100+ datasets found
  1. T

    United States Inflation Rate

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 12, 2025
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    TRADING ECONOMICS (2025). United States Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/inflation-cpi
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Aug 12, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1914 - Jul 31, 2025
    Area covered
    United States
    Description

    Inflation Rate in the United States remained unchanged at 2.70 percent in July. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  2. Monthly U.S. Dollar Index (DXY) development 1973-2025

    • statista.com
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    Statista, Monthly U.S. Dollar Index (DXY) development 1973-2025 [Dataset]. https://www.statista.com/statistics/1404145/us-dollar-index-historical-chart/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The US dollar index of February 2025 was higher than it was in 2024, although below the peak in late 2022. This reveals itself in a historical graphic on the past 50 years, measuring the relative strength of the U.S. dollar. This metric is different from other FX graphics that compare the U.S. dollar against other currencies. By July 15, 2025, the DXY index was around 98.01 points. The history of the DXY Index The index shown here – often referred to with the code DXY, or USDX – measures the value of the U.S. dollar compared to a basket of six other foreign currencies. This basket includes the euro, the Swiss franc, the Japanese yen, the Canadian dollar, the British pound, and the Swedish króna. The index was created in 1973, after the arrival of the petrodollar and the dissolution of the Bretton Woods Agreement. Today, most of these currencies remain connected to the United States' largest trade partners. The relevance of the DXY Index The index focuses on trade and the strength of the U.S. dollar against specific currencies. It less on inflation or devaluation, which is measured in alternative metrics like the Big Mac Index. Indeed, as the methodology behind the DXY Index has only been updated once – when the euro arrived in 1999 – some argue this composition is not accurate to the current state of the world. The price development of the U.S. dollar affects many things, including commodity prices in general.

  3. N

    Great Scott Township, Minnesota annual median income by work experience and...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Great Scott Township, Minnesota annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/great-scott-township-mn-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Great Scott Township, Minnesota
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    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 Great Scott 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 Great Scott township, the median income for all workers aged 15 years and older, regardless of work hours, was $57,250 for males and $22,625 for females.

    These income figures highlight a substantial gender-based income gap in Great Scott township. Women, regardless of work hours, earn 40 cents for each dollar earned by men. This significant gender pay gap, approximately 60%, underscores concerning gender-based income inequality in the township of Great Scott township.

    - Full-time workers, aged 15 years and older: In Great Scott township, among full-time, year-round workers aged 15 years and older, males earned a median income of $90,750, while females earned $47,250, leading to a 48% gender pay gap among full-time workers. This illustrates that women earn 52 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 similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Great Scott 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 Great Scott township median household income by race. You can refer the same here

  4. T

    United States Core Inflation Rate

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 15, 2025
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    TRADING ECONOMICS (2025). United States Core Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/core-inflation-rate
    Explore at:
    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Jul 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Feb 28, 1957 - Jul 31, 2025
    Area covered
    United States
    Description

    Core consumer prices in the United States increased 3.10 percent in July of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  5. A

    Argentina Time Deposit Rate: USD: 60 Days or More

    • ceicdata.com
    Updated May 15, 2021
    + more versions
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    CEICdata.com (2021). Argentina Time Deposit Rate: USD: 60 Days or More [Dataset]. https://www.ceicdata.com/en/argentina/deposit-rate/time-deposit-rate-usd-60-days-or-more
    Explore at:
    Dataset updated
    May 15, 2021
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2024 - Feb 1, 2025
    Area covered
    Argentina
    Variables measured
    Deposit Rate
    Description

    Argentina Time Deposit Rate: USD: 60 Days or More data was reported at 1.560 % pa in Mar 2025. This records an increase from the previous number of 1.026 % pa for Feb 2025. Argentina Time Deposit Rate: USD: 60 Days or More data is updated monthly, averaging 1.540 % pa from Apr 1993 (Median) to Mar 2025, with 384 observations. The data reached an all-time high of 11.953 % pa in Nov 2001 and a record low of 0.415 % pa in Feb 2024. Argentina Time Deposit Rate: USD: 60 Days or More data remains active status in CEIC and is reported by Central Bank of Argentina. The data is categorized under Global Database’s Argentina – Table AR.M005: Deposit Rate.

