1. This report examines the early career employment outcomes of UK-domiciled students who qualified from a full-time first degree course in the academic year 2008-09. It identifies differences in employment outcomes for different equality groups among those qualifying from publicly funded English higher education institutions, and examines whether differences seen in a graduate’s early career persist into the medium term.
2. Interactive graphs accompany this document, and provide more detailed data relating to some of the profiles and employment rates discussed here. They can be accessed on the HEFCE website at www.hefce.ac.uk/analysis/employment.
3. Research to understand differences in the higher education (HE) outcomes achieved by students from different backgrounds has previously looked at their retention in HE, their level of attainment, and whether they gain employment or progress to further study. Understanding how differences in graduates’ early career outcomes can persist into the medium term forms part of HEFCE’s ongoing programme of work in this area, and this report seeks to extend the existing evidence base by incorporating this additional dimension.
4. In future, the availability of HM Revenue and Customs data and HEFCE’s ability to track graduates throughout their careers will vastly enhance the evidence base relating to medium and longer term graduate outcomes. Until such time, this report fills some of the information gap that currently exists in this area.
5. This report seeks to build on previous HEFCE work that has highlighted significant differences between student groups (when controlling for other background characteristics) in terms of academic attainment in HE and in terms of employment and further study outcomes. It looks at UK-domiciled students who qualified from a full-time first degree course in the academic year 2008-09, and considers their employment and further study outcomes at both six months and three-and-a-half years (40 months) after they left HE. The report specifically examines differences in the employment outcomes of different equality groups.
6. We have not attempted to identify the specific causes behind the findings. We can show, however, that some suggestions about differences in HE employment outcomes, while plausible, are not supported by the evidence. The report uses statistical modelling techniques to isolate the effects of a number of different equality and diversity characteristics on the employment outcomes of students six months and 40 months after they left HE1. We have used these techniques to establish whether the patterns seen in the observed employment outcomes are robust to the effects of other measurable factors and unobserved institutional effects. This approach helps to determine whether these background and study characteristics might be responsible for the patterns we have observed.
7. For example, it might be supposed that employability differentials among HE qualifiers were the direct result of the higher education institution (HEI) that the student attended, rather than the qualifications they held upon entry to HE or some other aspect of their educational or socio-economic background. However, the modelling techniques employed in the report eliminate this possibility by making explicit allowance for differences in the outcomes of students from different HEIs. We can therefore be confident that our findings are not the result of institutional effects.
8. This study looks at UK-domiciled students who qualified from a full-time, first degree course in the academic year 2008-09, and considers differences identified in the employment outcomes of different equality groups. The key findings from this investigation largely focus on whether differences seen in a graduate’s early career persist into the medium term on the basis of the actual outcomes observed among these qualifiers. The main body of this report provides a fuller understanding of these differences, including in the context of statistical modelling.
Overall there is a substantial improvement in graduate outcomes between six and 40 months after leaving HE.
9. The proportion of qualifiers employed in professional and managerial roles or in further study 40 months after leaving HE was 77.8 per cent: this ‘professional employment rate’ was 13.7 percentage points higher than the equivalent figure six months after leaving.
10. Similarly the ‘employment rate’ – the proportion of qualifiers who were in either employment or further study – increased by 6.4 percentage points, from 90.0 per cent to 96.4 per cent in this period.
Differences in employment rates diminish between six and 40 months after leaving HE.
11. We find that differences seen in employment and professional employment rates six months after leaving HE have reduced substantially by 40 months for a number of the characteristics examined. In particular:
a. The large variation in employment rates among graduates from different subject areas diminishes as careers develop.
Six months after graduation employment rates varied considerably across subject areas; from 82.1 per cent among computer science qualifiers to 99.6 per cent for qualifiers from medicine and dentistry. Forty months after leaving HE computer science remained the subject area with the lowest employment rate. However, having increased to 94.2 per cent this results in variation in the employment rates observed across subject areas falling to below 6 percentage points.
Variation in ‘professional employment rates’ – the proportion of qualifiers who were in either professional employment or further study – also reduced across graduates’ early careers.
b. Employment rates among Chinese qualifiers increase dramatically across their early careers.
