In 2024, the education and health services industry employed the largest number of people in the United States. That year, about 37 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.

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

The statistic shows the distribution of the workforce across economic sectors in Japan from 2013 to 2023. In 2023, 3.01 percent of the workforce was employed in agriculture, 23.71 percent in industry and 73.29 percent in services. Employment and standard of living in Japan Japan’s economy is one of the strongest in the world, and the country’s standard of living is eminently high. Japan ranks third among the countries with the largest gross domestic product / GDP worldwide; a look at the distribution of gross domestic product / GDP across economic sectors in Japan shows that the vast majority of Japan’s GDP is generated by the services sector. The majority of Japan’s workforce is employed in this sector, with less than a third working in industry and only a little more than 1 percent working in agriculture. Similarly to its gross domestic product, the unemployment rate in Japan has been quite steady for the past few years, and even decreased slightly. The inflation rate in Japan, on the other hand, has been fluctuating in recent years, and is currently one of the lowest worldwide. Japan is famous for a high life expectancy, and the median age (i.e. one half of the population is younger and the other half is older) of the Japanese population is thus also among the highest in the world, as can be seen in a comparison of the median age of the population of selected countries. The median age in Japan is significantly higher than in other developed countries, like France or the United States.

VITAL SIGNS INDICATOR
Jobs by Industry (EC1)

FULL MEASURE NAME
Employment by place of work by industry sector

LAST UPDATED
December 2022

DESCRIPTION
Jobs by industry refers to both the change in employment levels by industry and the proportional mix of jobs by economic sector. This measure reflects the changing industry trends that affect our region’s workers.

DATA SOURCE
Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW) - https://www.bls.gov/cew/downloadable-data-files.htm
1990-2021

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Quarterly Census of Employment and Wages (QCEW) employment data is reported by the place of work and represent the number of covered workers who worked during, or received pay for, the pay period that included the 12th day of the month. Covered employees in the private-sector and in the state and local government include most corporate officials, all executives, all supervisory personnel, all professionals, all clerical workers, many farmworkers, all wage earners, all piece workers and all part-time workers. Workers on paid sick leave, paid holiday, paid vacation and the like are also covered.

Besides excluding the aforementioned national security agencies, QCEW excludes proprietors, the unincorporated self-employed, unpaid family members, certain farm and domestic workers exempted from having to report employment data and railroad workers covered by the railroad unemployment insurance system. Excluded as well are workers who earned no wages during the entire applicable pay period because of work stoppages, temporary layoffs, illness or unpaid vacations.

The location quotient (LQ) is used to evaluate level of concentration or clustering of an industry within the Bay Area and within each county of the region. A location quotient greater than 1 means there is a strong concentration for of jobs in an industry sector. For the Bay Area, the LQ is calculated as the share of the region’s employment in a particular sector divided by the share of California's employment in that same sector. For each county, the LQ is calculated as the share of the county’s employment in a particular sector divided by the share of the region’s employment in that same sector.

Data is mainly pulled from aggregation level 73, which is county-level summarized at the North American Industry Classification System (NAICS) supersector level (12 sectors). This aggregation level exhibits the least loss due to data suppression, in the magnitude of 1-2 percent for regional employment, and is therefore preferred. However, the supersectors group together NAICS 11 Agriculture, Forestry, Fishing and Hunting; NAICS 21 Mining and NAICS 23 Construction. To provide a separate tally of Agriculture, Forestry, Fishing and Hunting, the aggregation level 74 data was used for NAICS codes 11, 21 and 23.

QCEW reports on employment in Public Administration as NAICS 92. However, many government activities are reported with an industry specific code - such as transportation or utilities even if those may be public governmental entities. In 2021 for the Bay Area, the largest industry groupings under public ownership are Education and health services (58%); Public administration (29%) and Trade, transportation, and utilities (29%). With the exception of Education and health services, all other public activities were coded as government/public administration, regardless of industry group.

For the county data there were some industries that reported 0 jobs or did not report jobs at the desired aggregation/NAICS level for the following counties/years:

Farm:
(aggregation level: 74, NAICS code: 11) - Contra Costa: 2008-2010 - Marin: 1990-2006, 2008-2010, 2014-2020 - Napa: 1990-2004, 2013-2021 - San Francisco: 2019-2020 - San Mateo: 2013

Information:
(aggregation level: 73, NAICS code: 51) - Solano: 2001

Financial Activities:
(aggregation level: 73, NAICS codes: 52, 53) - Solano: 2001

Unclassified:
(aggregation level: 73, NAICS code: 99) - All nine Bay Area counties: 1990-2000 - Marin, Napa, San Mateo, and Solano: 2020 - Napa: 2019 - Solano: 2001

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.

VITAL SIGNS INDICATOR
Jobs by Industry (EC1)

FULL MEASURE NAME
Employment by place of work by industry sector

LAST UPDATED
December 2022

DESCRIPTION
Jobs by industry refers to both the change in employment levels by industry and the proportional mix of jobs by economic sector. This measure reflects the changing industry trends that affect our region’s workers.

