9 datasets found
  1. T

    United States Employment Rate

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +16more
    csv, excel, json, xml
    Updated Feb 17, 2024
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    TRADING ECONOMICS (2024). United States Employment Rate [Dataset]. https://tradingeconomics.com/united-states/employment-rate
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    Feb 17, 2024
    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 31, 1948 - Feb 28, 2025
    Area covered
    United States
    Description

    Employment Rate in the United States decreased to 59.90 percent in February from 60.10 percent in January of 2025. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  2. Job Openings and Posting Data in Latin America/Latam( Techsalerator)

    • datarade.ai
    Updated Sep 5, 2024
    + more versions
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    Techsalerator (2024). Job Openings and Posting Data in Latin America/Latam( Techsalerator) [Dataset]. https://datarade.ai/data-products/job-openings-and-posting-data-in-latin-america-latam-techsal-techsalerator
    Explore at:
    .json, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Sep 5, 2024
    Dataset provided by
    Techsalerator LLC
    Authors
    Techsalerator
    Area covered
    Americas, Latin America, French Guiana, Guadeloupe, Saint Vincent and the Grenadines, Haiti, Suriname, Montserrat, Trinidad and Tobago, Venezuela (Bolivarian Republic of), Bonaire, Virgin Islands (British)
    Description

    Techsalerator’s Job Openings Data in Latin America provides a thorough and insightful dataset designed to deliver businesses, recruiters, labor market analysts, and job seekers with a comprehensive view of employment opportunities across the Latin American region. This dataset aggregates job postings from a diverse array of sources on a daily basis, ensuring that users have access to the most current and extensive collection of job openings available throughout Latin America.

    Key Features of the Dataset: Extensive Coverage:

    The dataset aggregates job postings from a variety of sources, including company career sites, job boards, recruitment agencies, and professional networking platforms. This comprehensive coverage ensures that users receive a broad spectrum of job opportunities from multiple channels. Daily Updates:

    Data is updated daily, providing real-time insights into job market conditions. This frequent updating ensures that the dataset reflects the latest job openings and market trends. Sector-Specific Data:

    Job postings are categorized by industry sectors such as technology, healthcare, finance, education, manufacturing, and more. This segmentation allows users to analyze trends and opportunities within specific industries. Regional Breakdown:

    Detailed information is provided on job openings across different countries and key regions within Latin America. This regional breakdown helps users understand job market dynamics and opportunities in various geographic areas. Role and Skill Analysis:

    The dataset includes information on job roles, required skills, qualifications, and experience levels. This feature assists job seekers in identifying opportunities that match their expertise and helps recruiters find candidates with the desired skill sets. Company Insights:

    Users can access information about the companies posting job openings, including company names, industries, and locations. This data provides insights into which companies are hiring and where demand for talent is highest. Historical Data:

    The dataset may include historical job posting data, enabling users to perform trend analysis and comparative studies over time. This feature supports understanding changes and developments in the job market. Latin American Countries Covered: South America: Argentina Bolivia Brazil Chile Colombia Ecuador Guyana Paraguay Peru Suriname Uruguay Venezuela Central America: Belize Costa Rica El Salvador Guatemala Honduras Nicaragua Panama Caribbean: Cuba Dominican Republic Haiti (Note: Primarily French-speaking, but included due to geographic and cultural ties) Jamaica Trinidad and Tobago Benefits of the Dataset: Strategic Recruitment: Recruiters and HR professionals can use the data to identify hiring trends, understand competitive practices, and optimize their recruitment strategies based on real-time market insights. Labor Market Analysis: Analysts and policymakers can leverage the dataset to study employment trends, identify skill gaps, and evaluate job market opportunities across different regions and sectors. Job Seeker Support: Job seekers can access a comprehensive and updated list of job openings tailored to their skills and preferred locations, enhancing the efficiency and effectiveness of their job search. Workforce Planning: Companies can gain valuable insights into the availability of talent across Latin America, assisting with decisions related to market entry, expansion, and talent acquisition. Techsalerator’s Job Openings Data in Latin America is an essential tool for understanding the diverse and evolving job markets across the region. By providing up-to-date and detailed information on job postings, it supports effective decision-making for businesses, job seekers, and labor market analysts.

