South Africa is expected to register the highest unemployment rate in Africa in 2024, with around ** percent of the country's labor force being unemployed. Djibouti and Eswatini followed, with unemployment reaching roughly ** percent and ** percent, respectively. On the other hand, the lowest unemployment rates in Africa were in Niger and Burundi. The continent’s average stood at roughly ***** percent in the same year. Large shares of youth among the unemployed Due to several educational, socio-demographic, and economic factors, the young population is more likely to face unemployment in most regions of the world. In 2024, the youth unemployment rate in Africa was projected at around ** percent. The situation was particularly critical in certain countries. In 2022, Djibouti recorded a youth unemployment rate of almost ** percent, the highest rate on the continent. South Africa followed, with around ** percent of the young labor force being unemployed. Wide disparities in female unemployment Women are another demographic group often facing high unemployment. In Africa, the female unemployment rate stood at roughly ***** percent in 2023, compared to *** percent among men. The average female unemployment on the continent was not particularly high. However, there were significant disparities among African countries. Djibouti and South Africa topped the ranking once again in 2022, with female unemployment rates of around ** percent and ** percent, respectively. In contrast, Niger, Burundi, and Chad were far below Africa’s average, as only roughly *** percent or lower of the women in the labor force were unemployed.

Unemployment Rate in South Africa increased to 32.90 percent in the first quarter of 2025 from 31.90 percent in the fourth quarter of 2024. This dataset provides - South Africa Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

As of the fourth quarter of 2023, the unemployment rate in South Africa stood at 32.1 percent. The majority of unemployed individuals had an education level below matric (grade 12), while those that had finished their matric year represented around 34 percent. Graduates had the lowest share of unemployment at approximately 10 percent.

In the second quarter of 2024, the unemployment rate among Black South Africans was 36.9 percent, marking a year-on-year change of 0.8 percent compared to the second quarter of 2023. On the other hand, the unemployment rate among white South Africans was 7.9 percent in the second quarter of 2024, with a 0.5 percent year-on-year change. Unemployment prevalent among youth and women The unemployment rate is the share of the labor force population that is unemployed, while the labor force includes individuals who are employed as well as those who are unemployed but looking for work. South Africa is struggling to absorb its youth into the job market. For instance, the unemployment rate among young South Africans aged 15-24 years reached a staggering 60.7 percent in the second quarter of 2023. Furthermore, women had higher unemployment rates than men. Since the start of 2016, the unemployment rate of women has been consistently more than that of men, reaching close to 36 percent compared to 30 percent, respectively. A new minimum wage and most paying jobs      In South Africa, a new minimum hourly wage went into effect on March 1, 2022. The minimum salary reached 23.19 South African rand per hour (1.44 U.S. dollars per hour), up from 21.69 South African rand per hour (1.35 U.S. dollars per hour) in 2021. In addition, the preponderance of employed South Africans worked between 40 and 45 hours weekly in 2021. Individuals holding Executive Management and Change Management jobs were the highest paid in the country, with salaries averaging 74,000 U.S. dollars per year.

In 2023, South Africa had the highest unemployment rate in the world, at 32.1 percent. Of the 10 countries with the highest unemployment rates, six were in Sub-Saharan Africa. What exactly is unemployment? The unemployment rate is the number of people in the workforce currently looking for jobs but not working. This number does not include students and retirees, as they are not looking for work, nor does it include people who have given up on finding a job (known as discouraged workers). Comparing international unemployment rates can be problematic, however, as different countries use different methodologies when classifying unemployment. For example, Niger records the third lowest unemployment rate in the world, despite often being listed as the least developed country worldwide - this is because the majority of the population engage in subsistence farming, with very little opportunity for paid employment. Causes of unemployment in less developed countries A major driver in unemployment in these countries is conflict. In particular, internally displaced persons (IDPs) want to work, but moving to another part of the country disrupts their business network and moves them into a local economy with different labor demand. Countries with low levels of economic development, as roughly indicated by a low GDP per capita, often have fewer labor market opportunities, leading to high unemployment rates.

