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Graph and download economic data for Real Median Family Income in the United States (MEFAINUSA672N) from 1953 to 2024 about family, median, income, real, and USA.
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TwitterIn 2024 the median annual income of Asian households in the United States was 121,700 U.S. dollars. They were followed by White households, who's median earnings were 92,530 U.S. dollars. Furthermore, Black Americans and American Indian and Alaska Native families had the lowest household incomes. That year, median income among all U.S. household rose to 83,730 U.S. dollars.
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Graph and download economic data for Median Household Income in the United States (MEHOINUSA646N) from 1984 to 2024 about households, median, income, and USA.
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Graph and download economic data for Real Median Personal Income in the United States (MEPAINUSA672N) from 1974 to 2024 about personal income, personal, median, income, real, and USA.
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The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Great Valley town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2011 and 2021, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/great-valley-ny-median-household-income-by-race-trends.jpeg" alt="Great Valley, New York median household income trends across races (2011-2021, in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Racial categories include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Great Valley town median household income by race. You can refer the same here
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The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Rock Creek town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2011 and 2021, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/rock-creek-wi-median-household-income-by-race-trends.jpeg" alt="Rock Creek, Wisconsin median household income trends across races (2011-2021, in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Racial categories include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Rock Creek town median household income by race. You can refer the same here
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Graph and download economic data for Median Household Income in California (MEHOINUSCAA646N) from 1984 to 2024 about CA, households, median, income, and USA.
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This study re-analyzes Isaac Ehrlich's 1960 cross-section data on the relationship between aggregate levels of punishment and crime rates. It provides alternative model specifications and estimations. The study examined the deterrent effects of punishment on seven FBI index crimes: murder, rape, assault, larceny, robbery, burglary, and auto theft. Socio-economic variables include family income, percentage of families earning below half of the median income, unemployment rate for urban males in the age groups 14-24 and 35-39, labor force participation rate, educational level, percentage of young males and non-whites in the population, percentage of population in the SMSA, sex ratio, and place of occurrence. Two sanction variables are also included: 1) the probability of imprisonment, and 2) the average time served in prison when sentenced (severity of punishment). Also included are: per capita police expenditure for 1959 and 1960, and the crime rates for murder, rape, assault, larceny, robbery, burglary, and auto theft.
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Australia Household Income: Gross Disposable Income data was reported at 421,840.000 AUD mn in Dec 2024. This records a decrease from the previous number of 435,293.000 AUD mn for Sep 2024. Australia Household Income: Gross Disposable Income data is updated quarterly, averaging 72,770.500 AUD mn from Sep 1959 (Median) to Dec 2024, with 262 observations. The data reached an all-time high of 435,293.000 AUD mn in Sep 2024 and a record low of 2,931.000 AUD mn in Jun 1960. Australia Household Income: Gross Disposable Income data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.A287: SNA08: Household Saving Ratio and Household Income.
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BackgroundDebates exist as to whether, as overall population health improves, the absolute and relative magnitude of income- and race/ethnicity-related health disparities necessarily increase—or derease. We accordingly decided to test the hypothesis that health inequities widen—or shrink—in a context of declining mortality rates, by examining annual US mortality data over a 42 year period. Methods and FindingsUsing US county mortality data from 1960–2002 and county median family income data from the 1960–2000 decennial censuses, we analyzed the rates of premature mortality (deaths among persons under age 65) and infant death (deaths among persons under age 1) by quintiles of county median family income weighted by county population size. Between 1960 and 2002, as US premature mortality and infant death rates declined in all county income quintiles, socioeconomic and racial/ethnic inequities in premature mortality and infant death (both relative and absolute) shrank between 1966 and 1980, especially for US populations of color; thereafter, the relative health inequities widened and the absolute differences barely changed in magnitude. Had all persons experienced the same yearly age-specific premature mortality rates as the white population living in the highest income quintile, between 1960 and 2002, 14% of the white premature deaths and 30% of the premature deaths among populations of color would not have occurred. ConclusionsThe observed trends refute arguments that health inequities inevitably widen—or shrink—as population health improves. Instead, the magnitude of health inequalities can fall or rise; it is our job to understand why.
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The dataset illustrates the median household income in Canton town, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.
Key observations:
From 2010 to 2023, the median household income for Canton town decreased by $1,960 (2.62%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.
Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 8 years and declined for 5 years.
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 2022-inflation-adjusted dollars.
