This spreadsheet contains the original data tables that accompany the charts and tables in the main report.
The MAC have carried out analysis using Home Office Migrant Journey data, Home Office visa records and Home Office Certificate of Sponsorship (CoS) data.
We have included key caveats and limitations where possible, however please refer to the source data for detailed descriptions of the methodology and caveats.
Produced by Migration Advisory Committee.
Chapter 2: Data and Methodology
Table 2.1: MJ record link rates by year and in-country/out-of-country status
| Year |
In-country visa link rate |
Out-of-country visa link rate |
| 2014 |
95% |
94% |
| 2015 |
95% |
96% |
| 2016 |
96% |
97% |
| 2017 |
97% |
98% |
| 2018 |
97% |
98% |
| 2019 |
93% |
98% |
| 2020 |
90% |
95% |
| 2021 |
98% |
97% |
| 2022 |
97% |
97% |
| 2023 |
98% |
97% |
| 2024 |
97% |
97% |
| Total |
97% |
97% |
Source: MAC internal analysis.
Chapter 3: Descriptive Statistics
| Year |
Number of observations |
| 2014 |
23,000 |
| 2015 |
20,000 |
| 2016 |
19,000 |
| 2017 |
21,000 |
| 2018 |
26,000 |
| 2019 |
38,000 |
| 2020 |
33,000 |
| 2021 |
85,000 |
| 2022 |
187,000 |
| 2023 |
296,000 |
| 2024 |
168,000 |
| Total |
916,000 |
Source: MAC internal analysis.
| Cohort |
Proportion with expired leave |
Proportion with valid visas |
Proportion with ILR |
Proportion with citizenship |
| 2014 |
34% |
2% |
16% |
48% |
| 2015 |
34% |
2% |
18% |
46% |
| 2016 |
32% |
3% |
20% |
45% |
| 2017 |
30% |
5% |
24% |
42% |
| 2018 |
26% |
7% |
44% |
24% |
| 2019 |
20% |
21% |
56% |
3% |
| 2020 |
12% |
82% |
5% |
1% |
| 2021 |
12% |
86% |
2% |
0% |
| 2022 |
4% |
96% |
0% |
0% |
| 2023 |
2% |
98% |
0% |
0% |
| 2024 |
1% |
99% |
0% |
0% |
Source: MAC internal analysis. Note: Figure shows leave status on the 31 December 2024.
| Days since first SW visa |
Expiries |
| 0-91 |
700 |
| 91-183 |
1,500 |
| 183-274 |
2,000 |
| 274-365 |
3,400 |
| 365-457 |
7,300 |
| 457-548 |
1,000 |
| 548-639 |
1,500 |
| 639-730 |
2,700 |
| 730-822 |
6,300 |
| 822-913 |
900 |
| 913-1000 |
1,200 |
| 1000-1100 |
5,600 |
| 1100-1190 |
19,200 |
| 1190-1280 |
600 |
| 1280-1370 |
600 |
| 1370-1460 |
700 |
| 1460-1550 |
1,100 |
| 1550-1640 |
500 |
| 1640-1730 |
400 |
| 1730-1830 |
1,300 |
| 1830-1920 |
7,300 |
| 1920-2010 |
400 |
| 2010-2100 |
400 |
| 2100-2190 |
900 |
| 2190-2280 |
1,500 |
| 2280-2370 |
100 |
| 2370-2470 |
- |
| 2470-2560 |
- |
| 2560-2650 |
- |
| 2650-2740 |
- |
| 2740-2830 |
- |
| 2830-2920 |
- |
| 2920-3010 |
- |
| 3010-3100 |
- |
| 3100-3200 |
- |
| 3200-3290 |
- |
| 3290-3380 |
- |
| 3380-3470 |
- |
| 3470-3560 |
- |
| 3560-3650 |
- |
| 3650-3740 |
- |
| 3740-3840 |
- |
| 3840-3930 |
- |
| 3930-4020 |
- |
Source: MAC internal analysis. Note: Values marked with ‘-‘ have less than 100 observations.
| Previous leave subcategory |
Cohort |
Number of in-country migrants transferring to first skilled worker visa |
| Student |
2014-2020 |
43,700 |
| Tier 1 - Post Study |
2014-2020 |
5,900 |
| Tier 2 - Intra-company transfer |
2014-2020 |
800 |
| Youth Mobility Scheme |
2014-2020 |
600 |
| Tier 1 - Entrepreneur |
2014-2020 |
600 |
| Student |
2021-2024 |
137,800 |
| Graduate |
2021-2024 |
58,900 |
| Tier 2 - Intra-company transfer (long-term staff) |
2021-2024 |
14,900 |
| Youth Mobility Scheme |
2021-2024 |
6,400 |
| Dependants joining or accompanying |
2021-2024 |
5,200 |
Source: MAC internal analysis.
| Nationality |
In-country skilled worker visas granted |
Out-of-country skilled worker visas granted |
| India |
120,000 |
172,000 |
| Nigeria |
55,000 |
53,000 |
| Pakistan |
18,000 |
38,000 |
| Philippines |
1,000 |
48,000 |
| Zimbabwe |
1,000 |
38,000 |
| United States |
8,000 |
27,000 |
| China |
19,000 |
8,000 |
| Bangladesh |
10,000 |
17,000 |
| Ghana |
4,000 |
21,000 |
| South Africa |
1,000 |
15,000 |
Source: MAC internal analysis.
