In 2023, the education and health services industry employed the largest number of people in the United States. That year, about 36,4 million people were employed in the education and health services industry.

Education and Health Services Industry

Despite being one of the wealthiest nations in the world, the United States has started to fall behind in both education and the health care industry. Although the U.S. spends the most money in both these industries, they do not see their desired results in comparison to other nations. Furthermore, in the education services industry, there was a relatively significant wage gap between men and women. In 2019, men earned about 1,070 U.S. dollars per week on average, while their female counterparts only earned 773 U.S. dollars per week.

Employment in the U.S.

The 2008 financial crisis was a large-scale event that impacted the entire world, especially the United States. The economy started to improve after 2010, and the number of people employed in the United States has been steadily increasing since then. However, the number of people employed in the education sector is expected to slowly decrease until 2026. The overall unemployment rate in the United States has decreased since 2010 as well.

The statistic shows the distribution of the workforce across economic sectors in the United States from 2013 to 2023. In 2023, 1.57 percent of the workforce in the US was employed in agriculture, 19.34 percent in industry and 79.09 percent in services. See U.S. GDP per capita for more information. American workforce A significant majority of the American labor force is employed in the services sector, while the other sectors, industry and agriculture, account for less than 20 percent of the US economy. However, the United States is among the top exporters of agricultural goods – the total value of US agricultural exports has more than doubled since 2000. A severe plunge in the employment rate in the US since 1990 shows that the American economy is still in turmoil after the economic crisis of 2008. Unemployment is still significantly higher than it was before the crisis, and most of those unemployed and looking for a job are younger than 25; youth unemployment is a severe problem for the United States, many college or university graduates struggle to find a job right away. Still, the number of employees in the US since 1990 has been increasing slowly, with a slight setback during and after the recession. Both the number of full-time and of part-time workers have increased during the same period. When looking at the distribution of jobs among men and women, both project the general downward trend. A comparison of the employment rate of men in the US since 1990 and the employment rate of women since 1990 shows that more men tend to be employed than women.

In 2023, it was estimated that over 161 million Americans were in some form of employment, while 3.64 percent of the total workforce was unemployed. This was the lowest unemployment rate since the 1950s, although these figures are expected to rise in 2023 and beyond. 1980s-2010s Since the 1980s, the total United States labor force has generally risen as the population has grown, however, the annual average unemployment rate has fluctuated significantly, usually increasing in times of crisis, before falling more slowly during periods of recovery and economic stability. For example, unemployment peaked at 9.7 percent during the early 1980s recession, which was largely caused by the ripple effects of the Iranian Revolution on global oil prices and inflation. Other notable spikes came during the early 1990s; again, largely due to inflation caused by another oil shock, and during the early 2000s recession. The Great Recession then saw the U.S. unemployment rate soar to 9.6 percent, following the collapse of the U.S. housing market and its impact on the banking sector, and it was not until 2016 that unemployment returned to pre-recession levels. 2020s 2019 had marked a decade-long low in unemployment, before the economic impact of the Covid-19 pandemic saw the sharpest year-on-year increase in unemployment since the Great Depression, and the total number of workers fell by almost 10 million people. Despite the continuation of the pandemic in the years that followed, alongside the associated supply-chain issues and onset of the inflation crisis, unemployment reached just 3.67 percent in 2022 - current projections are for this figure to rise in 2023 and the years that follow, although these forecasts are subject to change if recent years are anything to go by.

Number of employees by North American Industry Classification System (NAICS) and type of employee, last 5 years.

By the year 2033, it is projected that the number of employees working in services for the elderly and persons with disabilities around 613,700 employees. Additionally, the computer systems design and related services workforce is expected to grow by around 487,600 workers.

Number of employees by North American Industry Classification System (NAICS) and data type (seasonally adjusted, trend-cycle and unadjusted), last 5 months. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.

Graph and download economic data for All Employees, Government (USGOVT) from Jan 1939 to Feb 2025 about establishment survey, government, employment, and USA.

