzquoten in der BRD und den USA. Demographie: Alter (klassiert); Familienstand; Konfession; Schulbildung; Beruf; Berufstätigkeit; Haushaltseinkommen; Parteipräferenz; Selbsteinschätzung der Schichtzugehörigkeit; Bundesland; Flüchtlingsstatus; innegehabte und innehabende Ämter; Mitgliedschaft. Interviewerrating: Kooperationsbereitschaft und Schichtzugehörigkeit des Befragten; Anzahl der Kontaktversuche. Zusätzlich verkodet wurden: Intervieweralter und Interviewergeschlecht; Ortsgröße.

1199 persons were interviewed in the FRG, 1228 in France, 1178 in Great Britain, 1164 in Italy and 500 in Greece. The study has the USIA-designation XX-17. The USIA-Studies of the XX-Series (international relations) from XX-2 to XX-18 are archived under ZA Study Nos. 1969-1976 as well as 2069-2074 and 2124-2127.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Technological innovation, often fueled by governments, drives industrial growth and helps raise living standards. Data here aims to shed light on countries technology base: research and development, scientific and technical journal articles, high-technology exports, royalty and license fees, and patents and trademarks. Sources include the UNESCO Institute for Statistics, the U.S. National Science Board, the UN Statistics Division, the International Monetary Fund, and the World Intellectual Property Organization.

Out of all 50 states, New York had the highest per-capita real gross domestic product (GDP) in 2024, at 92,341 U.S. dollars, followed closely by Massachusetts. Mississippi had the lowest per-capita real GDP, at 41,603 U.S. dollars. While not a state, the District of Columbia had a per capita GDP of more than 210,780 U.S. dollars. What is real GDP? A country’s real GDP is a measure that shows the value of the goods and services produced by an economy and is adjusted for inflation. The real GDP of a country helps economists to see the health of a country’s economy and its standard of living. Downturns in GDP growth can indicate financial difficulties, such as the financial crisis of 2008 and 2009, when the U.S. GDP decreased by 2.5 percent. The COVID-19 pandemic had a significant impact on U.S. GDP, shrinking the economy 2.8 percent. The U.S. economy rebounded in 2021, however, growing by nearly six percent. Why real GDP per capita matters Real GDP per capita takes the GDP of a country, state, or metropolitan area and divides it by the number of people in that area. Some argue that per-capita GDP is more important than the GDP of a country, as it is a good indicator of whether or not the country’s population is getting wealthier, thus increasing the standard of living in that area. The best measure of standard of living when comparing across countries is thought to be GDP per capita at purchasing power parity (PPP) which uses the prices of specific goods to compare the absolute purchasing power of a countries currency.

This statistic depicts the age distribution in the United States from 2014 to 2024. In 2024, about 17.32 percent of the U.S. population fell into the 0-14 year category, 64.75 percent into the 15-64 age group and 17.93 percent of the population were over 65 years of age. The increasing population of the United States The United States of America is one of the most populated countries in the world, trailing just behind China and India. A total population count of around 320 million inhabitants and a more-or-less steady population growth over the past decade indicate that the country has steadily improved its living conditions and standards for the population. Leading healthier lifestyles and improved living conditions have resulted in a steady increase of the life expectancy at birth in the United States. Life expectancies of men and women at birth in the United States were at a record high in 2012. Furthermore, a constant fertility rate in recent years and a decrease in the death rate and infant mortality, all due to the improved standard of living and health care conditions, have helped not only the American population to increase but as a result, the share of the population younger than 15 and older than 65 years has also increased in recent years, as can be seen above.

About this dataset

Context

The dataset presents median household incomes for various household sizes in Country Life Acres, MO, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, only 2, and 3-person households were found in Country Life Acres. Across the different household sizes in Country Life Acres the mean income is $270,229, and the standard deviation is $0. The coefficient of variation (CV) is 0%. This low CV indicates low relative variability, suggesting that the incomes are relatively consistent across different sizes of households. Please note that the U.S. Census Bureau uses $250,001 as a JAM value to report incomes of $250,000 or more. In the case of Country Life Acres, there were 2 household sizes where the JAM values were used. Thus, the numbers for the mean and standard deviation may not be entirely accurate and have a higher possibility of errors. However, to obtain an approximate estimate, we have used a value of $250,001 as the income for calculations, as reported in the datasets by the U.S. Census Bureau.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 2-person households, with an income of $270,229. It then further remained the same for 3-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/country-life-acres-mo-median-household-income-by-household-size.jpeg" alt="Country Life Acres, MO median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 Country Life Acres median household income. You can refer the same here

Public use data set on new legal immigrants to the U.S. that can address scientific and policy questions about migration behavior and the impacts of migration. A survey pilot project, the NIS-P, was carried out in 1996 to inform the fielding and design of the full NIS. Baseline interviews were ultimately conducted with 1,127 adult immigrants. Sample members were interviewed at baseline, 6 months, and 12 months, with half of the sample also interviewed at three months. The first full cohort, NIS-2003, is based on a nationally representative sample of the electronic administrative records compiled for new immigrants by the US government. NIS-2003 sampled immigrants in the period May-November 2003. The geographic sampling design takes advantage of the natural clustering of immigrants. It includes all top 85 Metropolitan Statistical Areas (MSAs) and all top 38 counties, plus a random sample of other MSAs and counties. Interviews were conducted in respondents'' preferred languages. The baseline was multi-modal: 60% of adult interviews were administered by telephone; 40% were in-person. The baseline round was in the field from June 2003 to June 2004, and includes in the Adult Sample 8,573 respondents, 4,336 spouses, and 1,072 children aged 8-12. A follow-up was planned for 2007. Several modules of the NIS were designed to replicate sections of the continuing surveys of the US population that provide a natural comparison group. Questionnaire topics include Health (self-reports of conditions, symptoms, functional status, smoking and drinking history) and use/source/costs of health care services, depression, pain; background; (2) Background: Childhood history and living conditions, education, migration history, marital history, military history, fertility history, language skills, employment history in the US and foreign countries, social networks, religion; Family: Rosters of all children; for each, demographic attributes, education, current work status, migration, marital status and children; for some, summary indicators of childhood and current health, language ability; Economic: Sources and amounts of income, including wages, pensions, and government subsidies; type, value of assets and debts, financial assistance given/received to/from respondent from/to relatives, friends, employer, type of housing and ownership of consumable durables. * Dates of Study: 2003-2007 * Study Features: Longitudinal * Sample Size: 13,981

Distribution of households by per capita equivalent total income (on average per month).