Note: Shows the top 10 nationalities from 2014 to 2024.
Table 3.1: Characteristics of migrants with or without valid immigration status five years after receiving their first Skilled Worker visa
| Variable |
Valid immigration status (assumed to have remained in the UK) |
Expired immigration status (assumed to have left the UK) |
| Demographic and salary variables |
|
|
| Average age on entry |
30.6 |
32.3 |
| % Male |
55.2% |
63.2% |
| % Obtaining first Skilled Worker visa in-country |
32.2% |
27.1% |
| Average annual salary on entry (2024 earnings level) |
£70,900 |
£94,400 |
| % in London based role |
44.4% |
43.6% |
| Industry breakdown |
|
|
| % Education |
11.5% |
24.7% |
| % Financial and insurance activities |
12.4% |
10.2% |
| % Human health and social work activities |
32.2% |
17.1% |
| % Information and communications |
11.5% |
11.8% |
| % Professional, scientific and technical activities |
16.1% |
16.5% |
| % Other industries |
16.2% |
19.7% |
| Number of observations |
117,400* |
29,700* |
Source: MAC internal analysis.
Note: Valid immigration status means an individual continues to hold a valid visa, indefinite leave to remain, or citizenship. Table includes individuals receiving their first Skilled Worker visa on a migrant journey between 1 January 2014 and 31 December 2019. Industry breakdown shows the percentage of migrants working in each industry by group. The total number of observations are approximately 3% lower for CoS dependent variables (salary, % in London based role and industry) given that match rates were not 100%.
Chapter 4: Results
Source: MAC internal analysis.
Note: For brevity and to ensure outputs are not disclosive of individuals, the results have been aggregated on the annual rather than daily level. Valid immigration status includes those with valid visas, ILR and citizenship.
2014 cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
96% |
| 3 |
90% |
| 4 |
77% |
| 5 |
74% |
| 6 |
69% |
| 7 |
67% |
| 8 |
67% |
| 9 |
66% |
| 10 |
66% |
| 11 |
66% |
2015 cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
96% |
| 3 |
90% |
| 4 |
79% |
| 5 |
77% |
| 6 |
69% |
| 7 |
66% |
| 8 |
66% |
| 9 |
66% |
| 10 |
66% |
2016 cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
96% |
| 3 |
90% |
| 4 |
80% |
| 5 |
77% |
| 6 |
71% |
| 7 |
68% |
| 8 |
68% |
| 9 |
68% |
2017 cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
96% |
| 3 |
91% |
| 4 |
81% |
| 5 |
79% |
| 6 |
72% |
| 7 |
71% |
| 8 |
70% |
2018 cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
96% |
| 3 |
91% |
| 4 |
84% |
| 5 |
82% |
| 6 |
76% |
| 7 |
74% |
2019 cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
94% |
| 4 |
86% |
| 5 |
85% |
| 6 |
79% |
2020 cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
94% |
| 4 |
88% |
| 5 |
86% |
2021 cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
94% |
| 4 |
86% |
2022 cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
94% |
2023 cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
98% |
2024 cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
98% |
Source: MAC internal analysis.
Note: For brevity and to ensure outputs are not disclosive of individuals, the results have been aggregated on the annual rather than daily level. Valid immigration status includes those with valid visas, ILR and citizenship.
