Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Wages in the United States increased 4.72 percent in May 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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Minimum Wages in Indonesia increased to 5.40 IDR Million/Month in 2025 from 5.07 IDR Million/Month in 2024. This dataset provides - Indonesia Minimum Wages- actual values, historical data, forecast, chart, statistics, economic calendar and news.
In April 2025, the UK minimum wage for adults over the age of 21 in will be 12.21 pounds per hour. For the 2025/26 financial year, there will be four minimum wage categories, three of which are based on age and one for apprentice workers. Apprentices, and workers under the age of 18 will have a minimum wage of 7.55 pounds an hour, increasing to ten pounds for those aged 18 to 20. When the minimum wage was first introduced in 1999, there were just two age categories; 18 to 21, and 22 and over. This increased to three categories in 2004, four in 2010, and five between 2016 and 2023, before being reduced down to four in the most recent year. The living wage The living wage is an alternative minimum wage amount that employers in the UK can voluntarily pay their employees. It is calculated independently of the legal minimum wage and results in a higher value figure. In 2023/24, for example, the living wage was twelve pounds an hour for the UK as a whole and 13.15 for workers in London, where the cost of living is typically higher. This living wage is different from what the UK government has named the national living wage, which was 10.42 in the same financial year. Between 2011/12 and 2023/24, the living wage has increased by 4.80 pounds, while the London living wage has grown by 4.85 pounds. Wage growth cancelled-out by high inflation 2021-2023 For a long period between the middle of 2021 and late 2023, average wage growth in the UK was unable to keep up with record inflation levels, resulting in the biggest fall in disposable income since 1956. Although the UK government attempted to mitigate the impact of falling living standards through a series of cost of living payments, the situation has still been very difficult for households. After peaking at 11.1 percent in October 2022, the UK's inflation rate remained in double figures until March 2023, and did not fall to the preferred rate of two percent until May 2024. As of November 2024, regular weekly pay in the UK was growing by 5.6 percent in nominal terms, and 2.5 percent when adjusted for inflation.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Wages in Italy increased 3.40 percent in April of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Italy Hourly Wage Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
Average hourly and weekly wage rate, and median hourly and weekly wage rate by North American Industry Classification System (NAICS), type of work, gender, and age group.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for WAGE GROWTH reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
The minimum wage is a basic labour standard that sets the lowest wage rate that an employer can pay to employees who are covered by the legislation. Today, one of its main purposes is to protect non-unionized workers in unskilled jobs, although it can also influence, directly or indirectly, the level of compensation of other employees as well. A minimum wage constitutes a floor above which employees or their unions may negotiate with management for higher remuneration. However, it is rarely static: adjustments are required from time to time to maintain its relevance in changing economic and social conditions.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in King County. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in King County. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2023
In terms of income distribution across age cohorts, in King County, householders within the 45 to 64 years age group have the highest median household income at $143,468, followed by those in the 25 to 44 years age group with an income of $138,933. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $74,575. Notably, householders within the under 25 years age group, had the lowest median household income at $62,672.
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 2023-inflation-adjusted dollars.
Age groups classifications 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 King County median household income by age. 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 mean household income for each of the five quintiles in Gold Beach, OR, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.
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 Levels:
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 Gold Beach median household income. You can refer the same here
https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/B9TEWMhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/B9TEWM
This dataset contains replication files for "The Fading American Dream: Trends in Absolute Income Mobility Since 1940" by Raj Chetty, David Grusky, Maximilian Hell, Nathaniel Hendren, Robert Manduca, and Jimmy Narang. For more information, see https://opportunityinsights.org/paper/the-fading-american-dream/. A summary of the related publication follows. One of the defining features of the “American Dream” is the ideal that children have a higher standard of living than their parents. We assess whether the U.S. is living up to this ideal by estimating rates of “absolute income mobility” – the fraction of children who earn more than their parents – since 1940. We measure absolute mobility by comparing children’s household incomes at age 30 (adjusted for inflation using the Consumer Price Index) with their parents’ household incomes at age 30. We find that rates of absolute mobility have fallen from approximately 90% for children born in 1940 to 50% for children born in the 1980s. Absolute income mobility has fallen across the entire income distribution, with the largest declines for families in the middle class. These findings are unaffected by using alternative price indices to adjust for inflation, accounting for taxes and transfers, measuring income at later ages, and adjusting for changes in household size. Absolute mobility fell in all 50 states, although the rate of decline varied, with the largest declines concentrated in states in the industrial Midwest, such as Michigan and Illinois. The decline in absolute mobility is especially steep – from 95% for children born in 1940 to 41% for children born in 1984 – when we compare the sons’ earnings to their fathers’ earnings. Why have rates of upward income mobility fallen so sharply over the past half-century? There have been two important trends that have affected the incomes of children born in the 1980s relative to those born in the 1940s and 1950s: lower Gross Domestic Product (GDP) growth rates and greater inequality in the distribution of growth. We find that most of the decline in absolute mobility is driven by the more unequal distribution of economic growth rather than the slowdown in aggregate growth rates. When we simulate an economy that restores GDP growth to the levels experienced in the 1940s and 1950s but distributes that growth across income groups as it is distributed today, absolute mobility only increases to 62%. In contrast, maintaining GDP at its current level but distributing it more broadly across income groups – at it was distributed for children born in the 1940s – would increase absolute mobility to 80%, thereby reversing more than two-thirds of the decline in absolute mobility. These findings show that higher growth rates alone are insufficient to restore absolute mobility to the levels experienced in mid-century America. Under the current distribution of GDP, we would need real GDP growth rates above 6% per year to return to rates of absolute mobility in the 1940s. Intuitively, because a large fraction of GDP goes to a small fraction of high-income households today, higher GDP growth does not substantially increase the number of children who earn more than their parents. Of course, this does not mean that GDP growth does not matter: changing the distribution of growth naturally has smaller effects on absolute mobility when there is very little growth to be distributed. The key point is that increasing absolute mobility substantially would require more broad-based economic growth. We conclude that absolute mobility has declined sharply in America over the past half-century primarily because of the growth in inequality. If one wants to revive the “American Dream” of high rates of absolute mobility, one must have an interest in growth that is shared more broadly across the income distribution.