Youth Unemployment Rate in South Africa increased to 62.40 percent in the first quarter of 2025 from 59.60 percent in the fourth quarter of 2024. This dataset provides - South Africa Youth Unemployment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Employment Rate in South Africa decreased to 40.30 percent in the first quarter of 2025 from 41.10 percent in the fourth quarter of 2024. This dataset provides - South Africa Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

In 2024, the youth unemployment rate in South Africa increased by 1.2 percentage points (+2.01 percent) compared to 2023. In total, the youth unemployment rate amounted to 60.89 percent in 2024. This increase was preceded by a declining youth unemployment rate.The youth unemployment rate of a country or region refers to the share of the total workforce aged 15 to 24 that is currently without work, but actively searching for employment. It does not include economically inactive persons such as full-time students or the long-term unemployed.Find more statistics on other topics about South Africa with key insights such as labor participation rate among the total population aged between 15 and 64, labor force participation rate for males, and female labor force participation rate.

Abstract

The survey is a tracer survey of the 2010 cohort of graduates from the four public universities in the Western Cape. These are the Cape Peninsula University of Technology (CPUT), University of Cape Town (UCT), Stellenbosch University (US), and the University of the Western Cape (UWC). The Survey was initiated and overseen by a reference group of the Cape Higher Education Consortium (CHEC) (representing these universities) with input from the Western Cape Government (WCG), as part of CHEC's ongoing work on graduate attributes. The primary task of the survey was to determine levels of graduate employment and unemployment and to understand the differing pathways from higher education to work. CHEC consultants conducted the survey between September to November 2012.

Geographic coverage

The lowest level of geographic aggregation of the data is Province.

Analysis unit

The survey was designed as a longitudinal survey of all students who graduated in 2010 from one of the four universities in the Western Cape. The survey was ‘longitudinal’ in that it was designed to trace graduates after two years of having obtained a qualification in 2010 and to possibly trace the same graduates further into the future.

Universe

The survey covered all graduates of 2010 at the four public Universities in the Western Cape

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample frame constituted a list of all graduates who received either a certificate, diploma or degree in 2010 at one of the four public universities in the Western Cape. The sample frame was compiled using Higher Education Management Information System (HEMIS) data from each of the four universities.

Mode of data collection

Internet [int]

Research instrument

The survey questionnaire made use of chronological rather than thematic sections to systematically guide the respondent from past to present to future. These included:

Section 1: At high school (which included questions about the graduate’s schooling background); Section 2: At university (which included questions about the graduate’s studies leading up to the qualification obtained in 2010); Section 3: Background, employment and relevance of qualification (which included questions about family background whilst studying, employment before and just after studying, employment as on 1 September 2012, and various questions in relation to different forms of employment or occupation, including relevance of qualification in relation to current employment); Section 4: Current studies (which included questions about qualification type (if studying further), field, reasons for further study); Section 5: Future plans (which included questions about possible future studies, current place of residence, emigration and reasons for emigration).

Response rate

There were a total of 5 560 responses – a response rate of 22.5% of the total of 24 710 graduates. Roughly half these responses were online (2 873 or about 52%) while the other half were from telephonic interviews (2 687 or about 48%). The aggregate response rates for institutions are as follow: CPUT – 21.8%, UCT – 21.9%, SU – 21.6% and UWC – 26.7%.

Abstract

The LFS is a twice-yearly rotating panel household survey, specifically designed to measure the dynamics of employment and unemployment in South Africa. It measures 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).

All editions of the LFS have been updated (some more than once) since their release. These version changes are detailed in a document available from DataFirst (in the "external documents" section titled "LFS 2000-2008 Collated Version Notes on the South African LFS").

Analysis unit

Households (dwellings) and individuals

Universe

The LFS 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 LFS is a twice-yearly rotating panel household survey. A rotating panel sample involves visiting the same dwelling units on a number of occasions (in this instance, five at most), and replacing a proportion of these dwelling units each round. New dwelling units are added to the sample to replace those that are taken out. The pilot round of LFS fieldwork took place in February 2000, based on a probability sample of 10 000 dwelling units. This survey took place six months later, using a larger probability sample of 30,000 dwelling units. Among the 10,000 households visited in February, approximately 40% were re-visited in September 2000. The fieldworkers had some difficulty in identifying certain dwelling units in the sample, particularly in those areas where there are no addresses.

