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ILOSTAT database description

Labour Force Statistics (LFS, STLFS, RURBAN databases)

Statistics on the informal economy

Labour statistics for the Sustainable Development Goals (SDGs)

Statistics on the population and labour force

Statistics on unemployment and labour underutilization

Statistics on employment

Statistics on working poverty

Statistics on youth

Worker and sector profiles (PROFILES database)

Overview

Sound evidence-based policy-making relies on identifying and quantifying not only best practices in the labour market but also inefficiencies – such as labour underutilization and decent work deficits. This is the first step in designing employment policies aimed at enhancing the well-being of workers while also promoting economic growth. This broad view of the world of work calls for comprehensive collection, organization and analysis of labour market information. In this context, labour force statistics and the related ILOSTAT databases serve as a foundation for monitoring and assessing many of the pertinent issues related to the functioning of labour markets.

This description focuses on labour force indicators (i.e., employment and labour underutilization measures) and applies to the following ILOSTAT databases:

Labour Force Statistics (LFS)
Short-Term Labour Force Statistics (STLFS)
Rural and Urban Labour Market Statistics (RURBAN)
Youth Labour Market Statistics (YouthSTATS) — refer to the YouthSTATS database description for youth-specific descriptions
Disability Labour Market Indicators (DLMI) — refer to the DLMI database description for disability-specific descriptions
Education and Mismatch Indicators (EMI) — refer to the EMI database description for education- and mismatch-specific descriptions

Also see the indicator descriptions for earnings and hours of work.

Indicators in the LFS and related databases listed above are based on concepts and definitions from the Resolution concerning statistics of the economically active population, employment, unemployment and underemployment, adopted by the 13th International Conference of Labour Statisticians (ICLS) in 1983. This differs from the indicators in the Work Statistics – 19th ICLS (WORK) database, which are based on the 19th ICLS standards adopted in 2013. Although the latter are the more recent statistical standards, most countries currently follow the 13th ICLS standards. Users should also note that most data in the WORK database are not comparable to those in databases based on the 13th ICLS. For more information, refer to the Quick guide to understanding the impact of the new statistical standards on ILOSTAT databases.

Labour force participation rate

Introduction

The labour force participation rate is a measure of the proportion of a country’s working-age population that engages actively in the labour market, either by working or looking for work; it provides an indication of the size of the supply of labour available to engage in the production of goods and services, relative to the population at working age. The breakdown of the labour force (formerly known as economically active population) by sex and age group gives a profile of the distribution of the labour force within a country.

ILOSTAT contains statistics from national sources on labour force participation rates by sex and age, rural/urban areas and education. ILOSTAT also includes ILO estimates of labour force participation rates by sex and age, which contain both nationally reported and imputed data, and where all estimates are national, meaning there are no geographic limitations in coverage.¹

Concepts and definitions

The labour force participation rate is the number of persons in the labour force as a percentage of the working-age population. The labour force is the sum of the number of persons employed and the number of persons unemployed.² Thus, the measurement of the labour force participation rate requires the measurement of both employment and unemployment. Employment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment.

The inactivity rate is equal to 100 minus the labour force participation rate, where the participation rate is expressed as a number between 0 and 100. ILOSTAT also contains statistics on persons outside the labour force (formerly known as the economically inactive population). The employment-to-population ratio is equal to the labour force participation rate after the deduction of unemployment from the numerator of the rate.

Method of computation

The labour force participation rate (LFPR) is calculated as follows:

LFPR (%) = 100 x Labour force / Working-age population

where the labour force is equal to employment plus unemployment.

For a given component group of the working-age population, the LFPR is the percentage of this group that is in the labour force. For example, the LFPR for women would be calculated as:

LFPRw (%) = 100 x Women in the labour force / Working-age women

Interpretation and uses

The labour force participation rate indicator plays a central role in the study of the factors that determine the size and composition of a country’s human resources and in making projections of the future supply of labour. The information is also used to formulate employment policies, to determine training needs and to calculate the expected working lives of the male and female populations and the rates of accession to, and retirement from, economic activity – crucial information for the financial planning of social security systems.

The indicator is also useful for understanding the labour market behaviour of different segments of the population. The level and pattern of labour force participation depends on employment opportunities and the demand for income, which may differ from one category of persons to another. For example, studies have shown that the labour force participation rates of women vary systematically, at any given age, with their marital status and level of education. There are also important differences in the participation rates of the urban and rural populations, and among different socio-economic groups.

Malnutrition, disability and chronic sickness can affect the capacity to work and are therefore also considered as major determinants of labour force participation, particularly in low-income environments. Another aspect closely studied by demographers is the relationship between fertility and female labour force participation. This relationship is used to predict the evolution of fertility rates, from the current pattern of female participation in economic activity.³

Comparison of the overall labour force participation rates of countries at different stages of development reveals a U-shaped relationship. In less-developed economies, labour force participation rates can be seen to decline with economic growth. Economic growth is associated with improved educational outcomes and longer time spent studying, a shift from labour-intensive agricultural activities to urban economic activities, and a rise in earning opportunities, particularly for the “prime” working age (25 to 54 years) head of household so that other household members with lower earning potential may choose not to work. These factors together tend to lower the overall labour force participation rate for both men and women, although the effect is weaker for the latter and shows a wider variation.

It is also instructive to look at labour force participation rates for males and females by age group. Labour force activity among the young (15 to 24 years) reflects the availability of educational opportunities, while labour force activity among older workers (55 to 64 years or 65 years and over) gives an indication of the attitude towards retirement and the existence of social safety nets for the retired. Labour force participation is generally lower for females than for males in each age category. Among the prime working age, the female rates are not only lower than the corresponding male rates, but they also typically exhibit a somewhat different pattern. During this period of their life-cycle, women tend to leave the labour force to give birth to and raise children, subsequently returning – but at a lower rate – to economically active life. In developed economies, the profile of female participation is increasingly becoming similar to that of men.

To some degree, the way in which the labour force is measured can have an effect on the extent to which men and women are included in labour force estimates. Unless specific probing questions are built into the survey questionnaire, participation among certain groups of workers may be underestimated – particularly the number of employed persons who (a) work for only a few hours in the reference period, especially if they do not do so regularly; (b) are in unpaid employment; or (c) work near or in their home, thus mixing work and personal activities during the day. Since women, more so than men, are found in these situations, it is to be expected that the number of women in employment (and thus the female labour force) will tend to be underestimated to a larger extent than the number of men.

Limitations

National data on labour force participation rates may not be comparable owing to differences in concepts and methodologies. The single most important factor affecting data comparability is the data source. Labour force data obtained from population censuses are often based on a restricted number of questions on the economic characteristics of individuals, with little possibility of probing. The resulting data, therefore, are generally not consistent with corresponding labour force survey data and may vary considerably from one country to another, depending on the number and type of questions included in the census. Establishment censuses and surveys can – by their nature – only provide data on the employed population, leaving out the unemployed and, in many countries, also excluding workers engaged in small establishments or in the informal economy who fall outside the scope of the survey or census.

For international comparisons of labour force data, the most comprehensive source is undoubtedly labour force surveys. Nevertheless, despite their strength, labour force survey data may contain non-comparable elements in terms of scope and coverage, mainly because of differences in the inclusion or exclusion of certain geographic areas, and the incorporation or non-incorporation of military conscripts. Also, there are variations in national definitions of the labour force concept, particularly with respect to the statistical treatment of some specific groups, such as “contributing family workers” and “persons not employed, available for work but not looking for work”.

Non-comparability may also arise from differences in the age limits used in measuring the labour force (formerly known as the economically active population). Some countries have adopted nonstandard upper-age limits for inclusion in the labour force, with a cut-off point of 65 or 70 years, which will affect broad comparisons, and especially comparisons of those at the higher age levels. Finally, differences in the dates to which the data refer, as well as the method of averaging over the year, may contribute to the non-comparability of the resulting statistics.

To a large extent, these comparability issues have been addressed in the construction of the ILO modelled estimates of labour force participation rates included in ILOSTAT. Only household labour force survey and population census data that are representative of the whole country (with no geographic limitation) were used in the construction of the estimates. In countries with more than one survey source, only one type of source was used. If a labour force survey was available for the country, labour force participation rates derived from this source were chosen in favour of those derived from population censuses.

