In the fourth quarter of 2024, the labor force participation rate peaked among South Africans aged 35 to 44, reaching 79.5 percent. Compared to the same quarter in 2023, there was a no year-on-year change of observed. Among the population between 45 and 54 years old, the participation in the labor market in South Africa was close to 75 percent, which was slightly higher than the 73.3 percent rate recorded for young South Africans (25 to 34 years).

South Africa ZA: Labour Force Participation Rate: National Estimate: Female: Aged 15-24 data was reported at 24.431 % in 2017. This records an increase from the previous number of 23.580 % for 2016. South Africa ZA: Labour Force Participation Rate: National Estimate: Female: Aged 15-24 data is updated yearly, averaging 23.609 % from Dec 1960 (Median) to 2017, with 26 observations. The data reached an all-time high of 27.782 % in 2008 and a record low of 11.260 % in 1960. South Africa ZA: Labour Force Participation Rate: National Estimate: Female: Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Labour Force. Labor force participation rate for ages 15-24 is the proportion of the population ages 15-24 that is economically active: all people who supply labor for the production of goods and services during a specified period.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

South Africa Labour Force Participation Rate: Female: 5-Year Bands: Total Age data was reported at 49.769 % in 2024. This records an increase from the previous number of 49.016 % for 2023. South Africa Labour Force Participation Rate: Female: 5-Year Bands: Total Age data is updated yearly, averaging 47.354 % from Dec 1960 (Median) to 2024, with 30 observations. The data reached an all-time high of 52.895 % in 2001 and a record low of 16.700 % in 1960. South Africa Labour Force Participation Rate: Female: 5-Year Bands: Total Age data remains active status in CEIC and is reported by International Labour Organization. The data is categorized under Global Database’s South Africa – Table ZA.ILO.LFS: Labour Force Participation Rate: By Sex and Age: Annual.

Labor Force Participation Rate in South Africa decreased to 59.70 percent in the third quarter of 2025 from 60.20 percent in the second quarter of 2025. This dataset provides - South Africa Labor Force Participation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

In the fourth quarter of 2023, the labor force participation rate among Black South Africans reached over 59 percent, marking a year-on-year change of two percent compared to the fourth quarter of 2022. However, the participation rate of the labor force among Indian/Asian South Africans dropped from about 61 percent in the previous year to 58 percent.

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The QLFS sample covers the non-institutional population of South Africa with one exception. The only institutional subpopulation included in the QLFS sample are individuals in worker's hostels. Persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

The QLFS uses a master sampling frame that is used by several household surveys conducted by Statistics South Africa. This wave of the QLFS is based on the 2013 master frame, which was created based on the 2011 census. There are 3324 PSUs in the master frame and roughly 33 000 dwelling units.

The sample for the QLFS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.

For each quarter of the QLFS, a quarter of the sampled dwellings are rotated out of the sample. These dwellings are replaced by new dwellings from the same PSU or the next PSU on the list. For more information see the statistical release.

Mode of data collection

Face-to-Face and Computer Assisted Personal and Telephone Interview

Research instrument

The survey questionnaire consists of the following sections: - Biographical information (marital status, education, etc.) - Economic activities for persons aged 15 years and older

South Africa Labour Force Participation Rate: Female: Aggregate Bands: Aged 15-24 data was reported at 24.673 % in 2024. This records a decrease from the previous number of 25.019 % for 2023. South Africa Labour Force Participation Rate: Female: Aggregate Bands: Aged 15-24 data is updated yearly, averaging 23.602 % from Dec 1960 (Median) to 2024, with 30 observations. The data reached an all-time high of 30.022 % in 2002 and a record low of 11.260 % in 1960. South Africa Labour Force Participation Rate: Female: Aggregate Bands: Aged 15-24 data remains active status in CEIC and is reported by International Labour Organization. The data is categorized under Global Database’s South Africa – Table ZA.ILO.LFS: Labour Force Participation Rate: By Sex and Age: Annual.

ABSTRACT: The Labour Force Survey is a twice-yearly rotating panel household survey, specifically designed to measure the dynamics of employment and unemployment in the country. It plans to measure a variety of issues related to the labour market, including unemployment rates (official and expanded), according to standard definitions of the International Labour Organisation (ILO). Demographic variables include Age, gender, level of education, marital status, migration, use of health services, economic activity, unemployment, employment and self-employment.