Differences in employment rates among many ethnic groups diminish between six and 40 months after leaving HE. The lowest employment rate (of 78.4 per cent, among Chinese qualifiers) was 12.8 percentage points lower six months after graduation than the highest rate, observed among White qualifiers (91.2 per cent). At 40 months White qualifiers were again found to have the highest rate (97.2 per cent), with Chinese qualifiers having a similar rate (96.5 per cent). At this point in graduates’ careers, these rates were around 9 percentage points higher than the lowest employment rate, observed among Black African qualifiers (88.1 per cent).
c. Female qualifiers have higher employment rates across their early careers, but male qualifiers make considerable gains to catch them up.
Employment and professional employment rates of male qualifiers increased across their early careers relative to female qualifiers. At six months, the employment rate for female qualifiers was 5.1 percentage points higher, but by 40 months the difference had reduced such that female qualifiers had a rate that was only 1.7 percentage points higher.
d. Higher professional employment rates among mature qualifiers do not persist.
Six months after leaving HE, mature qualifiers aged 30 and over had a professional employment rate of 76.1 per cent. Forty months after graduation the professional employment rate of mature qualifiers was 79.6 per cent. These rates were the highest for all age groups, but the differences between all age groups narrow considerably between six and 40 months.
But there are a number of characteristics where differences do not reduce across a graduate’s early career, especially with regards to professional employment.
12. However, for some characteristics and particularly in consideration of the professional employment rate, we find that differences seen six months after leaving HE have not reduced by 40 months and instead have remained persistent or increased. In particular:
a. Lower professional employment rates among disadvantaged students persist across their early careers.
Six months after leaving HE, professional employment rates ranged from 59.7 per cent among the most disadvantaged qualifiers (as measured by quintile 1 of HEFCE’s Participation of Local Areas – POLAR3 – classification) to 67.4 per cent among the least disadvantaged qualifiers (POLAR3 quintile 5): a difference of 7.7 percentage points.
These differences remain largely unchanged in outcomes observed 40 months after graduation. While the most disadvantaged qualifiers saw professional employment rates increase by 14.4 percentage points across their early careers (to 73.1 per cent), the least disadvantaged qualifiers saw a similar increase of 15.1 percentage points (to 80.5 per cent).
b. Ethnic groups see differences in their professional employment rates widen.
Conversely to the change identified in employment rates, differences in professional employment rates among ethnic groups appear to increase slightly across a graduate’s early career.
Black Caribbean qualifiers had the lowest rate of professional employment six months after graduation, of 55.4 per cent. This was 9.3 percentage points lower than the highest rate of 64.7 per cent, observed among White qualifiers. Forty months after leaving HE the difference between the highest and lowest professional employment rates had widened to 13.2 percentage points. Black African qualifiers had the lowest rate at this stage of graduates’ early careers (65.9 per cent), while Asian Indian and White qualifiers had the highest rates (79.1 per cent and 78.7 per cent respectively).
c. Similarities in the professional employment rates of male and female qualifiers diminish as careers develop, with a higher proportion of male qualifiers in professional employment or further study.
The professional employment rate of male qualifiers increased relative to female qualifiers between six and 40 months after leaving HE. While male qualifiers had a professional employment rate only 0.3 percentage points higher than female qualifiers six months after graduation, the male qualifiers’ rate was 1.9 percentage points higher 40 months after graduation.
13. Interactive graphs accompany this document and provide access to further, detailed data relating to the profiles and employment rates discussed above. They can be accessed on the HEFCE web-site at www.hefce.ac.uk/analysis/employment.
14. This document is for information only.
1 The measurable factors that have been accounted for in statistical modelling are: age (as at 31 August in the 2008-09 academic year of graduation); disability status; ethnicity; an area-based measure of disadvantage (POLAR3 quintile); sex; subject of study; region of domicile; prior attainment (in terms of qualifications held on entry to HE); degree classification; previous school type; teaching arrangements (whether or not the student was taught by an HEI’s partner institution under a franchising arrangement); sandwich year; institution attended.