© Marcel Crozet / ILO

Worker and sector profiles (PROFILES database)

Table of Contents


For information on basic labour force concepts, such as employment and unemployment for example, refer to the Labour Force Statistics (LFS) database description. The descriptions below are intended to provide further details on the definitions for groups of occupations and/or sectors recombined based on the International Standard Classification of Occupations (ISCO-08 or previous versions) and/or the International Standard Industrial Classification of All Economic Activities (ISIC rev. 4 or previous versions). 

The data are experimental series since there are no internationally agreed statistical definitions for these groups of workers. 

Paid care workers

Concepts and definitions

Care work refers to a wide range of “activities and relations involved in meeting the physical, psychological, and emotional needs of adults and children, old and young”. This broad conception of care work acknowledges that requirements for care extend across the life cycle: “New-borns and young people…adults…[and]…older persons [all] have physical, psychological, cognitive and emotional needs and require varying degrees of protection, care, or support”. 

Care activities are comprised of two broad kinds. First, those that consist of direct, face-to-face, personal care activities (sometimes referred to as “nurturing” or “relational” care), such as feeding a baby, supporting a person with disabilities, nursing a sick partner, helping an older person to take a bath, carrying out health check-ups or teaching young children. Second, those involving indirect care activities, which do not entail face-to-face personal care, such as cleaning, cooking, doing the laundry and other household maintenance tasks (sometimes referred to as “non-relational care” or “household work”), that provide the preconditions for personal caregiving. These two types of care activities cannot be separated from each other, and they frequently overlap in practice, both in households, communities and in facilities.

Care work can be paid or unpaid. The indicators in this database focus on paid care work, also referred to as care employment. Care employment is care work performed for profit or pay within a range of settings, such as private households (as in the case of domestic workers), communities and public or private hospitals, clinics, nursing homes, schools and other care or support establishments or facilities. Care workers may be in an employment relationship where the employer is a private individual or household, a public agency, a private for-profit enterprise or a private non-profit organization, or they may be working on their own account (self-employed).

The identification of persons in care employment is done using both ISCO and ISIC at two-digit levels.

Based on ISCO-08, care occupations are:

  • 22. Health Professionals;
  • 23. Teaching Professionals;
  • 32. Health Associate Professionals; and
  • 53. Personal Care Workers.

There are other care occupations (captured indirectly by combining ISCO and ISIC codes, as explained below) in:

  • 13. Production and Specialized Services Managers;
  • 26. Legal, Social and Cultural Professionals;
  • 34. Legal, Social, Cultural and Related Associate Professionals;
  • 51. Personal Service Workers; and
  • 91. Cleaners and Helpers.

Based on ISIC Rev. 4, care sectors are:

  • 85. Education;
  • 86. Human health activities;
  • 87. Residential care activities;
  • 88. Social work activities without accommodation.

Domestic workers (employed by households) are identified by being classified in ISIC Rev. 4 category 97. Activities of households as employers of domestic personnel. This differs from the more comprehensive definition in the ILO’s 2021 report on domestic workers.

The combination of care occupations, care sectors and households as employers makes it possible to identify persons in care employment and group them into four categories using ISCO-08 and ISIC Rev. 4, as follows:

  1. Care workers employed in care sectors
    • Workers in ISIC 85, 86, 87, 88 who are also in ISCO 22, 23, 32, 53 (core care occupations)
    • Workers in ISIC 85, 86, 87, 88 who are also in ISCO 13
    • Workers in ISIC 85, 86, 87, 88 who are also in ISCO 26 and 34
  2. Domestic workers (employed by households)
    • All workers in ISIC 97
    • (This captures many workers who are in ISCO 51 and 91, which are noted above in the paragraph on other care occupations)
  3. Care workers employed in non-care sectors
    • All other workers in ISCO 22 except for those working in ISIC 75 Veterinary activities
    • All other workers in ISCO 23
    • All other workers in ISCO 32 except for those working in ISIC 75 Veterinary activities
    • All other workers in ISCO 53
  4. Non-care workers employed in care sectors
    • Workers in ISIC 85, 86, 87, 88 who are not in ISCO 22, 23, 32, 53, 26, 34 and 13

Users should note that, at the direction of the 21st International Conference of Labour Statisticians, the ILO Department of Statistics is launching a new programme of work to develop a statistical reference definition, conceptual framework, and indicator framework for care work. The goal is to promote consistency and international comparability in the measurement of care work, in line with the latest international statistical standards and emerging best practices, and taking account of national policy priorities.