Years for which data is available:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Canton town median household income. You can refer the same here
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The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Florence: 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income brackets:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Florence median household income by age. You can refer the same here
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TwitterCriminologists are interested in the effect of punishment regimes on crime rates. This has been studied using aggregate data on 47 states of the USA for 1960. The data set contains the following columns:
Predict crime rate
Variable - Description M - percentage of males aged 14–24 in total state population So - indicator variable for a southern state Ed - mean years of schooling of the population aged 25 years or over Po1 - per capita expenditure on police protection in 1960 Po2 - per capita expenditure on police protection in 1959 LF - labour force participation rate of civilian urban males in the age group 14-24 M.F - number of males per 100 females Pop - state population in 1960 in hundred thousand NW - percentage of nonwhites in the population U1 - unemployment rate of urban males 14–24 U2 - unemployment rate of urban males 35–39 wealth - median value of transferable assets or family income Ineq - income inequality: percentage of families earning below half the median income Prob - probability of imprisonment: ratio of number of commitments to nunumber of offenses Time - average time in months served by offenders in state prisons before their first release Crime - crime rate: number of offenses per 100,000 population in 1960
Ehrlich, I. (1973) Participation in illegitimate activities: a theoretical and empirical investigation. Journal of Political Economy 81, 521–565. Vandaele, W. (1978) Participation in illegitimate activities: Ehrlich revisited. In Deterrence and Incapacitation, eds A. Blumstein, J. Cohen and D. Nagin, National Academy of Sciences, Washington DC, pp. 270–335. Venables, W., and Ripley, B. (1998). Modern Applied Statistics with S-Plus, Second Edition. Springer-Verlag.
The data given here is rounded data taken from Vandaele (1978). The column scales differ somewhat from Venables and Ripley (1998). The data was originally collected by Ehrlich from the Uniform Crime Report of the FBI and other US government sources.
Only one of Po1 and Po2, and only one of U1 and U2, remain in the final regression, because of high collinearity. Data gives association not causal relationships. For example, does crime really increase with police expenditure? Crime is negatively associated with the probprobability of imprisonment. Crime is slightly better modeled on a log scale.
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TwitterThe Aid to Families with Dependent Children (AFDC) program is the predecessor program to the TANF program (switched in 1997). The program provided financial aid to children of low income families. Data is available for years from 1960 to 1995. Average monthly counts for number of cases, total recipients, children recipients, and adult recipients (3 sets of these reports: Total, Basic, and Unemployed Parent). Reports have data columns for both fiscal and calendar year average monthly counts.
Units of Response: State AFDC Programs
Type of Data: Administrative
Tribal Data: No
COVID-19 Data: No
Periodicity: Annual
Data Use Agreement: https://www.icpsr.umich.edu/rpxlogin
Data Use Agreement Location: Unavailable
Equity Indicators: Unavailable
Granularity: Unavailable
Spatial: United States
Geocoding: State
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The dataset illustrates the median household income in Bradford County, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.
Key observations:
From 2010 to 2023, the median household income for Bradford County increased by $1,960 (3.39%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.
Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 7 years and declined for 6 years.
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 2022-inflation-adjusted dollars.
Years for which data is available:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Bradford County median household income. You can refer the same here
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Australia Household Income: Use of Gross Income data was reported at 573,515.000 AUD mn in Dec 2024. This records an increase from the previous number of 572,493.000 AUD mn for Sep 2024. Australia Household Income: Use of Gross Income data is updated quarterly, averaging 93,285.000 AUD mn from Sep 1959 (Median) to Dec 2024, with 262 observations. The data reached an all-time high of 573,515.000 AUD mn in Dec 2024 and a record low of 3,314.000 AUD mn in Mar 1960. Australia Household Income: Use of Gross Income data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.A287: SNA08: Household Saving Ratio and Household Income.
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Japan JP: Household and NPISH: Disposable Income: Net data was reported at 365,218.479 JPY bn in Dec 2026. This records an increase from the previous number of 363,517.238 JPY bn for Sep 2026. Japan JP: Household and NPISH: Disposable Income: Net data is updated quarterly, averaging 294,978.969 JPY bn from Mar 1960 (Median) to Dec 2026, with 268 observations. The data reached an all-time high of 365,218.479 JPY bn in Dec 2026 and a record low of 9,822.337 JPY bn in Mar 1960. Japan JP: Household and NPISH: Disposable Income: Net data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Japan – Table JP.OECD.EO: Household Sector Account: Forecast: OECD Member: Quarterly. YDH - Net household and non-profit institutions serving households disposable incomeHousehold disposable income consists essentially of income from employment and from the operation of unincorporated enterprises, plus receipts of interest, dividends and social benefits minus payments of interest, current taxes and social contributions. It also includes income from imputed rents received by owner-occupiers of dwellings. It can be measured on a gross basis, i.e. before deduction of consumption of fixed capital (CFC) or on a net basis, i.e., after the deduction of CFC.
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The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Falls 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income brackets:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Falls County median household income by age. You can refer the same here
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These data provide official index crime rates and social and economic indicators of crime rates at three levels of aggregation (city, state, and metropolitan areas) for four decennial years: 1950, 1960, 1970, and 1980. Information is provided on Uniform Crime Reports murder, rape, robbery, aggravated assault, burglary, larceny theft, and vehicle theft rates per 100,000 population. Social and economic indicators include percent black population, percent divorced males, the mean and median family incomes, families below the poverty line, and percent unemployed for each area. The availability of the data for the crime rates in 1980 determined the geographic locations included in the data collection. Data from earlier years do not exist for all geographic locations for which data were available in 1980.
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The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Lebanon: 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Lebanon median household income by age. You can refer the same here
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Graph and download economic data for Real Median Family Income in the United States (MEFAINUSA672N) from 1953 to 2024 about family, median, income, real, and USA.