India's agriculture sector was the leading industry in terms of employment in the financial year 2023 with the number of employees tallying over 253 million. Meanwhile, the mining industry recorded almost 1.9 million employees. The services sector is the next big sector in India after agriculture. Challenges facing the agriculture sector Agriculture is the mainstay of India’s workforce. It employs over 42 percent of India’s population. However, it is the lowest contributor to the country’s GDP when compared to other major sectors. Despite being one of the largest producers of crops in the world, agricultural productivity remains low. Key issues impacting productivity include the decreasing size of landholdings, dependence on monsoons, inadequate access to irrigation, lack of access to credit and finance for marginal farmers, inadequate agricultural infrastructure, vulnerability to market volatility, and climate change, among others. Service sector: Key GDP contributor The service sector contributes a lion’s share to India’s GDP. Driven by investments and a skilled workforce, India has now positioned itself on the global stage for services. Information technology, financial services, and communications are the key performing subsectors within the service industry. However, the rising labor productivity in the sector has reduced the demand for labor. This gap in output and employment parallels the disproportionately larger share of the service sector in GDP than employment.

The statistic shows the distribution of the workforce across economic sectors in China from 2013 to 2023. In 2023, around 22.8 percent of the workforce were employed in the agricultural sector, 29.1 percent in the industrial sector and 48.1 percent in the service sector. This year, the share of agriculture increased for the first time in more than two decades, which highlights the difficult situation of the labor market due to the pandemic and economic downturn at the end of the year.

Distribution of the workforce in China

In 2012, China became the largest exporting country worldwide with an export value of about two trillion U.S. dollars. China’s economic system is largely based on growth and export, with the manufacturing sector being a crucial contributor to the country’s export competitiveness. Economic development was accompanied by a steady rise of labor costs, as well as a significant slowdown in labor force growth. These changes present a serious threat to the era of China as the world’s factory. The share of workforce in agriculture also steadily decreased in China until 2021, while the agricultural gross production value displayed continuous growth, amounting to approximately 7.8 trillion yuan in 2021.

Development of the service sector

Since 2011, the largest share of China’s labor force has been employed in the service sector. However, compared with developed countries, such as Japan or the United States, where 73 and 79 percent of the work force were active in services in 2021 respectively, the proportion of people working in the tertiary sector in China has been relatively low. The Chinese government aims to continue economic reform by moving from an emphasis on investment to consumption, among other measures. This might lead to a stronger service economy. Meanwhile, the size of the urban middle class in China is growing steadily. A growing number of affluent middle class consumers could promote consumption and help China move towards a balanced economy.

Overview: Each quarter, the Temporary Foreign Worker Program (TFWP) publishes Labour Market Impact Assessment (LMIA) statistics on Open Government Data Portal, including quarterly and annual LMIA data related to, but not limited to, requested and approved TFW positions, employment location, employment occupations, sectors, TFWP stream and temporary foreign workers by country of origin. The TFWP does not collect data on the number of TFWs who are hired by an employer and have arrived in Canada. The decision to issue a work permit rests with Immigration, Refugees and Citizenship Canada (IRCC) and not all positions on a positive LMIA result in a work permit. For these reasons, data provided in the LMIA statistics cannot be used to calculate the number of TFWs that have entered or will enter Canada. IRCC publishes annual statistics on the number of foreign workers who are issued a work permit: https://open.canada.ca/data/en/dataset/360024f2-17e9-4558-bfc1-3616485d65b9. Please note that all quarterly tables have been updated to NOC 2021 (5 digit and training, education, experience and responsibilities (TEER) based). As such, Table 5, 8, 17, and 24 will no longer be updated but will remain as archived tables. Frequency of Publication: Quarterly LMIA statistics cover data for the four quarters of the previous calendar year and the quarter(s) of the current calendar year. Quarterly data is released within two to three months of the most recent quarter. The release dates for quarterly data are as follows: Q1 (January to March) will be published by early June of the current year; Q2 (April to June) will be published by early September of the current year; Q3 (July to September) will be published by early December of the current year; and Q4 (October to December) will be published by early March of the next year. Annual statistics cover eight consecutive years of LMIA data and are scheduled to be released in March of the next year. Published Data: As part of the quarterly release, the TFWP updates LMIA data for 28 tables broken down by: TFW positions: Tables 1 to 10, 12, 13, and 22 to 24; LMIA applications: Tables 14 to 18; Employers: Tables 11, and 19 to 21; and Seasonal Agricultural Worker Program (SAWP): Tables 25 to 28. In addition, the TFWP publishes 2 lists of employers who were issued a positive or negative LMIA: Employers who were issued a positive LMIA by Program Stream, NOC, and Business Location (https://open.canada.ca/data/en/dataset/90fed587-1364-4f33-a9ee-208181dc0b97/resource/b369ae20-0c7e-4d10-93ca-07c86c91e6fe); and Employers who were issued a negative LMIA by Program Stream, NOC, and Business Location (https://open.canada.ca/data/en/dataset/f82f66f2-a22b-4511-bccf-e1d74db39ae5/resource/94a0dbee-e9d9-4492-ab52-07f0f0fb255b). Things to Remember: 1. When data are presented on positive or negative LMIAs, the decision date is used to allocate which quarter the data falls into. However, when data are presented on when LMIAs are requested, it is based on the date when the LMIA is received by ESDC. 2. As of the publication of 2022Q1- 2023Q4 data (published in April 2024) and going forward, all LMIAs in support of 'Permanent Residence (PR) Only' are included in TFWP statistics, unless indicated otherwise. All quarterly data in this report includes PR Only LMIAs. Dual-intent LMIAs and corresponding positions are included under their respective TFWP stream (e.g., low-wage, high-wage, etc.) This may impact program reporting over time. 3. Attention should be given for data that are presented by ‘Unique Employers’ when it comes to manipulating the data within that specific table. One employer could be counted towards multiple groups if they have multiple positive LMIAs across categories such as program stream, province or territory, or economic region. For example, an employer could request TFWs for two different business locations, and this employer would be counted in the statistics of both economic regions. As such, the sum of the rows within these ‘Unique Employer’ tables will not add up to the aggregate total.