  6. T

    Crude Oil - Price Data

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 6, 2025
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    TRADING ECONOMICS (2025). Crude Oil - Price Data [Dataset]. https://tradingeconomics.com/commodity/crude-oil
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Sep 6, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 30, 1983 - Sep 5, 2025
    Area covered
    World
    Description

    Crude Oil fell to 61.97 USD/Bbl on September 5, 2025, down 2.38% from the previous day. Over the past month, Crude Oil's price has fallen 3.70%, and is down 8.42% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Crude Oil - values, historical data, forecasts and news - updated on September of 2025.

  7. N

    Eldorado Township, Minnesota annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Eldorado Township, Minnesota annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/eldorado-township-mn-income-by-gender/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Eldorado Township, Minnesota
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    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 Eldorado 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 Eldorado township, the median income for all workers aged 15 years and older, regardless of work hours, was $26,667 for males and $29,000 for females.

    Contrary to expectations, women in Eldorado township, women, regardless of work hours, earn a higher income than men, earning 1.09 dollars for every dollar earned by men. This analysis indicates a significant shift in income dynamics favoring females.

    - Full-time workers, aged 15 years and older: In Eldorado township, among full-time, year-round workers aged 15 years and older, males earned a median income of $48,750, while females earned $29,375, leading to a 40% gender pay gap among full-time workers. This illustrates that women earn 60 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.

    Surprisingly, across all roles (including non-full-time employment), women had a higher median income compared to men in Eldorado township. This might indicate a more advantageous income scenario for female workers across different employment patterns within the township of Eldorado township, particularly in non-full-time positions.

    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 Eldorado township median household income by race. You can refer the same here

  8. T

    Argentina - Cost To Export, Documentary Compliance (US$)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 2, 2017
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    TRADING ECONOMICS (2017). Argentina - Cost To Export, Documentary Compliance (US$) [Dataset]. https://tradingeconomics.com/argentina/cost-to-export-documentary-compliance-us$-wb-data.html
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Jun 2, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Argentina
    Description

    Cost to export, documentary compliance (US$) in Argentina was reported at 60 USD in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. Argentina - Cost to export, documentary compliance (US$) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

  9. Average cost 30-second advertisement Super Bowl U.S. broadcast 2002-2025

    • statista.com
    Updated Jul 4, 2025
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    Statista (2025). Average cost 30-second advertisement Super Bowl U.S. broadcast 2002-2025 [Dataset]. https://www.statista.com/statistics/217134/total-advertisement-revenue-of-super-bowls/
    Explore at:
    Dataset updated
    Jul 4, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    How much does a Super Bowl ad cost in 2025? In 2025, advertisers are paying an average of eight million U.S. dollars to air a 30-second long commercial during the Super Bowl LVI broadcast. The Super Bowl is one of the biggest events on the sporting calendar, but it is so much more than just the football being played on the pitch. The spectacle surrounding the event, which culminates in the legendary half-time show, is hotly anticipated and watched by millions around the world. With so many captive viewers before, during, and after the game, advertisers use the Super Bowl as a means of raising awareness for their products. However, this awareness and visibility comes at a cost – since 2017 the average price of a 30-second TV advertisement during Super Bowl stood at a minimum of five million U.S. dollars and has risen even further in the last few years. Super Bowl ads The Super Bowl commercials have become a phenomenon in their own right, with social media buzzing with speculation about the innovative ways in which big corporations will sell their products. A 2020 survey revealed that 79 percent of viewers see the commercials as entertainment, while almost 71 percent stated that they enjoyed watching the commercials. It also seems the viewers will go to some lengths to see these commercials beyond their original air date during the big game – during the 2019 Super Bowl, consumers spent 641 thousand hours watching Super Bowl ads on YouTube, representing a 58 percent increase over the previous year. Large corporations spend big The allure of a Super Bowl commercial spot is hard to resist for big corporations. Some of the largest Super Bowl advertisers in 2021 included Pepsico and T-Mobile, while Anheuser-Busch sat top of the list, spending 52 million U.S. dollars on advertising during the big game. As a result of this big spending, Super Bowl advertising revenue reached a record 485 million U.S. dollars in 2021, more than twice the figure of 2011.

