57% youth unemployment (15–24) • 3.5 million young people NEET • 79.7% of unemployed have been jobless for over a year • 43.8% youth unemployment rate (15–34) — up from 34.9% a decade ago • 3.7 million discouraged work-seekers • Eastern Cape: 51.4% underutilisation rate • Black African unemployment: 35.3% — 4× higher than White • LU4 composite rate: 44.5% • Only 11.1% of 15–24 year olds are employed • 57% youth unemployment (15–24) • 3.5 million young people NEET • 79.7% of unemployed have been jobless for over a year • 43.8% youth unemployment rate (15–34) — up from 34.9% a decade ago • 3.7 million discouraged work-seekers • Eastern Cape: 51.4% underutilisation rate • Black African unemployment: 35.3% — 4× higher than White • LU4 composite rate: 44.5% • Only 11.1% of 15–24 year olds are employed •
QLFS Q4:2025 — Youth Capital Data Report

STILL
SHUT
OUT.

South Africa's Q4:2025 QLFS is out. The headline says unemployment fell. The full picture says something more uncomfortable: more young people are excluded from the economy today than they were a decade ago. This is that story.

Read the Analysis
57%
Youth Unemployment (15–24)
Q4:2025 — Official Rate  |  Narrow Measure
The actual picture is worse.
43.8% Youth (15–34) Unemployment — up from 34.9% in 2015
3.5M Young people NEET (15–24) — one in three
79.7% Unemployed for a year or longer — structural, not cyclical
The headline says things are improving • The data tells a different story • More young people excluded today than a decade ago • Discouragement is not laziness — it is a rational response to a broken system • Where you are born still determines your chances • Race remains the strongest predictor of labour market exclusion • The headline says things are improving • The data tells a different story • More young people excluded today than a decade ago • Discouragement is not laziness — it is a rational response to a broken system • Where you are born still determines your chances • Race remains the strongest predictor of labour market exclusion •
The Numbers That Matter.
57.0%
One in two young people looking for work can't find it

The official unemployment rate for 15–24 year olds in Q4:2025. This is the highest of any age group — and it only counts those actively seeking work. Include discouraged youth and the real rate is far higher.

11.1%
Fewer than 1 in 9 young people (15–24) are employed

The absorption rate. Not "looking for work" — actually working. This is the most honest measure of how well the economy is incorporating young people, and it is devastating.

3.5M
Young people with nowhere to be

3.5 million people aged 15–24 are NEET — Not in Employment, Education, or Training. That is 34% of this entire age group. This number grew year-on-year.

3.7M
People who have stopped looking

3.7 million discouraged work-seekers. They want work. They have simply concluded — rationally — that the labour market has nothing for them. They are invisible in the headline unemployment rate.

79.7%
Long-term unemployment now dominates

Nearly 8 in 10 unemployed people have been out of work for a year or longer. In 2015 it was 66.9%. This is not a jobs crisis. It is a structural exclusion crisis.

+9 ppts
Youth unemployment is worse than a decade ago

The 15–34 unemployment rate was 34.9% in Q4:2015. It is 43.8% today — nearly 9 percentage points higher. A full decade of policy, programmes, and spending has not moved the dial in the right direction.

The Age Story:
Who Gets Left Behind and How Badly.

Ages 15–24 57% Unemployment Rate

This cohort faces the most severe exclusion of any age group. The majority are not even in the labour force — their participation rate is just 25.7%. That means three-quarters of 15–24 year olds are not counted in the unemployment figure at all. The absorption rate — the share actually employed — is just 11.1%.

Ages 25–34 39.2% Unemployment Rate

By 25–34, participation rises to 72.9% — most are actively engaging with the labour market. But four in ten are still being turned away. The absorption rate is 44.3% — better, but still well below older cohorts. Many in this group cycle between temporary work and unemployment with no stable foothold.

Ages 15–34 — Full Youth Cohort
43.8% Unemployment Q4:2025

Up from 34.9% in Q4:2015 — a full 9 percentage points worse over a decade.