Employment by economic activity

Introduction

This indicator provides information on employment across different economic activities. Information by sector of economic activity is particularly useful in identifying broad shifts in employment and stages of development. Having detailed statistics on employment by economic activity allows for the calculation of the share of manufacturing in total employment, which was included as one of the indicators proposed to measure progress towards the achievement of the Sustainable Development Goals (SDG), under Goal 9 (Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation).⁴

ILOSTAT contains statistics from national sources on employment by branch of economic activity, also disaggregated by sex, available using both aggregate and detailed categories of economic activity. ILOSTAT also includes ILO modelled estimates of employment by economic activity by sex, which contain both nationally reported and imputed data, and where all estimates are national, meaning there are no geographic limitations in coverage. Further information on the methodology used to produce ILO modelled estimates is provided here.

Concepts and definitions

Employment comprises all persons of working age who, during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or having a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).⁵

The classification by economic activity refers to the main activity of the establishment in which a person worked during the reference period. The branch of economic activity of a person does not depend on the specific duties or functions of the person’s job, but rather on the characteristics of the economic unit in which the person works.

Data presented by branch of economic activity is based on the International Standard Industrial Classification of All Economic Activities (ISIC). The ISIC is the international reference classification of productive activities. Its main purpose is to provide a set of activity categories that can be utilized for the collection and reporting of statistics according to such activities. The original version of ISIC was adopted in 1948, and it has been revised four times since then: in 1968 (ISIC Rev.2), in 1990 (ISIC Rev.3) and in 2008 (ISIC Rev.4). An updated version of the ISIC Rev.3 was introduced in 2002 to account for substantial changes in many countries’ economic structure (ISIC Rev. 3.1).⁶

Statistics on employment by economic activity are presented in ILOSTAT according to both the categories of the latest version of the ISIC available and aggregate categories, based on the following correspondence table:

Aggregate Economic Activity			Sections ISIC- Rev. 4	Sections ISIC- Rev. 3	Sections ISIC- Rev. 2
Agriculture			A	A, B	1
Non Agriculture	Industry	Manufacturing	C	D	3
		Construction	F	F	5
		Mining and quarrying; Electricity, gas and water supply	B, D, E	C, E	2, 4
	Services	Market Services (Trade; Transportation; Accommodation and food; and Business and administrative services)	G, H, I, J, K, L, M, N	G, H, I, J, K	6, 7, 8
	Services	Non-market services (Public administration; Community, Social and other services and activities)	O, P, Q, R, S, T, U	L, M, N, O, P, Q	9
Not elsewhere classified			X		0

Interpretation and uses

As economies develop, jobs are reallocated from agriculture and other labour-intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas. In a large majority of countries, services are currently the largest sector in terms of employment. In most of the remaining countries, agricultural employment often remains widespread.

Classification into broad groupings may obscure fundamental shifts within industrial patterns. An analysis of employment statistics by economic activity following the 1-digit level categories of the ISIC allows identification of individual industries and services where employment is growing or stagnating. Teamed with information on job vacancies by sector, the more detailed data, viewed over time, provides a picture of where demand for labour is focused and, as such, can serve as a guide for policy-makers designing skills and training programmes that are aimed at improving the match between labour supply and demand. Employment in the manufacturing sector (ISIC 4, tabulation category C, ISIC 3, tabulation category D and ISIC 2, major division 3) is of particular interest to many researchers. One could also investigate, for example, how employment in the accommodations and food services sector (ISIC 4, tabulation category I and ISIC 3 tabulation category H) has evolved in countries where tourism comprises a significant portion of gross national product.

It is also interesting to study sectoral employment flows in connection with productivity trends in order to separate within-sector productivity growth (i.e. resulting from changes in capital or technology) from productivity growth resulting from shifts of workers from lower- to higher-productivity sectors. The breakdown of the indicator by sex allows for analysis of gender segregation of employment by sector. Are men and women equally distributed across sectors, or is there a concentration of females in the services sector? Women may be drawn into lower paying service activities that allow for more flexible work schedules, thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from taking up certain types of jobs.

Limitations

A number of factors can limit the comparability of statistics on employment by economic activity between countries or over time.

Comparability of employment statistics across countries is affected most significantly by variations in the definitions used for the employment figures. Differences may result from age coverage, such as the lower and upper age bounds for labour force activity. Estimates of employment are also likely to vary according to whether members of the armed forces are included. When the armed forces are included in the measure of employment they are usually allocated to the services sector. Therefore, in countries that do not include armed forces, the services sector tends to be understated in comparison with countries where they are included.

Another area with scope for measurement differences has to do with the national treatment of particular groups of workers. The international definition of employment calls for inclusion of all persons who worked for at least one hour during the reference period.⁷ Workers could be in paid employment or in self-employment, including in less obvious forms of work, some of which are dealt with in detail in the resolution adopted by the 19th ICLS, such as unpaid family work, apprenticeship or non-market production. The majority of exceptions to coverage of all persons employed in a labour force survey have to do with slight national variations to the international recommendation applicable to the alternate employment statuses. For example, some countries measure persons employed in paid employment only and some countries measure “all persons engaged”, meaning paid employees plus working proprietors who receive some remuneration based on corporate shares. Other possible variations to the norms pertaining to measurement of total employment include hours limits (beyond one hour) placed on contributing family members before for inclusion in employment.⁸

Comparisons can also be problematic when the frequency of data collection varies. The range of information collection can run from one month to 12 months in a year. Given the fact that seasonality of various kinds is undoubtedly present in all countries, employment figures can vary for this reason alone. Also, changes in the level of employment can occur throughout the year, but this can be obscured when fewer observations are available.

It is also important to note that different versions of the ISIC can be used across countries, with countries moving to adopting the most recent version at different paces. A country may continue to use the previous version even after starting a new data series according to the most recent version. Although these different classification systems can have an impact on comparability at detailed levels of economic activity, changes from one ISIC to another should not have a significant impact on the information for the three broad sectors presented in ILOSTAT.

Employment by occupation

Introduction

This indicator provides information on the distribution of employment across different occupations. Having detailed statistics on employment by occupation also disaggregated by sex allows for the calculation of the proportion of women in managerial positions, which was included as one of the indicators to measure progress towards the achievement of the Sustainable Development Goals (SDG), under Goal 5 (Achieve gender equality and empower all women and girls).⁹

ILOSTAT contains statistics from national sources on employment by occupation disaggregated by sex, and available for both aggregate and detailed categories of occupation. ILOSTAT also includes ILO modelled estimates of employment by occupation by sex, which contain both nationally reported and imputed data, and where all estimates are national, meaning there are no geographic limitations in coverage. Further information on the methodology used to produce ILO modelled estimates is provided here.

Concepts and definitions

Employment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).¹⁰

Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person. Employed persons are classified by occupations through their relationship to a present job.¹¹

Data presented by occupation is based on the International Standard Classification of Occupation (ISCO). The development of the ISCO goes back many decades and has always been closely connected with the work of the International Conference of Labour Statisticians. The original version of the ISCO was published in 1958 (ISCO-58) and it has been revised three times since then: in 1968 (ISCO-68), in 1988 (ISCO-88) and in 2008 (ISCO-08).¹²

Statistics on employment by occupation are presented in ILOSTAT according to both the categories of the latest version of the ISCO available and broad skill levels, based on the following correspondence table:

Broad skill level	ISCO-08	ISCO-88
Skill levels 3 and 4	1. Managers	1. Legislators, senior officials and managers
	2. Professionals	2. Professionals
	3. Technicians and associate professionals	3. Technicians and associate professionals
Skill level 2	4. Clerical support workers	4. Clerks
	5. Service and sales workers	5. Service workers and shop and market sales workers
	6. Skilled agricultural, forestry and fishery workers	6. Skilled agricultural and fishery workers
	7. Craft and related trades workers	7. Craft and related trades workers
	8. Plant and machine operators, and assemblers	8. Plant and machine operators and assemblers
Skill level 1	9. Elementary occupations	9. Elementary occupations
Armed forces	0. Armed forces occupations	0. Armed forces
Not elsewhere classified	X. Not elsewhere classified	X. Not elsewhere classified

Interpretation and uses

Occupational statistics are used for research on labour market topics ranging from occupational safety and health to labour market segmentation. Occupational analyses also inform economic and labour policies in areas such as educational planning, migration and employment services. Occupational information is particularly important for the identification of changes in skill levels in the labour force.

