Average percentage of women and men in management positions, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, first quarter of 2025.

This table presents data on the distribution of business sizes (micro, small, and medium) across two genders of entrepreneurs (man and woman), using counts and percentages to illustrate the breakdown.Key Insights:Microbusinesses dominate the dataset, accounting for the vast majority of businesses. Women represent 69.2% of this category, while men make up 30.8%.Small businesses are more evenly split, with 54.4% women and 45.6% men.Medium Businesses are male-dominated, with men accounting for 61.5% while women represent 38.5%.The gender distribution across all business sizes shows that women are the majority (67.7%), while men make up 32.3%.

By measuring where the law treats men and women differently, this book shines a light on how women's incentives or capacity to work are affected by the legal environment and provides a basis for improving regulation. The fourth edition in a series, this book examines laws and regulations affecting women’s prospects as entrepreneurs and employees in 173 economies, across seven areas: accessing institutions, using property, getting a job, providing incentives to work, building credit, going to court, and protecting women from violence. The report's quantitative indicators are intended to inform research and policy discussions on how to improve women's economic opportunities and outcomes.

Citation
“World Bank Group. 2015. Women, Business and the Law 2016 : Getting to Equal. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/22546 License: CC BY 3.0 IGO.”

URI
http://hdl.handle.net/10986/22546

Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Sex for the U.S.: 2023.Table ID.ABSCS2023.AB00MYCSA01A.Survey/Program.Economic Surveys.Year.2023.Dataset.ECNSVY Annual Business Survey Company Summary.Source.U.S. Census Bureau, 2023 Economic Surveys, Annual Business Survey.Release Date.2025-11-20.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 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 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 data are shown for the U.S. only.For information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00") NAICS code. 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 2023 BERD sample, or have high receipts, payroll, or employment. Total sample size is 330,000 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 numbers: CBDRB-FY25-0115 and CBDRB-FY25-0410).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 and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, and more, see Technical Documentation..Weights.For more information about weighting, see Annual Business Survey Methodology..Table Information.FTP Download.https://www2.census.gov/programs-surveys/abs/data/2023/.API Information.Annual Business Survey (ABS) data are housed in the Census Bureau Application Programming Interface (API)..Symbols.S - Estimate does not meet publication standar...

About Mart Mart is an American multinational retail corporation that operates a chain of supercentres, discount departmental stores, and grocery stores from the United States. Mart has more than 100 million customers worldwide.

Business Problem The Management team at Mart Inc. wants to analyze the customer purchase behavior (specifically, purchase amount) against the customer’s gender and the various other factors to help the business make better decisions. They want to understand if the spending habits differ between male and female customers: Do women spend more on Black Friday than men? (Assume 50 million customers are male and 50 million are female).

This data comes from the World Bank project ‘Women, Business and the Law.’ Women, Business and the Law (WBL) is a group project within the World Bank that collects data on the laws and regulations that restrict women's economic opportunities.3 “Women, Business and the Law takes as its starting point that the equal participation of women and men will give every economy a chance to achieve its potential. Equality of opportunity allows women to make the choices that are best for them, their families, and their communities. It is also associated with improved economic outcomes.”4 Women, Business and the Law has collected and shared data from 1971 to 2020. The data measures the legal differences between women’s and men’s access to economic opportunities in 190 economies. The original data tracks thirty-five aspects of the law across 190 economies, and then scores those economies across eight indicators of four or five binary questions. Women, Business and the Law designed each of the indicators to represent a different phase of a woman’s career.5

