MAC Publishes New Analysis of Skilled Worker Visa Stay Rates in UK
The Migration Advisory Committee has released a detailed report examining long-term stay rates among Skilled Worker visa holders. The analysis covers data from 2014 to 2024 and highlights differences across occupations and earnings levels. Nurses show the highest retention while higher earners are more likely to depart.
The Migration Advisory Committee recently released findings on how long Skilled Worker migrants typically remain in the United Kingdom. The study uses Home Office administrative records spanning 2014 to 2024.
Key Findings from the Report
Nurses appear most likely to stay long term according to the data. In contrast, migrants with higher earnings show greater tendency to leave after their initial visa period.
Important Context
Stay rates refer only to valid immigration status and do not measure actual physical presence or integration outcomes. The MAC describes this as an initial step in understanding longer-term patterns.
- Data covers Skilled Worker route and predecessor Tier 2 (General) visas
- Health and Care Worker visa holders included in analysis
- Report spans entries from 2014 through 2024
Policy Implications
The committee notes that better understanding of stay rates can inform immigration policy and long-term integration considerations.
Report Access
The full 41-page document is available for download or online reading via official channels.
What does the MAC report measure?
It examines holding of valid immigration status among Skilled Worker visa holders over time.
Which groups show highest retention?
Nurses demonstrate the strongest likelihood of remaining long term based on the data examined.
Does the report assess integration?
No, it focuses on immigration status and notes this is a first step toward broader understanding.
The analysis draws on linked administrative records to identify variation across different migrant groups and occupations.
Stay Rate Highlights
Next Steps for Understanding
Further research may build on these findings to explore factors influencing decisions to remain or depart.