DATA SOURCE
Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW) - https://www.bls.gov/cew/downloadable-data-files.htm
1990-2021

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Quarterly Census of Employment and Wages (QCEW) employment data is reported by the place of work and represent the number of covered workers who worked during, or received pay for, the pay period that included the 12th day of the month. Covered employees in the private-sector and in the state and local government include most corporate officials, all executives, all supervisory personnel, all professionals, all clerical workers, many farmworkers, all wage earners, all piece workers and all part-time workers. Workers on paid sick leave, paid holiday, paid vacation and the like are also covered.

Besides excluding the aforementioned national security agencies, QCEW excludes proprietors, the unincorporated self-employed, unpaid family members, certain farm and domestic workers exempted from having to report employment data and railroad workers covered by the railroad unemployment insurance system. Excluded as well are workers who earned no wages during the entire applicable pay period because of work stoppages, temporary layoffs, illness or unpaid vacations.

The location quotient (LQ) is used to evaluate level of concentration or clustering of an industry within the Bay Area and within each county of the region. A location quotient greater than 1 means there is a strong concentration for of jobs in an industry sector. For the Bay Area, the LQ is calculated as the share of the region’s employment in a particular sector divided by the share of California's employment in that same sector. For each county, the LQ is calculated as the share of the county’s employment in a particular sector divided by the share of the region’s employment in that same sector.

Data is mainly pulled from aggregation level 73, which is county-level summarized at the North American Industry Classification System (NAICS) supersector level (12 sectors). This aggregation level exhibits the least loss due to data suppression, in the magnitude of 1-2 percent for regional employment, and is therefore preferred. However, the supersectors group together NAICS 11 Agriculture, Forestry, Fishing and Hunting; NAICS 21 Mining and NAICS 23 Construction. To provide a separate tally of Agriculture, Forestry, Fishing and Hunting, the aggregation level 74 data was used for NAICS codes 11, 21 and 23.

QCEW reports on employment in Public Administration as NAICS 92. However, many government activities are reported with an industry specific code - such as transportation or utilities even if those may be public governmental entities. In 2021 for the Bay Area, the largest industry groupings under public ownership are Education and health services (58%); Public administration (29%) and Trade, transportation, and utilities (29%). With the exception of Education and health services, all other public activities were coded as government/public administration, regardless of industry group.

For the county data there were some industries that reported 0 jobs or did not report jobs at the desired aggregation/NAICS level for the following counties/years:

Farm:
(aggregation level: 74, NAICS code: 11) - Contra Costa: 2008-2010 - Marin: 1990-2006, 2008-2010, 2014-2020 - Napa: 1990-2004, 2013-2021 - San Francisco: 2019-2020 - San Mateo: 2013

Information:
(aggregation level: 73, NAICS code: 51) - Solano: 2001

Financial Activities:
(aggregation level: 73, NAICS codes: 52, 53) - Solano: 2001

Unclassified:
(aggregation level: 73, NAICS code: 99) - All nine Bay Area counties: 1990-2000 - Marin, Napa, San Mateo, and Solano: 2020 - Napa: 2019 - Solano: 2001

Employment by industry and sex, UK, published quarterly, non-seasonally adjusted. Labour Force Survey. These are official statistics in development.

Provides estimates of contributions to labour productivity, measured as output per hour (OPH), using the "Generalised Exactly Additive Decomposition" (GEAD) methodology as described in Tang and Wang (2004), UK.

This dataset contains monthly employment counts in considerable industrial detail for Colorado and it's major cities. This includes all nonagricultural industries including governmet

In 2024, health sector and social work activities employed around 441,000 people in Finland. That year, the second largest industry sector was manufacturing with roughly 333,000 employees. Other major industries included professional, scientific, and technical activities, administration, as well as wholesale and retail trade.

The number of persons employed in the creative economy (both for-profit and non-profit). This number does not count those persons who identify themselves as being artists and does not count sole proprietorships or persons who work part-time in the arts. The same industries used to calculate the rate businesses in the creative economy are used to calculate total employment in the creative economy. Source: InfoUSA Years Available: 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

Analysis of ‘Employment (domestic concept) by economic sectors and sections of the economy. Average quarterly and annual values’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/20544257-bundesamt-fur-statistik-bfs on 17 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset presents the quarterly and annual employment figures by sector, sector and gender, since 1991. The descriptions of the variables in the CSV file are available in the appendix.

--- Original source retains full ownership of the source dataset ---

Number of persons in the labour force (employment and unemployment) and unemployment rate, by North American Industry Classification System (NAICS), gender and age group.

The statistic shows the distribution of employment in Indonesia by economic sector from 2013 to 2023. In 2023, 28.77 percent of the employees in Indonesia were active in the agricultural sector, 22.09 percent in industry and 49.15 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.

