About this dataset

Context

The dataset tabulates the population of Industry by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Industry. The dataset can be utilized to understand the population distribution of Industry by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Industry. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Industry.

Key observations

Largest age group (population): Male # 10-14 years (52) | Female # 10-14 years (36). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Industry population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Industry is shown in the following column.
• Population (Female): The female population in the Industry is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Industry for each age group.

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 Industry Population by Gender. You can refer the same here

Of the major industries around the world, only four had a share of 50 percent or more of female workers. The healthcare industry had the highest share with nearly two thirds. On the other hand, just above 20 percent of workers within oil, gas, and mining as well as infrastructure were women as of 2022.

About this dataset

Context

The dataset tabulates the population of Industry by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Industry across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 50.24% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Industry is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Industry total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Industry Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Industry by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Industry. The dataset can be utilized to understand the population distribution of Industry by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Industry. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Industry.

Key observations

Largest age group (population): Male # 30-34 years (94) | Female # 70-74 years (81). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Industry population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Industry is shown in the following column.
• Population (Female): The female population in the Industry is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Industry for each age group.

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 Industry Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Industry by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Industry. The dataset can be utilized to understand the population distribution of Industry by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Industry. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Industry.

Key observations

Largest age group (population): Male # 25-29 years (28) | Female # 55-59 years (17). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Industry population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Industry is shown in the following column.
• Population (Female): The female population in the Industry is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Industry for each age group.

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 Industry Population by Gender. You can refer the same here

According to a global software developer survey in 2022, the vast majority of developers are males, accounting for 91.88 percent of all respondents. Female developers amounted to only five percent of all respondents, demonstrating the male-dominating reality of software development jobs.

Gender imbalance in the tech industry
The tech industry has an overwhelming gender imbalance, in which women at leading tech companies tend to be the minority. Consider Dell’s workforce and Intel’s workforce as an example. In both leading tech companies, women make up only around 30 percent of the workforce. Computing related positions in the United States vary on gender breakdown, with computer hardware engineers ranking the lowest in terms of gender diversity as of late.

Diversity & inclusion initiatives
When tech industry CEOs and founders were asked whether diversity and inclusion (D&I) initiatives were effective, half indicated that they were not effective. This comes at an interesting time, especially given the overall gender imbalance in the tech industry. Not to mention, the majority of senior management positions within the IT industry are dominated by men. Diversity and inclusion initiatives could help to resolve workplace harassment and unequal treatment that many female executives experience within the tech industry today.

In Sweden, men dominated the field of engineering and manufacturing, with 1.3 million individuals compared to 218,000 women. The highest number of women, 940,000, was found within the field of general education, compared to 812,000 men. Women dominated the field of health care, nursing, and social care, with roughly 815,000 educated individuals. By comparison, 185,000 men were educated in this sector.

Data Series: Percentage distribution of employed population in service sector, by sex Indicator: I.8 - Percentage distribution of employed population by sector, each sex (Sectors here refer to Agriculture; Industry; Services) Source year: 2022 This dataset is part of the Minimum Gender Dataset compiled by the United Nations Statistics Division. Domain: Economic structures, participation in productive activities and access to resources

Economically Active Population Survey: Active population by nationality, sex and economic sector. Quarterly. National.

The 2018 edition of Woods and Poole Complete U.S. Database provides annual historical data from 1970 (some variables begin in 1990) and annual projections to 2050 of population by race, sex, and age, employment by industry, earnings of employees by industry, personal income by source, households by income bracket and retail sales by kind of business. The Complete U.S. Database contains annual data for all economic and demographic variables for all geographic areas in the Woods & Poole database (the U.S. total, and all regions, states, counties, and CBSAs). The Complete U.S. Database has following components: Demographic & Economic Desktop Data Files: There are 122 files covering demographic and economic data. The first 31 files (WP001.csv – WP031.csv) cover demographic data. The remaining files (WP032.csv – WP122.csv) cover economic data. Demographic DDFs: Provide population data for the U.S., regions, states, Combined Statistical Areas (CSAs), Metropolitan Statistical Areas (MSAs), Micropolitan Statistical Areas (MICROs), Metropolitan Divisions (MDIVs), and counties. Each variable is in a separate .csv file. Variables: Total Population Population Age (breakdown: 0-4, 5-9, 10-15 etc. all the way to 85 & over) Median Age of Population White Population Population Native American Population Asian & Pacific Islander Population Hispanic Population, any Race Total Population Age (breakdown: 0-17, 15-17, 18-24, 65 & over) Male Population Female Population Economic DDFs: The other files (WP032.csv – WP122.csv) provide employment and income data on: Total Employment (by industry) Total Earnings of Employees (by industry) Total Personal Income (by source) Household income (by brackets) Total Retail & Food Services Sales ( by industry) Net Earnings Gross Regional Product Retail Sales per Household Economic & Demographic Flat File: A single file for total number of people by single year of age (from 0 to 85 and over), race, and gender. It covers all U.S., regions, states, CSAs, MSAs and counties. Years of coverage: 1990 - 2050 Single Year of Age by Race and Gender: Separate files for number of people by single year of age (from 0 years to 85 years and over), race (White, Black, Native American, Asian American & Pacific Islander and Hispanic) and gender. Years of coverage: 1990 through 2050. DATA AVAILABLE FOR 1970-2019; FORECASTS THROUGH 2050