{"This study investigates to what extent the gender of the enterprise owner impacts the productive use of energy. Specifically, it explores how women and men differ in their productive use within micro, small, and medium-sized enterprises (MSME). Data collection methodology: - Period: January 2023 to January 2024. - Sampling Approach: Deliberate and convenience sampling. - Data Collection Tool: Structured questionnaire distributed via a web-based platform. Description of data: The dataset offers a gender-focused analysis of productive energy use, assessing 65 women-owned food and textile businesses across seven African countries: Egypt, Ghana, Kenya, Malawi, Nigeria, Tanzania, and Tunisia. These data complement the research article by providing in-depth insights into energy use patterns and business profiles. Structure of the dataset: - Sheet 1: This sheet contains the cleaned initial responses from participants, with basic assumptions added for calculation clarity and transparency. - Sheet 2: This sheet contains analysed data and calculations as presented in the accompanying research paper. It covers business profiles, legal statuses of women-owned enterprises, energy use patterns (demand levels, types of energy carriers, access type), and energy expenditure. Notable findings: 1. Energy carriers: Female-owned businesses typically rely on one or two energy carriers, whereas female-male co-owned enterprises use multiple energy carriers. 2. Fuel use: A variance in fuel use among different ownership structures is observed, with diesel, biomass, and liquefied petroleum gas being notable choices. 3. Awareness and demand levels: Increasing ownership diversity correlates with greater awareness of energy metrics and higher monthly demand for electric and mechanical power. A similar trend - with some variance - is observed for thermal energy. 4. Energy expenditure: Enterprises with diverse ownership structures tend to have lower energy expenditure per kilogram of production output (USD/kg/month). Some sole female-owned enterprises have energy expenditures exceeding 100 USD/kg/month, female-female partnerships may reach 100 USD/kg/month while female-male co-owned enterprises stay below 10 USD/kg/month. Conclusions and recommendations: This research highlights the importance of understanding gendered productive energy practices and the need for gender mainstreaming in energy access and use interventions. It underscores the necessity for renewable energy solutions and capacity-building programs to address the efficiency and accessibility challenges women entrepreneurs face. Additionally, it recommends further research to enhance the efficiency and sustainability of energy use in women-owned enterprises. Use of data: Researchers, policymakers, and practitioners can use this data to develop targeted energy access interventions for women-owned MSME, and design renewable energy solutions tailored to the specific needs of female entrepreneurs."}

Release Date: 2018-08-10.[NOTE: Includes firms with payroll at any time during 2016. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2016 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status or that were publicly held or not classifiable by gender, ethnicity, race, or veteran status. Percentages are for respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms by Language(s) Used for Customer Transactions by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016. ..Release Schedule. . This file was released in August 2018.. ..Key Table Information. . These data are related to all other 2016 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2016 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2016 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. In this file, "respondent firms" refers to all firms that reported gender, ethnicity, race, or veteran status for at least one owner or returned a survey form with at least one item completed and were publicly held or not classifiable by gender, ethnicity, race, and veteran status.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms by Language(s) Used for Customer Transactions by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. Percent of respondent firms with paid employees. Percent of sales and receipts of respondent firms with paid employees. Percent of number of employees of respondent firms with paid employees. Percent of annual payroll of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of respondent firms. . All firms. Female-owned. Male-owned. Equally male-/female-owned. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. All firms classifiable by gender, ethnicity, race, and veteran status. Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in busin...

Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Sex for the U.S.: 2022.Table ID.ABSCS2022.AB00MYCSA01A.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 the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Sex Female Male Equally male/female 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 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 data are shown for the U.S. only.For information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00") NAICS code. 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 and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, and more, see Technical Documentation..Weights.For more information about weighting, see Annual Business Survey Methodology..Table Information.FTP Download.https://www2.census.gov/programs-surveys/abs/data/2022/.API Information.Annual Business Survey (ABS) data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsS - Estimate does not meet publication standards bec...

The dataset consists of information about users who are potential customers for a product or service. It contains four input features - User ID, Gender, Age, and Estimated Salary - which are used to predict whether or not the user purchased the product, indicated by the output or target column 'Purchased'.

The User ID is a unique identifier assigned to each user, while Gender is the user's gender, which can be either male or female. Age is the age of the user in years, and Estimated Salary is an estimate of the user's annual salary.

The dataset is likely used for binary classification tasks to determine whether or not a user is likely to purchase a particular product or service. The features provided could potentially be used to create a model that predicts the probability of a user purchasing the product based on their age, gender, and estimated salary.

Time series data for the statistic A woman can register a business in the same way as a man (1=yes; 0=no) and country Lebanon. Indicator Definition:The indicator measures whether there are restrictions on a woman registering a business (i.e. if a woman needs her husband’s or guardian’s permission, signature or consent to register a business; or the registration process at any stage requires a woman to provide additional information or documentation that is not required of a man).