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.

India's agriculture sector was the leading industry in terms of employment in the financial year 2023 with the number of employees tallying over *** million. Meanwhile, the mining industry recorded almost *** 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.

This 6MB download is a zip file containing 5 pdf documents and 2 xlsx spreadsheets. Presentation on COVID-19 and the potential impacts on employment

May 2020Waka Kotahi wants to better understand the potential implications of the COVID-19 downturn on the land transport system, particularly the potential impacts on regional economies and communities.

To do this, in May 2020 Waka Kotahi commissioned Martin Jenkins and Infometrics to consider the potential impacts of COVID-19 on New Zealand’s economy and demographics, as these are two key drivers of transport demand. In addition to providing a scan of national and international COVID-19 trends, the research involved modelling the economic impacts of three of the Treasury’s COVID-19 scenarios, to a regional scale, to help us understand where the impacts might be greatest.

Waka Kotahi studied this modelling by comparing the percentage difference in employment forecasts from the Treasury’s three COVID-19 scenarios compared to the business as usual scenario.

The source tables from the modelling (Tables 1-40), and the percentage difference in employment forecasts (Tables 41-43), are available as spreadsheets.

Arataki - potential impacts of COVID-19 Final Report

Employment modelling - interactive dashboard

The modelling produced employment forecasts for each region and district over three time periods – 2021, 2025 and 2031. In May 2020, the forecasts for 2021 carried greater certainty as they reflected the impacts of current events, such as border restrictions, reduction in international visitors and students etc. The 2025 and 2031 forecasts were less certain because of the potential for significant shifts in the socio-economic situation over the intervening years. While these later forecasts were useful in helping to understand the relative scale and duration of potential COVID-19 related impacts around the country, they needed to be treated with care recognising the higher levels of uncertainty.

The May 2020 research suggested that the ‘slow recovery scenario’ (Treasury’s scenario 5) was the most likely due to continuing high levels of uncertainty regarding global efforts to manage the pandemic (and the duration and scale of the resulting economic downturn).

The updates to Arataki V2 were framed around the ‘Slower Recovery Scenario’, as that scenario remained the most closely aligned with the unfolding impacts of COVID-19 in New Zealand and globally at that time.

Find out more about Arataki, our 10-year plan for the land transport system

May 2021The May 2021 update to employment modelling used to inform Arataki Version 2 is now available. Employment modelling dashboard - updated 2021Arataki used the May 2020 information to compare how various regions and industries might be impacted by COVID-19. Almost a year later, it is clear that New Zealand fared better than forecast in May 2020.Waka Kotahi therefore commissioned an update to the projections through a high-level review of:the original projections for 2020/21 against performancethe implications of the most recent global (eg International monetary fund world economic Outlook) and national economic forecasts (eg Treasury half year economic and fiscal update)The treasury updated its scenarios in its December half year fiscal and economic update (HYEFU) and these new scenarios have been used for the revised projections.Considerable uncertainty remains about the potential scale and duration of the COVID-19 downturn, for example with regards to the duration of border restrictions, update of immunisation programmes. The updated analysis provides us with additional information regarding which sectors and parts of the country are likely to be most impacted. We continue to monitor the situation and keep up to date with other cross-Government scenario development and COVID-19 related work. The updated modelling has produced employment forecasts for each region and district over three time periods - 2022, 2025, 2031.The 2022 forecasts carry greater certainty as they reflect the impacts of current events. The 2025 and 2031 forecasts are less certain because of the potential for significant shifts over that time.

Data reuse caveats: as per license.

Additionally, please read / use this data in conjunction with the Infometrics and Martin Jenkins reports, to understand the uncertainties and assumptions involved in modelling the potential impacts of COVID-19.

COVID-19’s effect on industry and regional economic outcomes for NZ Transport Agency [PDF 620 KB]

Data quality statement: while the modelling undertaken is high quality, it represents two point-in-time analyses undertaken during a period of considerable uncertainty. This uncertainty comes from several factors relating to the COVID-19 pandemic, including:

a lack of clarity about the size of the global downturn and how quickly the international economy might recover differing views about the ability of the New Zealand economy to bounce back from the significant job losses that are occurring and how much of a structural change in the economy is required the possibility of a further wave of COVID-19 cases within New Zealand that might require a return to Alert Levels 3 or 4.

While high levels of uncertainty remain around the scale of impacts from the pandemic, particularly in coming years, the modelling is useful in indicating the direction of travel and the relative scale of impacts in different parts of the country.

Data quality caveats: as noted above, there is considerable uncertainty about the potential scale and duration of the COVID-19 downturn. Please treat the specific results of the modelling carefully, particularly in the forecasts to later years (2025, 2031), given the potential for significant shifts in New Zealand's socio-economic situation before then.

As such, please use the modelling results as a guide to the potential scale of the impacts of the downturn in different locations, rather than as a precise assessment of impacts over the coming decade.