Interpretation and uses

Care work is essential for the sustainability of humanity and the planet, the reproduction of the future workforce, for the health, education and well-being of the current workforce, children and the growing numbers of older people and persons with disabilities. Most care workers are women, frequently working in the informal economy, in very poor conditions and receiving low levels of pay. Yet, paid care work is likely to remain an important source of employment in the future, especially among women. Decent care work is therefore central to ensuring a future of work that is founded on and that promotes gender equality and social justice, for the benefit of all.


Care employment is a subset of the care economy, since it does not capture unpaid care workers. Most of the unpaid care work throughout the world is undertaken by women and is a key factor in determining whether women can enter, stay and progress in employment and the quality of jobs they perform.
As noted above, the definition for domestic workers is limited to those employed by households and thus undercounts this group of workers.

As noted above, the definition for domestic workers is limited to those employed by households and thus undercounts this group of workers. 

Key workers

Key workers are non-teleworkable occupations identified at the 2-digit level of ISCO: 

  • food systems workers;
  • health workers;
  • retail workers;
  • security workers;
    • (occupations at the four-digit level: security guards, police officers, firefighters, prison guards)
  • manual workers (includes plant operators and warehouse workers);
  • cleaning and sanitation workers;
  • transport workers; and
  • technicians and clerical workers.

Workers in STEM occupations

Concepts and definitions

National statistical offices typically define Science, Technology, Engineering and Mathematics (STEM) occupations using categories at 4-digit level. For practical reasons, this experimental data series is currently based mainly on 2-digit categories of ISCO. The selection is similar to the list of STEM occupations selected by the U.S. Bureau of Labor Statistics  (BLS) and O*NET. It includes the following occupational groups:

ISCO-08 categoryExamples
12. Administrative and commercial managers in scientific research and development (ISIC 72)Research and development (R&D) managers
13. Production and specialised services managers in computer programming, consultancy and information service activities (ISIC 62-63)Information, Communication and Technology (ICT) service managers
21. Science and engineering professionalsEngineers, physicists, biologists, statisticians, actuaries
22. Health professionalsDoctors, dentists, nurses, pharmacists, veterinarians
24. Business and administration professionals in R&D and ICT (ISIC 62-63 and 72)Sales engineers, medical sales professionals
25. Information and communications technology professionalsSystems analysts and administrators, software developers
31. Science and engineering associate professionalsMechanical and electrical engineering technicians
32. Health associate professionalsMedical assistants, dental hygienists, lab technicians
35. Information and communications techniciansComputer network and systems technicians, web technicians

Interpretation and uses

STEM occupations play an ever-increasing role in today’s complex world, driving innovation, job opportunities and solutions to important challenges. They are higher skilled occupations that typically provide higher wages and better working conditions. 

Data on STEM occupations enable informed decision-making, facilitate targeted interventions, and support the development of strategies to foster a robust and diverse STEM workforce. For example, data on STEM occupations help policymakers, educational institutions, and industry leaders to identify and anticipate the demand for specific skills and expertise in the job market. This information aids in developing effective strategies for workforce planning and ensuring a sufficient supply of skilled professionals in STEM fields. These data can also shed light on the representation and participation of various demographic groups within the STEM workforce. Analyzing this data helps identify gaps and disparities, enabling targeted efforts to improve diversity and inclusion in STEM fields, creating opportunities for underrepresented groups and fostering a more inclusive and equitable workforce.


STEM occupations are defined based on more aggregate categories than what is typically done at the national level. This also implies that it was not possible at the 2-digit level of ISCO to include STEM-related postsecondary teachers nor social science-based occupations classified as legal, social and cultural professionals (for example economists and psychologists), although the latter are considered STEM-related occupations by O*NET but not BLS.

Data on STEM occupations in ILOSTAT provide high-level statistics, such as employment numbers, earnings, hours of work and other variables available in household surveys. However, they lack detailed contextual information, such as specific job responsibilities and workplace conditions. Such details are essential for gaining a comprehensive understanding of the STEM workforce.

STEM fields tend to evolve rapidly, with new technologies, disciplines, and job roles emerging constantly. Emerging fields may not yet have established standardized classifications (i.e., the occupation does not yet exist in the latest version of ISCO), making it challenging to capture them accurately in data.