In many advanced economies, but also in developing economies, occupational employment projection models are used to inform policies aiming to meet future skills needs, as well as to advise students and jobseekers on expected job prospects. Changes in the occupational distribution of an economy can be used to identify and analyse stages of development. As economies develop and labour flows from agriculture to the industrial and services sectors, these flows will be visible in the occupational distribution as well. The share of skilled agricultural and fishery workers will typically decrease, while increased skill requirements are likely to be reflected in a decreasing share of elementary occupations and rising shares of high-skilled occupational groups such as professionals and technicians.

In developed economies, increases in the shares of high-skilled occupational groups are associated with the advance of the knowledge economy and additional changes in the structure of economies. Furthermore, shifts within occupational groups may be equally important. For example, the growing importance of information and communication technology (ICT) has resulted in a proliferation of ICT-related jobs.

The breakdown of the indicator by sex allows for an analysis of gender segregation of employment. Division of labour markets on the basis of sex is one of the most pervasive characteristics of labour markets around the world, which is reflected in different occupational distributions between men and women.

Limitations

A number of factors can limit the comparability of statistics on employment by occupation between countries or over time. Comparability of employment statistics across countries is affected most significantly by variations in the definitions used for the employment figures. Age coverage, such as the lower and upper bounds for labour force activity, can affect comparability. Estimates of employment are also likely to vary according to whether members of the armed forces are included. Armed forces constitute a separate occupational major group, but in some countries they are included in the most closely matching civilian occupation, depending on the type of work performed by the individual armed forces member concerned, or are included in non-classifiable workers. Another area with scope for measurement differences has to do with the national treatment of particular groups of workers. The international definition of employment calls for inclusion of all persons who worked for at least one hour during the reference period.¹³ Workers could be in paid employment or in self-employment, including in less obvious forms of work, some of which are dealt with in detail in the resolution adopted by the 19th ICLS, such as unpaid family work, apprenticeship or non-market production. The majority of exceptions to coverage of all persons employed in a labour force survey have to do with slight national variations to the international recommendation applicable to the alternate employment statuses. For example, some countries only measure persons employed in paid employment while some countries measure “all persons engaged”, meaning paid employees plus working proprietors who receive some remuneration based on corporate shares. Other possible variations to the norms pertaining to measurement of total employment include hours limits (beyond one hour) placed on contributing family members before for inclusion in employment.¹⁴ Comparisons can also be problematic when the frequency of data collection varies. The range of information collection can run from one month to 12 months in a year. Given the fact that seasonality of various kinds is undoubtedly present in all countries, employment figures can vary for this reason alone. Also, changes in the level of employment can occur throughout the year, but this can be obscured when fewer observations are available.

Employment by status in employment

Introduction

This indicator provides information on how people’s jobs are classified based on the associated type of economic risk and the type of authority of job incumbents over establishments and other workers. ILOSTAT contains statistics from national sources on employment by status in employment, also disaggregated by sex, available using both aggregate and detailed categories of status in employment. ILOSTAT also includes ILO modelled estimates of status in employment by sex, which contain both nationally reported and imputed data, and where all estimates are national, meaning there are no geographic limitations in coverage.¹⁵

Concepts and definitions

The classification by status in employment refers to inherent characteristics of the jobs held by the employed population. Jobs can be classified with respect to the type of explicit or implicit contract of employment the person has with other persons or organizations. The basic criteria used to define the groups of the classification are the type of economic risk and the type of authority over establishments and other workers which the job incumbents have.

Data presented by status in employment is based on the 1993 International Classification of Status in Employment (ICSE-93). The ICSE-93 classifies jobs into five main categories, which can be grouped under two main types of jobs: paid employment jobs (employees) and self-employment jobs (employers, own-account workers, contributing family workers and members of producers’ cooperatives). A sixth category is reserved for workers not classifiable by status.¹⁷

Employees are those workers who hold the type of jobs defined as “paid employment jobs”, where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work. Employers are those workers who, working on their own account or with one or a few partners, hold the type of jobs defined as a “self- employment jobs” (i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced), and, in this capacity, have engaged, on a continuous basis, one or more persons to work for them as employee(s). Own-account workers are those workers who, working on their own account or with one or more partners, hold the type of jobs defined as “self-employment jobs”, and have not engaged on a continuous basis any employees to work for them. Members of producers’ cooperatives are workers who hold “self-employment jobs” in a cooperative producing goods and services. Contributing family workers are those workers who hold “self-employment jobs” as own-account workers in a market-oriented establishment operated by a related person living in the same household.

Statistics on employment by status in employment are presented in ILOSTAT according to both the categories of the ICSE-93 and the two major groups employees and the self-employed. It is worth noting that the ICSE-93 was updated with ICSE-18, although most countries have not yet implemented the latest classification. For information on this classification, refer to the ICSE page.

Interpretation and uses

This indicator provides information on the distribution of the workforce by status in employment and can be used to answer questions such as what proportion of employed persons in a country (a) work for wages or salaries; (b) run their own enterprises, with or without hired labour; or (c) work without pay within the family unit?

Breaking down employment information by status in employment provides a statistical basis for describing workers’ conditions of work and for defining an individual’s socio-economic group. A high proportion of wage and salaried workers in a country typically signifies advanced economic development. If, on the other hand, the proportion of own- account workers (self-employed without hired employees) is sizeable, it may be an indication of a large agriculture sector and low growth in the formal economy. Contributing family work is a form of labour – generally unpaid, although compensation might come indirectly in the form of family income – that supports production for the market. It is particularly common among women, especially women in households where other members engage in self-employment, specifically in running a family business or in farming. Where large shares of workers are contributing family workers, there is likely to be poor development, little job growth, widespread poverty and often a large rural economy.

Own-account workers and contributing family workers have a lower likelihood of having formal work arrangements, and are therefore more likely to lack elements associated with decent employment, such as adequate social security and a voice at work. Therefore, the two statuses are summed to create a classification of ‘vulnerable employment’, while wage and salaried workers together with employers constitute ‘non-vulnerable employment’. The vulnerable employment rate, which is the share of vulnerable employment in total employment, was an indicator of the (now finished) Millennium Development Goals, under the employment, target on decent work.

The indicator of status in employment is strongly linked to the employment by economic activity indicator. Economic development is typically associated with a shift in employment from the agricultural to the industrial and services sectors, which, in turn, is reflected in an increase in the number of wage and salaried workers. A shrinking share of employment in agriculture would also result in a lower proportion of contributing family workers, who are often widespread in the rural sector in developing economies.

Limitations

A number of factors can limit the comparability of statistics on status in employment between countries or over time. Comparability of employment statistics across countries is affected most significantly by variations in the definitions used for the employment figures. Differences can result from age coverage, such as the lower and upper bounds for labour force activity. Estimates of employment are also likely to vary according to whether members of the armed forces are included. Another area with scope for measurement differences has to do with the national treatment of particular groups of workers. The international definition of employment calls for inclusion of all persons who worked for at least one hour during the reference period.¹⁸ Workers could be in paid employment or in self-employment, including in less obvious forms of work, some of which are dealt with in detail in the resolution adopted by the 19th ICLS, such as unpaid family work, apprenticeship or non-market production. The majority of exceptions to coverage of all persons employed in a labour force survey have to do with national variations to the international recommendation applicable to the alternate employment statuses. For example, some countries measure persons employed in paid employment only and some countries measure “all persons engaged”, meaning paid employees plus working proprietors who receive some remuneration based on corporate shares. Other possible variations to the norms pertaining to measurement of total employment include hours limits (beyond one hour) placed on contributing family members before for inclusion in employment.¹⁹ Comparisons can also be problematic when the frequency of data collection differs. The range of data collection can run from one month to 12 months in a year. Given the fact that seasonality of various kinds is undoubtedly present in all countries, employment figures can vary for this reason alone. Some countries group together some of the ICSE categories (including for example members of producers’ cooperatives with wage and salaried workers, or own-account workers with employers), affecting the comparability of the statistics. Importantly, the classification by status in employment does not provide information about finer distinctions in working status (for instance, whether workers have casual or regular contracts and the kind of protection the contracts provide against dismissals).

