Some 43% of Sri Lankans aged 15 to 24 who hold post-secondary education are unemployed — the highest rate among 12 Asia-Pacific economies in an International Monetary Fund comparison, Daily Mirror reported.
The data was presented at the IMF’s regional economic outlook briefing for Asia and the Pacific on 16 April and reproduced in the September edition of the Fund’s Finance & Development magazine. NewsFirst names the article “Graduating into Uncertainty”.
What the figure is, and is not
It is not the graduate unemployment rate. It measures one narrow cohort — the youngest educated entrants, aged 15 to 24 with post-secondary qualifications. NewsFirst describes it more loosely as “graduate unemployment of around 43 percent”; Daily Mirror’s framing is the precise one.
The distinction matters because the two figures point in opposite directions. Against Department of Census and Statistics data, the 43% is:
- more than double the 19.5% unemployment rate among all Sri Lankans aged 15–24 in 2025
- roughly 11 times the national unemployment rate of 3.9%
Yet unemployment among those educated to G.C.E. Advanced Level and above, across all age groups, fell to 6.0% from 7.8% in 2024.
Read together, those numbers describe a transition problem rather than an employability problem. Sri Lanka’s labour market does eventually absorb its qualified workers — the all-ages rate is low and improving. What it does badly is absorb them at the point of entry. Neither outlet draws this out.
The regional pattern
Sri Lanka sits seven percentage points above Bangladesh, which at about 36% marks the lower end of the South Asian range, and more than three times above Thailand’s 13.2%.
Thailand is the instructive comparison. Its overall youth unemployment rate was just 3.9% last year — meaning educated young Thais are about three times more likely to be jobless than their peers. That inversion, where joblessness rises rather than falls with educational attainment, recurs across most of Southeast Asia. In South Asia it is considerably wider.
Srinivasan on the AI risk
Krishna Srinivasan, Director of the IMF’s Asia and Pacific Department, told the April briefing that “highly educated young workers are struggling to find positions that match their qualifications.”
Artificial intelligence, he cautioned, could lift growth and productivity but may also intensify pressure on young workers if adoption runs ahead of skills development — strengthening the case for universities and technical programmes to track employer demand more closely.
NewsFirst notes the publication does not treat technological change as purely a threat: productivity-enhancing tools can also draw investment, expand firms and create new categories of work. The benefit is conditional on whether countries equip young people to take it up.
One attribution the two reports dispute
The reports disagree on the source of the headline global figure. NewsFirst attributes the estimate that 1.2 billion young people will enter developing-country labour markets over the next decade to the IMF publication itself. Daily Mirror attributes it to the World Bank, in a June estimate, and adds the context that this likely-largest-ever youth cohort enters an economy where global growth is roughly a third lower than around the turn of the century.
The World Bank attribution is the more specific of the two and carries a date.
The figure is five months old
Worth stating plainly: the 43% was published in April and is circulating now because Finance & Development reprinted it in September. It is not a new measurement, and it is not a September reading of the Sri Lankan labour market.
Sri Lanka’s broader labour-market picture — including the participation-rate paradox of low unemployment alongside weak engagement — was reported earlier this month.
Not reported
Neither outlet gives the 12 economies in the comparison, the year the 43% refers to, or the survey definition of “post-secondary education” the IMF used — which matters, because a figure this far above the national series suggests a different measurement basis rather than simply a worse cohort. Neither reports a government response, nor whether the female-male split in the national data (where educated women fare markedly worse) holds in the IMF’s cohort.