  10. N

    Bluffton, MN annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Bluffton, MN annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/bluffton-mn-income-by-gender/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Bluffton, Minnesota
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    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 Bluffton. 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 Bluffton, the median income for all workers aged 15 years and older, regardless of work hours, was $58,438 for males and $35,000 for females.

    These income figures highlight a substantial gender-based income gap in Bluffton. Women, regardless of work hours, earn 60 cents for each dollar earned by men. This significant gender pay gap, approximately 40%, underscores concerning gender-based income inequality in the city of Bluffton.

    - Full-time workers, aged 15 years and older: In Bluffton, among full-time, year-round workers aged 15 years and older, males earned a median income of $60,972, while females earned $40,625, leading to a 33% gender pay gap among full-time workers. This illustrates that women earn 67 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 similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Bluffton, 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 Bluffton median household income by race. You can refer the same here

  11. A

    Armenia Commercial Bank Lending Rate: NB: Residents: USD: 31 to 60 Days

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). Armenia Commercial Bank Lending Rate: NB: Residents: USD: 31 to 60 Days [Dataset]. https://www.ceicdata.com/en/armenia/commercial-bank-lending-rate/commercial-bank-lending-rate-nb-residents-usd-31-to-60-days
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Feb 1, 2024 - Jan 1, 2025
    Area covered
    Armenia
    Variables measured
    Lending Rate
    Description

    Armenia Commercial Bank Lending Rate: NB: Residents: USD: 31 to 60 Days data was reported at 8.060 % pa in Mar 2025. This records a decrease from the previous number of 9.586 % pa for Feb 2025. Armenia Commercial Bank Lending Rate: NB: Residents: USD: 31 to 60 Days data is updated monthly, averaging 10.750 % pa from Jan 2000 (Median) to Mar 2025, with 303 observations. The data reached an all-time high of 44.272 % pa in Jan 2000 and a record low of 3.730 % pa in Oct 2017. Armenia Commercial Bank Lending Rate: NB: Residents: USD: 31 to 60 Days data remains active status in CEIC and is reported by Central Bank of Armenia. The data is categorized under Global Database’s Armenia – Table AM.M003: Commercial Bank Lending Rate.

  12. N

    Wildwood, MO annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Cite
    Neilsberg Research (2025). Wildwood, MO annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/wildwood-mo-income-by-gender/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Wildwood, Missouri
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    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 Wildwood. 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 Wildwood, the median income for all workers aged 15 years and older, regardless of work hours, was $100,534 for males and $39,730 for females.

    These income figures highlight a substantial gender-based income gap in Wildwood. Women, regardless of work hours, earn 40 cents for each dollar earned by men. This significant gender pay gap, approximately 60%, underscores concerning gender-based income inequality in the city of Wildwood.

    - Full-time workers, aged 15 years and older: In Wildwood, among full-time, year-round workers aged 15 years and older, males earned a median income of $140,088, while females earned $84,182, leading to a 40% gender pay gap among full-time workers. This illustrates that women earn 60 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 similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Wildwood, 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 Wildwood median household income by race. You can refer the same here

  13. N

    Manchester, IL annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Cite
    Neilsberg Research (2025). Manchester, IL annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/manchester-il-income-by-gender/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Illinois, Manchester
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    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 Manchester. 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 Manchester, the median income for all workers aged 15 years and older, regardless of work hours, was $48,000 for males and $28,750 for females.

    These income figures highlight a substantial gender-based income gap in Manchester. Women, regardless of work hours, earn 60 cents for each dollar earned by men. This significant gender pay gap, approximately 40%, underscores concerning gender-based income inequality in the village of Manchester.