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 Totally or Partly Paid Employee Benefits 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 Totally or Partly Paid Employee Benefits 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 busines...

In 2022, 42.86 percent of the workforce in India were employed in agriculture, while the other half was almost evenly distributed among the two other sectors, industry and services. While the share of Indians working in agriculture is declining, it is still the main sector of employment. A BRIC powerhouseTogether with Brazil, Russia, and China, India makes up the four so-called BRIC countries. They are the four fastest-growing emerging countries dubbed BRIC, an acronym, by Jim O’Neill at Goldman Sachs. Being major economies themselves already, these four countries are said to be at a similar economic developmental stage -- on the verge of becoming industrialized countries -- and maybe even dominating the global economy. Together, they are already larger than the rest of the world when it comes to GDP and simple population figures. Among these four, India is ranked second across almost all key indicators, right behind China. Services on the riseWhile most of the Indian workforce is still employed in the agricultural sector, it is the services sector that generates most of the country’s GDP. In fact, when looking at GDP distribution across economic sectors, agriculture lags behind with a mere 15 percent contribution. Some of the leading services industries are telecommunications, software, textiles, and chemicals, and production only seems to increase – currently, the GDP in India is growing, as is employment.

Abstract

Statistical information on all aspects of the population is vital for the design, implementation, monitoring and evaluation of economic and social development plan and policy issues. Labour force survey is among the important sources of data to assess the participation of the population in the economic and social development process of the country. It is useful to indicate the extent of available and unutilized human resources that must be absorbed by the national economy to ensure full employment and economic wellbeing of the population.

The general objective of the 2013 National Labor Force Survey was designed to provide statistical data on the size, distribution and characteristics of the economically active and the distribution in the various sectors of the economy in both urban and rural areas. The data will be useful for policy makers, planners, researchers, and other institutions and individuals engaged in the design, implementation and monitoring of human resource development plans, programs and projects. The specific objectives of this survey are: • Generate data on the size of the potential work force that is available to participate in production process; • Determine the activity status and rate of economic participation of different sub-groups of the population; • Identify those who are actually contributing to the economic development (i.e., employed) and those who are out of the sphere of productive activities; • Identify the size, distribution and characteristics of employed population by occupation and Industry, status in employment, sector of employment and earnings from employment...etc. • Provide data on the size, distribution and characteristics of unemployed population and rate of unemployment; • Assess the situation of women's employment or the participation of women in the labour force; • Provide time series data to trace changes over time.

Geographic coverage

The survey covered all rural and urban parts of the country except the non-sedentary areas of six zones of Somali region.