Employment-to-population ratio

Introduction

The employment-to-population ratio is defined as the proportion of a country’s working-age population that is employed. A high ratio means that a large proportion of a country’s population is employed, while a low ratio means that a large share of the population is not involved directly in market-related activities, because they are either unemployed or (more likely) out of the labour force altogether.

ILOSTAT contains statistics from national sources on employment-to-population ratios by sex and age, and rural/urban areas. ILOSTAT also includes ILO modelled estimates of employment-to-population ratios by sex and age, which contain both nationally reported and imputed data, and where all estimates are national, meaning there are no geographic limitations in coverage. Further information on the methodology used to produce ILO modelled estimates is provided here.

Concepts and definitions

The employment-to-population ratio is the proportion of a country’s working-age population that is employed. Employment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).²⁰

The working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices. For many countries, this age corresponds directly to societal standards for education and work eligibility. However, in some countries, particularly developing ones, it is often appropriate to include younger workers because “working age” can, and often does, begin earlier. Some countries in these circumstances use a lower official bound and include younger workers in their measurements. Similarly, some countries have an upper limit for eligibility, such as 65 or 70 years, although this requirement is imposed rather infrequently.

The population base for employment-to-population ratios can vary across countries for issues other than differences in age limits. In most cases, the resident non-institutional population of working age living in private households is used, excluding members of the armed forces and individuals residing in mental, penal or other types of institutions. Many countries, however, include the armed forces in the population base for their employment-to-population ratios even when they do not include them in the employment figures. In general, information for this indicator is derived from household surveys, mainly labour force surveys. Some countries, however, use “official estimates” or population censuses as the source of their employment figures.

Method of computation

The employment-to-population ratio (EPR) is calculated as follows:

EPR (%) = 100 x Persons employed / Working-age population

For a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:

EPRw (%) = 100 x Employed women / Working-age women

Interpretation and uses

The employment-to-population ratio provides information on the ability of an economy to create employment; for many countries the indicator is often more insightful than the unemployment rate. Although a high overall ratio is typically considered as positive, the indicator alone is not sufficient for assessing the level of decent work or decent work deficits.²¹ Additional indicators are required to assess such issues as earnings, hours of work, informal sector employment, underemployment and working conditions. In fact, the ratio could be high for reasons that are not necessarily positive – for example, where education options are limited, young people tend to take up any work available rather than staying in school to build their human capital. For these reasons, it is strongly advised that indicators should be reviewed collectively in any evaluation of country-specific labour market policies.

The notion that employment – specifically, access to decent work – is central to poverty reduction was firmly acknowledged in the framework of the Millennium Development Goals (MDGs) with the adoption of an employment-based target under the goal of halving the share of the world’s population living in extreme poverty. The employment-to-population ratio was adopted as one of four indicators to measure progress towards target 1b on “achieving full and productive employment and decent work for all, including women and young people”.²² After the MDGs came to an end in 2015, the crucial role of decent work in poverty reduction was reinforced in the Sustainable Development Goals (SDGs). In fact, the eighth SDG constitutes the goal of “promoting inclusive and sustainable economic growth, employment and decent work for all”.²³

Employment-to-population ratios are becoming increasingly common as a basis for labour market comparisons across countries or groups of countries. Employment numbers alone are inadequate for purposes of comparison unless expressed as a share of the population who could be working. One might assume that a country employing 30 million persons is better off than a country employing 3 million persons, whereas the addition of the working-age population component would show another picture; if there are 3 million persons employed in Country A out of a possible 5 million persons (60 per cent employment-to-population ratio) and 30 million persons employed in Country B out of a possible 70 million (43 per cent employment-to-population ratio), then the employment-generating capacity of Country A is superior to that of Country B. The use of a ratio helps determine how much of the population of a country – or group of countries – is contributing to the production of goods and services.

Employment-to-population ratios are of particular interest when broken down by sex, as the ratios for men and women can provide information on gender differences in labour markets. However, it should also be emphasized that this indicator has a gender bias insofar as there is a tendency to under-count women who do not consider their work as “employment” or are not perceived by others as “working”. Women are often the primary child caretakers and responsible for various tasks at home, which can prohibit them from seeking paid employment, particularly if they are not supported by socio-cultural attitudes and/or family-friendly policies and programmes that allow them to balance work and family responsibilities.

Limitations

Comparability of employment-to-population ratios across countries is affected most significantly by variations in the definitions used for the employment and population figures. Differences result from age coverage, such as the lower and upper bounds for labour force activity. Estimates of both employment and population are also likely to vary according to whether members of the armed forces are included. Another area with scope for measurement differences has to do with the national treatment of particular groups of workers. The international definition of employment calls for inclusion of all persons who worked for at least one hour during the reference period.²⁴ Workers could be in paid employment or in self-employment, including in less obvious forms of work, some of which are dealt with in detail in the resolution adopted by the 19th ICLS, such as unpaid family work, apprenticeship or non-market production. The majority of exceptions to coverage of all persons employed in a labour force survey have to do with national variations to the international recommendation applicable to the alternate employment statuses. For example, some countries measure persons employed in paid employment only and some countries measure “all persons engaged”, meaning paid employees plus working proprietors who receive some remuneration based on corporate shares. Other possible variations to the norms pertaining to measurement of total employment include hours limits (beyond one hour) placed on contributing family members for inclusion in employment.²⁵ Comparisons can also be problematic when the frequency of data collection varies. The range of information collection can run from one month to 12 months in a year. Given the fact that seasonality of various kinds is undoubtedly present in all countries, employment-to-population ratios can vary for this reason alone. Countries with employment-to-population ratios based on less than full-year survey periods can be expected to have ratios that are not directly comparable with those from full-year, month-by-month collections. For example, an annual average based on 12 months of observations, all other things being equal, is likely to be different from an annual average based on four (quarterly) observations.

Informality

Introduction

The informal sector represents an important part of the economy, and certainly of the labour market, in many countries. It also plays a major role in employment creation, production and income generation. In lower-income countries with high rates of population growth or urbanization, the informal sector tends to absorb most of the expanding labour force in the urban areas. Informal employment offers a necessary survival strategy in countries that lack social safety nets, such as unemployment insurance. In these situations, indicators such as the unemployment rate and time-related underemployment are not sufficient to describe the labour market completely. Statistics on informality are key to assess the quality of employment in an economy, and are relevant to both developing and developed countries.

ILOSTAT presents statistics from national sources on various indicators pertaining to informality including levels and shares of informal employment and employment outside the formal sector (as a per cent of total employment), disaggregated by sex and other classifications.

Concepts and definitions

Concepts and definitions are based on the Resolution concerning statistics on the informal economy, adopted by the 21st ICLS in 2023.

Informal employment comprises persons who in their main or secondary jobs were:

Own-account workers, employers and members of producers’ cooperatives employed in their own informal sector enterprises. The informal nature of their jobs follows directly from the characteristics of the enterprise.
Own-account workers engaged in the production of goods exclusively for own final use by their household (e.g. subsistence farming or do-it-yourself construction of own dwellings), if covered.
Contributing family workers, irrespective of whether they work in formal or informal sector enterprises. The informal nature of their jobs is due to the fact that contributing family workers usually do not have explicit, written contracts of employment, and that usually their employment is not subject to labour legislation, social security regulations or collective agreements.
Employees holding informal jobs, whether employed by formal sector enterprises, informal sector enterprises, or as paid domestic workers by households. Employees are considered to have informal jobs if their employment relationship is, in law or in practice, not subject to national labour legislation, income taxation, social protection or entitlement to certain employment benefits (paid annual or sick leave, etc.) for reasons such as: non-declaration of the jobs or the employees; casual jobs or jobs of a limited short duration; jobs with hours of work or wages below a specified threshold (e.g. for social security contributions); employment by unincorporated enterprises or by persons in households; or jobs for which labour regulations are not applied, not enforced, or not complied with for any other reason. Operational criteria used by countries to define informal jobs of employees include:
- Lack of coverage by social security system;
- Lack of entitlement to paid annual or sick leave;
- Lack of written employment contract.