Public sector workers

Concepts and definitions

For most indicators, public sector refers to general government plus public corporations under the LFS framework. The identification of whether a job is in the public versus private sector is made by the respondent, usually by responding to a single question.

For the indicator on public employment by sectors and sub-sectors of national accounts, data should be consistent with the System of National Accounts (SNA). The SNA consists of a coherent, consistent and integrated set of macroeconomic accounts, balance sheets and tables based on a set of internationally agreed concepts, definitions, classifications and accounting rules. Public sector employment covers all employment of the general government sector as defined in 2008 SNA plus employment of public corporations. Definitions for the sectors and sub-sectors of national accounts are defined as follows:

  • General government sector employment is the total employment of all resident institutional units operating at central, state and local levels of government; i.e. all government units, social security funds and non-market Non Profit Institutions (NPIs) that are controlled by public authority. Government units carry out government functions and have fiscal, legislative and executive authority, which extend to their competent geographical areas (see 2008 SNA, paragraph 4.9): 
      • Central government units consist in general of a single institution composed of departments or ministries, of autonomous agencies carrying out special functions, and of all non-market NPIs which are controlled by public authority. Their fiscal, legislative
        and executive authority extends over the entire territory of the country. The administration units which provide some services to local residents but which are directly dependent on central units should be an integral part of central government unit (see 2008 SNA, paragraphs 4.134 to 4.139).
      • State government units consist of state governments which are separate institutional units plus those non-market NPIs that are controlled by state governments. Their fiscal, legislative and executive authority extends to the territory of the state into the country (see 2008 SNA, paragraphs 4.140 to 4.144).
      • Local government units are institutional units, plus those non-market NPIs that are controlled by local governments, whose fiscal, legislative and executive authority is generally much less than that of central or state governments. They typically provide a
        wide range of services to local residents and often depend on grants or transfers from higher levels of governments (see 2008 SNA, paragraphs 4.145 and 4.146). Non Profit Institutions (NPIs) are legal or social entities which are separately identified from government units. They are classified under the general government (in each corresponding level) if they are non-market, and controlled by public authority.
      • Social security funds are institutional units that refer to social insurance schemes covering the community as a whole or large sections of the community, and are imposed and controlled by government units. They operate at all levels of government and can be recorded separately as sub-sector of general government or alternatively included in each level of government (see 2008 SNA, paragraphs 4.147 and 4.148).
  • Employment of public corporations is the employment of all units producing goods or services for the market and which are controlled (e.g. mainly owned) by government units. This category is not included in general government sector employment.

For more detailed information, refer to the 2008 System of National Accounts

Interpretation and uses

Public workforces lie at the heart of broader public sector transformations involving digitization, automation, innovative service delivery, and crisis preparedness. Emerging workforce dynamics, including an aging civil service, evolving skill requirements, and shifts in the ways of working, require data and evidence to adjust practices in human resources management and create effective mid-term and long-term policies.


Public sector in the LFS framework may include public corporations whereas in national accounts, the reference is to general government (non-market services). Moreover, no further breakdown by institutional sectors of government is available. While there is a strong need to improve labour statistics for local and regional government workers in particular, their identification is not possible through LFSs. Meanwhile, activities for general government can be identified as being mainly in the following ISIC sections:

  • O “Public administration and defence, compulsory social security”
  • P “Education”
  • Q “Human health and social work activities”

When comparing LFS data and SNA statistics on public sector employment, generally both sources are broadly aligned in terms of the general direction of the employment growth. In some cases, however, they can show important differences. This is usually the case if the SNA data are not predominantly based on the LFS data.

Tourism sector workers

Concepts and definitions

Tourism is defined as the activities of persons travelling to and staying in places outside their usual
environment for not more than one consecutive year for leisure, business and other purposes. For ILOSTAT purposes, the identification of persons in the tourism sector is done using ISIC Rev. 4 at the 4-digit level, using the following classes:

Accommodation for visitors        

  • 5510 Short term accommodation activities
  • 5520 Camping grounds, recreational vehicle parks and trailer parks
  • 5590 Other accommodation

Food and beverage serving activities      

  • 5610 Restaurants and mobile food service activities
  • 5629 Other food service activities
  • 5630 Beverage serving activities