The Master Sample is based on the 1996 Population Census of enumeration areas (EA) and the estimated number of dwelling units from the 1996 Population Census. All 3000 PSUs included in the Master Sample were used in the Labour Force Survey. A PSU is either one EA or several EAs when the number of dwelling units in the base or originally selected EA was found to have less than 100 dwelling units. Each EA had to have approximately 150 dwelling units but it was discovered that many contained less. Thus, in some cases, it has been found necessary to add EAs to the original (census) EA to ensure that the minimum requirement of 100 dwellings, in the first stage of forming the PSUs, was met. The size of the PSUs in the Master Sample varied from 100 to 2445 dwelling units. Special dwellings such as prisons, hospitals, boarding houses, hotels, guest houses (whether catering or self-catering), schools and churches were excluded from the sample.

Explicit stratification of the PSUs was done by province and area type (urban/rural). Within each explicit stratum, the PSUs were implicitly stratified by District Council, Magisterial District and, within the magisterial district, by average household income (for formal urban areas and hostels) or EA. The allocated number of EAs was systematically selected with "probability proportional to size" in each stratum. Once the PSUs included in the sample were known, their boundaries had to be identified on the ground. After boundary identification, the next stage was to list accurately all the dwelling units in the PSUs.

The second stage of the sample selection was to draw from the dwelling units listing whereby a systematic sample of 10 dwelling units was drawn from each PSU. As a result, approximately 30,000 households (units) were interviewed. However, if there was growth of more than 20% in a PSU, then the sample size was increased systematically according to the proportion of growth in the PSU.

The first pilot round of LFS fieldwork took place in February 2000, based on a probability sample of 10 000 dwelling units. The sample was increased to 30 000 dwelling units in September 2000. Both of these surveys were published as discussion documents. The third round took place in February 2001, using the same 30 000 dwelling units. The fourth round of the LFS, which took place in September 2001 drew a new sample of 30 000 dwelling units were visited. Rotation of 20% of this commenced with the fifth round being conducted (February/March 2002)

Mode of data collection

Face-to-face [f2f]

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.