21.2 ppts Gap vs. 35–64 year olds

Youth unemployment is 21.2 percentage points above older workers — and that gap has widened over 10 years.

43.3% NEET Rate (15–34)

Nearly half of all young people aged 15–34 are not in employment, education, or training.

!
Q4 seasonal caution: The fourth quarter typically shows modest employment improvements in retail, agriculture, and festive-economy sectors. Quarter-on-quarter gains at year-end are structurally inflated. The honest comparison is Q4:2025 versus Q4:2024 — and year-on-year, the NEET rate increased by 0.5 percentage points, not decreased.

The Invisible Majority:
Participation, Discouragement & Disappearance.

LU1 — Official Rate 31.4%
The headline number. Counts only those actively seeking work.
LU2 — Incl. Underemployed 34.3%
Adds 705 000 people working fewer hours than they need.
LU3 — Incl. Potential LF 42.1%
Adds 4.6 million who want work but have stopped seeking or aren't available.
LU4 — Full Composite 44.5%
The most complete picture of labour underutilisation. 13 points above the headline.

When the official unemployment rate falls, many assume that means the economy is getting better. But that is only true if people are moving from unemployment into jobs. It is not true when they are moving from unemployment into discouragement.

In Q4:2025, the labour force participation rate fell by 0.4 percentage points to 59.3%. That means people left the labour market — they stopped being counted as unemployed. The absorption rate (the share actually employed) fell by 0.1 points to 40.6%. Both measures got worse. The headline improved only because fewer people were counted.

For young people, this dynamic is especially severe. The 15–24 participation rate is just 25.7%. Three-quarters of this age group are not in the labour force count at all. They are in school, caring for family members, or — crucially — have simply given up. Their absence makes the youth unemployment rate appear lower than it actually is.

The 10.7 percentage-point gap between LU1 and LU3 represents 4.6 million people who want work but are not captured in the headline. For advocates and policymakers, this is the number that matters.

3.7M Discouraged Work-Seekers

These are people who want work but have stopped actively looking — not because they lack ambition, but because they have concluded the market has nothing for them.

Discouragement grew by 233,000 in a single quarter. It accounts for 80.5% of the entire Potential Labour Force.

This is systemic failure, not individual failure.

The Race Gap:
Still Widest Where it Hurts Most.

Black African
35.3% — Q4:2025  |  Was 27.6% in 2015  ↑
35.3%
Coloured
21.2% — Was 21.6% in 2015 ≈
21.2%
Indian/Asian
14.7% — Was 10.9% in 2015  ↑
14.7%
White
8.1% — Was 6.9% in 2015
8.1%
National
31.4% National Average
31.4%

27 points separate the top and bottom. That gap is called apartheid.

Black African unemployment (35.3%) is more than four times higher than White unemployment (8.1%). This is not a coincidence of individual choices or cultural differences. It is the direct, measurable, ongoing consequence of apartheid-era spatial planning, differential access to quality schooling, unequal social networks and recruitment systems, and persistent labour market discrimination.

Ten years of data confirm this gap is not closing. The Black African rate has risen from 27.6% to 35.3%. The racial hierarchy of South Africa's labour market remains structurally intact.

For young Black Africans, the compounding is catastrophic.

When race and age intersect, the disadvantage multiplies. Young Black African women aged 15–24, particularly in rural Eastern Cape and Limpopo, face unemployment rates that almost certainly exceed 70% when discouragement is included. No amount of personal effort can overcome the structural barriers of geography, educational quality, network access, and hiring discrimination simultaneously.

Reject any analysis that explains this through individual behaviour. The 10-year persistence of these gaps is the signature of structural failure — not personal failure.

Where You're Born
Still Determines Your Chances.