Employment outside the formal sector includes persons who are employed in the informal sector and in households, the latter of which is mainly comprised of persons employed by households as paid domestic workers. Employment in the informal sector refers all persons who, during a given reference period, were employed in at least one informal sector enterprise, irrespective of their status in employment and whether it was their main or a secondary job. An informal sector enterprise satisfies the following criteria:

It is an unincorporated enterprise, which means that:
- It is not constituted as a legal entity separate from its owners, and
- It is owned and controlled by one or more members of one or more households, and
- It is not a quasi-corporation (it does not have a complete set of accounts, including balance sheets);
It is a market enterprise: this means that it sells at least some of the goods or services it produces. It therefore excludes households employing paid domestic workers;
And at least one of the following criteria:
- The number of persons engaged / employees / employees employed on a continuous basis, is below a threshold determined by the country
- The enterprise is not registered
- The employees of the enterprise are not registered.

Statistics presented in ILOSTAT refer to the main job of employed persons, as the required information to assess (in)formality of the second job is usually not available.

The harmonized series on informality are derived by the Department of Statistics from processing national household survey microdata files using a consistent navigational path. The process involves identifying the production unit (formal sector, informal sector or household) and the nature of the job (formal job or informal job) of each employed person in their main job in order to derive the final indicators.

First, the unit of production is identified as either formal sector, informal sector or household. The operational definitions used are:

Informal sector: All workers in unincorporated enterprises that produce at least partly for the market and are not registered. It excludes households that produce exclusively for own final use, subsistence agriculture, construction of own dwellings, etc.
Formal sector: all workers in incorporated enterprises.
Household: All workers in unincorporated enterprises that produce goods and services exclusively for own final use. It includes paid domestic employees, subsistence agriculture, construction of own dwellings, manufacture of own wearing apparel, own furniture, water and fuel collection for own use, among others.

If households cannot be identified, only the formal and informal sectors are tabulated. This occurs in many cases and as such, it is the rationale for deriving the final indicator on employment outside the formal sector, i.e. with the informal sector and households combined since these often cannot be differentiated.

The definitions are derived from the following criteria:

In any of the scenarios, if one of the questions is not asked, the step is skipped to move on to the next step in the flow diagram. The variables in the flow diagram are defined as follows:

Institutional sector refers to the legal organization and ownership. Government, all corporations and non-profit institutions are considered in the formal sector while owners who are persons or households, not legal persons, are categorized as households.
Destination of production captures whether the economic unit produces at least some goods or services for sale (identified as those that sell at least partly for the market, if relevant in the country context).
Only for employees: Social security coverage refers to whether an employee is affiliated to a social security schemes related to that job. If the social security coverage cannot be established through a direct question, it may be defined using a proxy question on entitlement to a pension fund such as: “Does your employer pay contributions to a pension fund for you?”
Bookkeeping refers to whether the economic unit maintains a set of accounts required by law (e.g., balance sheets); it is enough that the economic unit keeps some official accounts to be considered as formal (excludes quasi-corporations).
Registration refers to whether the economic unit is registered under national legislation, such as registration with social security authorities, sales or income tax authorities (which should be at a national level). Being in the process of registration is considered as not registered.

The second step is to identify the nature of the job, i.e., whether the person is in formal or informal employment. The operational definitions are:

Informal employment includes persons who are:
- Employees (or persons not classified by status in employment) not protected by national labour legislation in that job, which includes:
  - Employees not affiliated to a social security schemes related to the job (or as a proxy pension funds), and
  - Employees not entitled to certain employment benefits, such as paid annual vacation and paid sick leave
  - (NOTE: If none of these questions are asked, the variable based on nature of job is not produced);
- Entrepreneurs in a unit of production that is considered informal, where entrepreneurs refer to employers, members of producers’ cooperatives and own account workers (only if what is produced is for sale); and
- Contributing family workers.
Formal employment refers to persons who are employed and are not in informal employment according to the above criteria.

The definitions are derived from the following criteria:

Method of computation

From the process described above, the level figures are obtained for four variables – formal sector; outside the formal sector, which includes the informal sector and households; formal employment; and informal employment – from which the shares in total employment are calculated, as follows:

Share of informal employment in total employment = Informal employment / Total employment x 100

Share of employment outside the formal sector = Informal sector and households / Total employment x 100

Interpretation and uses

The informal economy represents a challenge to policy-makers that pursue the following goals: improving the working conditions and legal and social protection of persons in informal sector employment and for employees in informal jobs; increasing the productivity of informal economic activities; developing training and skills; organizing informal sector producers and workers; and implementing appropriate regulatory frameworks, governmental reforms, and urban development. Poverty, too, as a policy issue, overlaps with the informal economy. There is a link – although not a perfect correlation – between informal employment and being poor. This stems from the lack of labour legislation and social protection covering workers in informal employment, and from the fact that persons in informal employment earn, on average, less than workers in formal employment.

Statistics on informal employment are essential for a full assessment of the contributions of all workers, women in particular, to the economy. Indeed, the informal economy has been considered as “the fallback position for women who are excluded from paid employment. (…) The dominant aspect of the informal economy is self-employment. It is an important source of livelihood for women in the developing world, especially in those areas where cultural norms bar them from work outside the home or where, because of conflict with household responsibilities, they cannot undertake regular employee working hours”.²⁶

Limitations

The concept of informal sector was consciously kept flexible in order to accommodate differing country situations and specific country needs. In practice, this has led to a collection of national statistics on employment in the informal sector, with countries reporting on their preferred variation of the criteria laid out in the international resolution. Some countries apply the criterion of non-registered enterprises but registration requirements can vary from country to country. Others apply the employment size criterion only (which also may vary from country to country) and other countries apply a combination of the two. As a result of the national differences in definitions and coverage, the international comparability of the nationally-reported informal sector data is limited. Problems with data comparability for the measure of the informal sector result especially from the following factors: differences in data sources; differences in geographic coverage; differences in the branches of economic activity covered; differences in the criteria used to define the informal sector, for example, size of the enterprise or establishment versus non-registration of the enterprise or the worker; different cut-offs used for enterprise size; inclusion or exclusion of paid domestic workers; and inclusion or exclusion of persons who have a secondary job in the informal sector but whose main job is outside the informal sector. As with the concept of the informal sector, the concept of informal employment was designed in such a way as to allow countries to accommodate their own situations and needs, which hinders comparability across countries. Given the lack of international comparability that arises from the flexibility of the concepts, the ILO developed a harmonized series on informal sector and informal employment. This was achieved by applying a consistent navigational path in processing household microdata files to define the production unit and nature of the job, thereby greatly reducing the variability of definitions used across countries. However, this does not imply that all criteria can be applied equally since each country’s questionnaire will contain different sets of questions. As such, comparability issues remain even in the harmonized series. As expected, there can be significant differences between the nationally-reported figures and those of the harmonized series, despite being based on the same household surveys.

Unemployment rate

Introduction

The unemployment rate is probably the best-known labour market measure and certainly one of the most widely quoted by media in many countries. The unemployment rate is a useful measure of the underutilization of the labour supply. It reflects the inability of an economy to generate employment for those persons who want to work but are not doing so, even though they are available for employment and actively seeking work. It is thus seen as an indicator of the efficiency and effectiveness of an economy to absorb its labour force and of the performance of the labour market.

