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 Willard. The dataset can be utilized to gain insights into gender-based income distribution within the Willard population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/willard-mo-income-distribution-by-gender-and-employment-type.jpeg" alt="Willard, MO 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 Willard median household income by gender. You can refer the same here
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.
When adjusted for inflation, the 2024 federal minimum wage in the United States is over 40 percent lower than the minimum wage in 1970. Although the real dollar minimum wage in 1970 was only 1.60 U.S. dollars, when expressed in nominal 2024 dollars this increases to 13.05 U.S. dollars. This is a significant difference from the federal minimum wage in 2024 of 7.25 U.S. dollars.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Romania RO: Wages Index data was reported at 169.459 2010=100 in 2017. This records an increase from the previous number of 148.427 2010=100 for 2016. Romania RO: Wages Index data is updated yearly, averaging 0.021 2010=100 from Dec 1955 (Median) to 2017, with 60 observations. The data reached an all-time high of 169.459 2010=100 in 2017 and a record low of 0.004 2010=100 in 1955. Romania RO: Wages Index data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Romania – Table RO.IMF.IFS: Wages, Labour Cost and Employment Index: Annual.
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 Blackwell. The dataset can be utilized to gain insights into gender-based income distribution within the Blackwell 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 Blackwell median household income by race. You can refer the same here
Between 1948 and 1981, average wages in the U.S. agricultural sector grew by a factor of five. Agricultural wages doubled between 1955 and 1970, and doubled again by 1980. These rates were slightly higher, but similar to, wage growth in the industrial sector during these years.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Japan Number of Persons: Annual Salary: >5 Million data was reported at 13,920,018.000 Person in 2016. This records an increase from the previous number of 13,673,908.000 Person for 2015. Japan Number of Persons: Annual Salary: >5 Million data is updated yearly, averaging 5,800,878.000 Person from Dec 1952 (Median) to 2016, with 65 observations. The data reached an all-time high of 16,313,809.000 Person in 1997 and a record low of 0.000 Person in 1955. Japan Number of Persons: Annual Salary: >5 Million data remains active status in CEIC and is reported by National Tax Agency. The data is categorized under Global Database’s Japan – Table JP.G104: Number of Private Sector Employees: Annual Salary.
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 Dickenson County. The dataset can be utilized to gain insights into gender-based income distribution within the Dickenson County 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 Dickenson County 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 Carpinteria. The dataset can be utilized to gain insights into gender-based income distribution within the Carpinteria 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 Carpinteria 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 Sweetwater. The dataset can be utilized to gain insights into gender-based income distribution within the Sweetwater population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/sweetwater-tn-income-distribution-by-gender-and-employment-type.jpeg" alt="Sweetwater, TN 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 Sweetwater 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 Childress. The dataset can be utilized to gain insights into gender-based income distribution within the Childress population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/childress-tx-income-distribution-by-gender-and-employment-type.jpeg" alt="Childress, 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 Childress median household income by gender. You can refer the same here
In 2024, gross domestic product per capita in the United Kingdom was 36,977 British pounds, compared with 37,028 pounds in the previous year. This was the second-consecutive year that GDP per head has fallen in the UK, with the measure shrinking by 0.9 percent in 2023. In general, while GDP per capita has grown quite consistently throughout this period, there are noticeable declines, especially between 2007 and 2009, and between 2019 and 2020, due to the Global Financial Crisis, and COVID-19 pandemic, respectively. Why is GDP per capita falling when the economy is growing? During the last two years that GDP per capita fell in the UK, the overall economy grew by 0.4 percent in 2023 and 0.9 percent in 2024. While the overall UK economy is therefore larger than it was in 2022, the UK's population has grown at a faster rate, resulting in the lower GDP per capita figure. The long-term slump in the UK's productivity, as measured by output per hour worked, has meant that the gap between GDP growth and GDP per capita growth has been widening for some time. Economy remains the main concern of UK voters As of February 2025, the economy was seen as the main issue facing the UK, just ahead of immigration, health, and several other problems in the country. While Brexit was seen as the most important issue before COVID-19, and concerns about health were dominant throughout 2020 and 2021, the economy has generally been the primary facing voters issue since 2022. The surge in inflation throughout 2022 and 2023, and the impact this had on wages and living standards, resulted in a very tough period for UK households. As of January 2025, 57 percent of households were still noticing rising living costs, although this is down from a peak of 91 percent in August 2022.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for State Government Tax Collections, Individual Income Taxes in Hawaii (HIINCTAX) from 1955 to 2023 about individual, HI, tax, government, income, and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Malaysia GDP: Gross National Income data was reported at 1,195,480.000 MYR mn in 2016. This records an increase from the previous number of 1,125,611.000 MYR mn for 2015. Malaysia GDP: Gross National Income data is updated yearly, averaging 73,072.000 MYR mn from Dec 1955 (Median) to 2016, with 62 observations. The data reached an all-time high of 1,195,480.000 MYR mn in 2016 and a record low of 4,756.000 MYR mn in 1955. Malaysia GDP: Gross National Income data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Malaysia – Table MY.IMF.IFS: Gross Domestic Product: by Expenditure: Annual.
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 Bridgeville. The dataset can be utilized to gain insights into gender-based income distribution within the Bridgeville population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/bridgeville-pa-income-distribution-by-gender-and-employment-type.jpeg" alt="Bridgeville, PA 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 Bridgeville 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 Jericho town. The dataset can be utilized to gain insights into gender-based income distribution within the Jericho town population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/jericho-town-vt-income-distribution-by-gender-and-employment-type.jpeg" alt="Jericho Town, Vermont 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 Jericho town median household income by gender. You can refer the same here
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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 Willard. The dataset can be utilized to gain insights into gender-based income distribution within the Willard population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/willard-mo-income-distribution-by-gender-and-employment-type.jpeg" alt="Willard, MO 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 Willard median household income by gender. You can refer the same here