Analysis unit

• Households
• Individuals (household members aged 5 years and above)

Kind of data

Sample survey data [ssd]

Frequency of data collection

Every five years

Sampling procedure

Sampling Frame The list of Sampling Frame obtained from the 2007 Population and Housing Census is used to select EAs. A fresh list of households from each EA was prepared at the beginning of the survey period. The list was then used as a frame for selecting sample households of each EAs.

Sample Design For the purpose of the survey the country was divided into three broad categories, rural (Category I), major urban center (Category II) and other urban center categories (Category III).

Sample Size and Selection Scheme Category I: Totally 842 EAs and 25260 households were selected from this category. Sample EAs of each reporting level was selected using Probability Proportional to Size (PPS) systematic sampling technique; size being number of household obtained from the 2007 Population and Housing Census. From the fresh list of households prepared at the beginning of the survey 30 households per EA were systematically selected and surveyed. For the distribution of planned and covered number of samples from each domain see

Category II: In this category 817 EAs and 24510 households were selected. Sample EAs from each reporting level in this category were also selected using probability proportional to size (PPS) systematic sampling; size being number of households obtained from the 2007 Population and Housing Census is used to select EAs. From the fresh list of households prepared at the beginning of the survey 30 households per EA were systematically selected and covered by the study. The table below (Summary Table 2.2) shows planned and covered EAs and households in each domain.

Category III: 127 urban centers, 296 EAs and 8,880 households were selected in this category. Urban centers from each domain and EAs from each urban center were selected using probability proportional to size systematic selection method; size being number of households obtained from the 2007 Population and Housing Census is used to select EAs. From the fresh listing of each EA 30 households were systematically selected and the study carried out on the 30 households ultimately selected. Summary Table 2.3 below shows the number of planned and sampled EAs and households by domain.

For details on sampling design, see: Ethiopian Central Statistical Agency. Analytica Report on The 2013 National Labour Force Survey

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey is mainly aimed at providing information on the economic characteristics of the population aged 10 years and above, i.e., their activity status, employment, and unemployment situation during the last seven days prior to the survey date. It has also covered detailed socio-demographic background variables such as age, sex, relationship to the head of household, migration, disability, literacy status, educational level, training and marital status. The survey has used a structured questionnaire to produce the required data. Before taking its final shape, the draft questionnaire was commented by CSA senior staff member from different directorate as well as top management. Based on the comment given by professionals, the content, layout and presentation of the questionnaire were amended.

The questionnaire was organized in to six sections; Section 1: Area identification of the selected household: this section dealt with area identification of the respondents such as region, zone, wereda, etc. Section 2: Socio- demographic characteristics of households: it consisted of the general socio-demographic characteristics of the population such as age, sex, education, status and type of migration, disability, literacy status, educational Attainment, types of training and marital status. Section 3: Economic activities during the last seven days: this section dealt with a range of questions which helps to see the status and characteristics of employed persons in a current status approach such as hours of work in productive activities, occupation, industry, status in employment, earnings from employment, job mobility, service year for paid employees employment in the formal and informal sector and time related under employment. Section 4: Unemployment and characteristics of unemployed persons: this section focused on the size, rate and characteristics of the unemployed population. Section 5: Economic activities during the last twelve months: this section consists of the usual economic activity status refereeing to the long reference period i.e. engaged in productive activities during most of the last twelve months, reason for not being active, status in employment, main occupation and industry with two digit codes. Section 6: Economic activities of children aged 5-17 years: this section comprises information on the participation of children aged 5-17 years in the economic activities, whether attending education, reason for not attending education, whether they were working during the last seven days, reason for working, for whom they are working, types of injury at work place, whether using protective wear while working and frequency of working periods, and orphan hood status.

The questionnaire used in the field for data collection was prepared in Amharic language. Most questions have pre-coded answers. A copy of the questionnaire translated to English is attached as an external resource.

Cleaning operations

The filled-in questionnaires that were retrieved from the field were first subjected to manual editing and coding. During the fieldwork the field supervisors and the heads of branch statistical offices have checked the filled-in questionnaires and carried out some editing. However, the major editing and coding operation was carried out at the head office. All the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry by the subject matter experts.