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Memphis. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Memphis. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2023
In terms of income distribution across age cohorts, in Memphis, householders within the 45 to 64 years age group have the highest median household income at $58,790, followed by those in the 25 to 44 years age group with an income of $52,615. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $45,024. Notably, householders within the under 25 years age group, had the lowest median household income at $33,103.
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 2023-inflation-adjusted dollars.
Age groups classifications 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 Memphis median household income by age. 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
Wages in Manufacturing in the United States remained unchanged at 28.87 USD/Hour in June. This dataset provides - United States Average Hourly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Inflation rates experienced by different groups of consumers within a country vary. This is because the prices of goods and services and the expenditure patterns of consumers differ. The published inflation rate is used for important decisions regarding the preservation of consumer purchasing power. These include the adjustment of social grants and minimum wages by government and the benchmarking of returns by investors when making investment decisions. It is thus vital that inflation is measured accurately to ensure the purchasing power of consumers is preserved. Current measures of inflation published by Stats SA are applicable to typical consumers and are not relevant to each individual. This resource supplements a study that seeks to provide a publicly available model that can be used by consumers to calculate their personal rate of inflation.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Wake County. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Wake County. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2023
In terms of income distribution across age cohorts, in Wake County, householders within the 45 to 64 years age group have the highest median household income at $122,011, followed by those in the 25 to 44 years age group with an income of $108,405. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $69,553. Notably, householders within the under 25 years age group, had the lowest median household income at $53,790.
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 2023-inflation-adjusted dollars.
Age groups classifications 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 Wake County median household income by age. 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 distribution of median household income among distinct age brackets of householders in Seattle. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Seattle. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2023
In terms of income distribution across age cohorts, in Seattle, householders within the 45 to 64 years age group have the highest median household income at $142,211, followed by those in the 25 to 44 years age group with an income of $142,082. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $68,000. Notably, householders within the under 25 years age group, had the lowest median household income at $56,112.
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 2023-inflation-adjusted dollars.
Age groups classifications 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 Seattle median household income by age. 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 distribution of median household income among distinct age brackets of householders in Los Angeles. Based on the latest 2022 1-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Los Angeles. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2022
In terms of income distribution across age cohorts, in Los Angeles, householders within the 25 to 44 years age group have the highest median household income at $85,933, followed by those in the 45 to 64 years age group with an income of $82,229. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $52,852. Notably, householders within the under 25 years age group, had the lowest median household income at $46,395.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.
Age groups classifications 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 Los Angeles median household income by age. 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 mean household income for each of the five quintiles in Santa Barbara County, CA, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.
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 Levels:
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 Santa Barbara County median household income. 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 distribution of median household income among distinct age brackets of householders in Wichita County. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Wichita County. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2021
In terms of income distribution across age cohorts, in Wichita County, householders within the 45 to 64 years age group have the highest median household income at $80,243, followed by those in the 25 to 44 years age group with an income of $69,359. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $60,531. Notably, householders within the under 25 years age group, had the lowest median household income at $16,382.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.
Age groups classifications 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 Wichita County median household income by age. 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 distribution of median household income among distinct age brackets of householders in Washington. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Washington. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2022
In terms of income distribution across age cohorts, in Washington, householders within the 25 to 44 years age group have the highest median household income at $63,405, followed by those in the 45 to 64 years age group with an income of $52,762. Meanwhile householders within the under 25 years age group report the second lowest median household income of $49,775. Notably, householders within the 65 years and over age group, had the lowest median household income at $44,788.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications 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 Washington median household income by age. 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
Wages in the United States increased 4.72 percent in May 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.