The statistic shows the female to male earnings ratio in the United States in the fourth quarter of 2022, based on the median income in current U.S. dollars, by age group. In the fourth quarter of 2022, the earnings ratio of female to male workers aged between 16 to 24 years was at about 92.9 percent.
The Health Inequality Project uses big data to measure differences in life expectancy by income across areas and identify strategies to improve health outcomes for low-income Americans.
This table reports life expectancy point estimates and standard errors for men and women at age 40 for each percentile of the national income distribution. Both race-adjusted and unadjusted estimates are reported.
This table reports life expectancy point estimates and standard errors for men and women at age 40 for each percentile of the national income distribution separately by year. Both race-adjusted and unadjusted estimates are reported.
This dataset was created on 2020-01-10 18:53:00.508
by merging multiple datasets together. The source datasets for this version were:
Commuting Zone Life Expectancy Estimates by year: CZ-level by-year life expectancy estimates for men and women, by income quartile
Commuting Zone Life Expectancy: Commuting zone (CZ)-level life expectancy estimates for men and women, by income quartile
Commuting Zone Life Expectancy Trends: CZ-level estimates of trends in life expectancy for men and women, by income quartile
Commuting Zone Characteristics: CZ-level characteristics
Commuting Zone Life Expectancy for larger populations: CZ-level life expectancy estimates for men and women, by income ventile
This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by state of residence and year. Both race-adjusted and unadjusted estimates are reported.
This table reports US mortality rates by gender, age, year and household income percentile. Household incomes are measured two years prior to the mortality rate for mortality rates at ages 40-63, and at age 61 for mortality rates at ages 64-76. The “lag” variable indicates the number of years between measurement of income and mortality.
Observations with 1 or 2 deaths have been masked: all mortality rates that reflect only 1 or 2 deaths have been recoded to reflect 3 deaths
This table reports coefficients and standard errors from regressions of life expectancy estimates for men and women at age 40 for each quartile of the national income distribution on calendar year by commuting zone of residence. Only the slope coefficient, representing the average increase or decrease in life expectancy per year, is reported. Trend estimates for both race-adjusted and unadjusted life expectancies are reported. Estimates are reported for the 100 largest CZs (populations greater than 590,000) only.
This table reports life expectancy estimates at age 40 for Males and Females for all countries. Source: World Health Organization, accessed at: http://apps.who.int/gho/athena/
This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by county of residence. Both race-adjusted and unadjusted estimates are reported. Estimates are reported for counties with populations larger than 25,000 only
This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by commuting zone of residence and year. Both race-adjusted and unadjusted estimates are reported. Estimates are reported for the 100 largest CZs (populations greater than 590,000) only.
This table reports US population and death counts by age, year, and sex from various sources. Counts labelled “dm1” are derived from the Social Security Administration Data Master 1 file. Counts labelled “irs” are derived from tax data. Counts labelled “cdc” are derived from NCHS life tables.
This table reports numerous county characteristics, compiled from various sources. These characteristics are described in the county life expectancy table.
Two variables constructed by the Cen
In 2023, the median usual weekly earnings of employed men over 65 years old amounted to 1,181 current U.S. dollars. Weekly earnings for men were highest in that year for those between the ages of 45 and 54 years old, at 1,396 current U.S. dollars.
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License information was derived automatically
Context
The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Norway. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.
Key observations: Insights from 2023
Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Norway, the median income for all workers aged 15 years and older, regardless of work hours, was $49,167 for males and $38,750 for females.
These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 21% between the median incomes of males and females in Norway. With women, regardless of work hours, earning 79 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Norway.
- Full-time workers, aged 15 years and older: In Norway, among full-time, year-round workers aged 15 years and older, males earned a median income of $63,333, while females earned $38,750, leading to a 39% gender pay gap among full-time workers. This illustrates that women earn 61 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.Remarkably, across all roles, including non-full-time employment, women displayed a lower gender pay gap percentage. This indicates that Norway offers better opportunities for women in non-full-time positions.
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.
Gender classifications include:
Employment type 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 Norway median household income by race. You can refer the same here
https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal
Women and Men in Spain: Average annual net income by household by age of the reference person and period. Annual. National.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Average female and male earnings and female-to-male earnings ratio, Canada.