    - Full-time workers, aged 15 years and older: In Manchester, among full-time, year-round workers aged 15 years and older, males earned a median income of $48,000, while females earned $28,750, leading to a 40% gender pay gap among full-time workers. This illustrates that women earn 60 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 similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Manchester, 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 Manchester median household income by race. You can refer the same here

  14. N

    Hettinger County, ND annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Cite
    Neilsberg Research (2025). Hettinger County, ND annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a51c54ca-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    North Dakota, Hettinger County
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    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 Hettinger County. 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 Hettinger County, the median income for all workers aged 15 years and older, regardless of work hours, was $58,194 for males and $23,317 for females.

    These income figures highlight a substantial gender-based income gap in Hettinger County. Women, regardless of work hours, earn 40 cents for each dollar earned by men. This significant gender pay gap, approximately 60%, underscores concerning gender-based income inequality in the county of Hettinger County.

    - Full-time workers, aged 15 years and older: In Hettinger County, among full-time, year-round workers aged 15 years and older, males earned a median income of $72,240, while females earned $43,047, leading to a 40% gender pay gap among full-time workers. This illustrates that women earn 60 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 similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Hettinger County, 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 Hettinger County median household income by race. You can refer the same here

  15. N

    Grantsburg Town, Wisconsin annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Cite
    Neilsberg Research (2025). Grantsburg Town, Wisconsin annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/grantsburg-town-wi-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Grantsburg, Wisconsin, Grantsburg
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    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 Grantsburg town. 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 Grantsburg town, the median income for all workers aged 15 years and older, regardless of work hours, was $53,500 for males and $30,536 for females.

    These income figures highlight a substantial gender-based income gap in Grantsburg town. Women, regardless of work hours, earn 57 cents for each dollar earned by men. This significant gender pay gap, approximately 43%, underscores concerning gender-based income inequality in the town of Grantsburg town.

    - Full-time workers, aged 15 years and older: In Grantsburg town, among full-time, year-round workers aged 15 years and older, males earned a median income of $75,000, while females earned $44,792, leading to a 40% gender pay gap among full-time workers. This illustrates that women earn 60 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 similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Grantsburg town, 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 Grantsburg town median household income by race. You can refer the same here

  16. N

    Carlos Township, Minnesota annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Close
    Cite
    Neilsberg Research (2025). Carlos Township, Minnesota annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/carlos-township-mn-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Carlos Township, Minnesota
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    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 Carlos 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 Carlos township, the median income for all workers aged 15 years and older, regardless of work hours, was $70,880 for males and $42,243 for females.

    These income figures highlight a substantial gender-based income gap in Carlos township. Women, regardless of work hours, earn 60 cents for each dollar earned by men. This significant gender pay gap, approximately 40%, underscores concerning gender-based income inequality in the township of Carlos township.

    - Full-time workers, aged 15 years and older: In Carlos township, among full-time, year-round workers aged 15 years and older, males earned a median income of $91,389, while females earned $54,654, leading to a 40% gender pay gap among full-time workers. This illustrates that women earn 60 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 similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Carlos 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 Carlos township median household income by race. You can refer the same here

  17. N

    Brevator Township, Minnesota annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Click to copy link
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    Close
    Cite
    Neilsberg Research (2025). Brevator Township, Minnesota annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a505698a-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Brevator Township, Minnesota
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    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 Brevator 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 Brevator township, the median income for all workers aged 15 years and older, regardless of work hours, was $53,846 for males and $32,440 for females.

    These income figures highlight a substantial gender-based income gap in Brevator township. Women, regardless of work hours, earn 60 cents for each dollar earned by men. This significant gender pay gap, approximately 40%, underscores concerning gender-based income inequality in the township of Brevator township.

    - Full-time workers, aged 15 years and older: In Brevator township, among full-time, year-round workers aged 15 years and older, males earned a median income of $72,625, while females earned $55,781, leading to a 23% gender pay gap among full-time workers. This illustrates that women earn 77 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 Brevator township.