Using the computer edit specifications prepared earlier for this purpose, the entered data were checked for consistencies and then computer editing or data cleaning was made by referring back to the filled-in questionnaire. This is an important part of data processing operation in attaining the required level of data quality. Consistency checks and re-checks were also made based on frequency and tabulation results. This was done by senior programmers using CSPro software in collaboration with the senior subject experts from Labour Statistics Team of the CSA.

Response rate

• For the rural domains, the response rate was 99.60%
• For the major urban centers domains, the response rate was 99.51%
• For the other urban centers domains, the response rate was 99.62%

Abstract

This survey was conducted in Jordan between May 2013 and January 2014. The survey was a joint initiative of the World Bank, the European Bank for Reconstruction and Development (EBRD) and the European Investment Bank (EIB).

The Enterprise Surveys, through interviews with firms in the manufacturing and services sectors, capture business perceptions on the biggest obstacles to enterprise growth, the relative importance of various constraints to increasing employment and productivity, and the effects of a country's business environment on its international competitiveness. They are used to create statistically significant business environment indicators that are comparable across countries. The Enterprise Surveys are also used to build a panel of enterprise data that will make it possible to track changes in the business environment over time and allow, for example, impact assessments of reforms.

In Jordan, data from 573 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses.

The survey topics include firm characteristics, information about sales and suppliers, competition, infrastructure services, judiciary and law enforcement collaboration, security, government policies, laws and regulations, financing, overall business environment, bribery, capacity utilization, performance and investment activities, and workforce composition.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or universe of the study, is the non-agricultural economy. It comprises: all manufacturing sectors according to the group classification of ISIC Revision 3.1: (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Jordan was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

The universe was stratified into three manufacturing industries (food manufacturing, garment manufacturing, and other manufacturing), and two service industries (retail, and other services).

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not common practice, except in the sectors of construction and agriculture.

Regional stratification was defined in five regions (city and the surrounding business area) throughout Jordan. The five regions were Amman, Irbid, Zarqa, Aqaba, and Balqa.

The sample frame used for the survey in Jordan was from several sources: the World Bank SME survey in Jordan, the Amman Chamber of Industry, the Amman Chamber of Commerce, the Irbid Chamber of Industry, the Irbid Chamber of Commerce, the Zarqa Chamber of Industry, the Zarqa Chamber of Commerce, the Aqaba Chamber of Industry, the Aqaba Chamber of Commerce, the Balqa Chamber of Industry, the Balqa Chamber of Commerce, and the Orbis database (Bureau van Dijk for the validation of large-sized firms).

The enumerated establishments were then used as the frame for the selection of a sample with the aim of obtaining interviews at 600 establishments with five or more employees.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 8.7 % (182 out of 2,104 establishments).

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available: - Manufacturing Questionnaire; - Services Questionnaire.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether, while the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect the refusal to respond as a different option from don’t know. b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

The number of realized interviews per contacted establishment was 0.27. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The number of rejections per contact was 0.08.

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 Totally or Partly Paid Employee Benefits 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 Totally or Partly Paid Employee Benefits 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...

In 2025, there were estimated to be approximately 3.6 billion people employed worldwide, compared to 2.23 billion people in 1991 - an increase of around 1.4 billion people. There was a noticeable fall in global employment between 2019 and 2020, when the number of employed people fell from due to the sudden economic shock caused by the COVID-19 pandemic. Formal vs. Informal employment globally Worldwide, there is a large gap between the informally and formally employed. Most informally employed workers reside in the Global South, especially Africa and Southeast Asia. Moreover, men are slightly more likely to be informally employed than women. The majority of informal work, nearly 90 percent, is within the agricultural sector, with domestic work and construction following behind. Women’s employment As the number of employees has risen globally, so has the number of employed women. Overall, care roles such as nursing and midwifery have the highest shares of female employees globally. Moreover, while the gender pay gap has shrunk over time, it still exists. As of 2024, the uncontrolled gender pay gap was 0.83, meaning women made, on average, 83 cents per every dollar earned by men.

Abstract

The 61st round of the Nationbal Sample Survey was conducted during July, 2004 to June, 2005. The survey was spread over 7,999 villages and 4,602 urban blocks covering 1,24,680 households (79,306 in rural areas and 45,374 in urban areas) and enumerating 6,02,833 persons (3,98,025 in rural areas and 2,04,808 in urban areas). Employment and unemployment were measured with three different approaches, viz. usual status with a reference period of one year, current weekly status with one week reference period and current daily status based on the daily activity pursued during each day of the reference week. Unless otherwise stated, ‘all’ usual status workers will mean all workers taking into consideration the usual principal and subsidiary status taken together.