This dataset provides median earnings in past 12 months for civilian employed population 16 years and over by sex and occupation 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 B24012. Sex categories included: Male, Female, and Both Occupation categories included: Management occupations, Business and financial operations occupations, Computer and mathematical occupations, Architecture and engineering occupations, Life physical and social science occupations, Community and social service occupations, Legal occupations, Education training and library occupations, Arts design entertainment sports and media occupations, Health diagnosing and treating practitioners and other technical occupations, Health technologists and technicians, Healthcare support occupations, Fire fighting and prevention and other protective service workers including supervisors, Law enforcement workers including supervisors, Food preparation and serving related occupations, Building and grounds cleaning and maintenance occupations, Personal care and service occupations, Sales and related occupations, Office and administrative support occupations, Farming fishing and forestry occupations, Construction and extraction occupations, Installation maintenance and repair occupations, Production occupations, Transportation occupations, and Material moving occupations. Occupations are organized into broader occupation groups and categories.

This data contains information about all the business firms in the Town of Dumfries. This including men-owned, women-owned, veteran-owned, and minority-owned businesses. This data comes from the most recent U.S. Census provided by the United States Census Bureau. Data will be updated accordingly with the schedule of the U.S Census. https://data.census.gov/cedsci/profile?g=1600000US5123760

E-Commerce Synthetic Dataset

This synthetic dataset simulates a large-scale e-commerce platform with 100,000 records, ideal for data analysis, machine learning, and visualization projects. It includes various data types and reflects real-world e-commerce operations, making it suitable for portfolio projects focused on user behavior analysis, sales trends, and product performance.

Dataset Overview

This dataset contains 100,000 rows with details on users, products, and transactions, as well as user engagement and transaction attributes. It is crafted to resemble actual e-commerce data, providing insights into customer demographics, purchasing patterns, and engagement.

Columns Description

1. UserID: Unique identifier for each user.
2. UserName: Simulated username for each user.
3. Age: Age of the user (ranging from 18 to 70).
4. Gender: Gender of the user, with possible values: Male, Female, and Non-Binary.
5. Country: User's country, chosen from USA, Canada, UK, Australia, India, and Germany.
6. SignUpDate: The date when the user signed up for the platform.

Product Information

1. ProductID: Unique identifier for each product.
2. ProductName: Name of the product purchased (Laptop, Smartphone, Headphones, Shoes, T-shirt, Book, Watch).
3. Category: Category of the product, including Electronics, Apparel, Books, and Accessories.
4. Price: Price of the product (randomly set between $10 and $1,000).

Transaction Details

1. PurchaseDate: Date of purchase.
2. Quantity: Number of units purchased in the transaction.
3. TotalAmount: Total amount spent on the transaction (Price * Quantity).

User Engagement Metrics

1. HasDiscountApplied: Indicates whether a discount was applied (True or False).
2. DiscountRate: Discount rate applied to the transaction (ranging from 0 to 0.5).
3. ReviewScore: User's review score for the product, ranging from 1 to 5.
4. ReviewText: Text-based review (Excellent, Good, Average, Poor).

User Behavior Metrics

1. LastLogin: Date of the user’s last login.
2. SessionDuration: Duration of the user’s session in minutes (ranging from 5 to 120 minutes).
3. DeviceType: Device type used by the user, including Mobile, Desktop, and Tablet.
4. ReferralSource: Source of referral, which could be Organic Search, Ad Campaign, Email Marketing, or Social Media.

Usage

This dataset is intended for: - Exploratory Data Analysis (EDA): Understanding customer demographics, popular products, and sales distribution. - Data Visualization: Visualizing user engagement, sales trends, and product category performance. - Machine Learning Models: Training models on customer segmentation, purchase prediction, and review rating analysis.

Notes

• Synthetic Data: This dataset is entirely synthetic and generated for educational purposes.
• No Personally Identifiable Information (PII): All names, IDs, and records are fictional.

License

This dataset is freely available for use in projects and portfolios. When sharing results derived from this dataset, please credit it as a synthetic data source.