Bangladesh
| Year |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
100% |
| 2 |
99% |
| 3 |
95% |
| 4 |
90% |
| 5 |
88% |
| 6 |
87% |
| 7 |
86% |
| 8 |
86% |
| 9 |
86% |
| 10 |
86% |
| 11 |
85% |
China
| Year |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
95% |
| 3 |
87% |
| 4 |
75% |
| 5 |
72% |
| 6 |
67% |
| 7 |
65% |
| 8 |
65% |
| 9 |
65% |
| 10 |
65% |
| 11 |
64% |
Ghana
| Year |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
100% |
| 2 |
99% |
| 3 |
98% |
| 4 |
94% |
| 5 |
93% |
| 6 |
89% |
| 7 |
89% |
| 8 |
89% |
| 9 |
89% |
| 10 |
88% |
| 11 |
88% |
India
| Year |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
100% |
| 2 |
98% |
| 3 |
95% |
| 4 |
88% |
| 5 |
87% |
| 6 |
82% |
| 7 |
81% |
| 8 |
80% |
| 9 |
80% |
| 10 |
80% |
| 11 |
80% |
Nigeria
| Year |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
100% |
| 2 |
99% |
| 3 |
98% |
| 4 |
94% |
| 5 |
94% |
| 6 |
92% |
| 7 |
91% |
| 8 |
91% |
| 9 |
91% |
| 10 |
91% |
| 11 |
91% |
Pakistan
| Year |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
98% |
| 3 |
95% |
| 4 |
90% |
| 5 |
89% |
| 6 |
88% |
| 7 |
87% |
| 8 |
87% |
| 9 |
87% |
| 10 |
87% |
| 11 |
86% |
Philippines
| Year |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
100% |
| 2 |
99% |
| 3 |
98% |
| 4 |
93% |
| 5 |
92% |
| 6 |
88% |
| 7 |
86% |
| 8 |
85% |
| 9 |
85% |
| 10 |
85% |
| 11 |
85% |
South Africa
| Year |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
93% |
| 4 |
81% |
| 5 |
79% |
| 6 |
73% |
| 7 |
72% |
| 8 |
71% |
| 9 |
71% |
| 10 |
71% |
| 11 |
71% |
United States
| Year |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
97% |
| 2 |
93% |
| 3 |
87% |
| 4 |
70% |
| 5 |
67% |
| 6 |
49% |
| 7 |
45% |
| 8 |
44% |
| 9 |
44% |
| 10 |
43% |
| 11 |
43% |
Zimbabwe
| Year |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
100% |
| 2 |
99% |
| 3 |
98% |
| 4 |
93% |
| 5 |
91% |
| 6 |
89% |
| 7 |
88% |
| 8 |
88% |
| 9 |
87% |
| 10 |
87% |
| 11 |
91% |
Other
| Year |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
98% |
| 2 |
95% |
| 3 |
89% |
| 4 |
80% |
| 5 |
78% |
| 6 |
71% |
| 7 |
69% |
| 8 |
68% |
| 9 |
68% |
| 10 |
68% |
| 11 |
68% |
| Country |
Five year stay rate (% with valid immigration status after five years) |
GDP per capita (2024 prices) |
| Albania |
85% |
£27,100 |
| Algeria |
80% |
£17,600 |
| Argentina |
75% |
£30,400 |
| Australia |
61% |
£72,100 |
| Azerbaijan |
80% |
£25,100 |
| Bahrain |
75% |
£66,900 |
| Bangladesh |
85% |
£9,600 |
| Barbados |
80% |
£24,800 |
| Belarus |
83% |
£33,000 |
| Brazil |
78% |
£22,300 |
| Burma (Myanmar) |
93% |
£6,000 |
| Cameroon |
76% |
£5,600 |
| Canada |
70% |
£64,600 |
| Chile |
65% |
£36,200 |
| China |
70% |
£27,100 |
| Colombia |
72% |
£22,300 |
| Egypt |
88% |
£19,100 |
| Ghana |
91% |
£8,000 |
| Guyana |
84% |
£80,200 |
| Hong Kong |
81% |
£75,200 |
| India |
83% |
£11,200 |
| Indonesia |
76% |
£16,400 |
| Iran |
85% |
£19,900 |
| Iraq |
80% |
£14,500 |
| Israel |
72% |
£57,200 |
| Jamaica |
85% |
£12,900 |
| Japan |
63% |
£52,000 |
| Jordan |
83% |
£10,800 |
| Kazakhstan |
82% |
£40,900 |
| Kenya |
80% |
£6,600 |
| Libya |
90% |
£14,300 |
| Malaysia |
79% |
£38,800 |
| Mauritius |
86% |
£31,800 |
| Mexico |
75% |
£26,200 |
| Morocco |
83% |
£10,400 |
| Nepal |
79% |
£5,700 |
| New Zealand |
67% |
£55,600 |
| Nigeria |
93% |
£9,100 |
| Pakistan |
87% |
£6,300 |
| Peru |
80% |
£17,800 |
| Philippines |
92% |
£11,800 |
| Russia |
85% |
£47,400 |
| Saudi Arabia |
55% |
£71,400 |
| Serbia |
80% |
£32,800 |
| Singapore |
73% |
£150,700 |
| South Africa |
75% |
£15,500 |
| South Korea |
66% |
£61,100 |
| Sri Lanka |
74% |
£15,600 |
| Sudan |
92% |
£2,100 |
| Tanzania |
84% |
£4,200 |
| Thailand |
64% |
£24,700 |
| Trinidad and Tobago |
85% |
£36,300 |
| Tunisia |
82% |
£14,500 |
| Turkey |
85% |
£45,600 |
| Uganda |
81% |
£3,300 |
| Ukraine |
85% |
£18,600 |
| United States |
66% |
£85,800 |
| Vietnam |
81% |
£16,400 |
| Zambia |
87% |
£4,200 |
| Zimbabwe |
88% |
£5,900 |
Source: MAC internal analysis using GDP per capita data from the World Bank.