Given its usefulness in conveying valuable information on a country’s labour market situation and the fact that it is widely recognized as a headline labour market indicator, it was included as one of the indicators to measure progress towards the achievement of the Sustainable Development Goals (SDG), under Goal 8 (Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all).²⁷

ILOSTAT contains statistics from national sources on unemployment rates by sex and age, rural/urban areas, disability status and education. ILOSTAT also includes ILO modelled estimates of unemployment rates by sex and age, which contain both nationally reported and imputed data, and where all estimates are national, meaning there are no geographic limitations in coverage. Further information on the methodology used to produce ILO modelled estimates is provided here.

Concepts and definitions

The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labour force. The labour force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed.²⁸ Thus, the measurement of the unemployment rate requires the measurement of both employment and unemployment.

The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labour market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programmes, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.

In many national contexts there may be persons not currently in the labour market who want to work but do not actively “seek” work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or other structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (in the past often called the “hidden unemployed” or the “unemployed according to the relaxed definition”, which also included persons formerly known as “discouraged workers”) is a criterion that affects the count of both women and men, although women may have a higher probability of being excluded from the count of unemployed because they face greater social barriers impeding them from meeting this criterion. Another factor leading to exclusion from the unemployment count concerns the criterion that workers are available for work during a given (short) reference period. A short availability period tends to exclude those who would need to make personal arrangements before starting work, such as for child care or other household affairs, even if they are “available for work” soon after the short reference period. As women are often responsible for household affairs and care, they represent a significant part of this group.

With a view to overcoming these limitations of the concept of unemployment, and in order to acknowledge the two population groups mentioned above (persons without work but either not available or not actively seeking work), the 19th ICLS resolution introduced the concept of the “potential labour force”. This potential labour force comprises “unavailable jobseekers”, defined as persons who sought employment even though they were not available, but would become available in the near future, and “available potential jobseekers”, defined as persons who did not seek employment but wanted it and were available. Thus, persons without work formerly included in the “relaxed definition” of unemployment are now comprised in the potential labour force. The 19th ICLS resolution also identifies a particular group within the available potential jobseekers, the “discouraged jobseekers”, made up of those persons available for work but who did not seek employment for labour market-related reasons (such as the past failure to find a suitable job or the lack of experience).²⁹

Method of computation

The unemployment rate (UR) is calculated as follows:

UR = 100 x Persons unemployed / Labour force

For a given component group of the labour force, the UR is the percentage of this group that is unemployed. For example, the UR for women would be calculated as:

URw (%) = 100 x Unemployed women / Women in the labour force

Interpretation and uses

Even though in most developed countries the unemployment rate continues to prove its usefulness as an important indicator of labour market performance, and specifically, as a key measure of labour underutilization, in many developing countries, the significance and meaning of the unemployment rate could be questioned. In the absence of unemployment insurance systems or social safety nets, persons of working age must avoid unemployment, resorting to engaging in some form of economic activity, however insignificant or inadequate. Thus, in this context, other measures should supplement the unemployment rate to comprehensively assess labour underutilization, such as time-related underemployment and potential labour force indicators.

Regarding the international comparability of unemployment rates, there are a host of reasons why the statistics may not be comparable between countries. Where the information is based on household surveys or population censuses, differences in the questionnaires can lead to different statistics − even allowing for full adherence to ILO guidelines. In other words, differences in the measurement tool can affect the comparability of results across countries. Also, national statistical offices, even when basing themselves on the ILO conceptual guidelines, may not follow the strictest measurement of employment and unemployment. They may differ in their choices concerning the conceptual basis for estimating unemployment. They may also choose to derive the unemployment rate from the civilian labour force rather than the total labour force. There may also be variations in the operational criteria used to define individuals’ job search activities (methods of job search included, reference period used, etc.).

Statistics for any given year can also differ depending on the number of observations − monthly, quarterly, once or twice a year, and so on. Among other things, a considerable degree of seasonality can influence the results when the full year is not covered.

The geographic coverage of the underlying survey or other data source also has an impact on the comparability of the resulting statistics. Geographic coverage limitations – urban areas, city, regional areas only – results in obvious limitations to comparability to the extent that coverage is not representative of the country as a whole.

Limitations

The overall unemployment rate for a country is a widely used measure of its unutilized labour supply. If employment is taken as the desired situation for people in the the labour force, unemployment is clearly an undesirable situation. Still, some short-term unemployment can be necessary for ensuring adjustment to economic fluctuations. Unemployment rates by specific groups, defined by age, sex, occupation or industry, are also useful in identifying groups of workers and sectors most vulnerable to joblessness. While the unemployment rate may be considered the most informative labour market indicator, reflecting the general performance of the labour market and the economy as a whole, it should not be interpreted as a measure of economic hardship or of well-being. When based on the internationally-recommended standards, the unemployment rate simply reflects the proportion of the labour force that does not have a job but is available and actively looking for work. It says nothing about the economic resources of unemployed workers or their family members. Its use should, therefore, be limited to serving as a measurement of the utilization of labour and an indication of the failure to find work. Other measures, including income-related indicators, would be needed to evaluate economic hardship. An additional criticism of the aggregate unemployment measure is that it masks information on the composition of the jobless population and therefore misses out on the particularities of the education level, ethnic origin, socio-economic background, work experience, etc. of the unemployed. Moreover, the unemployment rate says nothing about the type of unemployment – whether it is cyclical and short-term or structural and long-term – which is a critical issue for policy makers in the development of their policy responses, especially given that structural unemployment cannot be addressed by boosting market demand only. Paradoxically, low unemployment rates may well disguise substantial poverty, as high unemployment rates can occur in countries with significant economic development and low incidence of poverty. In countries without a safety net of unemployment insurance and welfare benefits, many individuals, despite strong family solidarity, simply cannot afford to be unemployed. Instead, they must eke out a living as best they can, often in the informal economy or in informal work arrangements. In countries with well-developed social protection schemes or when savings or other means of support are available, workers can better afford to take the time to find more desirable jobs. Therefore, the problem in many developing countries is not so much unemployment but rather the lack of decent and productive work, which results in various forms of labour underutilization (i.e. underemployment, low income, and low productivity).³⁰ A useful purpose served by the unemployment rate in a country, when available on at least an annual basis, is the tracking of business cycles. When the rate is high, the country is unable to provide sufficient numbers of jobs for the available workers and it could be a sign of economic recession. The goal, then, is to introduce policies and measures to bring the incidence of unemployment down to a more acceptable level. What that level is, or should be, has often been the source of considerable discussion, as many consider that there is a point below which an unemployment rate cannot fall without the occurrence of inflationary pressures. Because of this supposed trade-off, the unemployment rate is closely tracked over time. The usual policy goal of governments, employers and trade unions is to have a rate that is as low as possible, yet also consistent with other economic and social policy objectives, such as low inflation and a sustainable balance-of-payments situation. When using the unemployment rate as a gauge for tracking cyclical developments, we are interested in looking at changes in the measure over time. In that context, the precise definition of unemployment used (whether a country-specific definition or one based on the internationally-recommended standards) does not matter nearly as much – so long as it remains unchanged – as the fact that the statistics are collected and disseminated with regularity, so that measures of change are available for study. Internationally, the unemployment rate is frequently used to compare how labour markets in specific countries differ from one another or how different regions of the world contrast in this regard. Unemployment rates may also be used to address issues of gender differences in labour force behaviour and outcomes. The unemployment rate has often been higher for women than for men. Possible explanations are numerous but difficult to quantify; women are more likely than men to exit and reenter the labour force for family-related reasons; and there is a general “crowding” of women into fewer occupations than men so that women may find fewer opportunities for employment. Other gender inequalities outside the labour market, for example in access to education and training, also negatively affect how women fare in finding jobs.

Time-related underemployment rate

Introduction

The time-related underemployment rate is a measure of labour underutilization that provides information regarding the share of employed persons who are willing and available to increase their working time (for production within the SNA production boundary) and worked fewer hours than a specified time threshold during the reference period. It signals inadequate employment and complements other indicators of labour slack and labour underutilization such as the unemployment rate and the potential labour force.

ILOSTAT contains statistics from national sources on time-related underemployment by sex and age, as well as modelled estimates.

