In 2023, the median usual weekly earnings of a white full-time employee in the United States amounted to 1,138 U.S. dollars. Dollar value is based on 2023 U.S. dollars. Unadjusted median wages for white workers in the U.S. can be found here.

Graph and download economic data for Consumer Price Index for All Urban Wage Earners and Clerical Workers: Information and Information Processing in U.S. City Average (CWUR0000SAE21) from Jan 1993 to Jun 2025 about clerical workers, information, urban, wages, CPI, inflation, price index, indexes, price, and USA.

In 2023, the median usual weekly earnings of an African American full-time employee in the United States amounted to 920 U.S. dollars. Dollar value is based on 2023 U.S. dollars. In 1979, the median weekly earnings of African American full-time employees was 783 constant 2023 U.S. dollars. Median weekly earnings of Black and African Americans not adjusted for inflation can be found here.

Graph and download economic data for Consumer Price Index for All Urban Wage Earners and Clerical Workers: Personal Care Products in U.S. City Average (CWUR0000SEGB) from Mar 1947 to Jun 2025 about clerical workers, urban, wages, production, personal, CPI, inflation, price index, indexes, price, and USA.

Graph and download economic data for Consumer Price Index for All Urban Wage Earners and Clerical Workers: Energy Services in U.S. City Average (CWUR0000SEHF) from Mar 1935 to Jun 2025 about clerical workers, energy, urban, wages, services, CPI, inflation, price index, indexes, price, and USA.

SELECTED ECONOMIC CHARACTERISTICS INCOME AND BENEFITS (IN 2021 2022 INFLATION-ADJUSTED DOLLARS) - DP03 Universe - Total households Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Total income is the sum of the amounts reported separately for wage or salary income; net self-employment income; interest, dividends, or net rental or royalty income or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); public assistance or welfare payments; retirement, survivor, or disability pensions; and all other income. Receipts from the following sources are not included as income: capital gains, money received from the sale of property (unless the recipient was engaged in the business of selling such property); the value of income “in kind” from food stamps, public housing subsidies, medical care, employer contributions for individuals, etc.; withdrawal of bank deposits; money borrowed; tax refunds; exchange of money between relatives living in the same household; gifts and lump-sum inheritances, insurance payments, and other types of lump sum receipts.

Wages in Italy increased 2.70 percent in May 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.

The inflation rate in the United States is expected to decrease to 2.1 percent by 2029. 2022 saw a year of exceptionally high inflation, reaching eight percent for the year. The data represents U.S. city averages. The base period was 1982-84. In economics, the inflation rate is a measurement of inflation, the rate of increase of a price index (in this case: consumer price index). It is the percentage rate of change in prices level over time. The rate of decrease in the purchasing power of money is approximately equal. According to the forecast, prices will increase by 2.9 percent in 2024. The annual inflation rate for previous years can be found here and the consumer price index for all urban consumers here. The monthly inflation rate for the United States can also be accessed here. Inflation in the U.S.Inflation is a term used to describe a general rise in the price of goods and services in an economy over a given period of time. Inflation in the United States is calculated using the consumer price index (CPI). The consumer price index is a measure of change in the price level of a preselected market basket of consumer goods and services purchased by households. This forecast of U.S. inflation was prepared by the International Monetary Fund. They project that inflation will stay higher than average throughout 2023, followed by a decrease to around roughly two percent annual rise in the general level of prices until 2028. Considering the annual inflation rate in the United States in 2021, a two percent inflation rate is a very moderate projection. The 2022 spike in inflation in the United States and worldwide is due to a variety of factors that have put constraints on various aspects of the economy. These factors include COVID-19 pandemic spending and supply-chain constraints, disruptions due to the war in Ukraine, and pandemic related changes in the labor force. Although the moderate inflation of prices between two and three percent is considered normal in a modern economy, countries’ central banks try to prevent severe inflation and deflation to keep the growth of prices to a minimum. Severe inflation is considered dangerous to a country’s economy because it can rapidly diminish the population’s purchasing power and thus damage the GDP .

Rents paid for housing in Mexico increased year-on-year between 2011 and 2023. Nevertheless, the inflation-adjusted change was negative throughout this period, suggesting that rents grew at a slower rate than inflation. In 2023, the nominal increase in rents paid for housing amounted to **** percent, while the real change (adjusted for inflation) was recorded at a negative **** percent.