  3. d

    Pittsburgh American Community Survey Census Data 2014 - Sex by Occupation

    • catalog.data.gov
    • data.wprdc.org
    • +3more
    Updated Jan 24, 2023
    + more versions
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    City of Pittsburgh (2023). Pittsburgh American Community Survey Census Data 2014 - Sex by Occupation [Dataset]. https://catalog.data.gov/dataset/pittsburgh-american-community-survey-census-data-2014-sex-by-occupation
    Explore at:
    Dataset updated
    Jan 24, 2023
    Dataset provided by
    City of Pittsburgh
    Area covered
    Pittsburgh
    Description

    Occupation describes the kind of work a person does on the job. Occupation data were derived from answers to questions 45 and 46 in the 2015 American Community Survey (ACS). Question 45 asks: “What kind of work was this person doing?” Question 46 asks: “What were this person’s most important activities or duties?” These questions were asked of all people 15 years old and over who had worked in the past 5 years. For employed people, the data refer to the person’s job during the previous week. For those who worked two or more jobs, the data refer to the job where the person worked the greatest number of hours. For unemployed people and people who are not currently employed but report having a job within the last five years, the data refer to their last job. These questions describe the work activity and occupational experience of the American labor force. Data are used to formulate policy and programs for employment, career development, and training; to provide information on the occupational skills of the labor force in a given area to analyze career trends; and to measure compliance with antidiscrimination policies. Companies use these data to decide where to locate new plants, stores, or offices.

  4. T

    Peru Employment Rate

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +16more
    csv, excel, json, xml
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    Peru Employment Rate [Dataset]. https://tradingeconomics.com/peru/employment-rate
    Explore at:
    xml, excel, csv, jsonAvailable download formats
    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
    May 31, 2001 - Feb 28, 2025
    Area covered
    Peru
    Description

    Employment Rate in Peru decreased to 93.70 percent in February from 93.80 percent in January of 2025. This dataset provides - Peru Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  5. Quarterly Census of Employment and Wages (QCEW)

    • catalog.data.gov
    • data.ca.gov
    Updated Nov 27, 2024
    + more versions
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    California Employment Development Department (2024). Quarterly Census of Employment and Wages (QCEW) [Dataset]. https://catalog.data.gov/dataset/quarterly-census-of-employment-and-wages-qcew-a6fea
    Explore at:
    Dataset updated
    Nov 27, 2024
    Dataset provided by
    Employment Development Departmenthttp://www.edd.ca.gov/
    Description

    The Quarterly Census of Employment and Wages (QCEW) Program is a Federal-State cooperative program between the U.S. Department of Labor’s Bureau of Labor Statistics (BLS) and the California EDD’s Labor Market Information Division (LMID). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by California Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit industry codes from the North American Industry Classification System (NAICS) at the national, state, and county levels. At the national level, the QCEW program publishes employment and wage data for nearly every NAICS industry. At the state and local area level, the QCEW program publishes employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. In accordance with the BLS policy, data provided to the Bureau in confidence are used only for specified statistical purposes and are not published. The BLS withholds publication of Unemployment Insurance law-covered employment and wage data for any industry level when necessary to protect the identity of cooperating employers. Data from the QCEW program serve as an important input to many BLS programs. The Current Employment Statistics and the Occupational Employment Statistics programs use the QCEW data as the benchmark source for employment. The UI administrative records collected under the QCEW program serve as a sampling frame for the BLS establishment surveys. In addition, the data serve as an input to other federal and state programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses the QCEW data as the base for developing the wage and salary component of personal income. The U.S. Department of Labor’s Employment and Training Administration (ETA) and California's EDD use the QCEW data to administer the Unemployment Insurance program. The QCEW data accurately reflect the extent of coverage of California’s UI laws and are used to measure UI revenues; national, state and local area employment; and total and UI taxable wage trends. The U.S. Department of Labor’s Bureau of Labor Statistics publishes new QCEW data in its County Employment and Wages news release on a quarterly basis. The BLS also publishes a subset of its quarterly data through the Create Customized Tables system, and full quarterly industry detail data at all geographic levels.

