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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 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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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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TwitterThis table contains 22 series, with data for years 1926 - 1960 (not all combinations necessarily have data for all years), and was last released on 2000-02-18. This table contains data described by the following dimensions (Not all combinations are available): Geography (11 items: Canada; Newfoundland and Labrador; Nova Scotia; Prince Edward Island ...), Wages and salaries (2 items: Based on Standard Industrial Classification; 1948 (SIC); Based on Standard Industrial Classification; 1980 (SIC) ...).
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TwitterIn 2023, the usual median hourly rate of a worker's wage in the United States was 19.24 U.S. dollars, a decrease from the previous year. Dollar value is based on 2023 U.S. dollars. In 1979, the median hourly earnings in the U.S. was 17.48 dollars.
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Wages in the United States increased 4.86 percent in August of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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TwitterBetween 1914 and 1969, weekly wages in manufacturing industries in the United States grew by a factor of 12. In the first half of the century, the most significant periods of increase came during the World Wars, as manufacturing industries were at the core of the war effort. However, wages then fell sharply after both World Wars, due to post-war recessions and oversaturation of the job market as soldiers returned home. Interwar period Wage growth during the interwar period was often stagnant, despite the significant economic growth during the Roarin' 20s, and manufacturing wages remained steady at around 24 dollars from 1923 to 1929. This was, again, due to oversaturation of the job market, as employment in the agricultural sector declined due to mechanization and many rural workers flocked to industrial cities in search of employment. The Great Depression then saw the largest and most prolonged period of decline in manufacturing wages. From September 1929 to March 1933, weekly wages fell from 24 dollars to below 15 dollars, and it would take another four years for them to return to pre-Depression levels. Postwar prosperity After the 1945 Recession, the decades that followed the Second World War then saw consistent growth in manufacturing wages in almost every year, as the U.S. cemented itself as the foremost economic power in the world. This period is sometimes referred to as the Golden Age of Capitalism, and the U.S. strengthened its economic presence in Western Europe and other OECD countries, while expanding its political and military presence across Asia. Manufacturing and exports played a major role in the U.S.' economic growth in this period, and wages grew from roughly 40 dollars per week in 1945 to more than 120 dollars by the late 1960s.
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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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Wages in China increased to 120698 CNY/Year in 2023 from 114029 CNY/Year in 2022. This dataset provides - China Average Yearly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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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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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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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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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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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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A striking graph from the Social Security Administration (https://www.ssa.gov/policy/docs/factsheets/at-a-glance/earnings-men-1988-2018.html) shows that median annual earnings for all men above the age of 20 have decreased since 1988:
https://www.ssa.gov/policy/docs/factsheets/at-a-glance/earnings-men-1988-2018.svg" alt="">
I wanted to better understand how educational attainment has played a role in the above trend, and to come up with a model to forecast the future trend for earnings by educational attainment.
As I began looking at the data from the Bureau of Labor Statistics website, there was a striking trend: the median weekly earnings for all groups of people who did not have a bachelors degree or higher had decreased from 1979 levels, in constant 2020 dollars.
I collated data from the US Bureau of Labor Statistics (https://www.bls.gov/webapps/legacy/cpsatab4.htm) and (https://www.bls.gov/cps/cpswktabs.htm) and the US Census Bureau (https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-income-people.html) to create this dataset.
I have omitted details of gender and race, to solely look at the correlation between educational attainment and median weekly earnings over the years. All of the data is for ages 25 and higher unless otherwise stated in the column header.
An important note is that all the earnings data are in constant base 2020 dollars. This removes the effects of inflation and makes it possible to compare the numbers over the years.
The data starts at the year 1960, but unfortunately only overall labor force data, and population percentages of persons with a high school graduation (HSG) and persons with a Bachelors or Higher Degree are available. Median weekly earnings data categorized by educational attainment is available from 1979 onwards, while labor force data i.e., labor force level, labor force participation rate and the employment level by educational attainment is available only from 1992 onwards.