Rents paid for housing in Austria have increased nominally year-on-year between 2011 and 2023. Nevertheless, the inflation-adjusted change was negative between 2021 and 2022, suggesting that rents grew at a slower rate than inflation. In 2023, the nominal increase in rents paid for housing amounted to **** percent, while the real change (adjusted for inflation) amounted to **** percent. Overall rents in Austria have grown faster than the average in the euro area.

About this dataset

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 Goodview. 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 Goodview, the median income for all workers aged 15 years and older, regardless of work hours, was $52,219 for males and $40,667 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 22% between the median incomes of males and females in Goodview. With women, regardless of work hours, earning 78 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Goodview.

- Full-time workers, aged 15 years and older: In Goodview, among full-time, year-round workers aged 15 years and older, males earned a median income of $64,250, while females earned $48,650, leading to a 24% gender pay gap among full-time workers. This illustrates that women earn 76 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Goodview, showcasing a consistent income pattern irrespective of employment status.

Content

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:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Goodview median household income by race. You can refer the same here

Rents paid for housing in Luxembourg increased nominally year-on-year between 2011 and 2023. Nevertheless, the inflation-adjusted change was negative between 2021 and 2023, suggesting that rents grew at a slower rate than inflation. In 2023, the nominal increase in rents paid for housing amounted to **** percent, while the real change (adjusted for inflation) was recorded at a negative **** percent. In 2023, the average residential rent in Luxembourg City was nearly ***** euros.

Rents paid for housing in Israel increased year-on-year between 2011 and 2023. Nevertheless, the inflation-adjusted change was negative between 2021 and 2022, suggesting that rents grew at a slower rate than inflation. In 2023, the nominal growth in rent prices amounted to **** percent, while the real change (adjusted for inflation) amounted to **** percent.

About this dataset

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 Staples. 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 Staples, the median income for all workers aged 15 years and older, regardless of work hours, was $40,174 for males and $29,867 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 26% between the median incomes of males and females in Staples. With women, regardless of work hours, earning 74 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Staples.

- Full-time workers, aged 15 years and older: In Staples, among full-time, year-round workers aged 15 years and older, males earned a median income of $56,071, while females earned $46,532, leading to a 17% gender pay gap among full-time workers. This illustrates that women earn 83 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Staples, showcasing a consistent income pattern irrespective of employment status.

Content

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:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Staples median household income by race. You can refer the same here

About this dataset

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 Garden township. 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 Garden township, the median income for all workers aged 15 years and older, regardless of work hours, was $49,375 for males and $38,438 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 22% between the median incomes of males and females in Garden township. With women, regardless of work hours, earning 78 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetownship of Garden township.

- Full-time workers, aged 15 years and older: In Garden township, among full-time, year-round workers aged 15 years and older, males earned a median income of $60,000, while females earned $48,250, leading to a 20% gender pay gap among full-time workers. This illustrates that women earn 80 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Garden township, showcasing a consistent income pattern irrespective of employment status.

Content

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:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Garden township median household income by race. You can refer the same here

About this dataset

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 Victor. 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 Victor, the median income for all workers aged 15 years and older, regardless of work hours, was $56,693 for males and $42,036 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 26% between the median incomes of males and females in Victor. With women, regardless of work hours, earning 74 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thevillage of Victor.

- Full-time workers, aged 15 years and older: In Victor, among full-time, year-round workers aged 15 years and older, males earned a median income of $82,188, while females earned $62,273, leading to a 24% gender pay gap among full-time workers. This illustrates that women earn 76 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Victor, showcasing a consistent income pattern irrespective of employment status.

Content

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:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Victor median household income by race. You can refer the same here

Wages in Germany increased 1.20 percent in March of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Germany Wage Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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.

This feature layer consists of the contiguous United States and District of Columbia, with Alaska and Hawaii. It comprises state minimum wage data for 2018, as well as historical data since 1968, and future data where available. The data was compiled from the U.S. Department of Labor, the National Conference of State Legislatures, and the U.C. Berkeley Labor Center, with living wage data from MIT's Living Wage Calculator. This layer uses the composite geographies layout to position Alaska and Hawaii adjacent to the contiguous United States.Attributes:

Field Name Unit Description

PeakMW Nominal dollar value Highest minimum wage value planned to be reached in future years (2019-2022)

PeakYR Year The year that the highest minimum wage value is planned to be reached (2019-2022)

DiffPeak2018 Nominal dollar value (difference) The difference between the peak minimum wage and the 2018 minimum wage (PeakMW - DiffPeak2018)

MW2018 Nominal dollar value 2018 state minimum wage

Increase2017 Nominal dollar value (difference) The difference between the 2018 minimum wage and the 2017 minimum wage (MW2018 - MW2017)

Increase2000 2017 dollar value (difference) The difference between the 2018 minimum wage and the 2000 minimum wage (MW2018-MW2000)

Effective2018 Nominal dollar value The minimum wage effective in 2018. For states with minimum wages below the federal minimum wage of $7.25, or for states that have no minimum wage requirement, the federal minimum wage applies.