Highest EC Eastern Cape 42.5% LU3: 51.4%
FS Free State 37.2% LU3: 44.1%
NW North West 35.1% LU3: 50.9%
GP Gauteng 33.0% LU3: 39.4%
MP Mpumalanga 32.3% LU3: N/A
KZN KwaZulu-Natal 32.3% LU3: 47.1%
LP Limpopo 28.2% LU3: 46.1%
NC Northern Cape 27.1% LU3: 42.9%
Lowest WC Western Cape 18.1% LU3: 23.7%

The Eastern Cape Crisis Is a Policy Emergency

EC has exceeded the national unemployment average for the entire 10-year period — and shows no sign of convergence. It is heavily rural, has limited private sector activity outside Nelson Mandela Bay's automotive corridor, and relies on social grants and public employment as primary income sources. For young people here, migration to Gauteng or the Western Cape is frequently the only visible path out — but that path is blocked by transport costs, housing access, and destination-city inequality.

The Discouraged-Worker Gap Reveals Rural Collapse

In Limpopo, the gap between official unemployment (28.2%) and the full underutilisation rate (LU3: 46.1%) is 17.9 percentage points — the widest in the country. This signals that enormous numbers of working-age people have simply given up searching. You cannot actively look for a job that does not exist within accessible distance. This is not discouragement — it is geography. Policy must reckon with spatial exclusion, not just skills gaps.

10 Years.
No Progress.

The economy is employing a smaller share of its people today than it was in 2015.

Across a full decade — through periods of moderate growth, major policy pivots, COVID disruption, and billions spent on social support and public employment — the fundamental position of young South Africans in the labour market has not improved. It has worsened.

Q4:2015
Q4:2025
Youth (15–34) Unemployment
34.9%
43.8%
Total Unemployed
5.2M
7.8M
Absorption Rate
44.2%
40.6%
Long-Term Unemployed
66.9%
79.7%
Official Unemp. Rate
24.5%
31.4%

This Is Structural, Not Cyclical

Youth unemployment that persists — and worsens — across a full decade, through multiple economic cycles, governments, and policy frameworks, is not a temporary fluctuation. It is a structural feature of the economy. GDP growth alone will not fix it because the structure of that growth does not connect to the young people who most need entry points.

Long-Term Unemployment Is Now the Norm

When 79.7% of unemployed people have been out of work for over a year, the standard tools of job-seeking — keeping CVs updated, networking, reapplying — have already been exhausted. Skills erode. Confidence erodes. Networks thin. The longer someone is unemployed, the harder re-entry becomes. We are creating a generation locked out.

The COVID Cohort Is Now 3–4 Years In

Young people who entered the labour market in 2020–2022 and failed to find work are now in their third or fourth year without stable employment. For many, this coincided with their critical early career years — the window during which networks are built, credentials are tested, and pathways are established. That window may not reopen.

Stop
Saying This.

Five things that people say about youth unemployment that the data directly contradicts.

❌ Commonly Said

"Unemployment is falling, so things are improving."

✓ What the Data Shows

"Unemployment fell because people stopped being counted."

In Q4:2025, unemployment fell by 0.5 points — but labour force participation also fell by 0.4 points, and discouragement grew by 233,000. The employment gain was just 44,000 jobs in a quarter when the working-age population grows by ~250,000. Fewer counted unemployed does not mean more people are working.

❌ Commonly Said

"Young people don't want to work."

✓ What the Data Shows

"3.7 million people stopped looking because the market failed them."

Discouraged work-seekers are defined as those who want work but believe none is available. A participation rate of 72.9% for 25–34 year olds shows strong market engagement. NEET youth include caregivers, people with disabilities, and those in areas without accessible employment — not people who have opted out of effort.

❌ Commonly Said

"Informal work means entrepreneurship is booming."

✓ What the Data Shows

"Informal work fell by 293,000 in Q4. Most of it is survivalist, not entrepreneurial."

The QLFS cannot tell us incomes, stability, or growth trajectories of informal workers. Research consistently shows most young informal workers earn below subsistence levels, have no social protection, and cycle between informal work and unemployment in short intervals. This is not entrepreneurship — it is the absence of alternatives.

❌ Commonly Said

"Youth unemployment is the same problem for everyone."

✓ What the Data Shows

"A young White graduate and a young Black African school-leaver in the Eastern Cape face categorically different labour markets."