Release Date: 2018-08-10.[NOTE: Includes firms with payroll at any time during 2016. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2016 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status or that were publicly held or not classifiable by gender, ethnicity, race, or veteran status. Percentages are for respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms That Had E-Commerce Sales by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016. ..Release Schedule. . This file was released in August 2018.. ..Key Table Information. . These data are related to all other 2016 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2016 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2016 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. In this file, "respondent firms" refers to all firms that reported gender, ethnicity, race, or veteran status for at least one owner or returned a survey form with at least one item completed and were publicly held or not classifiable by gender, ethnicity, race, and veteran status.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms That Had E-Commerce Sales by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. Percent of respondent firms with paid employees. Percent of sales and receipts of respondent firms with paid employees. Percent of number of employees of respondent firms with paid employees. Percent of annual payroll of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of respondent firms. . All firms. Female-owned. Male-owned. Equally male-/female-owned. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. All firms classifiable by gender, ethnicity, race, and veteran status. Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in business. Firms with 16 or more ye...

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

Release Date: 2017-07-13.[NOTE: Includes firms with payroll at any time during 2015. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2015 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status or that were publicly held or not classifiable by gender, ethnicity, race, or veteran status. Percentages are for respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms That Had E-Commerce Sales by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015. ..Release Schedule. . This file was released in July 2017.. ..Key Table Information. . These data are related to all other 2015 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2015 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2015 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. In this file, "respondent firms" refers to all firms that reported gender, ethnicity, race, or veteran status for at least one owner or returned a survey form with at least one item completed and were publicly held or not classifiable by gender, ethnicity, race, and veteran status.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms That Had E-Commerce Sales by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. Percent of respondent firms with paid employees. Percent of sales and receipts of respondent firms with paid employees. Percent of number of employees of respondent firms with paid employees. Percent of annual payroll of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of respondent firms. . All firms. Female-owned. Male-owned. Equally male-/female-owned. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. All firms classifiable by gender, ethnicity, race, and veteran status. Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in business. Firms with 16 or more year...

Time series data for the statistic A woman can register a business in the same way as a man (1=yes; 0=no) and country Papua New Guinea. Indicator Definition:The indicator measures whether there are restrictions on a woman registering a business (i.e. if a woman needs her husband’s or guardian’s permission, signature or consent to register a business; or the registration process at any stage requires a woman to provide additional information or documentation that is not required of a man).

This dataset provides information on the number of students enrolled in public colleges and universities in Qatar, categorized by college and gender. It includes various colleges such as Education, Arts and Sciences, Sharia and Islamic Studies, Engineering, Business and Economics, and Law. This dataset helps in analyzing the distribution of male and female students across different academic disciplines in public higher education institutions in Qatar.

To understand the impacts and costs of Violence Against Women and Girls (VAWG), the UK Department for International Development (DFID) has funded a project to investigate the social and economic costs of VAWG. Working in Pakistan, South Sudan and Ghana, the National University of Ireland, Galway with Ipsos-MORI and International Centre for Research on Women (ICRW) in collaboration with in-country partners has conducted research to estimate the economic losses caused by VAWG as well as the non-economic costs of violence that impact on economic growth, development, and social stability. Three surveys were done for the collection of data: Household survey, Women and Girls survey, and Business survey. Household Survey - this survey collects data about the general household (e.g. income and property ownership) and individuals within the household. It also acts as a means for safe selection of women to take part in the women’s survey. The data collected in the household survey provides important detail on socio-economic status, occupational distribution and other factors for examining economic and social impacts of VAWG. Individual Women and Girls Survey - the women and girls survey is the most intensive of the quantitative tools, gathering data on a comprehensive set of domains. Questions in the survey explored in detail the costs associated with experiences of VAWG. Questions in the survey are designed to produce a range of scales which will facilitate deeper analysis. Business Survey - Employees, both male and female, and managers were asked to complete the business survey. For male employees, the survey covers both their experiences of violence and also their perpetration of violence. For female employees, the survey covers their experience of violence. This is in addition to the questions on absenteeism and presenteeism due to IPV.