Women's earnings as a share of men's have increased since 1982 across all age groups. While 25-35 year old women's median hourly earnings were ** percent of their male counterparts, the pay gap becomes more extreme as women age.
Average and median gender pay ratio in annual employment income and in annual wages, salaries and commissions. Data are available by National Occupational Classification (NOC) and age group.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Indian Beach. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.
Key observations: Insights from 2021
Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Indian Beach, the median income for all workers aged 15 years and older, regardless of work hours, was $54,046 for males and $24,321 for females.
These income figures highlight a substantial gender-based income gap in Indian Beach. Women, regardless of work hours, earn 45 cents for each dollar earned by men. This significant gender pay gap, approximately 55%, underscores concerning gender-based income inequality in the town of Indian Beach.
- Full-time workers, aged 15 years and older: In Indian Beach, for full-time, year-round workers aged 15 years and older, the Census Bureau did not report the median income for both males and females due to an insufficient number of sample observations.As income data for both males and females was unavailable, conducting a comprehensive analysis of gender-based pay disparity in the town of Indian Beach was not possible.
https://i.neilsberg.com/ch/indian-beach-nc-income-by-gender.jpeg" alt="Indian Beach, NC gender based income disparity">
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.
Gender classifications include:
Employment type 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 Indian Beach median household income by gender. You can refer the same here
In 2024 men aged between 50 and 59 were the highest full-time earners in the United Kingdom among different gender and age groups, with men of different ages consistently earning more than women.
https://www.arcgis.com/sharing/rest/content/items/89679671cfa64832ac2399a0ef52e414/datahttps://www.arcgis.com/sharing/rest/content/items/89679671cfa64832ac2399a0ef52e414/data
Lake County, Illinois Demographic Data. Explanation of field attributes:
Total Population – The entire population of Lake County.
White – Individuals who are of Caucasian race. This is a percent.African American – Individuals who are of African American race. This is a percent.Asian – Individuals who are of Asian race. This is a percent.
Hispanic – Individuals who are of Hispanic ethnicity. This is a percent.
Does not Speak English- Individuals who speak a language other than English in their household. This is a percent.
Under 5 years of age – Individuals who are under 5 years of age. This is a percent.
Under 18 years of age – Individuals who are under 18 years of age. This is a percent.
18-64 years of age – Individuals who are between 18 and 64 years of age. This is a percent.
65 years of age and older – Individuals who are 65 years old or older. This is a percent.
Male – Individuals who are male in gender. This is a percent.
Female – Individuals who are female in gender. This is a percent.
High School Degree – Individuals who have obtained a high school degree. This is a percent.
Associate Degree – Individuals who have obtained an associate degree. This is a percent.
Bachelor’s Degree or Higher – Individuals who have obtained a bachelor’s degree or higher. This is a percent.
Utilizes Food Stamps – Households receiving food stamps/ part of SNAP (Supplemental Nutrition Assistance Program). This is a percent.
Median Household Income - A median household income refers to the income level earned by a given household where half of the homes in the area earn more and half earn less. This is a dollar amount.
No High School – Individuals who have not obtained a high school degree. This is a percent.
Poverty – Poverty refers to families and people whose income in the past 12 months is below the poverty level. This is a percent.
In 2023, the median annual earnings of full-time male workers in the United States stood at 66,790 U.S. dollars after being adjusted for inflation, which was significantly higher than the median earnings of full-time women at 52,850. For further reading, see the female to male earnings ratio.
In 2023, the mean income of women with a doctorate degree in the United States stood at 139,100 U.S. dollars. For men with the same degree, mean earnings stood at 175,500 U.S. dollars. On average in 2023, American men earned 91,590 U.S. dollars, while American women earned 65,987 U.S. dollars.
Since 2009 and 2010, respectively, employment rates among men and women in Sweden increased steadily until the outbreak of COVID-19 in 2020, when it fell for both genders. The fall was more steep for women than men. In 2023, the employment rate for men was nearly 72 percent, whereas it was 67 percent for women. The total employment rate in the country was 69 percent. The income gap Even though the employment rate was higher for men than for women for all years in the period, Sweden was still among the countries with the highest female employment rates worldwide. The gap between male and female salaries is also small. In 2022, women’s average earnings as a percentage of men’s was 95 percent, when controlled for occupation, age, education, sector and number of working hours.Different employment types for men and women More men than women were permanent employees and self-employed in Sweden, while a higher number of women than men were temporary employees. Around 332,000 men and 403,000 women were temporary employees.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).