In the fourth quarter of 2024, the unemployment rate in South Africa was 27.2 percent among workers aged 35 to 44 years. The figure decreased from 27.7 percent in the same quarter of the previous year. This age group corresponded to the largest share of the labor force participation in the country. Among young South Africans (15 to 24 years), the unemployment rate was at its highest, at 59.6 percent.

ZA: Labour Force With Intermediate Education: % of Total Working-age Population data was reported at 62.143 % in 2017. This records an increase from the previous number of 61.765 % for 2016. ZA: Labour Force With Intermediate Education: % of Total Working-age Population data is updated yearly, averaging 60.166 % from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 66.650 % in 2008 and a record low of 27.084 % in 2002. ZA: Labour Force With Intermediate Education: % of Total Working-age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Labour Force. The percentage of the working age population with an intermediate level of education who are in the labor force. Intermediate education comprises upper secondary or post-secondary non tertiary education according to the International Standard Classification of Education 2011 (ISCED 2011).; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average;

Labor force, total in South Africa was reported at 27765994 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. South Africa - Labor force, total - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). The survey collects data on the labour market activities of individuals aged 15 years and above who live in South Africa. The objective of the QLFS is to collect quarterly information about persons in the labour market, i.e., those who are employed; those who are unemployed and those who are not economically active.

The Quarterly Labour Force Survey (QLFS) frame has been developed as a general-purpose household survey frame that can be used by all other household surveys, irrespective of the sample size requirement of the survey. The sample size for the QLFS is roughly 30,000 dwellings per quarter. The sample is based on information collected during the 2001 Population Census conducted by Stats SA. The sample is designed to be representative at provincial level and within provinces at metro/non-metro level. Within the metros, the sample is further distributed by geography type. The four geography types are: urban formal, urban informal, farms, and tribal. This implies, for example, that within a metropolitan area the sample is representative of the different geography types that may exist within that metro.

Geographic coverage

National Coverage

Analysis unit

Members of households aged 15 years or older.

Universe

The QLFS sample covers the non-institutional population except for workers' hostels. However, persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample size for the QLFS is roughly 30,000 dwellings.The sample is based on information collected during the 2001 Population Census conducted by Statistics South Africa (Stats SA). In preparation for Census 2001, the country was divided into 80,787 enumeration areas (EAs). Some of these EAs are small in terms of the number of households that were enumerated in them at the time of Census 2001. The Stats SA household-based surveys use a Master Sample of primary sampling units (PSUs) which comprises EAs that are drawn from across the country. For the purposes of the Master Sample, the EAs that contained fewer than 25 households were excluded from the sampling frame, and those that contained between 25 and 99 households were combined with other EAs of the same geographic type to form primary sampling units (PSUs). The number of EAs per PSU ranges between one and four. On the other hand, very large EAs represent two or more PSUs.

The sample is designed to be representative at provincial level and within provinces at metro/non-metro level. Within the metros, the sample is further distributed by geography type. The four geography types are: urban formal, urban informal, farms, and tribal. This implies that, for example, within a metropolitan area the sample is designed to be representative at the different geography types that may exist within that metro.

The current sample size is 3,080 PSUs. It is equally divided into four subgroups or panels called rotation groups. The rotation groups are designed in such a way that each of these groups has the same distribution pattern as that which is observed in the whole sample. They are numbered from one to four and these numbers also correspond to the quarters of the year in which the sample will be rotated for the particular group.

The sample for the Labour Force Survey is based on a stratified two-stage design with probability proportional to size (PPS) sampling of primary sampling units (PSUs) in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. The sampled PSUs have been assigned to 4 rotation groups, and dwellings selected from the PSUs assigned to rotation group '1' are rotated in the first quarter. Similarly, the dwellings selected from the PSUs assigned to rotation group '2' are rotated in the second quarter, and so on. Thus, each sampled dwelling will remain in the sample for four consecutive quarters. It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for, say 2 quarters, and a new household moves in, then the new household will be enumerated for the next two quarters. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (unoccupied). At the end of each quarter, a quarter of the sampled dwellings rotate out of the sample and are replaced by new dwellings from the same PSU or the next PSU on the list. A total of 3 080 PSUs were selected for the redesigned LFS, and 770 have been assigned to each of the four rotation groups.