Passenger transportation

  • 4911 Passenger rail transport, interurban
  • 4921 Urban and suburban passenger land transport
  • 4922 Other passenger land transport
  • 5011 Sea and coastal passenger water transport
  • 5021 Inland passenger water transport
  • 5110 Passenger air transport
  • 5221 Service activities incidental to land transportation
  • 5222 Service activities incidental to water transportation
  • 5223 Service activities incidental to air transportation
  • 7710 Renting and leasing of motor vehicles

Recreation and entertainment

  • 7721 Renting and leasing of recreational and sports goods
  • 9000 Creative, arts and entertainment activities
  • 9102 Museums activities and operation of historical sites and buildings
  • 9103 Botanical and zoological gardens and nature reserves activities
  • 9200 Gambling and betting activities
  • 9311 Operation of sports facilities
  • 9319 Other sports activities
  • 9321 Activities of amusement parks and theme parks
  • 9329 Other amusement and recreation activities n.e.c.

Travel services

  • 7911 Travel agency activities
  • 7912 Tour operator activities
  • 7990 Other reservation service and related activities

Users should also note that the UN World Trade Organization (UNWTO), in partnership with leading countries, the ILO and the United Nations Statistics Division, has created a multidisciplinary and multi-stakeholder Expert Group on Measuring the Sustainability of Tourism to lead the development of a Statistical Framework for Measuring the Sustainability of Tourism. The framework aims to support a more harmonized and integrated measurement of the impacts and dependencies of tourism on the economy, society and the environment, at both the national and sub-national levels. The framework may result in a statistical definition for tourism-related employment which differs from the above. 

Interpretation and uses

The ILO and UNWTO jointly consider tourism to be one of the most dynamic sectors of economic activity in modern times, generating a wide range of benefits for tourism host and tourist-generating countries and destinations, including employment generation, foreign exchange earnings and contribution to GDP. The measurement of persons in the tourism sector sheds light on the sector’s role in job creation and economic development. This data provides insights into the scale and significance of tourism employment within a country. By tracking the number of individuals employed in various tourism-related sectors – from hospitality and transportation to cultural services – policymakers, businesses, and labour analysts can assess the sector’s contribution to overall employment, gauge its stability, and tailor targeted workforce development strategies. 

Tourism employment can play a pivotal role particularly in developing countries by generating jobs, fostering income distribution, and spurring economic growth. As a labour-intensive industry, it offers diverse employment opportunities ranging from hospitality to local services, benefiting both urban and rural communities. Tourism jobs can alleviate poverty, reduce inequality, and empower local populations, particularly in regions with limited economic prospects. Moreover, these jobs often enhance skills and vocational training, contributing to human capital development. By creating pathways to livelihoods and fostering economic resilience, tourism employment can serve as a catalyst for broader socio-economic advancement in developing nations.


With increased granularity, the potential for data errors and inconsistencies also increases. Data collection and reporting errors at the 4-digit level can lead to unreliable results. In some cases, certain 4-digit categories might have very small sample sizes. However, aggregating data to a broader category reduces the impact of inconsistencies and makes the data more robust statistically by reducing the impact of outliers and small sample sizes. Meanwhile, some policy decisions or analyses might require data at a specific level of granularity to be effective. Aggregating data might not provide the necessary level of detail for nuanced decision-making.

Forest sector

Employment in the forest sector is defined as the sum of employment in three sub-sectors using ISIC at the 2-digit level:

  • forestry and logging (ISIC rev. 4 or ISIC rev. 3 division 02)
  • manufacture of wood and products of wood (ISIC rev. 4 division 16 or ISIC rev. 3 division 20)
  • paper manufacture (ISIC rev. 4 division 17 or ISIC rev. 3 division 21)

The methodology is further explained in the document “Contribution of the forest sector to total employment in national economies: Estimating the number of people employed in the forest sector” prepared by the Thünen-Institute for Rural Areas, of Forestry and Fisheries. It serves as a technical background paper to the FAO’s flagship report “The State of the World’s Forests 2022”.

Data were strictly used for a blog on the topic but can easily be reconstituted 

Environmental sector (selected)

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Unless otherwise indicated, the indicators are produced using detailed data from the ILO’s Harmonized Microdata collection, which is comprised of mostly labour force and household surveys processed and maintained by the ILO Department of Statistics. The specific survey used is available as metadata when downloading the data.

For countries where ISIC and/or ISCO is available only at the 2- or 3-digit level, data are estimated using weighted shares from countries in the same income group with available 4-digit level data. The assumption is that the employment distribution is similar within countries of the same income group. The methodology is described here. These data points are indicated with the value status “estimated”. 

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