Note: Analysis includes all nationalities with 100 or more first Skilled Worker journeys in sample period (2014-2019) aside from those for which the World Bank does not publish GDP per capita data (e.g. Taiwan, Lebanon and Syria). Only nationalities with 1000 or more first Skilled Worker journeys in the sample period are labelled on the chart, although, some overlapping labels have been removed for readability. Solid line shows the linear relationship between GDP per capita and five-year stay rate. The shaded band shows the 95% confidence interval for the fitted line (mean stay rate for a given GDP per capita) around this estimate.
Source: MAC internal analysis.
Note: For brevity and to ensure outputs are not disclosive of individuals, the results have been aggregated on the annual rather than daily level. Valid immigration status includes those with valid visas, ILR and citizenship.
Aged <25
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
93% |
| 4 |
84% |
| 5 |
82% |
| 6 |
77% |
| 7 |
75% |
| 8 |
74% |
| 9 |
74% |
| 10 |
74% |
| 11 |
74% |
25-34
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
93% |
| 4 |
86% |
| 5 |
84% |
| 6 |
78% |
| 7 |
76% |
| 8 |
76% |
| 9 |
76% |
| 10 |
75% |
| 11 |
75% |
35-44
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
93% |
| 4 |
84% |
| 5 |
82% |
| 6 |
74% |
| 7 |
72% |
| 8 |
71% |
| 9 |
71% |
| 10 |
71% |
| 11 |
70% |
45-54
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
96% |
| 3 |
91% |
| 4 |
78% |
| 5 |
74% |
| 6 |
58% |
| 7 |
54% |
| 8 |
54% |
| 9 |
53% |
| 10 |
53% |
| 11 |
52% |
55+
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
96% |
| 2 |
90% |
| 3 |
81% |
| 4 |
62% |
| 5 |
56% |
| 6 |
36% |
| 7 |
31% |
| 8 |
30% |
| 9 |
30% |
| 10 |
29% |
| 11 |
29% |
Source: MAC internal analysis.
Note: For brevity and to ensure outputs are not disclosive of individuals, the results have been aggregated on the annual rather than daily level. Valid immigration status includes those with valid visas, ILR and citizenship.
Male
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
96% |
| 3 |
91% |
| 4 |
82% |
| 5 |
80% |
| 6 |
73% |
| 7 |
71% |
| 8 |
70% |
| 9 |
70% |
| 10 |
70% |
| 11 |
70% |
Female
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
98% |
| 3 |
95% |
| 4 |
87% |
| 5 |
85% |
| 6 |
80% |
| 7 |
77% |
| 8 |
77% |
| 9 |
77% |
| 10 |
76% |
| 11 |
76% |
Source: MAC internal analysis.
Note: For brevity and to ensure outputs are not disclosive of individuals, the results have been aggregated on the annual rather than daily level. Valid immigration status includes those with valid visas, ILR and citizenship.
In-country
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
98% |
| 3 |
94% |
| 4 |
87% |
| 5 |
86% |
| 6 |
83% |
| 7 |
81% |
| 8 |
81% |
| 9 |
81% |
| 10 |
81% |
| 11 |
81% |
Out-of-country
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
93% |
| 4 |
83% |
| 5 |
81% |
| 6 |
73% |
| 7 |
70% |
| 8 |
70% |
| 9 |
70% |
| 10 |
69% |
| 11 |
69% |
Source: MAC internal analysis.
Note: For brevity and to ensure outputs are not disclosive of individuals, the results have been aggregated on the annual rather than daily level. Salaries are inflated to reflect 2024 earning levels. Valid immigration status includes those with valid visas, ILR and citizenship.