LV2016 Nominal dollar value 2016 living wage for a single adult at the state level

DiffMWLV Nominal dollar value (difference) The difference between the 2018 minimum wage and the 2016 living wage

CurrentMW Category The type of minimum wage policy in place at the state level

PoliciesMW Text When a state has an indexed minimum wage, the type of policy is described here

Update2018 Category Yes = the state implemented an update to its minimum wage in 2018; No = no policy update in 2018

MW2017 Nominal dollar value 2017 minimum wage

MW2016 2017 dollar value 2016 minimum wage, adjusted for inflation to 2017 dollars

MW2015 2017 dollar value 2015 minimum wage, adjusted for inflation to 2017 dollars

MW2014 2017 dollar value 2014 minimum wage, adjusted for inflation to 2017 dollars

MW2013 2017 dollar value 2013 minimum wage, adjusted for inflation to 2017 dollars

MW2012 2017 dollar value 2012 minimum wage, adjusted for inflation to 2017 dollars

MW2011 2017 dollar value 2011 minimum wage, adjusted for inflation to 2017 dollars

MW2010 2017 dollar value 2010 minimum wage, adjusted for inflation to 2017 dollars

MW2009 2017 dollar value 2009 minimum wage, adjusted for inflation to 2017 dollars

MW2008 2017 dollar value 2008 minimum wage, adjusted for inflation to 2017 dollars

MW2007 2017 dollar value 2007 minimum wage, adjusted for inflation to 2017 dollars

MW2006 2017 dollar value 2006 minimum wage, adjusted for inflation to 2017 dollars

MW2005 2017 dollar value 2005 minimum wage, adjusted for inflation to 2017 dollars

MW2004 2017 dollar value 2004 minimum wage, adjusted for inflation to 2017 dollars

MW2003 2017 dollar value 2003 minimum wage, adjusted for inflation to 2017 dollars

MW2002 2017 dollar value 2002 minimum wage, adjusted for inflation to 2017 dollars

MW2001 2017 dollar value 2001 minimum wage, adjusted for inflation to 2017 dollars

MW2000 2017 dollar value 2000 minimum wage, adjusted for inflation to 2017 dollars

MW1998 2017 dollar value 1998 minimum wage, adjusted for inflation to 2017 dollars

MW1997 2017 dollar value 1997 minimum wage, adjusted for inflation to 2017 dollars

MW1996 2017 dollar value 1996 minimum wage, adjusted for inflation to 2017 dollars

MW1994 2017 dollar value 1994 minimum wage, adjusted for inflation to 2017 dollars

MW1992 2017 dollar value 1992 minimum wage, adjusted for inflation to 2017 dollars

MW1991 2017 dollar value 1991 minimum wage, adjusted for inflation to 2017 dollars

MW1988 2017 dollar value 1988 minimum wage, adjusted for inflation to 2017 dollars

MW1981 2017 dollar value 1981 minimum wage, adjusted for inflation to 2017 dollars

MW1980 2017 dollar value 1980 minimum wage, adjusted for inflation to 2017 dollars

MW1979 2017 dollar value 1979 minimum wage, adjusted for inflation to 2017 dollars

MW1976 2017 dollar value 1976 minimum wage, adjusted for inflation to 2017 dollars

MW1972 2017 dollar value 1972 minimum wage, adjusted for inflation to 2017 dollars

MW1970 2017 dollar value 1970 minimum wage, adjusted for inflation to 2017 dollars

MW1968 2017 dollar value 1968 minimum wage, adjusted for inflation to 2017 dollars

About this dataset

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 Haskell. 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 Haskell, the median income for all workers aged 15 years and older, regardless of work hours, was $51,875 for males and $33,292 for females.

These income figures highlight a substantial gender-based income gap in Haskell. Women, regardless of work hours, earn 64 cents for each dollar earned by men. This significant gender pay gap, approximately 36%, underscores concerning gender-based income inequality in the city of Haskell.

- Full-time workers, aged 15 years and older: In Haskell, among full-time, year-round workers aged 15 years and older, males earned a median income of $62,819, while females earned $49,018, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Haskell.

Content

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:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Haskell median household income by race. You can refer the same here