Concepts and definitions

Persons in time-related underemployment comprise all persons in employment who satisfy the following three criteria during the reference period: a) are willing to work additional hours; b) are available to work additional hours i.e., are ready, within a specified subsequent period, to work additional hours given opportunities for additional work; and c) worked less than a threshold relating to working time (i.e., persons whose hours actually worked in all jobs during the reference period were below a threshold, to be chosen according to national circumstances).

Regarding the first criterion, workers should report that they want another job or jobs in addition to their current employment, that they want to replace any of their current jobs with another job or jobs with increased hours of work, that they want to increase the hours of work of any of their current jobs or that they want a combination of the above. This criterion also encompasses those persons who actively seek to work additional hours, using for this purpose the same definition of job search as in the measurement of unemployment.

Examples of practices used to determine the working time threshold include the boundary between full-time and part-time employment; median values, averages, or norms for hours of work as specified in relevant legislation; and collective agreements or agreements on working time arrangements or labour practices in countries.

Method of computation

The time-related underemployment rate (TRU) is calculated as follows:

TRU (%) = 100 x Persons in time-related underemployment / Persons employed

Interpretation and uses

Underemployment reflects under-utilization of the productive capacity of the labour force. The concept of underutilization is a complex one with many facets. In order to draw a more complete picture of underutilization, one needs to examine a set of indicators which includes but is not limited to labour force, employment-to-population ratios, inactivity rates, status in employment, working poverty and labour productivity. Utilizing a single indicator to grasp labour underutilization will provide an incomplete picture.

Underemployment has been broadly interpreted and has come to be used to imply any sort of employment that is “unsatisfactory” (as perceived by the worker) in terms of insufficient hours, insufficient compensation or insufficient use of one’s skills. The fact that the judgement about underemployment is based on personal assessment makes it a concept that is difficult to quantify and to interpret. It is better to deal with the more specific (more quantifiable) components of underemployment separately. “Visible” underemployment can be measured in terms of hours of work (time-related underemployment), whereas “invisible” underemployment, which is measured in terms of income earned from the activity, low productivity, or the extent to which education or skills are underutilized or mismatched, are much more difficult to quantify. Time-related underemployment is the only component of underemployment to date that has been agreed on and properly defined within the international community of labour statisticians.

Statistics on time-related underemployment are useful as a supplement to information on employment and unemployment, particularly the latter, as they enrich an analysis of the efficiency of the labour market in terms of the ability of the country to provide full employment to all those who want it. In fact, the resolution adopted by the 19th ICLS in 2013, restated the definition of time-related underemployment and its central role as a measure of labour underutilization. A new indicator meant to account for time-related underemployment and to supplement the unemployment rate was also introduced, the “combined rate of time-related underemployment and unemployment” (calculated as the number of persons in unemployment or time-related underemployment as a percentage of the labour force). Thus, the indicator on time-related underemployment can provide insights for the design, implementation and evaluation of employment, income and social policies and programmes. Particularly in developing economies, people only rarely fall under the clear-cut dichotomy of either “employed” or “unemployed”. Rather, many workers will be the underemployed who eke out a living from small-scale agriculture and other types of informal activities.

Whereas unemployment is the most common indicator used to assess the performance of the labour market, in isolation it does not provide sufficient information for an understanding of the shortcomings of the labour market in a country. Low unemployment rates do not necessarily mean that the labour market is healthy. The low rates may mask the fact that a considerable number of workers work fewer hours, earn lower incomes, use their skills less, and, in general, work less productively than they could do and would like to do. As a result, many are likely to be competing with the unemployed in their search for alternative jobs and a clearer picture of the underutilization of the labour force can be gained by adding the number of underemployed to the number of unemployed as a share of the overall labour force. Therefore, the time-related underemployment indicator can assist in building a better understanding of the true employment situation.

Limitations

National definitions of time-related underemployment vary significantly between countries, as do the operational criteria used, affecting the comparability of the data. Most definitions include persons whose “hours actually worked” during the reference week were below a certain threshold. Some definitions include persons whose “hours usually worked” were below a certain threshold and other definitions include both groups of workers. Perhaps because no international definition of “part time” work exists, national determinations of hourly thresholds are not always consistent. In a few countries, the threshold is defined in terms of the legal hours or the usual hours worked by full-time workers. Some countries inquire directly as to whether workers work part time, or define the threshold in terms of the worker’s own usual hours of work. As a consequence, the threshold used varies significantly from country to country.

Share of youth not in employment, education or training (youth NEET rate)

Introduction

The share of youth not in education, employment or training (also known as “the NEET rate”) conveys the number of young persons not in education, employment or training as a percentage of the total youth population. It provides a measure of youth who are outside the educational system, not in training and not in employment, and thus serves as a broader measure of potential youth labour market entrants than youth unemployment, since it also includes young persons outside the labour force not in education or training. This indicator is also a better measure of the current universe of potential youth labour market entrants compared to the youth inactivity rate, as the latter includes those youth who are not in the labour force and are in education, and thus cannot be considered currently available for work.

Given its usefulness in conveying valuable information on the labour market situation of a country’s young population, it was included as one of the indicators to measure progress towards the achievement of the Sustainable Development Goals (SDG), under Goal 8 (Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all).³²

ILOSTAT contains statistics from national sources on youth NEET rates by sex. ILOSTAT also includes ILO modelled estimates of youth NEET rates by sex, which contain both nationally reported and imputed data, and where all estimates are national, meaning there are no geographic limitations in coverage. Further information on the methodology used to produce ILO modelled estimates is provided here.

Concepts and definitions

For the purposes of this indicator, youth is defined as all persons between the ages of 15 and 24 (inclusive).

According to the International Standard Classification of Education (ISCED), education is defined as organized and sustained communication designed to bring about learning. Formal education is defined in ISCED as education that is institutionalized, intentional, and planned through public organizations and recognized private bodies and, in their totality, make up the formal education system of a country. Non-formal education, like formal education is defined in ISCED as education that is institutionalized, intentional and planned by an education provider, but is considered an addition, alternative and/or a complement to formal education. It may be short in duration and/or low in intensity and it is typically provided in the form of short courses, workshops or seminars. Informal learning is defined in ISCED as forms of learning that are intentional or deliberate, but not institutionalized. It is thus less organized and less structured than either formal or non-formal education. Informal learning may include learning activities that occur in the family, in the workplace, in the local community, and in daily life, on a self-directed, family-directed or socially-directed basis. For the purposes of this indicator, persons will be considered in education if they are in formal or non-formal education, as described above, but excluding informal learning.

For the purposes of this indicator, persons are considered to be in training if they are in a nonacademic learning activity through which they acquire specific skills intended for vocational or technical jobs. Vocational training prepares trainees for jobs that are based on manual or practical activities, and for skilled operative jobs, both blue and white collar related to a specific trade, occupation or vocation. Technical training on the other hand imparts learning that can be applied in intermediate-level jobs, in particular those of technicians and middle managers. The coverage of vocational and technical training includes only programmes that are solely school-based vocational and technical training. Employer-based training is, by definition, excluded from the scope of this indicator.

In cases where ILO experts process the household survey microdata in order to produce the indicators published on ILOSTAT, international statistical standards are strictly applied to ensure comparability across countries. Thus, ILOSTAT data may differ from what is nationally reported. The magnitude of the differences depends on the extent to which a country is applying international statistical standards.

Method of computation

The youth NEET rate is calculated as follows:

NEET rate = (Youth – Youth in employment – Youth not in employment but in education or training) / Youth x 100

It is important to note here that youth both in employment and education or training simultaneously should not be double counted when subtracted from the total number of youth. The formula can also be expressed as:

NEET rate = [(Unemployed youth + Youth outside the labour force) – (Unemployed youth in education or training + Youth outside the labour force in education or training)] / Youth x 100

Interpretation and uses

The NEET rate is a broad measure of untapped potential of youth who could contribute to national development through work. Because the NEET group is neither improving their future employability through investment in skills nor gaining experience through employment, this group is particularly at risk of both labour market and social exclusion. In addition, the NEET group is already in a disadvantaged position due to lower levels of education and lower household incomes. In view of the fact that the NEET group includes unemployed youth as well as youth outside the labour force, the NEET rate provides important complementary information to labour force participation rates and unemployment rates. For example, if youth participation rates decrease during an economic downturn due to discouragement, this may be reflected in an upward movement in the NEET rate. More generally, a high NEET rate and a low youth unemployment rate may indicate significant discouragement of young people. A high relative NEET rate for young women suggests their engagement in household chores, and/or the presence of strong institutional barriers limiting female participation in labour markets.