2014-2016 cohort
<£40,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
98% |
| 3 |
92% |
| 4 |
82% |
| 5 |
80% |
| 6 |
78% |
| 7 |
77% |
| 8 |
77% |
| 9 |
76% |
| 10 |
76% |
| 11 |
76% |
£40,000-£50,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
98% |
| 2 |
94% |
| 3 |
86% |
| 4 |
75% |
| 5 |
72% |
| 6 |
69% |
| 7 |
67% |
| 8 |
67% |
| 9 |
67% |
| 10 |
67% |
| 11 |
67% |
£50,000-£75,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
90% |
| 4 |
79% |
| 5 |
76% |
| 6 |
71% |
| 7 |
69% |
| 8 |
69% |
| 9 |
68% |
| 10 |
68% |
| 11 |
68% |
£75,000-£125,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
94% |
| 4 |
80% |
| 5 |
79% |
| 6 |
65% |
| 7 |
62% |
| 8 |
62% |
| 9 |
62% |
| 10 |
62% |
| 11 |
62% |
£125,000+ sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
98% |
| 2 |
96% |
| 3 |
91% |
| 4 |
73% |
| 5 |
70% |
| 6 |
51% |
| 7 |
45% |
| 8 |
45% |
| 9 |
44% |
| 10 |
44% |
| 11 |
43% |
2017-2019 cohort
<£40,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
99% |
| 3 |
96% |
| 4 |
91% |
| 5 |
90% |
| 6 |
87% |
| 7 |
84% |
| 8 |
84% |
£40,000-£50,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
98% |
| 2 |
93% |
| 3 |
86% |
| 4 |
77% |
| 5 |
74% |
| 6 |
71% |
| 7 |
70% |
| 8 |
69% |
£50,000-£75,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
92% |
| 4 |
85% |
| 5 |
83% |
| 6 |
78% |
| 7 |
77% |
| 8 |
76% |
£75,000-£125,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
96% |
| 3 |
93% |
| 4 |
85% |
| 5 |
84% |
| 6 |
74% |
| 7 |
73% |
| 8 |
72% |
£125,000+ sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
92% |
| 4 |
79% |
| 5 |
76% |
| 6 |
55% |
| 7 |
53% |
| 8 |
52% |
2020-2022 cohort
<£40,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
98% |
| 3 |
96% |
| 4 |
89% |
| 5 |
88% |
£40,000-£50,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
98% |
| 2 |
95% |
| 3 |
89% |
| 4 |
82% |
| 5 |
79% |
£50,000-£75,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
96% |
| 3 |
92% |
| 4 |
85% |
| 5 |
82% |
£75,000-£125,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
95% |
| 4 |
88% |
| 5 |
85% |
£125,000+ sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
93% |
| 4 |
84% |
| 5 |
81% |
2023-2024 cohort
<£40,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
98% |
£40,000-£50,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
98% |
| 2 |
94% |
£50,000-£75,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
97% |
| 2 |
93% |
£75,000-£125,000 sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
97% |
| 2 |
95% |
£125,000+ sub-cohort
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
97% |
| 2 |
95% |
Source: MAC internal analysis.
Note: For brevity and to ensure outputs are not disclosive of individuals, the results have been aggregated on the annual rather than daily level. Valid immigration status includes those with valid visas, ILR and citizenship.
Education
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
97% |
| 2 |
89% |
| 3 |
79% |
| 4 |
70% |
| 5 |
66% |
| 6 |
62% |
| 7 |
60% |
| 8 |
59% |
| 9 |
59% |
| 10 |
59% |
| 11 |
58% |
Financial and Insurance Activities
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
98% |
| 2 |
97% |
| 3 |
95% |
| 4 |
84% |
| 5 |
83% |
| 6 |
73% |
| 7 |
70% |
| 8 |
69% |
| 9 |
69% |
| 10 |
69% |
| 11 |
68% |
Human Health and Social Work Activities
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
100% |
| 2 |
98% |
| 3 |
96% |
| 4 |
91% |
| 5 |
90% |
| 6 |
87% |
| 7 |
85% |
| 8 |
85% |
| 9 |
85% |
| 10 |
85% |
| 11 |
84% |
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
93% |
| 4 |
84% |
| 5 |
82% |
| 6 |
72% |
| 7 |
70% |
| 8 |
70% |
| 9 |
69% |
| 10 |
69% |
| 11 |
69% |
Professional, Scientific and Technical Activities
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
97% |
| 3 |
92% |
| 4 |
81% |
| 5 |
80% |
| 6 |
73% |
| 7 |
71% |
| 8 |
70% |
| 9 |
70% |
| 10 |
70% |
| 11 |
70% |
Other
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
96% |
| 3 |
91% |
| 4 |
81% |
| 5 |
79% |
| 6 |
70% |
| 7 |
68% |
| 8 |
68% |
| 9 |
67% |
| 10 |
67% |
| 11 |
67% |
Source: MAC internal analysis.
Note: For brevity and to ensure outputs are not disclosive of individuals, the results have been aggregated on the annual rather than daily level. SOC codes are presented in the 2010 format. Valid immigration status includes those with valid visas, ILR and citizenship.
*Incomplete year, presented data is stay rate at final available data point.
Natural and social science professionals n.e.c.