    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 Brevator township median household income by race. You can refer the same here

  18. A

    Argentina Time Deposit Rate: USD: Other Financial Entities: 60 Days or More

    • ceicdata.com
    + more versions
    Share
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    CEICdata.com, Argentina Time Deposit Rate: USD: Other Financial Entities: 60 Days or More [Dataset]. https://www.ceicdata.com/en/argentina/deposit-rate/time-deposit-rate-usd-other-financial-entities-60-days-or-more
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2024 - Feb 1, 2025
    Area covered
    Argentina
    Variables measured
    Deposit Rate
    Description

    Argentina Time Deposit Rate: USD: Other Financial Entities: 60 Days or More data was reported at 0.551 % pa in Mar 2025. This records an increase from the previous number of 0.425 % pa for Feb 2025. Argentina Time Deposit Rate: USD: Other Financial Entities: 60 Days or More data is updated monthly, averaging 2.337 % pa from Jan 2000 (Median) to Mar 2025, with 303 observations. The data reached an all-time high of 12.478 % pa in Nov 2001 and a record low of 0.000 % pa in May 2004. Argentina Time Deposit Rate: USD: Other Financial Entities: 60 Days or More data remains active status in CEIC and is reported by Central Bank of Argentina. The data is categorized under Global Database’s Argentina – Table AR.M005: Deposit Rate.

  19. Ruble USD/RUB FX rate, up to Aug 27, 2025

    • statista.com
    Updated Aug 28, 2025
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    Statista (2025). Ruble USD/RUB FX rate, up to Aug 27, 2025 [Dataset]. https://www.statista.com/statistics/376232/usd-rub-exchange-rate-monthly/
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    Dataset updated
    Aug 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Dec 22, 2017 - Aug 27, 2025
    Area covered
    Worldwide
    Description

    The USD to ruble value lost significant ground after Russia's invasion of Ukraine, reaching a low of 135 rubles in March 2022. This devaluation is also observed in a chart that compares the monthly average of the ruble against both the U.S. dollar and the euro since 2008. A decline started in November 2020 and continued into 2021; no specific reason was given for the timing of this development. Interestingly, the USD/RUB exchange rate reached its highest point earlier in 2020, as one U.S. dollar could buy nearly 80 rubles in March 2020. Values were noticeably different years later, however, as the USD/RUB exchange rate was valued at 80.49 on August 27, 2025.

  20. Monthly inflation rate and Federal Reserve interest rate in the U.S....

    • statista.com
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    Statista, Monthly inflation rate and Federal Reserve interest rate in the U.S. 2018-2025 [Dataset]. https://www.statista.com/statistics/1312060/us-inflation-rate-federal-reserve-interest-rate-monthly/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2018 - Jul 2025
    Area covered
    United States
    Description

    The inflation rate in the United States declined significantly between June 2022 and July 2025, despite rising inflationary pressures towards the end of 2024. The peak inflation rate was recorded in June 2022, at *** percent. In August 2023, the Federal Reserve's interest rate hit its highest level during the observed period, at **** percent, and remained unchanged until September 2024, when the Federal Reserve implemented its first rate cut since September 2021. By January 2025, the rate dropped to **** percent, signalling a shift in monetary policy. What is the Federal Reserve interest rate? The Federal Reserve interest rate, or the federal funds rate, is the rate at which banks and credit unions lend to and borrow from each other. It is one of the Federal Reserve's key tools for maintaining strong employment rates, stable prices, and reasonable interest rates. The rate is determined by the Federal Reserve and adjusted eight times a year, though it can be changed through emergency meetings during times of crisis. The Fed doesn't directly control the interest rate but sets a target rate. It then uses open market operations to influence rates toward this target. Ways of measuring inflation Inflation is typically measured using several methods, with the most common being the Consumer Price Index (CPI). The CPI tracks the price of a fixed basket of goods and services over time, providing a measure of the price changes consumers face. At the end of 2023, the CPI in the United States was ****** percent, up from ****** a year earlier. A more business-focused measure is the producer price index (PPI), which represents the costs of firms.

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TRADING ECONOMICS (2025). United States Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/inflation-cpi

United States Inflation Rate

United States Inflation Rate - Historical Dataset (1914-12-31/2025-07-31)

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131 scholarly articles cite this dataset (View in Google Scholar)
json, excel, xml, csvAvailable download formats
Dataset updated
Aug 12, 2025
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Dec 31, 1914 - Jul 31, 2025
Area covered
United States
Description

Inflation Rate in the United States remained unchanged at 2.70 percent in July. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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