CLEARANCE CERTIFICATE NUMBER: 2020FOBREC828

The rising unemployment rate is one of many challenges facing South Africa, especially among the youth. Government and business leaders are faced with the task of curbing this epidemic, as it is increasingly affecting the status of the country in terms of slow economic growth and a high crime rate. Entrepreneurship has been identified as an important aspect of many countries’ economic models, to enhance economic activity and create employment for the growing population worldwide. Across the globe, many universities are tasked with increasing their entrepreneurship content in their programmes to create more young entrepreneurs and curb the rising unemployment statistics. Entrepreneurship education and exposure thereof have a positive effect on students’ intention to become entrepreneurial savvy. Entrepreneurship programmes that promote knowledge, skills and a particular set of attributes, have a positive effect on the overall entrepreneurial intention of university students hence this study is guided by the Social Cognitive Theory and Bandura’s Agentic theory which depicts that career goals and choices are self-efficacy related and motivation by self-belief of an individual’s talent and abilities can control their goals. Entrepreneurship education has become a global phenomenon, with the intention to improve societies and the economy. There are various studies done in Asia, America, Europe and central to north Africa regarding entrepreneurship in general and entrepreneurship education, but the literature lacks data, especially from a South African context. This quantitative study sought to investigate the entrepreneurial knowledge, skills and attributes that agile hospitality students require to succeed in the tourism and hospitality industry, especially as entrepreneurs. The study used a quantitative research approach following a positivist paradigm. The study employed a descriptive cross-sectional research design, incorporating a quantitative survey using an online questionnaire. First, the researcher conducted documentary reviews in the form of Hospitality Management learning guides to familiarize and identify the entrepreneurship outcomes, teaching methods and modalities in the module. The reviews along with the literature review helped the researcher develop an understanding of the module and develop a list of entrepreneurial questions included in the questionnaire. The study focused on hospitality management students as a sample, at an institution of Higher Learning offering Hospitality Management. The questionnaire was distributed to a total of 400 students and the response was 228, thus giving a response rate of 57%. The data gathered was analysed using Statistical Package for Social Sciences version 28. Descriptive and inferential statistics were then presented, followed by a confirmatory factor analysis and regression model. The study sample showed that there were more female than male students (73%). Together, the average age of the respondents was between 21 and 25 years (62%). The results from the questionnaire showed out of the three years of study, first-year students dominated by 46% above second- and third-year students. With regards to ethnicity, there was a vast difference between the groups where African participants were a majority of 82%. The participants needed to notify whether the choice of hospitality management was their first, second or third choice, just over half of the respondents indicated it as their first choice (58%). The factor analysis showed 7 factors that need to be taken as those that influence entrepreneurial knowledge, skills and attributes. From the data collected, information regarding their knowledge, skills and attributes was questioned. Information such as business aspirations mainly indicated the student’s intention to start a business was because they believe in themselves (60.09%), the know they are hard workers (55.26%), passion is what drives them (51.75%) and above all the students advocate determining their own future (64.91%). The students felt that entrepreneurship education in the hospitality management course has developed a need for achievement in them (49.12%), time management ability (48.25%) and problem-solving ability (47.81%). Data was collected to understand how entrepreneurial teaching methods have enhanced the students’ capabilities in the course, and students regarded mentorship by entrepreneurs and industry interaction as a significant aspect (40.79%). Teaching techniques enhancing the student’s mindset entrepreneurial capabilities indicated that students would prefer to interact more frequently with small business development agencies (39.91%), interact with successful entrepreneurs (38.60%) and felt that adding the entrepreneurship component to more than one subject would be beneficial in stimulating the mind towards a future in entrepreneurship (38.16%). The participants have shown an understanding concerning their entrepreneurship mindset based on their learning, for example knowing that running a business takes a lot of hard work and sacrifice (77.63%), also the confidence in their abilities like being able to assess strengths and weaknesses of a business (51.32%), students are confident in understanding the mindset of consumers (50.88%) and can see themselves starting a business (67.98%). The main findings revealed that entrepreneurship education influences self-efficacy, attitude towards becoming and entrepreneur and entrepreneurial confidence coupled with an entrepreneurial mindset. The responses also showed that more students would rather have a programme that incorporated more practice and influence of outside stakeholders, like mentors and entrepreneurs with profitable businesses. Generally, higher education institutions should develop programmes that incorporate entrepreneurial capabilities, that foster knowledge, skills, and attributes that would encourage students to become entrepreneurial.

The unemployment rate in South Africa increased by 1.1 percentage points (+3.43 percent) in 2024 in comparison to the previous year. In total, the unemployment rate amounted to 33.17 percent in 2024. This increase was preceded by a declining unemployment rate.The unemployment rate refers to the share of the workforce that is currently not working but is actively searching for work. It does not include the economically inactive population, such as the long-term unemployed, those aged under 15 years, or retired persons.Find more statistics on other topics about South Africa with key insights such as gross tertiary enrollment ratio, youth literacy rate (people aged 15-24), and Gender Parity Index (GPI) in youth literacy.

Over the observed period, the unemployment rate in South Africa has increased, dropping significantly only in the second quarter of 2020. It was continuously higher among women than men, recording approximately 35.8 percent of the total labor force during the second quarter of 2024. The unemployment rate is the percentage of a country's labor force without jobs, and includes those who are available to work and are actively seeking employment.

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).

In 2024, around 11.2 percent of the African youth, those aged between 15 and 24 years old, were expected to be unemployed. According to data from the International Labor Organization, this figure has remained stable since 2021. The rate of unemployment among youths in the continent has fluctuated in the period under review, overall slightly dropping in comparison to the share in 2012, the lowest in the period reviewed.