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
96% |
| 2 |
85% |
| 3 |
72% |
| 4 |
62% |
| 5 |
57% |
| 6 |
54% |
| 7 |
52% |
| 8 |
52% |
| 9 |
52% |
| 10 |
51% |
| 11 |
51% |
IT business analysts, architects and systems designers
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
98% |
| 3 |
94% |
| 4 |
87% |
| 5 |
86% |
| 6 |
80% |
| 7 |
78% |
| 8 |
78% |
| 9 |
78% |
| 10 |
77% |
| 11 |
77% |
Programmers and software development professionals
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
98% |
| 3 |
95% |
| 4 |
87% |
| 5 |
86% |
| 6 |
76% |
| 7 |
74% |
| 8 |
74% |
| 9 |
74% |
| 10 |
74% |
| 11 |
74% |
Medical practitioners
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
93% |
| 3 |
88% |
| 4 |
85% |
| 5 |
83% |
| 6 |
82% |
| 7 |
81% |
| 8 |
81% |
| 9 |
81% |
| 10 |
81% |
| 11 |
81% |
Nurses
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
100% |
| 2 |
100% |
| 3 |
99% |
| 4 |
94% |
| 5 |
93% |
| 6 |
89% |
| 7 |
87% |
| 8 |
86% |
| 9 |
86% |
| 10 |
86% |
| 11 |
86% |
Management consultants and business analysts
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
98% |
| 3 |
95% |
| 4 |
84% |
| 5 |
83% |
| 6 |
75% |
| 7 |
73% |
| 8 |
73% |
| 9 |
72% |
| 10 |
72% |
| 11 |
72% |
Care workers and home carers
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
100% |
| 2 |
99% |
| 3* |
99% |
Senior care workers
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
100% |
| 2 |
100% |
| 3 |
97% |
| 4* |
95% |
All other occupations
| Years since arrival |
Stay rate (% with valid immigration status) |
| 0 |
100% |
| 1 |
99% |
| 2 |
96% |
| 3 |
92% |
| 4 |
81% |
| 5 |
79% |
| 6 |
71% |
| 7 |
68% |
| 8 |
68% |
| 9 |
67% |
| 10 |
67% |
| 11 |
67% |
| Region |
Stay rate among skilled worker visa holders |
| East Midlands |
81% |
| East of England |
82% |
| London |
80% |
| North East |
80% |
| North West |
80% |
| Northern Ireland |
81% |
| Scotland |
73% |
| South East |
79% |
| South West |
81% |
| Wales |
78% |
| West Midlands |
83% |
| Yorkshire and the Humber |
78% |
Source: MAC internal analysis.
Table 4.1: Logistic regression results presented in odds ratios
| Variable |
Odds Ratio |
Lower or higher odds of holding valid immigration status after five years? (compared to reference) |
| Visa application was submitted out-of-country |
0.71*** |
Lower |
| Applicant is female |
1.27*** |
Higher |
| Age at entry (reference: age less than 25) |
|
|
| 25-34 |
1.31*** |
Higher |
| 35-44 |
1.14*** |
Higher |
| 45-54 |
0.85*** |
Lower |
| 55+ |
0.53*** |
Lower |
| Region of origin (reference: Europe – non-EU) |
|
|
| Africa |
1.04 |
Not statistically significant |
| Western Asia |
0.80*** |
Lower |
| Southern Asia |
0.80*** |
Lower |
| Asia (other) |
0.57*** |
Lower |
| Latin America and the Caribbean |
0.67*** |
Lower |
| North America |
0.41*** |
Lower |
| Oceania |
0.30*** |
Lower |
| Industry (reference: all other industries) |
|
|
| Education |
0.52*** |
Lower |
| Financial and insurance activities |
1.39*** |
Higher |
| Human health and social work activities |
1.77*** |
Higher |
| Information and communications |
1.02 |
Not statistically significant |
| Professional, scientific and technical activities |
1.04 |
Not statistically significant |
| Employer UK nation or region (reference: London) |
|
|
| East Midlands |
0.90** |
Lower |
| East of England |
0.94* |
Lower |
| North East |
0.99 |
Not statistically significant |
| North West |
0.81*** |
Lower |
| Northern Ireland |
0.87* |
Lower |
| Scotland |
0.76*** |
Lower |
| South East |
0.86*** |
Lower |
| South West |
0.92* |
Lower |
| Wales |
0.72*** |
Lower |
| West Midlands |
0.96 |
Not statistically significant |
| Yorkshire and the Humber |
0.90* |
Lower |
| Year of entry (reference: 2014) |
|
|
| 2015 |
1.27*** |
Higher |
| 2016 |
1.36*** |
Higher |
| 2017 |
1.50*** |
Higher |
| 2018 |
1.70*** |
Higher |
| 2019 |
1.91*** |
Higher |
Source: MAC internal analysis.
Note: *** p < 0.001; ** p < 0.01; * p < 0.05. No asterisk signifies that the result is not statistically significant. All values in the table are rounded to two decimal places.
