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Graph and download economic data for Real Median Family Income in the United States (MEFAINUSA672N) from 1953 to 2023 about family, median, income, real, and USA.
Demobilization following the First World War saw millions of soldiers return to their home countries from the trenches, and in doing so, they brought with them another wave of the deadliest and far-reaching pandemic of all time. As the H1N1 influenza virus, known as the Spanish Flu, spread across the world and infected between one third and a quarter of the global population, it impacted all areas of society. One such impact was on workers' wages, as the labor shortage drove up the demand for skilled workers, which then increased wages. In the United States, wages had already increased due to the shortage of workers caused by the war, however the trend increased further in the two or three years after the war, despite the return of so many personnel from overseas.
In the first fifteen years of the twentieth century, wages across the shown industries had increased gradually and steadily in line with inflation, with the hourly wage in manufacturing increasing from roughly 15 cents per hour to 21 cents per hour in this period. Between 1915 and 1921 or 1921 however, the hourly rate more than doubled across most of these industries, with the hourly wage in manufacturing increasing from 21 cents per hour in 1915 to 56 cents per hour in 1920. Although manufacturing wages were the lowest among those shown here, the trend was similar across even the highest paying trades, with hourly wages in the building trade increasing from 57 cents per hour in 1915 to one dollar and eight cents in 1921. The averages of almost all these trades decreased again in 1922, before plateauing or increasing at a slower rate throughout the late 1920s. Other factors, such as the Wall Street Crash of 1929 and subsequent Great Depression, make comparing this data with wages in later decades more difficult, but it does give some insight into the economic effects of pandemics in history.
Compared to the mid-20th century, wage increases in the United States' industrial sector did not change as drastically over the preceding 150 years. Industrial wages in the 1800s peaked in the final year of the American Civil War in 1865, and they were double the value of wages in 1830; yet wages did not exceed this value until the following century. Throughout the 1900s, however, the increase was much more pronounced; between 1943 and 1955 alone, industrial wages doubled, and quadrupled by 1972. In fact, wages in 1985 were over five times higher than they were in 1955, and ten times higher than in 1943. The only times during the 20th century when industrial wages fell was during the post-WWI recession in 1921, and again during the Great Depression in the 1930s.
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During the early days of professional baseball, the dominant major leagues imposed a “reserve clause” designed to limit player wages by restricting competition for labor. Entry into the market by rival leagues challenged the incumbent monopsony cartel’s ability to restrict compensation. Using a sample of player salaries from the first 40 years of the reserve clause (1880-1919), this study examines the impact of inter-league competition on player wages. This study finds a positive salary effect associated with rival league entry that is consistent with monopsony wage suppression, but the effect is stronger during the 20th century than the 19th century. Changes in levels of market saturation and minor-league competition may explain differences in the effects between the two eras.
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License information was derived automatically
Wages in Macedonia increased 10.60 percent in April of 2025 over the same month in the previous year. This dataset provides - Macedonia Real Wage Growth- actual values, historical data, forecast, chart, statistics, economic calendar and news.
Compared to Western Europe, the development of average incomes differed between Scandinavia and and East-Central Europe between 1900 and 1950. Over these five decades, income in Scandinavia gradually caught up with the rest of Western Europe, eventually overtaking it by the middle of the century. By contrast, income across East-Central Europe fell further behind the west over this period, falling from 42 percent of the west's rate in 1900 to 37 percent in 1950.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Calumet Park. The dataset can be utilized to gain insights into gender-based income distribution within the Calumet Park population, 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
Employment type classifications include:
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 Calumet Park median household income by race. You can refer the same here
In 2023, employees who graduated in computer science earned around 2,150 euros net per month five years after obtaining their master's degree. Industrial and information engineers were paid 2,000 euros monthly. By contrast, graduates in psychology and education earned on average 1,400 euros, 370 euros less than the national mean. There were significant salary differences between male and female graduates, too. Women graduated in 2018 received 1,640 euros monthly in 2023, whereas men were paid an average of 1900 euros.