Data Series: Percentage distribution of employed population in agricultural sector, by sex Indicator: I.6 - Percentage distribution of employed population by sector, each sex (Sectors here refer to Agriculture; Industry; Services) Source year: 2024 This dataset is part of the Minimum Gender Dataset compiled by the United Nations Statistics Division. Domain: Economic structures, participation in productive activities and access to resources

Diversity in Tech Statistics: In today's tech-driven world, discussions about diversity in the technology sector have gained significant traction. Recent statistics shed light on the disparities and opportunities within this industry. According to data from various sources, including reports from leading tech companies and diversity advocacy groups, the lack of diversity remains a prominent issue. For example, studies reveal that only 25% of computing jobs in the United States are held by women, while Black and Hispanic individuals make up just 9% of the tech workforce combined. Additionally, research indicates that LGBTQ+ individuals are underrepresented in tech, with only 2.3% of tech workers identifying as LGBTQ+. Despite these challenges, there are promising signs of progress. Companies are increasingly recognizing the importance of diversity and inclusion initiatives, with some allocating significant resources to address these issues. For instance, tech giants like Google and Microsoft have committed millions of USD to diversity programs aimed at recruiting and retaining underrepresented talent. As discussions surrounding diversity in tech continue to evolve, understanding the statistical landscape is crucial in fostering meaningful change and creating a more inclusive industry for all. Editor’s Choice In 2021, 7.9% of the US labor force was employed in technology. Women hold only 26.7% of tech employment, while men hold 73.3% of these positions. White Americans hold 62.5% of the positions in the US tech sector. Asian Americans account for 20% of jobs, Latinx Americans 8%, and Black Americans 7%. 83.3% of tech executives in the US are white. Black Americans comprised 14% of the population in 2019 but held only 7% of tech employment. For the same position, at the same business, and with the same experience, women in tech are typically paid 3% less than men. The high-tech sector employs more men (64% against 52%), Asian Americans (14% compared to 5.8%), and white people (68.5% versus 63.5%) compared to other industries. The tech industry is urged to prioritize inclusion when hiring, mentoring, and retaining employees to bridge the digital skills gap. Black professionals only account for 4% of all tech workers despite being 13% of the US workforce. Hispanic professionals hold just 8% of all STEM jobs despite being 17% of the national workforce. Only 22% of workers in tech are ethnic minorities. Gender diversity in tech is low, with just 26% of jobs in computer-related sectors occupied by women. Companies with diverse teams have higher profitability, with those in the top quartile for gender diversity being 25% more likely to have above-average profitability. Every month, the tech industry adds about 9,600 jobs to the U.S. economy. Between May 2009 and May 2015, over 800,000 net STEM jobs were added to the U.S. economy. STEM jobs are expected to grow by another 8.9% between 2015 and 2024. The percentage of black and Hispanic employees at major tech companies is very low, making up just one to three percent of the tech workforce. Tech hiring relies heavily on poaching and incentives, creating an unsustainable ecosystem ripe for disruption. Recruiters have a significant role in disrupting the hiring process to support diversity and inclusion. You May Also Like To Read Outsourcing Statistics Digital Transformation Statistics Internet of Things Statistics Computer Vision Statistics

About this dataset

Context

The dataset tabulates the population of Industry town by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Industry town across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of female population, with 58.28% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Industry town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Industry town total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Industry town Population by Race & Ethnicity. You can refer the same here

This dataset provides the number of economically active individuals aged 15 years and above in the State of Qatar, classified by nationality (Qatari and Non-Qatari), gender (male and female), and economic sector. It includes both government and private sector participation, as well as mixed, nonprofit, diplomatic, and domestic work. The dataset enables analysis of labor force participation patterns across demographic and institutional dimensions.

Economically Active Population Survey: Employed persons by age group, sex and economic sector. Quarterly. National.

This dataset provides median earnings in past 12 months for civilian employed population 16 years and older by sex and industry for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B24032. Sex categories include Male and Female. The dataset includes the following industries: Agriculture forestry fishing and hunting, Mining quarrying and oil and gas extraction, Construction, Manufacturing, Wholesale trade, Retail trade, Transportation and warehousing, Utilities, Information, Finance and insurance, Real estate and rental and leasing, Professional scientific and technical services, Management of companies and enterprises, Administrative and support and waste management services, Educational services, Health care and social assistance, Arts entertainment and recreation, Accommodation and food services, Other services except public administration, and Public administration. Some industries roll up into a broader industry group.

