Key Points
Retrenchments hit 4,620 in Q2 2026, highest since late 2020.
Re-entry rate fell to 54.9%, down from 60.7% in Q1.
Retrenched PMETs face median 25% wage cut when returning to lower-paying jobs.
MOM weighing administrative action against firms refusing to pay retrenchment benefits.
Singapore’s job market is weakening sharply. Retrenchments jumped to 4,620 in the second quarter of 2026, the highest level since late 2020. More troubling, only 54.9% of retrenched workers found new jobs within six months, down from 60.7% in the first quarter. The Ministry of Manpower is now weighing administrative action against employers who refuse to pay retrenchment benefits despite having the financial capacity to do so.
Retrenchment benefits remain voluntary but under pressure
Retrenchment benefits are not mandated by law in Singapore. Employers follow a tripartite advisory setting the norm at two weeks to one month’s salary per year of service. In 2025, about 88% of employers paid these benefits. Of those who did not, one-fifth cited financial difficulties. The rest cited lack of legal obligation or said they provided alternative support such as keeping employees on payroll longer. Close to 80% of workers who received no retrenchment benefits worked at firms with fewer than 200 employees.
MOM signals tougher enforcement ahead
Acting Manpower Minister Jasmin Lau told Parliament on October 6 that MOM is weighing possible administrative action against employers able but unwilling to pay retrenchment benefits after repeated warnings. Tripartite partners are also considering bringing forward the mandatory retrenchment notification window so affected staff can receive job support earlier. Under current rules, firms with 10 or more employees have up to five working days after notifying staff to inform MOM.
Re-entry rates fall as fresh grads struggle
The re-entry rate for retrenched workers dropped to 54.9% in Q2 2026, down from 60.7% in Q1. Fresh graduates are also taking longer to secure full-time jobs. Of 18,000 fresh graduates from autonomous universities, 3,600 were still seeking employment as of June 2026. For the 2025 cohort, 74.4% of university graduates secured a full-time role within six months, compared with 87.5% in 2022. Retrenched workers finding it harder to land new jobs reflects softer hiring conditions across the economy.
Older workers and PMETs face steeper pay cuts
Retrenched professionals, managers, executives and technicians (PMETs) who return to work often accept lower pay. Among those earning less after retrenchment, the median wage reduction was around 25% of their pre-retrenchment wages. About six in 10 retrenched PMETs earned more than before, but older workers had lower re-entry rates at both 12 and 24-month marks. Those in their 40s and 50s accounted for more than half of all retrenched residents. Degree holders were the largest educational group, rising from 51% in 2021 to 66.4% in 2025.
Final Thoughts
Singapore’s labour market is cooling fast. With retrenchments at a seven-year high and re-entry rates falling, workers face longer jobless spells and steeper pay cuts. The government’s push to enforce retrenchment benefits signals recognition that the burden on workers has become unsustainable.
FAQs
The second quarter of 2026 saw 4,620 retrenchments, reflecting softer hiring conditions and weaker economic demand across sectors.
Retrenched professionals, managers, executives and technicians who return to work earning less face a median 25% wage reduction.
Only 54.9% of retrenched residents returned to employment within six months in Q2 2026, down from 60.7% in Q1.
No. Retrenchment benefits are not mandated by law but guided by a tripartite advisory setting the norm at two weeks to one month’s salary per year of service.
Disclaimer:
The content shared by Meyka AI PTY LTD is solely for research and informational purposes. Meyka is not a financial advisory service, and the information provided should not be considered investment or trading advice.
About Author

Huzaifa Zahoor
Co FounderHuzaifa Zahoor is the engineer who built Meyka. He has spent years writing Python, training AI models, and building data pipelines specifically for financial markets. His technical articles have reached over 30,000 readers on Medium, so he knows how to make complex things easy to follow. If this article touches on how the tools work, he is the person who actually built them.
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