| Variable |
Raw Odds Ratio |
Adjusted Odds Ratio |
Lower or higher odds of holding valid immigration status after five years? (compared to reference) |
| Visa application was submitted out-of-country |
0.82 |
0.71*** |
Lower |
| Applicant is female |
1.42 |
1.27*** |
Higher |
| Age at entry (reference: age less than 25) |
|
|
|
| 25-34 |
1.03 |
1.31*** |
Higher |
| 35-44 |
0.8 |
1.14*** |
Higher |
| 45-54 |
0.5 |
0.85*** |
Lower |
| 55+ |
0.26 |
0.53*** |
Lower |
| Region of origin (reference: Europe – non-EU) |
|
|
|
| Africa |
1.16 |
1.04 |
Not statistically significant |
| Western Asia |
0.81 |
0.80*** |
Lower |
| Southern Asia |
0.94 |
0.80*** |
Lower |
| Asia (other) |
0.75 |
0.57*** |
Lower |
| Latin America and the Caribbean |
0.67 |
0.67*** |
Lower |
| North America |
0.38 |
0.41*** |
Lower |
| Oceania |
0.31 |
0.30*** |
Lower |
| Industry (reference: all other industries) |
|
|
|
| Education |
0.57 |
0.52*** |
Lower |
| Financial and insurance activities |
1.51 |
1.39*** |
Higher |
| Human health and social work activities |
2.35 |
1.77*** |
Higher |
| Information and communications |
1.19 |
1.02 |
Not statistically significant |
| Professional, scientific and technical activities |
1.21 |
1.04 |
Not statistically significant |
| Employer UK nation or region (reference: London) |
|
|
|
| East Midlands |
1.07 |
0.90** |
Lower |
| East of England |
1.14 |
0.94* |
Lower |
| North East |
0.96 |
0.99 |
Not statistically significant |
| North West |
0.96 |
0.81*** |
Lower |
| Northern Ireland |
1.07 |
0.87* |
Lower |
| Scotland |
0.65 |
0.76*** |
Lower |
| South East |
0.9 |
0.86*** |
Lower |
| South West |
1.04 |
0.92* |
Lower |
| Wales |
0.85 |
0.72*** |
Lower |
| West Midlands |
1.17 |
0.96 |
Not statistically significant |
| Yorkshire and the Humber |
0.85 |
0.90* |
Lower |
| Year of entry (reference: 2014) |
|
|
|
| 2015 |
1.15 |
1.27*** |
Higher |
| 2016 |
1.25 |
1.36*** |
Higher |
| 2017 |
1.39 |
1.50*** |
Higher |
| 2018 |
1.68 |
1.70*** |
Higher |
| 2019 |
2.09 |
1.91*** |
Higher |
Source: MAC internal analysis.
Note: For adjusted ORs *** p < 0.001; ** p < 0.01; * p < 0.05. No asterisk signifies that the adjusted OR is not statistically significant. European nationality group includes non-EU countries only with Russians and Ukrainians being the most commonly occurring. The dark blue line surrounding each adjusted OR shows the range of values in its 95% confidence interval.
Table 4.2: Occupation logistic regression results: odds ratios
| Occupation (reference: all other occupations) |
Odds Ratio |
Lower or higher odds of holding valid immigration status after five years? (compared to reference) |
| Natural and social science professionals |
0.35*** |
Lower |
| IT business analysts, architects and systems designers |
1.35*** |
Higher |
| Programmers and software development professionals |
1.32*** |
Higher |
| Medical practitioners |
1.17*** |
Higher |
| Nurses |
3.93*** |
Higher |
| Management consultants and business analysts |
1.17*** |
Higher |
Source: MAC internal analysis.
Note: *** p < 0.001; ** p < 0.01; * p < 0.05. No asterisk signifies that the result is not statistically significant. All values in the table are rounded to two decimal places. We control for the full set of covariates presented in Table 4.1 with the exception of industry due to the risk of multicollinearity; the odds ratios for factors we have previously controlled for have been omitted for brevity.
Table 4.3: Salary band logistic regression results: odds ratios
| Salary band (reference: <£40,000) |
Odds Ratio |
Lower or higher odds of holding valid immigration status after five years? (compared to reference) |
| £40,000-£50,000 |
0.52*** |
Lower |
| £50,000-£75,000 |
0.77*** |
Lower |
| £75,000-£125,000 |
0.94* |
Lower |
| £125,000+ |
0.86*** |
Lower |
Source: MAC internal analysis.
Note: *** p < 0.001; ** p < 0.01; * p < 0.05. No asterisk signifies that the result is not statistically significant. All values in the table are rounded to two decimal places. We control for the full set of covariates presented in Table 4.1 with the exception of industry and age due to the risk of multicollinearity; age band was found to be highly correlated with salary. The odds ratios for factors we have previously controlled for have been omitted for brevity. Salaries have been adjusted to 2024 earning levels.