Mode of data collection

Face-to-face [f2f]

Research instrument

The QLFS questionnaire was developed in English. The contents of the QLFS questionnaire are summarised as follows:

-Cover page of the QLFS core questionnaire: The cover page contains details that enable the tracking of the questionnaire and monitoring of fieldwork at Head Office, the Provincial offices and District offices. -Section 1 of the QLFS core questionnaire: This section has socio-demographic questions which are completed for all household members regardless of age. -Section 2 of the QLFS core questionnaire: The questions in this section determine those individuals, aged 15-64 years, who are employed and those who are not employed. -Section 3 of the QLFS core questionnaire: This section determines which respondents are unemployed and which respondents are not economically active. -Section 4 of the QLFS core questionnaire: This section contains questions about the work situation of respondents who are employed. It includes questions about the number of jobs at which the respondent works, the hours of work, the industry and occupation of the respondent as well as whether or not the person is employed in the formal or informal sector, etc.

Future improvement to the questionnaire design and analysis include: a) Development of a short core questionnaire (59 questions) to reduce respondent fatigue and facilitate dissemination of results on a quarterly basis. b) Development of automated tables for analysis to ensure minimised manual intervention in the production process. c) Analysis of key results on a quarterly basis to monitor labour market changes on a regular basis. d) Provision of link factors to enable historical continuity with the LFS. e) In-depth analysis of quarterly results on an annual basis.

Cleaning operations

QLFS uses the editing and imputation module to ensure that output data is both clean and complete. There are three basic components, called functions, in the Edit and Imputation Module: Function A: Record acceptance Function B: Edit and imputation Function C: Clean up, derived variables and preparation for weighting

Response rate

Below is a list of response rate by province for the period of January-March 2013: Western Cape: 90.4% Eastern Cape: 98.7% Northern Cape: 90.2% Free State: 97.8% KwaZulu-Natal: 96.8% North West: 93.6% Gauteng: 84.2% Mpumalanga: 91.5% Limpopo: 98.7%

South Africa: 93.1%

Sampling error estimates

Because estimates are based on sample data, they differ from figures that would have been obtained from complete enumeration of the population using the same instrument. Results are subject to both sampling and non-sampling errors. Non-sampling errors include biases from inaccurate reporting, processing, and tabulation etc., as well as errors from non-response and incomplete reporting. These types of errors cannot be measured readily. However, to the extent possible, non-sampling errors can be minimised through the procedures used for data collection, editing, quality control, and non-response adjustment. The variances of the survey estimates are used to measure sampling errors.

Abstract

The Post-Apartheid Labour Market Series (PALMS) is a stacked cross sectional dataset created by DataFirst at the University of Cape Town. The latest (v4) PALMS dataset consists of microdata from 92 household surveys conducted by Statistics South Africa between 1994 and 2025, as well as the 1993 Project for Statistics on Living Standards and Development conducted by SALDRU at UCT. The Statistics South Africa surveys include the October Household Surveys from 1994 to 1999, the bi-annual Labour Force Surveys from 2000-2007, including the smaller LFS pilot survey from February 2000, and the Quarterly Labour Force Surveys from 2008-2025. The data is at individual level, but household level variables may be created using the household id variable uqnr. No attempt has been made to link individuals or households across waves, although there was a rotating panel element to parts of the LFS and as well as the QLFS.

There are currently 120 variables in the main data file and nearly 7.5 million observations, including children and the elderly. The variables included are mainly those to do with the labour market, although some household variables, such as dwelling type and access to services, as well as access to government social grants, are also included for some waves where these were asked. Not all variables from the data from all surveys are included. The surveys are regarded as one of the more reliable sources of labour market data, including earnings. However they generally contain little other income information, except for some incomplete attempts at capturing government grants. The PSLSD and OHSs were more omprehensive but the other forms of income data collected in these surveys have not been included in PALMS. One of the key pieces of value added in PALMS is the creation of a consistent earnings variable over all waves that collected earnings.

Geographic coverage

The surveys used to construct PALMS had national coverage

Analysis unit

Households and individuals

Universe

The target population is all households. Coverage of workers' hostels, convents/monasteries, as well as institutions such as old age homes, hospitals, prisons and military barracks varied across the surveys. Data users will need to consult the individual OHS, LFS and QLFS datasets for information on the universe for each survey.