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License information was derived automatically
Russia Population: Percent of Total: Household Income per Capita: 14000.1 - 19000 RUB per Month data was reported at 13.800 % in Dec 2018. This records a decrease from the previous number of 14.400 % for Sep 2018. Russia Population: Percent of Total: Household Income per Capita: 14000.1 - 19000 RUB per Month data is updated quarterly, averaging 15.400 % from Dec 2011 (Median) to Dec 2018, with 29 observations. The data reached an all-time high of 16.300 % in Mar 2014 and a record low of 13.800 % in Dec 2018. Russia Population: Percent of Total: Household Income per Capita: 14000.1 - 19000 RUB per Month data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA013: Population by Average Household Income.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Centralia. The dataset can be utilized to gain insights into gender-based income distribution within the Centralia population, 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
Employment type classifications include:
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 Centralia median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within River Grove. The dataset can be utilized to gain insights into gender-based income distribution within the River Grove population, 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
Employment type classifications include:
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 River Grove median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Plattsburgh town. The dataset can be utilized to gain insights into gender-based income distribution within the Plattsburgh town population, 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
Employment type classifications include:
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 Plattsburgh town median household income by race. You can refer the same here
This table contains 11 series, with data for years 1926 - 1960 (not all combinations necessarily have data for all years), and was last released on 2009-01-21. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Income-based estimates (11 items: Gross domestic product (GDP) at market prices; Net domestic income at factor cost; Wages; salaries and supplementary labour income; Corporation profits before taxes ...).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Cape Elizabeth town. The dataset can be utilized to gain insights into gender-based income distribution within the Cape Elizabeth town population, 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
Employment type classifications include:
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 Cape Elizabeth town median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Jenkins township. The dataset can be utilized to gain insights into gender-based income distribution within the Jenkins township population, 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
Employment type classifications include:
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 Jenkins township median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Fleming County. The dataset can be utilized to gain insights into gender-based income distribution within the Fleming County population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/fleming-county-ky-income-distribution-by-gender-and-employment-type.jpeg" alt="Fleming County, KY gender and employment-based income distribution analysis (Ages 15+)">
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
Employment type classifications include:
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 Fleming County median household income by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Kalkaska County. The dataset can be utilized to gain insights into gender-based income distribution within the Kalkaska County population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/kalkaska-county-mi-income-distribution-by-gender-and-employment-type.jpeg" alt="Kalkaska County, MI gender and employment-based income distribution analysis (Ages 15+)">
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
Employment type classifications include:
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 Kalkaska County median household income by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Seagoville. The dataset can be utilized to gain insights into gender-based income distribution within the Seagoville population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/seagoville-tx-income-distribution-by-gender-and-employment-type.jpeg" alt="Seagoville, TX gender and employment-based income distribution analysis (Ages 15+)">
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
Employment type classifications include:
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 Seagoville median household income by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This spreadsheet contains our most complete series of income/expenditure data for Royal Society publishing, 1880-2010. It shows the income from sales and from grants; the expenditure on printing, distribution and other costs, for the Transactions and for the Proceedings; it provides calculations of surplus/deficit and expense recovery rate (which, given the nature of RS publishing in this period, is a more useful measure than expressing surplus as % of sales income). A variety of graphs are included, some of which appeared in my 2022 article 'From philanthropy to business' https://royalsocietypublishing.org/doi/full/10.1098/rsnr.2022.0021 Sources of Data: Data for 1880-1899 come from the series of financial ledgers and annual balance sheets in the Royal Society archives. They do not distinguish between costs/income for Transactions or Proceedings
From 1900 onwards, the main run of income/expenditure data comes from the published annual accounts of the Royal Society (in the Year Book until 1999; and thereafter in the separately-published Trustees' Report). For certain years, e.g. in the mid-20thC, it has been possible to supplement this with more detailed breakdowns from the archival series.
The data available become less detailed over time. Cost breakdowns for paper/printing/illustrations etc are only available up to 1966. Income/expenditure breakdowns by journal (i.e. Proceedings/Transactions/other) are only availble until 2005. Salary and overhead costs are only sometimes available.
Inconsistencies
There are various inconsistencies to be aware of:
The Society changed its accounting year occasionally. This spreadsheet reports the results for whichever accounting year the Society was using at the time, and so users should be aware of moments of transition. Traditionally, the Society's accounting year had ended on its anniversary day (30 November). In 1939, it moved to a year-end of 30 Sept (so, 1939 figures are for an 11-month 'year'). In 1968, it moved to a year-end of 31 Aug (so, 1968 figures are for a 11-month 'year'). In 1991, it adopted a year-end of 31 March (so, 1991 figures are for a 7-month 'year'). And, by c.2004, the Publishing Team was reporting internally by Calendar Year, even though RS officially still kept a March financial year...
Decimalisation in 1971
Annual average net outlays for vehicle purchases came to above 5,500 U.S. dollars for all U.S. consumers in 2023, ranging between around 1,900 U.S. dollars for those in the lowest income bracket to nearly 14,100 U.S. dollars for consumers in the highest income group.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Real Median Family Income in the United States (MEFAINUSA672N) from 1953 to 2023 about family, median, income, real, and USA.