  6. N

    American Canyon, CA annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). American Canyon, CA annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/american-canyon-ca-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
    California, American Canyon, United States
    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, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. 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 the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within American Canyon. The dataset can be utilized to gain insights into gender-based income distribution within the American Canyon population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within American Canyon, among individuals aged 15 years and older with income, there were 7,373 men and 7,343 women in the workforce. Among them, 4,141 men were engaged in full-time, year-round employment, while 3,295 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 7.20% fell within the income range of under $24,999, while 11.08% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 30.04% of men in full-time roles earned incomes exceeding $100,000, while 29.20% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    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.

    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 American Canyon median household income by race. You can refer the same here

  7. N

    American Fork, UT annual median income by work experience and sex dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
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    Neilsberg Research (2025). American Fork, UT 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/american-fork-ut-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
    American Fork, Utah
    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 American Fork. 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 American Fork, the median income for all workers aged 15 years and older, regardless of work hours, was $54,439 for males and $27,701 for females.

    These income figures highlight a substantial gender-based income gap in American Fork. Women, regardless of work hours, earn 51 cents for each dollar earned by men. This significant gender pay gap, approximately 49%, underscores concerning gender-based income inequality in the city of American Fork.

    - Full-time workers, aged 15 years and older: In American Fork, among full-time, year-round workers aged 15 years and older, males earned a median income of $71,091, while females earned $50,384, leading to a 29% gender pay gap among full-time workers. This illustrates that women earn 71 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 American Fork.

    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 American Fork median household income by race. You can refer the same here

  8. N

    American Fork, UT annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    Share
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    Click to copy link
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    Cite
    Neilsberg Research (2025). American Fork, UT annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/american-fork-ut-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
    American Fork, Utah
    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, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. 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 the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within American Fork. The dataset can be utilized to gain insights into gender-based income distribution within the American Fork population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within American Fork, among individuals aged 15 years and older with income, there were 12,169 men and 10,456 women in the workforce. Among them, 7,760 men were engaged in full-time, year-round employment, while 3,803 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 6.07% fell within the income range of under $24,999, while 7.18% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 34.82% of men in full-time roles earned incomes exceeding $100,000, while 11.89% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    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.

    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 American Fork median household income by race. You can refer the same here

  9. N

    American Falls, ID annual median income by work experience and sex dataset :...

    • neilsberg.com
    csv, json
    Updated Jan 9, 2024
    + more versions
    Share
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    Cite
    Neilsberg Research (2024). American Falls, ID annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars) [Dataset]. https://www.neilsberg.com/research/datasets/94075644-9816-11ee-99cf-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jan 9, 2024
    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
    American Falls
    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) 2010-2022 5-Year Estimates. To portray the income for both the genders (Male and Female), we conducted an initial analysis and categorization of the data. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). 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 American Falls. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2021

    Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In American Falls, the median income for all workers aged 15 years and older, regardless of work hours, was $46,155 for males and $23,058 for females.

    These income figures highlight a substantial gender-based income gap in American Falls. Women, regardless of work hours, earn 50 cents for each dollar earned by men. This significant gender pay gap, approximately 50%, underscores concerning gender-based income inequality in the city of American Falls.

    - Full-time workers, aged 15 years and older: In American Falls, among full-time, year-round workers aged 15 years and older, males earned a median income of $48,075, while females earned $31,436, leading to a 35% gender pay gap among full-time workers. This illustrates that women earn 65 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 American Falls, showcasing a consistent income pattern irrespective of employment status.

    https://i.neilsberg.com/ch/american-falls-id-income-by-gender.jpeg" alt="American Falls, ID gender based income disparity">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

    Gender classifications include:

    • 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 2022
    • 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 American Falls median household income by gender. You can refer the same here

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TRADING ECONOMICS (2024). United States Employment Rate [Dataset]. https://tradingeconomics.com/united-states/employment-rate

United States Employment Rate

United States Employment Rate - Historical Dataset (1948-01-31/2025-02-28)

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60 scholarly articles cite this dataset (View in Google Scholar)
excel, xml, json, csvAvailable download formats
Dataset updated
Feb 17, 2024
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 31, 1948 - Feb 28, 2025
Area covered
United States
Description

Employment Rate in the United States decreased to 59.90 percent in February from 60.10 percent in January of 2025. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

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