Graduate unemployment is 10.3%. Matric-holder unemployment is 33.7%. White unemployment is 8.1%. Black African unemployment is 35.3%. Provincial unemployment ranges from 18.1% (WC) to 42.5% (EC). Policy designed for the average young person will serve nobody well.

❌ Commonly Said

"Education alone will solve youth unemployment."

✓ What the Data Shows

"There aren't enough jobs for the skills being produced — at any level."

Graduate unemployment is 10.3% — education helps, but does not protect. Matric-holder unemployment of 33.7% shows that the credential most young people work toward barely helps. Education can improve the quality of labour supply; it cannot, by itself, generate demand. The failure is economic structure, not only education.

What the Data Can't See.

The QLFS is the best available regular source of labour market data in South Africa. But honest analysis requires knowing what it misses — and for youth policy, the gaps are significant.

Job quality and income adequacy

The QLFS counts any hour of paid work as "employment." Two hours of casual piece-rate farm work counts identically to a permanent contract with benefits. For young people cycling between ultra-casual work and unemployment, the official employment number can improve while lived poverty deepens. We have no regular picture of whether young people can actually sustain a livelihood on the work they find.

Employment cycling and precarity

The QLFS is a snapshot, not a video. It cannot show how many young people moved between employment and unemployment in the past quarter, how long each spell lasted, or how often the same individuals cycle between statuses. Many of the "employed" in one quarter are "unemployed" in the next. Panel data consistently shows churning beneath the apparent stability of aggregate numbers.

Sub-provincial spatial inequality

Provincial averages hide enormous within-province differences. Johannesburg's labour market and rural Sekhukhune District are categorically different — but the QLFS cannot reliably produce estimates below provincial level. The most severe concentrations of youth unemployment in specific districts and municipalities are invisible in the data.

Care work, gender, and unpaid activity

Young women who are not in employment, education, or training are disproportionately counted as homemakers or carers. Their unpaid care work is economically significant but invisible in employment statistics. The NEET category does not distinguish between someone resting between job searches and someone providing full-time care. These require categorically different policy responses.

Section 10 — Final Synthesis

So What
Now?

What Remains Structurally Broken

The education-to-employment transition. The spatial concentration of exclusion. The racial hierarchy of the labour market. The absence of entry-level job creation in sectors where young people without qualifications can enter. Ten years of data confirm that none of these have been resolved — and several have worsened. The system is not broken. It is working exactly as it was built to work. It needs to be rebuilt.

Where Weak Pathways Exist

Construction (+35,000 in Q4) offers apprenticeship-accessible pathways. Community services employment grew — but reflects public spending, not private sector demand. The Western Cape shows that functional institutions and economic diversification can produce better outcomes. Some youth do find more stable footing by their late twenties — but at 39.2% unemployment for 25–34 year olds, that stabilisation arrives too late for too many.

The Question That Isn't Being Asked

Given that youth unemployment is higher today than a decade ago — despite significant public expenditure on employment programmes — what honest assessment exists of why current approaches are not working? What different approach would produce genuinely different outcomes? The question is not "how do we reduce the unemployment rate?" It is "how do we create conditions where young people can build sustainable livelihoods?"

What Policymakers Should Ask Next

What happens to NEET youth after they leave public employment programmes — and what interventions are associated with durable transitions into work? How do the spatial, racial, and educational dimensions of exclusion interact, and what programmes address all three simultaneously? What is the income adequacy of the work that young South Africans are actually accessing? And who is accountable for a decade of no progress?

South Africa cannot afford to treat youth unemployment as a problem at the margins of economic policy. It is the central structural challenge of this generation. The Q4:2025 QLFS, read honestly, is an urgent call for a fundamentally different scale of ambition — not for young people, but with them.

Youth Capital — QLFS Q4:2025 Analysis  |  February 2026  |  Data: Stats SA
Youth unemployment is not a skills problem • It is a structural exclusion problem • 3.5 million young people NEET • 10 years of data. No progress. • The system is not broken • It was built this way • Rebuild it • Youth unemployment is not a skills problem • It is a structural exclusion problem • 3.5 million young people NEET • 10 years of data. No progress. • The system is not broken • It was built this way • Rebuild it •