Geographic coverage

The survey covered the whole of the Indian Union except (i) Leh (Ladakh) and Kargil districts of Jammu & Kashmir, (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Analysis unit

Household, individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Outline of sample design: A stratified multi-stage design has been adopted for the 61st round survey. The first stage units (FSU) are the 2001 census villages in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units (USU) are households in both the sectors. In the case of large villages/blocks requiring hamlet-group (hg)/sub-block (sb) formation, one intermediate stage is the selection of two hgs/sbs from each FSU.

Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the list of latest available Urban Frame Survey (UFS) blocks has been considered as the sampling frame.

Stratification: Within each district of a State/UT, two basic strata have been formed: i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, if there are one or more towns with population 10 lakhs or more as per population census 2001 in a district, each of them will also form a separate basic stratum and the remaining urban areas of the district will be considered as another basic stratum. There are 27 towns with population 10 lakhs or more at all-India level as per census 2001.

Sub-stratification:

• Rural sector: If 'r' be the sample size allocated for a rural stratum, the number of sub-strata formed is 'r/2'. The villages within a district as per frame have been first arranged in ascending order of population. Then sub-strata 1 to 'r/2' have been demarcated in such a way that each sub-stratum comprises a group of villages of the arranged frame and has more or less equal population.

• Urban sector: If 'u' be the sample size for a urban stratum, 'u/2' number of sub-strata have been formed. The towns within a district, except those with population 10 lakhs or more, have been first arranged in ascending order of population. Next, UFS blocks of each town have been arranged by IV unit no. × block no. in ascending order. From this arranged frame of UFS blocks of all the towns, 'u/2' number of sub-strata has been formed in such a way that each sub-stratum has more or less equal number of UFS blocks.

For towns with population 10 lakhs or more, the urban blocks have been first arranged by IV unit no. × block no. in ascending order. Then 'u/2' number of sub-strata has been formed in such a way that each sub-stratum has more or less equal number of blocks.

Total sample size (FSUs): 12784 FSUs have been allocated at all-India level on the basis of investigator strength in different States/UTs for central sample and 14992 for state sample.

Allocation of total sample to States and UTs: The total number of sample FSUs is allocated to the States and UTs in proportion to population as per census 2001 subject to the availability of investigators ensuring more or less uniform work-load.

Allocation of State/UT level sample to rural and urban sectors: State/UT level sample size is allocated between two sectors in proportion to population as per census 2001 with 1.5 weightage to urban sector subject to the restriction that urban sample size for bigger states like Maharashtra, Tamil Nadu etc. should not exceed the rural sample size. A minimum of 8 FSUs has been allocated to each state/UT separately for rural and urban areas.

Allocation to strata: Within each sector of a State/UT, the respective sample size is allocated to the different strata in proportion to the stratum population as per census 2001. Allocations at stratum level have been adjusted to a multiple of 4 with a minimum sample size of 4.

Selection of FSUs: Two FSUs have been selected from each sub-stratum of a district of rural sector with Probability Proportional to Size With Replacement (PPSWR), size being the population as per Population Census 2001. For urban sector, two FSUs have been selected from each sub-stratum by using Simple Random Sampling Without Replacement (SRSWOR). Within each sub-stratum, samples have been drawn in the form of two independent sub-samples in both the rural and urban sectors.

Selection of hamlet-groups/sub-blocks/households - important steps

Criterion for hamlet-group/sub-block formation: Large villages/blocks having approximate present population of 1200 or more will be divided into a suitable number (say, D) of 'hamlet-groups' in the rural sector and 'sub-blocks' in the urban sector as stated below.

approximate present population of the sample village/block / no. of hgs/sbs to be formed (D)

less than 1200 (no hamlet-groups/sub-blocks): 1
1200 to 1799: 3 1800 to 2399: 4 2400 to 2999: 5 3000 to 3599: 6 …..and so on

For rural areas of Himachal Pradesh, Sikkim and Poonch, Rajouri, Udhampur, Doda districts of Jammu and Kashmir and Idukki district of Kerala, the number of hamlet-groups formed is as follows.

approximate present population of the sample village / no. of hgs to be formed

less than 600 (no hamlet-groups): 1
600 to 899: 3
900 to 1199: 4
1200 to 1499: 5 …..and so on

Two hamlet-groups/sub-blocks are selected from a large village/UFS block wherever hamlet-groups/sub-blocks have been formed, by SRSWOR. Listing and selection of the households are done independently in the two selected hamlet-groups/sub-blocks. In case hamlet-groups/sub-blocks are to be formed in the sample FSU, the same would be done by more or less equalizing population.