Population: Economically Active: Luxor: Female data was reported at 589,768.000 Person in 2016. This records an increase from the previous number of 576,385.000 Person for 2015. Population: Economically Active: Luxor: Female data is updated yearly, averaging 232,194.000 Person from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 589,768.000 Person in 2016 and a record low of 190,670.000 Person in 2000. Population: Economically Active: Luxor: Female data remains active status in CEIC and is reported by Central Agency for Public Mobilization and Statistics. The data is categorized under Global Database’s Egypt – Table EG.G007: Population: Economically Active: by Sex, Industry and Region.

Key Table Information.Table Title.Nonemployer Statistics by Demographics series (NES-D): Statistics for Employer and Nonemployer Firms by Industry and Sex for the U.S., States, and Metro Areas: 2018.Table ID.ABSNESD2018.AB00MYNESD01A.Survey/Program.Economic Surveys.Year.2018.Dataset.ECNSVY Nonemployer Statistics by Demographics Company Summary.Source.U.S. Census Bureau, 2018 Economic Surveys, Nonemployer Statistics by Demographics.Release Date.2021-12-16.Release Schedule.The Nonemployer Statistics by Demographics (NES-D) is released yearly, beginning in 2017..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Table Universe.Data in this table combines estimates from the Annual Business Survey (employer firms) and the Nonemployer Statistics by Demographics (nonemployer firms).Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series).Includes U.S. employer firms estimates of business ownership by sex, ethnicity, race, and veteran status from the 2019 Annual Business Survey (ABS) collection. The employer business 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 2017 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered.Data are also obtained from administrative records and other economic surveys. Note: For employer data only, the collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2019 ABS collection year produces statistics for the 2018 reference year. The "Year" column in the table is the reference year..Methodology.Data Items and Other Identifying Records.Total number of employer and nonemployer firmsTotal sales, value of shipments, or revenue of employer and nonemployer firms ($1,000)Number of nonemployer firmsSales, value of shipments, or revenue of nonemployer firms ($1,000)Number of employer firmsSales, value of shipments, or revenue of employer firms ($1,000)Number of employeesAnnual payroll ($1,000)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Sex Female Male Equally male-owned and female-owned Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) 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 NES-D and the ABS are 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.Data are shown for the total for all sectors (00) and the 2-digit NAICS levels for the U.S., states and District of Columbia, and metro areas.For 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 levels 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)Management of Companies and Enterprises (NAICS 55)Private Households (NAICS 814)Public Administration (NAICS 92)Industries Not Classified (NAICS 99)For information about NAICS, see North American Industry Classification System..Sampling.NES-D nonemployer data are not conducted through sampling. Nonemployer Statistics (NES) data originate from statistical information obtained through business income tax records that the Internal Revenue Service (IRS) provides to the Census Bureau. The NES-D adds demographic characteristics to the NES data and produces the total firm counts and the total receipts by those demographic characteristics. The NES-D utilizes various administrative records (AR) and the Census Bureau data sources that include the Business Register (BR), Internal Revenue Service ...

Economically Active Population Survey: Percentage distribution of the Employed persons by economic sector, Autonomous Community and sex. Quarterly. Autonomous Communities and Cities.

The gap between the number of women and men in Russia was measured at approximately 10.3 million as of January 1, 2024, with the female population of the country historically outnumbering the male population. Both genders saw a decrease in inhabitants compared to the previous year. Why are there more women than men in Russia? One of the factors explaining gender imbalance in modern Russia is the gap in average life expectancy between the genders. In 2022, Russian women outlived men by around 10 years. In particular, working-age men were six times more likely to die from external causes of death, such as accidents and suicides, compared to working age women in that year. Furthermore, partial mobilization announced as a result of the Russia-Ukraine war resulted in a mass exodus of young men fleeing from conscription. In response to the government’s call to recruit up to 300,000 reservists in end-September 2022, Google search interest in the term "How to leave Russia" increased sharply. Gender imbalance and its consequences for Russia In Russia, the labor market remains highly segregated by gender. Manual jobs in equipment operation, metal industry, manufacturing, and mechanics are male dominated. The labor shortage in these spheres could limit the country’s potential for increased industrial production. Furthermore, fewer men exacerbate the issue of falling births in Russia. In 2023, only 1.26 million births were recorded nationwide, the lowest over the past decade. Coupled with a decreasing number of working-age men, such a decline in live births could lead to less innovation, a larger share of retired people, and rising government expenditure on pensions and healthcare.