United States - Unemployment Level - Women, Veterans, Other Service Periods, 18 Years and over was 6.00000 Thous. of Persons in June of 2025, according to the United States Federal Reserve. Historically, United States - Unemployment Level - Women, Veterans, Other Service Periods, 18 Years and over reached a record high of 49.00000 in March of 2011 and a record low of 0.00000 in October of 2017. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Unemployment Level - Women, Veterans, Other Service Periods, 18 Years and over - last updated from the United States Federal Reserve on July of 2025.

United States CES: FL: IBT: Unemployment & Workers, Veteran Benefits data was reported at 0.000 USD in 2017. This records a decrease from the previous number of 707.000 USD for 2012. United States CES: FL: IBT: Unemployment & Workers, Veteran Benefits data is updated yearly, averaging 351.500 USD from Dec 1984 (Median) to 2017, with 30 observations. The data reached an all-time high of 1,242.000 USD in 2011 and a record low of 0.000 USD in 2017. United States CES: FL: IBT: Unemployment & Workers, Veteran Benefits data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.H045: Consumer Expenditure Survey: By Occupation.

United States CES: Ret: IBT: Unemployment & Workers, Veteran Benefits data was reported at 0.000 USD in 2017. This records a decrease from the previous number of 462.000 USD for 2012. United States CES: Ret: IBT: Unemployment & Workers, Veteran Benefits data is updated yearly, averaging 355.500 USD from Dec 1984 (Median) to 2017, with 30 observations. The data reached an all-time high of 903.000 USD in 2010 and a record low of 0.000 USD in 2017. United States CES: Ret: IBT: Unemployment & Workers, Veteran Benefits data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.H045: Consumer Expenditure Survey: By Occupation.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2017 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Employment and unemployment estimates may vary from the official labor force data released by the Bureau of Labor Statistics because of differences in survey design and data collection. For guidance on differences in employment and unemployment estimates from different sources go to Labor Force Guidance..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2017 American Community Survey 1-Year Estimates

Ukraine Unemployment: Demobilized After Term Military Service data was reported at 0.700 % in 2017. This stayed constant from the previous number of 0.700 % for 2016. Ukraine Unemployment: Demobilized After Term Military Service data is updated yearly, averaging 1.200 % from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 2.300 % in 2001 and a record low of 0.300 % in 2015. Ukraine Unemployment: Demobilized After Term Military Service data remains active status in CEIC and is reported by State Statistics Service of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.G012: Unemployment.

Data on military service status by industry subsectors - North American Industry Classification System (NAICS) 2017, occupation - National Occupational Classification (NOC) 2021, work activity during the reference year, age and gender for the population aged 17 and over who worked since 2020, in private households, Canada, provinces and territories.

The Annual Social and Economic (ASEC) 2017 Supplement is part of the Current Population Survey (CPS) Series. The CPS is a source of the official Government statistics on employment and unemployment. The Census Bureau conducts the ASEC (known as the Annual Demographic File prior to 2003) over a three-month period, in February, March, and April, with most of the data collected in the month of March. The ASEC uses two sets of survey questions, the basic CPS and a set of supplemental questions. The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage, and salaried employees, and estimates of total unemployment. In addition to the basic CPS questions, respondents were asked questions from the ASEC, which provides supplemental data on poverty, geographic mobility/migration, and work experience. Comprehensive work experience information was given on the employment status, occupation, and industry of persons aged 15 and over. Additional data for persons aged 15 and older were available concerning weeks worked and hours per week worked, reason not working full-time, total income and supplemental income components. Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income. Data on employment and income refer to the previous calendar year, although demographic data refer to the time of the survey. The occupation and industry information variables in this data collection can help the data users identify individuals who worked in arts and culture related fields. The occupations are listed in a category entitled "Arts, Design, Entertainment, Sports, and Media Occupations," which includes professions such as artists, designers, actors, musicians, and writers (see Appendix B of the User Guide for further category details). Industries related to the arts and culture are in the "Arts, Entertainment, and Recreation" category (see Appendix C of the User Guide for further category details). For example, using the occupation and industry information variables from the ASEC help data users to obtain statistics about people in artists occupations that receive supplemental income, live public housing, or are full-time students. The ASEC data provided by the Census Bureau are distributed in a hierarchical file structure, with three record types present: Household, Family, and Person. The ASEC is designed to be a multistage stratified sample of housing units, where the hierarchical file structure can be thought of as a person within a family within a household unit. Here the main unit of analysis is the household unit.

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 Veteran 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 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Veteran town, the median income for all workers aged 15 years and older, regardless of work hours, was $42,214 for males and $27,276 for females.

These income figures highlight a substantial gender-based income gap in Veteran town. Women, regardless of work hours, earn 65 cents for each dollar earned by men. This significant gender pay gap, approximately 35%, underscores concerning gender-based income inequality in the town of Veteran town.