Kind of data

Survey data

Mode of data collection

Other

South Africa ZA: Labour Force With Advanced Education: % of Total Working-age Population data was reported at 80.460 % in 2017. This records an increase from the previous number of 80.300 % for 2016. South Africa ZA: Labour Force With Advanced Education: % of Total Working-age Population data is updated yearly, averaging 80.580 % from Dec 2008 (Median) to 2017, with 10 observations. The data reached an all-time high of 83.310 % in 2008 and a record low of 79.080 % in 2012. South Africa ZA: Labour Force With Advanced Education: % of Total Working-age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Labour Force. The percentage of the working age population with an advanced level of education who are in the labor force. Advanced education comprises short-cycle tertiary education, a bachelor’s degree or equivalent education level, a master’s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average;

Unemployment Rate in South Africa decreased to 31.90 percent in the third quarter of 2025 from 33.20 percent in the second quarter of 2025. This dataset provides - South Africa Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

As of the second quarter of 2024, nearly 3.83 million people in South Africa worked within the community and social services industry. The sector concentrated the highest number of employees, followed by the trade industry, which employed about 3.36 million people. A struggling labor market The South African labor market faces severe challenges and obstacles. In 2023, the country had the highest unemployment rate in Africa, with almost 30 percent of the labor force being jobless. In addition, only 40 percent of the population was employed in 2021. Indeed, South Africans were the most concerned globally about finding jobs and being unemployed. According to a survey, 64 percent of South African respondents reported being worried about unemployment as of September 2023. A highly unequal country South Africa is the most income-unequal country in the world, as it registered a Gini score of 63 in 2021. The major reasons for this inequality originate from the country’s infamous Apartheid regime and the failure of the job market to provide enough opportunities for its people. For example, the unemployment rate among Black South Africans was close to 37 percent, compared to eight percent for white South Africans. Furthermore, unemployment in the country was more widespread among individuals with a lower level of education. Specifically, in 2023, over 50 percent of the jobless South Africans had an education level lower than matric (grade 12).

The total population of South Africa amounted to approximately 63.20 million people in 2024. Following a continuous upward trend, the total population has risen by around 34.12 million people since 1980. Between 2024 and 2030, the total population will rise by around 5.88 million people, continuing its consistent upward trajectory.This indicator describes the total population in the country at hand. This total population of the country consists of all persons falling within the scope of the census.

South Africa ZA: Labour Force With Basic Education: % of Total Working-age Population data was reported at 40.948 % in 2017. This records an increase from the previous number of 39.994 % for 2016. South Africa ZA: Labour Force With Basic Education: % of Total Working-age Population data is updated yearly, averaging 36.888 % from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 42.452 % in 2012 and a record low of 15.282 % in 2002. South Africa ZA: Labour Force With Basic Education: % of Total Working-age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Labour Force. The percentage of the working age population with a basic level of education who are in the labor force. Basic education comprises primary education or lower secondary education according to the International Standard Classification of Education 2011 (ISCED 2011).; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average;

Abstract

The Post-Apartheid Labour Market Series (PALMS) version 3.3 is a stacked cross sectional dataset created by DataFirst at the University of Cape Town. The data consists of microdata from 69 household surveys conducted by Statistics South Africa between 1994 and 2019, as well as the 1993 Project for Statistics on Living Standards and Development conducted by SALDRU at UCT. The Statistics South Africa surveys include the October Household Surveys from 1994 to 1999, the bi-annual Labour Force Surveys from 2000-2007, including the smaller LFS pilot survey from February 2000, and the Quarterly Labour Force Surveys from 2008-2019. The data is at individual level, but household level variables may be created using the household id variable uqnr. No attempt has been made to link individuals or households across waves, although there was a panel element to the earlier rounds of the LFS, as well as the QLFS.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Universe

The target population is all households. Coverage of workers' hostels, convents/monasteries, as well as institutions such as old age homes, hospitals, prisons and military barracks varied across the surveys. Data users will need to consult the individual OHS, LFS and QLFS datasets for information on the universe for each survey.

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Employment Rate in South Africa increased to 40.70 percent in the third quarter of 2025 from 40.20 percent in the second quarter of 2025. This dataset provides - South Africa Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.