In terms of the analysis of the indicator, in order to avoid misinterpreting it, it is important to bear in mind that it is composed of two different sub-groups (unemployed youth not in education or training and youth outside the labour force not in education or training). The prevalence and composition of each sub-group would have policy implications, and thus, should also be considered when analysing the NEET rate.

Limitations

A number of factors can limit the comparability of statistics on the youth NEET rate between countries or over time.

When differing from international standards, the operational criteria used to define employment and the participation in education or training will naturally affect the comparability of the resulting statistics, as will the coverage of the source of statistics (geographical coverage, population coverage, age coverage, etc.).

NEET rates are calculated preferably for youth defined as persons aged 15 to 24, but when studying these rates it is important to keep in mind that not all persons complete their education by the age of 24.

Short-term indicators

Short-term indicators refer to monthly and quarterly indicators and are available in the Short-Term Labour Force Statistics (STLFS) database. This database provides insights into the most recent employment and labour market trends. Data users should note that fewer countries carry out high frequency surveys to capture these indicators and as such, data for fewer countries are available than in the LFS database with annual data.

Rural and urban areas

Indicators disaggregated by rural and urban areas are available in the Rural and Urban Labour Market Statistics (RURBAN) database. There is no internationally-agreed definition for rural and urban areas. Therefore, the differentiation between these area types is made according to national definitions. Since data are obtained from household surveys, the determination for the area type is based on the location of the household (i.e., the dwelling) rather than that of the job (if any of the household members are employed).

Data sources

Household surveys

Labour force surveys are the preferred source of information for determining the labour force participation rate and related indicators. Such surveys can be designed to cover virtually the entire non-institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labour force in a coherent framework.

Other types of household surveys with an appropriate module on the labour force could also be used as sources of data on the labour force.

Population censuses

Population censuses are another major source of data on the labour force and its components. The labour force participation rates obtained from population censuses, however, tend to be lower, as census forms do not typically allow for detailed probing on the labour market activities of the respondents.

Establishment surveys

In the absence of the above-mentioned sources, establishment surveys or administrative records can provide information on employment by economic activity, but they do not cover the entire employed population (e.g., excludes the self-employed), typically excluding the informal economy, small establishments and some specific economic activities such as public administration or even in some cases agriculture.

Administrative records

Administrative records such as employment office records and social insurance statistics can also serve as sources of unemployment statistics. However, the statistics derived from these administrative records refer to a different unemployment concept: “registered unemployment”. Although statistics on registered unemployment might be useful, they are in no way comparable to the unemployment statistics derived from household surveys following the three-criteria definition (persons not employed, available for work and looking for work). A national count of either unemployed persons or work applicants that are registered at employment offices is likely to be only a limited subset of the total number of unemployed, especially in countries where the system of employment offices is not extensive. This may be because of eligibility requirements that exclude those who have never worked or have not worked recently, or to other impediments to registration. Administrative records can sometimes overstate registered unemployment because of double-counting, failure to remove people from the registers when they are no longer looking for a job, or because it allows inclusion of persons who have done some work during the reference period.

Given the lack of comparability with data from labour force surveys, administrative data are not used for unemployment statistics in any of the LFS-related databases.

Differences with national data

Modelled estimates

The indicators described above are also part of the ILO modelled estimates (ILOEST) database. Refer to the ILOEST database description for the methodology.

Publications

Note: Many publications are available only in English. If available in other languages, a new page will open displaying these options.

ILOSTAT Microdata Processing Quick Guide: Principles and methods underlying the ILO’s processing of anonymized household survey microdata

September 26, 2024

This Quick Guide (last updated in September 2024) presents the anonymized microdata processing undertaken by the Data Production and Analysis Unit in the ILO Department of Statistics. It describes why and how the unit carries out this activity, as well as the potential expansion of this work. It also mentions considerations and limitations to take into account by data users.

Note on the implementation of statistical standards from the 19th, 20th and 21st ICLS through household surveys

July 18, 2024

This note provides an overview of the requirements to apply the latest statistical standards through household surveys.

Own-use provision of services: Measurement guide

November 1, 2023

This guide provides guidance on implementing the ILO add-on module for own-use provision of services (OPS) in national labour force surveys. It is aimed at low- and middle-income countries and is designed to support NSOs to produce statistics on OPS when resource constraints or other considerations impede an independent time-use survey.

Quick guide to understanding the impact of the new statistical standards on ILOSTAT databases

September 5, 2022

This quick guide explains the differences between the 13th and 19th ICLS standards, the impact of the revisions on headline indicators, and how the ILO handles this on ILOSTAT.

Global review of impacts of the COVID-19 pandemic on labour force surveys and dissemination of labour market statistics

September 30, 2021

In March 2021, the ILO undertook a global survey of national data producers to understand the impacts of the pandemic on their statistical operations particularly in the domain of labour statistics.

COVID-19 impact on labour market statistics

May 11, 2020

The restrictions necessary to combat COVID-19 pose a huge obstacle to data collection operations, precisely when there is a massive increase in demand for information. The ILO reached out to national data producers to understand the impacts of the pandemic on their statistical operations particularly in the domain of labour statistics. Last update: May 2020

Guidance to data producers to maintain labour force survey data collection

April 29, 2020

The most immediate impact of the pandemic on LFS data collection for most countries is the suspension of face-to-face interviewing. This note provides guidance to countries on the range of options available and challenges to deal with in order to change their data collection approach and maintain continuity in data availability.

Essential labour force survey content and treatment of special groups

April 8, 2020

International standards are still sound reference, but due to this unprecedented pandemic, this note provides guidance to data producers to maintain labour force survey (LFS) operations. It highlights the range of topics to prioritize in national LFS and suggested clarifications to support consistent treatment of special cases becoming more prevalent, such as job absences of uncertain duration, business closures, and overall reduced job search activity.

Quick guide on sources and uses of labour statistics

November 3, 2017

This guide walks readers through the basics of labour statistics, from their conception to their final use. It includes key information on sources, standards, concepts, definitions, scope and interpretation of labour statistics, making it a valuable tool for anyone wanting to learn the essentials of labour statistics.

Key Labor Market Indicators: Analysis with Household Survey Data

October 20, 2016

This publication is an introduction to labour market indicator analysis and a guide for analysing household survey data using the ADePT ILO Labour Market Indicators Module. The ADePT module is a powerful tool for producing and analysing KILM indicators using household survey data. The software allows researchers and practitioners to automate data production, to minimize data production errors and to quickly produce a wide range of labour market data from labour force surveys or other household surveys that contain labour market information.

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Table of Contents

Related pages

Overview

Labour force participation rate

Introduction

Concepts and definitions

Method of computation

Interpretation and uses

Limitations

Employment by economic activity

Introduction

Concepts and definitions

Interpretation and uses

Limitations

Employment by occupation

Introduction

Concepts and definitions

Interpretation and uses

Limitations

Employment by status in employment

Introduction

Concepts and definitions

Interpretation and uses

Limitations

Employment-to-population ratio

Introduction

Concepts and definitions

Method of computation

Interpretation and uses

Limitations

Informality

Introduction

Concepts and definitions

Method of computation

Interpretation and uses

Limitations

Unemployment rate

Introduction

Concepts and definitions

Method of computation

Interpretation and uses

Limitations

Time-related underemployment rate

Introduction

Concepts and definitions

Method of computation

Interpretation and uses

Limitations

Share of youth not in employment, education or training (youth NEET rate)​

Introduction

Concepts and definitions

Method of computation

Interpretation and uses

Limitations

Short-term indicators

Rural and urban areas

Data sources

Household surveys

Population censuses

Establishment surveys

Administrative records

Differences with national data

Modelled estimates

Publications

Share of youth not in employment, education or training (youth NEET rate)