The gender overall earnings gap is a synthetic indicator. It measures the impact of the three combined factors, namely: (1) the average hourly earnings, (2) the monthly average of the number of hours paid (before any adjustment for part-time work) and (3) the employment rate, on the average earnings of all women of working age - whether employed or not employed - compared to men.
These tables only cover individuals with some liability to tax.
These statistics are classified as accredited official statistics.
You can find more information about these statistics and collated tables for the latest and previous tax years on the Statistics about personal incomes page.
Supporting documentation on the methodology used to produce these statistics is available in the release for each tax year.
Note: comparisons over time may be affected by changes in methodology. Notably, there was a revision to the grossing factors in the 2018 to 2019 publication, which is discussed in the commentary and supporting documentation for that tax year. Further details, including a summary of significant methodological changes over time, data suitability and coverage, are included in the Background Quality Report.
De gender loonkloof geeft het verschil weer tussen het gemiddelde bruto uurloon van vrouwen en mannen, uitgedrukt als een percentage van het gemiddelde mannenloon. In een formule geeft dit de volgende uitdrukking: Gender loonkloof = (uurloon mannen – uurloon vrouwen) / uurloon mannen De gender loonkloof wordt berekend op basis van de Loonenquête. De statistische populatie bestaat uit alle loontrekkenden die werkzaam zijn in ondernemingen: die minstens 10 werknemers tellen; waarvan de voornaamste economische activiteit ressorteert onder de NACE Rev.2 secties B-S (-O). Er gelden geen beperkingen naar leeftijd of arbeidsduur. De gender loonkloof omvat dus zowel voltijdse- als deeltijdse tewerkgestelde loontrekkenden. Het gehanteerde loonconcept omvat betaalde overuren evenals deze premies die iedere betalingsperiode worden uitbetaald. Premies voor nacht- of weekendwerk zijn hier voorbeelden van. Premies die slechts op uitzonderlijke basis worden uitgekeerd, zoals een dertiende maand of het dubbel vakantiegeld, worden uitgesloten. Alle lidstaten van de EU hanteren dezelfde geharmoniseerde concepten en methoden bij de berekening van de gender loonkloof. Hierdoor kunnen we de Belgische situatie vergelijken met de loonkloof in de overige EU-lidstaten. De gender loonkloof wordt eenmaal om de vier jaar berekend op basis van de Loonenquête. Dit is het geval voor de referentiejaren 2010, 2014, 2018 en 2022. In de tussenliggende jaren schat Statbel op basis van RSZ-gegevens de loonkloof. Hiervoor worden de cijfers van de recentste Loonenquête geactualiseerd op basis van een evolutie die afgeleid wordt uit de RSZ-datasets. De cijfers van 2023 werden op deze manier geschat. Tenslotte worden de nationale schattingen eenmaal om de vier jaar, namelijk na de publicatie van een nieuwe Loonenquête, door Eurostat herzien. De cijfers voor de jaren 2007-2009, 2011-2013, 2015-2017 en 2019-2021 werden bijgevolg door Eurostat berekend.
Average hourly earnings of female and male employees, by occupation, age and persons with disabilities.
In 2024, the average monthly earnings in Finland amounted to 4,051 euros. The average earnings in the central government sector reached 4,467 euros per month, while the corresponding figure in the non-profit institutions serving households sector was 3,548 euros per month. The gender pay gap remains Despite an overall increase in average earnings across all sectors, the gender pay gap in Finland has remained relatively stable, with men continuing to earn higher salaries than women. As of 2023, men earned around 650 euros more on average than women. However, the employment rate among women was higher than among men. Finland's aging population Finland's population is getting older, as can be seen through the increasing median age of its inhabitants. Between 1960 and 2023, the crude birth rate more than halved. In 2023, 7.8 births were recorded per 1,000 population of the country. Moreover, there is a gender gap in Finland's life expectancy, with women expected to live roughly five years longer than men.
The statistic shows the female to male earnings ratio in the United States in the fourth quarter of 2022, based on the median income in current U.S. dollars, by age group. In the fourth quarter of 2022, the earnings ratio of female to male workers aged between 16 to 24 years was at about 92.9 percent.