The International Social Survey Programme (ISSP) is a continuous programme of cross-national collaboration running annual surveys on topics important for the social sciences. The programme started in 1984 with four founding members - Australia, Germany, Great Britain, and the United States – and has now grown to almost 50 member countries from all over the world. As the surveys are designed for replication, they can be used for both, cross-national and cross-time comparisons. Each ISSP module focuses on a specific topic, which is repeated in regular time intervals. Please, consult the documentation for details on how the national ISSP surveys are fielded. The present study focuses on questions about political attitudes and the role of government.
Attitude to compliance with law; attitudes to various forms of protest against the government; views regarding freedom of speech for extremists; attitude to justice error; attitudes towards state intervention in the economy; attitude to increased government spending for environmental protection, public health system, the police, education system, defense, pensions, unemployment benefits, culture and arts; attitude to welfare state and responsibility for jobs, price control, health care, decent standard of living, economic growth, reduction of income differences, support for students, housing supply and protection of environment; political interest; rating the government performance in providing health care and living standards as well as dealing with country`s security threats, controlling crime, fighting unemployment and protecting environment; attitude towards surveillance measures of the authorities in case of security challenges; political efficacy; trust in politicians and civil servants; assessment of tax equity with various income groups; trust in people; being treated fairly by public officials; treatment by public officials depends on personal contact; perceived amount of politicians and public officials involved in corruption; how often asked for bribe by public officials; number of persons respondent is in contact with per week.

Demography: sex; age; marital status; steady life partner; years of schooling; highest education level; country specific education and degree; current employment status (respondent and partner); hours worked weekly; occupation (ISCO 1988) (respondent and partner); supervising function at work; working for private or public sector or self-employed (respondent and partner); if self-employed: number of employees; trade union membership; earnings of respondent (country specific); family income (country specific); size of household; household composition; party affiliation (left-right); country specific party affiliation; participation in last election; religious denomination; religious main groups; attendance of religious services; self-placement on a top-bottom scale; region (country specific); size of community (country specific); type of community: urban-rural area; country of origin or ethnic group affiliation.

Additionally coded: administrative mode of data-collection; weight.

South Africa's education landscape is dominated by public schools, which account for over 90 percent of the country's nearly 25,000 educational institutions. As of 2024, there are 22,381 public schools compared to 2,469 independent schools. This stark contrast highlights the government's significant role in providing education to the nation's youth and underscores the challenges faced in ensuring quality education across such a vast network of schools. Regional disparities in school distribution and staffing KwaZulu-Natal leads the nation with 6,030 schools, followed by the Eastern Cape and Limpopo. However, when it comes to teaching staff, Gauteng takes the top spot with 98,140 educators, despite having fewer schools than KwaZulu-Natal and the Eastern Cape. This disparity suggests varying student-to-teacher ratios across provinces, potentially impacting educational quality and outcomes. The concentration of independent school teachers in Gauteng also indicates a more diverse educational landscape in the province. Education's impact on employment prospects The distribution of schools and teachers across South Africa has far-reaching implications for the country's workforce. As of the fourth quarter of 2023, the unemployment rate stood at 32.1 percent, with individuals having less than a matric education constituting the largest portion of the unemployed. In contrast, university graduates had the lowest unemployment rate at approximately 10 percent. This stark difference underscores the critical importance of accessible, quality education in improving employment prospects and addressing South Africa's persistent unemployment challenges.

The average monthly salary for South Africans who were employed in the formal non-agricultural sector was just over 26,800 South African rands (comparable to roughly 1,500 U.S. dollars) in November 2023, which represented a yearly increase of tw0 percent. During the period under review, the overall growth trend was positive, with the earnings increasing by 24.4 percent from 21,500 South African rands (approximately 1,180 U.S. dollars) in November 2018.    Minimum wage and highest-paid professions    Starting in March 2023, the minimum hourly wage in the country increased to 25.42 South African rands (comparable to 1.40 U.S. dollars), which represented an increase of 9.6 percent from 23.19 South African rands (1.27 U.S. dollars) per hour in the preceding year. On the other hand, professionals in executive and change management positions were paid the highest salaries in South Africa, with an average of 74,000 U.S. dollars yearly. Individuals with jobs in retail, trade, and craft followed, receiving an average of 66,000 U.S. dollars per annum.       Highest unemployment among Black South Africans In 2022, the unemployment rate in South Africa was nearly 30 percent following an increasing trend since 2008. The rate was highest among Black South Africans reaching as high as 36.8 percent in the second quarter of 2023. Moreover, Colored South Africans followed with around 22 percent, while white South Africans had a much lower unemployment rate of over 7 percent.