Formation of Second Stage Strata and allocation of households

For both Schedule 1.0 and Schedule 10, households listed in the selected village/block/ hamlet-groups/sub-blocks are stratified into three second stage strata (SSS) as given below.

Rural: The three second-stage-strata (SSS) in the rural sector are formed in the following order:

SSS 1: relatively affluent households
SSS 2: from the remaining households, households having principal earning from non- agricultural activity
SSS 3: other households

Urban: In the urban sector, the three second-stage strata (SSS) are formed as under:

Two cut-off points, say 'A' and 'B', based on MPCE of NSS 55th round, have been determined at NSS Region level in such a way that top 10% of households have MPCE more than 'A' and bottom 30% have MPCE less than 'B'. Then three second-stage-strata (SSS) are formed in the urban sector in the following order:

SSS 1: households with MPCE more than A (i.e. MPCE > A)
SSS 2: households with MPCE equal to or less than A but equal to or more than B ( i.e. B = MPCE = A)
SSS 3: households with MPCE less than B (i.e. MPCE < B)

The number of households to be surveyed in each FSU is 10 for each of the schedules 1.0 and 10. C

Selection of households for Schedules 1.0 and 10: From each SSS the sample households for both the schedules are selected by SRSWOR. If a household is selected both for schedule 1.0 and schedule 10, only schedule 1.0 would be canvassed in that household and the sample household for schedule 10 would be replaced by next household in the frame for schedule 10.

Mode of data collection

Face-to-face [f2f]

Research instrument

In the present round, Schedule 10 on employment-unemployment consists of 16 blocks.

The first three blocks, viz. Blocks 0, 1 and 2, are used to record identification of sample households and particulars of field operations, as is the common practice in usual NSS rounds. Similarly, the last two blocks, viz., Blocks 10 & 11, are again the usual blocks to record the remarks of investigator and comments by supervisory officer(s), respectively. Block 3 will be for recording the household characteristics like household size, religion, social group, land possessed and cultivated, monthly per capita consumer expenditure, etc., and Block 3.1 for recording particulars of indebtedness of rural labour households.

Block 4 is used for recording the demographic particulars and attendance in educational institutions of all the household members. Particulars of vocational training receiving/received by the household members will also be collected in block 4.

In Block 5.1, particulars of usual principal activity of all the household members will be recorded along with some particulars of the enterprises in which the usual status workers (excluding those in crop and plantation activities) are engaged. Information on informal employment will also be collected in block 5.1. Similarly, the particulars of one subsidiary economic activity of the household members along with some

This statistic shows the number of private sector manufacturing employees in the United States from 1985 to 2023. In 2023, roughly 14.92 million people were employed in the private sector manufacturing industry.

The statistic shows the distribution of employment in Indonesia by economic sector from 2012 to 2022. In 2022, 29.28 percent of the employees in Indonesia were active in the agricultural sector, 21.87 percent in industry and 48.85 percent in the service sector. Indonesia's GDP The economic sector in Indonesia with the biggest share in gross domestic product over the past decade has been the industry sector, closely followed by services. The industry sector makes up around 45.7 percent of gross domestic product in Indonesia. Due to Indonesia's economy rapidly improving, the unemployment rate is decreasing, with most Indonesians working in the services sector (including tourism, hospitality, etc), while GDP and GDP per capita have been steadily increasing simultaneously. The country’s gross domestic product per capita has almost quadrupled over the past decade, with GDP also increasing at the same rate. Nowadays, Indonesia is among the leading countries in the world with the largest gross domestic product.

There were over 31 million people working in the manufacturing sector in the European Union, as of 2024, the most of any economic sector. Employees working in wholesale and retail trade numbered approximately 25.8 million, while there were just over 22.2 million people working in human health and social work.