- Full-time workers, aged 15 years and older: In Veteran town, among full-time, year-round workers aged 15 years and older, males earned a median income of $54,909, while females earned $51,150, resulting in a 7% gender pay gap among full-time workers. This illustrates that women earn 93 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the town of Veteran town.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Veteran town.

https://i.neilsberg.com/ch/veteran-ny-income-by-gender.jpeg" alt="Veteran, New York 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 Veteran town median household income by gender. You can refer the same here

Serbia Employment: Military Officers data was reported at 16,400.000 Person in Sep 2018. This records an increase from the previous number of 15,000.000 Person for Jun 2018. Serbia Employment: Military Officers data is updated quarterly, averaging 17,400.000 Person from Mar 2014 (Median) to Sep 2018, with 19 observations. The data reached an all-time high of 21,100.000 Person in Dec 2015 and a record low of 14,000.000 Person in Dec 2017. Serbia Employment: Military Officers data remains active status in CEIC and is reported by Statistical Office of the Republic of Serbia. The data is categorized under Global Database’s Serbia – Table RS.G011: Labour Force Survey: Employment: Quarterly.

Brazil Heavy Military Equipment, Firearms & Ammunition: Employment data was reported at 6,887.000 Person in 2017. This records an increase from the previous number of 6,692.000 Person for 2016. Brazil Heavy Military Equipment, Firearms & Ammunition: Employment data is updated yearly, averaging 7,822.000 Person from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 8,625.000 Person in 2011 and a record low of 6,677.000 Person in 2014. Brazil Heavy Military Equipment, Firearms & Ammunition: Employment data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Metal and Steel Sector – Table BR.WAM009: Metal Financial Data: Heavy Military Equipment, Firearms & Ammunition.

The Vocational School Student Survey (VET Student Survey) 2017 is a total study charting experiences of young people studying in Finnish vocational education institutions. The survey was conducted by the Research Foundation for Studies and Education (Otus) in collaboration with the National Union of Vocational Students in Finland (SAKKI), which also funded the study with funding received from the Ministry of Education and Culture and the Ministry of Economic Affairs and Employment. Main themes of the survey included applying for studies, experiences relating to studies and teaching, financial circumstances, plans for the future and working life, and wellbeing and leisure time. Relating to studies at the time of the survey, the respondents were asked, among other things, their field of education, year of study, and distance to the vocational institution. They were also asked whether they had moved to another municipality due to their current studies. Earlier studies and applying for vocational studies were examined with questions regarding, for instance, whether vocational studies had been discussed or recommended in their families or at school, whether their friends or siblings had studied in a vocational institution, and how clear the decision to opt for vocational studies had been. They were also asked whether they had worked or completed other studies before starting vocational studies, and how they had performed in earlier education. Experiences of studies and teaching were examined with questions about the time spent on studies in a week, form and sufficiency of the teaching and guidance received, balancing and managing studies, and money spent on study materials. Possible learning difficulties and support received for these difficulties were also surveyed. With regard to study progress, satisfaction with studies and the institution itself was charted as well as feelings of studying the right field, prospects of graduating, things slowing down study progress, and views on the importance of vocational studies. Working, housing and financial circumstances were investigated by asking about working during studies and in the summer, housing during semesters, financial help from parents and relatives, and sufficiency of money for expenses. Concerning occupational life, opinions were probed on a number of statements about employment, employment prospects after graduation, and the importance of various things for a successful career. Future plans to study were also surveyed. Finally, wellbeing and leisure time were examined with questions concerning e.g. friends, social relationships, bullying and discrimination, sleep, alcohol use, hobbies and Internet use. Background variables included the respondent's year of birth (categorised), gender, and mother tongue. The time the respondent had lived in Finland was further charted, along with languages spoken with parents, and parents' employment status and education level.

Key Table Information.Table Title.Annual Business Survey: Employment Size of Firm Statistics for Employer Firms by Sector, Sex, Ethnicity, Race, and Veteran Status for the U.S., States, Metro Areas, and Counties: 2022.Table ID.ABSCS2022.AB2200CSA04.Survey/Program.Economic Surveys.Year.2022.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2024-12-19.Release Schedule.The Annual Business Survey (ABS) occurs every year, beginning in reference year 2017.For more information about ABS planned data product releases, see Tentative ABS Schedule..Dataset Universe.The dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Methodology.Data Items and Other Identifying Records.Number of employer firms (firms with paid employees)Sales and receipts of employer firms (reported in $1,000s of dollars)Number of employees (during the March 12 pay period)Annual payroll (reported in $1,000s of dollars)These data are aggregated by sex, ethnicity, race, and veteran status when classifiable.The data are also shown for the employment size of firms (during the March 12 pay period):Employment Size: Firms with no employees Firms with 1 to 4 employees Firms with 5 to 9 employees Firms with 10 to 19 employees Firms with 20 to 49 employees Firms with 50 to 99 employees Firms with 100 to 249 employees Firms with 250 to 499 employees Firms with less than 500 employees Firms with 500 employees or more Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the ABS are employer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The 2022 reference year data are shown for the total for all sectors (00) and the 2-digit NAICS code levels for:United StatesStates and the District of ColumbiaIn addition, data are shown for the total for all sectors (00) for:Metropolitan Statistical AreasCountiesFor information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00"), and at the 2-digit NAICS code level depending on geography. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Office of Notaries (NAICS 541120)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.The ABS sample includes firms that are selected with certainty if they have known research and development activities, were included in the 2022 BERD sample, or have high receipts, payroll, or employment. Total sample size is 850,000 firms. The universe is stratified by state, industry group, and expected demographic group. Firms selected to the sample receive a questionnaire. For all data on this table, firms not selected into the sample are represented with administrative, 2022 Economic Census, or other economic surveys records.For more information about the sample design, see Annual Business Survey Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0351).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business' data or identity.To comply with data quality standards, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the Annual Business Survey Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data a...