Annex
| fir |
Raw Odds Ratio |
Adjusted Odds Ratio |
Lower or higher odds of holding valid immigration status after five years? (compared to reference) |
| Visa application was submitted out-of-country |
0.82 |
0.65*** |
Lower |
| Applicant is female |
1.42 |
1.14*** |
Higher |
| Age at entry (reference: age less than 25) |
|
|
|
| 25-34 |
1.03 |
1.31*** |
Higher |
| 35-44 |
0.8 |
1.15*** |
Higher |
| 45-54 |
0.5 |
0.84*** |
Lower |
| 55+ |
0.26 |
0.51*** |
Lower |
| Region of origin (reference: Europe – non-EU) |
|
|
|
| Africa |
1.16 |
1.12* |
Higher |
| Western Asia |
0.81 |
0.85** |
Lower |
| Southern Asia |
0.94 |
0.79*** |
Lower |
| Asia (other) |
0.75 |
0.53*** |
Lower |
| Latin America and the Caribbean |
0.67 |
0.65*** |
Lower |
| North America |
0.38 |
0.43*** |
Lower |
| Oceania |
0.31 |
0.34*** |
Lower |
| Occupation (reference: all other occupations) |
|
|
|
| Natural and social science professionals |
0.39 |
0.35*** |
Lower |
| IT business analysts, architects and system designers |
1.63 |
1.35*** |
Higher |
| Programmers and development professionals |
1.58 |
1.32*** |
Higher |
| Medical practitioners |
1.55 |
1.17*** |
Higher |
| Management consultants and business analysts |
1.38 |
1.17*** |
Higher |
| Nurses |
4.46 |
3.93*** |
Higher |
| Employer UK nation or region (reference: London) |
|
|
|
| East Midlands |
1.07 |
0.86*** |
Lower |
| East of England |
1.14 |
0.92** |
Lower |
| North East |
0.96 |
0.92 |
Not statistically significant |
| North West |
0.96 |
0.77*** |
Lower |
| Northern Ireland |
1.07 |
0.77*** |
Lower |
| Scotland |
0.65 |
0.78*** |
Lower |
| South East |
0.9 |
0.81*** |
Lower |
| South West |
1.04 |
0.89*** |
Lower |
| Wales |
0.85 |
0.78*** |
Lower |
| West Midlands |
1.17 |
1.01 |
Not statistically significant |
| Yorkshire and the Humber |
0.85 |
0.95 |
Not statistically significant |
| Year of entry (reference: 2014) |
|
|
|
| 2015 |
1.15 |
1.31*** |
Higher |
| 2016 |
1.25 |
1.42*** |
Higher |
| 2017 |
1.39 |
1.57*** |
Higher |
| 2018 |
1.68 |
1.75*** |
Higher |
| 2019 |
2.09 |
1.88*** |
Higher |
Source: MAC internal analysis.
Note: For adjusted ORs *** p < 0.001; ** p < 0.01; * p < 0.05. No asterisk signifies that the adjusted OR is not statistically significant. European nationality group includes non-EU countries only with Russians and Ukrainians being the most commonly occurring. The dark blue line surrounding each adjusted OR shows the range of values in its 95% confidence interval.
| Variable |
Raw Odds Ratio |
Adjusted Odds Ratio |
Lower or higher odds of holding valid immigration status after five years? (compared to reference) |
| Visa application was submitted out-of-country |
0.82 |
0.79*** |
Lower |
| Applicant is female |
1.42 |
1.39*** |
Higher |
| Region of origin (reference: Europe – non-EU) |
|
|
|
| Africa |
1.16 |
1.3*** |
Higher |
| Western Asia |
0.81 |
0.81*** |
Lower |
| Southern Asia |
0.94 |
0.95 |
Not statistically significant |
| Asia (other) |
0.75 |
0.65*** |
Lower |
| Latin America and the Caribbean |
0.67 |
0.67*** |
Lower |
| North America |
0.38 |
0.36*** |
Lower |
| Oceania |
0.31 |
0.32*** |
Lower |
| Salary band (reference: < £40,000) |
|
|
|
| £40,000-£50,000 |
0.44 |
0.52*** |
Lower |
| £50,000-£75,000 |
0.66 |
0.77*** |
Lower |
| £75,000-£125,000 |
0.73 |
0.94* |
Lower |
| £125,000+ |
0.45 |
0.86*** |
Lower |
| Employer UK nation or region (reference: London) |
|
|
|
| East Midlands |
1.07 |
0.88** |
Lower |
| East of England |
1.14 |
0.96 |
Not statistically significant |
| North East |
0.96 |
0.92 (.) |
Lower |
| North West |
0.96 |
0.78*** |
Lower |
| Northern Ireland |
1.07 |
0.92 |
Not statistically significant |
| Scotland |
0.65 |
0.69*** |
Lower |
| South East |
0.9 |
0.82*** |
Lower |
| South West |
1.04 |
0.88*** |
Lower |
| Wales |
0.85 |
0.72*** |
Lower |
| West Midlands |
1.17 |
1.02 |
Not statistically significant |
| Yorkshire and the Humber |
0.85 |
0.78*** |
Lower |
| Year of entry (reference: 2014) |
|
|
|
| 2015 |
1.15 |
1.28*** |
Higher |
| 2016 |
1.25 |
1.42*** |
Higher |
| 2017 |
1.39 |
1.55*** |
Higher |
| 2018 |
1.68 |
1.75*** |
Higher |
| 2019 |
2.09 |
2.06*** |
Higher |
Source: MAC internal analysis.
Note: For adjusted ORs *** p < 0.001; ** p < 0.01; * p < 0.05; . p < 0.1. No asterisk/dot signifies that the adjusted OR is not statistically significant. European nationality group includes non-EU countries only with Russians and Ukrainians being the most commonly occurring. The dark blue line surrounding each adjusted OR shows the range of values in its 95% confidence interval.