The only columns that have data from 1960 onwards are: (i) overall labor force level, (ii) civilian non-institutional population level, (iii) overall labor force participation rate, (iv) overall employment level, (v) overall percentage of high school graduates, and (vi) overall percentage of persons with a bachelors degree or higher.
Some of the columns can be calculated from other columns, for instance the civilian non-institutional population level can be calculated from the labor force participation rate.
All of this data is from the Bureau of Labor Statistics, and the Census Bureau: https://www.bls.gov/webapps/legacy/cpsatab4.htm , https://www.bls.gov/cps/cpswktabs.htm and https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-income-people.html .
A big thank you to all those who worked so hard to collect and organize this data.
The main question is: what is the best way to generate forecasts for median weekly earnings for each educational attainment level?
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The 1960 Growth of American Families survey was the second in a series of two surveys that measured women's attitudes on various topics relating to fertility and family planning for 3,256 currently married White women aged 18-44 living in private households, previously married White women aged 23-44, who were married and living with their husband in 1960, and currently married non-White women aged 18-39, living with their husband. Main topics in the survey included residence history, marital history, education, employment and income, parent's characteristics, religiosity, siblings, attitude towards contraception, past use of contraceptives, fertility history, fecundity, attitudes and opinions on childbearing and rearing, desired family size, fertility intentions, and fertility expectations. Respondent's were asked to give detailed information pertaining to their residence history dating back to their birth. They were also asked if they ever lived on a farm. Respondents were also queried on their marital history, specifically, when their marriage(s) took place, ended, and how they ended. Respondents were asked to report their level of education, if they ever attended a school or college that belonged to a church or a religious group, and if so, what specific church or religious group. Respondents were also queried about their employment and income. Specifically, they were asked to report their own and their husband's occupation and industry. They were also queried on whether they worked between their pregnancies and if the work was part-time or full-time. They were asked to state their total family income and their husband's earnings. Characteristics of the respondent's parents were also asked for including nationality, occupation while respondent was growing up, and religious preference. Respondent's religiosity was also explored with questions about religious activities in their daily lives, as well as her own and her husband's religious preferences. Respondents were asked if they had attended Sunday school as a child and if their children currently attended Sunday school. Respondents were asked how many brothers and sisters they had while growing up as well as their attitude on the number of siblings in their household. Their attitude toward contraception was measured with questions that asked if it would be okay if couples did something to limit the number of pregnancies they had or to control the time when they get pregnant. They were also asked if they approved of couples using the rhythm method to keep from getting pregnant. They were also queried on what specific types of contraception they had used in the past and between pregnancies. Furthermore, they were asked if they ever used methods together. Fecundity was also explored with questions about whether they or their husband had had treatments or an operation that made them sterile. Respondents were also asked what they thought was the ideal number of children for the average American family. Desired family size was queried in a number of other ways including the number of children the respondent and her husband wanted before marriage, how many children the respondent wanted a year after the first child was born, and how many children the respondent expected in all.
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TwitterIn 2022, about 14.88 million households in the United States had an income of 200,000 U.S. dollars or more a year. Another 20.77 million households however, had an income of less than 25,000 U.S. dollars in the same year, The total number of households in the U.S. since 1960 can be found here.
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Indonesia GDP: SNA 1953: 1960p: National Income data was reported at 616.000 IDR bn in 1973. This records an increase from the previous number of 570.000 IDR bn for 1972. Indonesia GDP: SNA 1953: 1960p: National Income data is updated yearly, averaging 387.850 IDR bn from Dec 1960 (Median) to 1973, with 14 observations. The data reached an all-time high of 616.000 IDR bn in 1973 and a record low of 340.200 IDR bn in 1960. Indonesia GDP: SNA 1953: 1960p: National Income data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.AC005: Gross National Product: Constant Price: Discontinued.
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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.