By Esteban Aucejo, Claudia Hupkau and Jenifer Ruiz-Valenzuela
Following the
unprecedented number of job losses and the bleak economic outlook due to the
Covid-19 crisis, more people will be considering staying on or returning to
education. Vocational education and training (VET) is likely to play a crucial
role in providing the skills needed for economic recovery, including retraining
workers who have been made redundant. In this context, it is crucial to have
good information on the returns to different fields of study that can be taken
at FE colleges, and whether it matters which institution one attends for
earnings and employment prospects. Our new research published by the Centre
for Vocational Education Research (CVER) finds that when it comes to vocational
education and training (VET), what you study is very important for future
earnings. Whereas where you study can
also matter for younger people but less so for adults.
We
used data from more than one million students over 13 years to investigate how
much value attending an FE college adds in terms of academic achievement,
earnings and employment, taking into account learners’ prior achievements and
their socio-economic background. Our study considers both young learners, who mostly
join FE colleges shortly after compulsory education, as well as adult learners,
who have often worked for many years before attending FE college.
Our value-added measure indicates
that moving a student from a college ranked in the bottom 15 percent of the
college value-added distribution to one ranked in the top 15% implies a fairly
modest 3% higher earnings on average, measured at around seven years after
leaving FE college. The difference in earnings for adult learners is smaller,
at 1.5%. The fact that college quality seems to matter more for young learners is
likely due to young learners spending more time in FE colleges (i.e. they enrol
in and complete substantially more learning than adults). The results in terms
of the likelihood of being employed show even smaller differences across FE
colleges.
There is considerably more
variation in FE colleges' contributions to the educational attainment of their
young learners. On average, the young people in our sample enrol in just under
600 learning hours, but only achieve about 413 (or 69% of them), around 42%
achieve a Level 3 qualification, and 38% progress to higher education.
But were we to move a
learner from a college ranked in the bottom 15% by value-added to one ranked in
the top 15%, they would, on average, achieve 6.5% more learning hours (from 69%
to 73.4%). They would be almost 11% more likely to achieve a Level 3
qualification (from 42% to 46.5%) and the likelihood of attending higher
education would increase by 10% (from 38% to 42%). These are large effects. As
young people are likely to attend their nearest college, the variability in
value-added between institutions is a source of unequal opportunity between geographic
areas.
What differentiates high
value-added colleges from low value-added ones? Learning characteristics seem
to play an important role. Colleges that offer a larger share of their courses
in the classroom (as opposed to in the workplace or at a distance) have higher
value-added in earnings for young learners. This is particularly relevant in
light of the current crisis, where online and distance learning is expected to
remain a regular feature, at least in the medium term. We also find significant
correlations between the curriculum offer and value-added measures, with
colleges offering more exam-assessed qualifications (as opposed to competency-based)
showing higher value-added.
While
where you study does not imply large differences in earnings after college,
what you study has a much bigger effect, especially for female and young
learners. We carried out a separate analysis looking at students’ earnings
before and after attending FE college. In this analysis the young people were
aged 18-20 and so had been working for up to two years’ prior to study. Table 1
below shows the 3 most popular fields (in terms of learners doing most of their
guided learning hours in that particular field, i.e. specialising in them) by
gender and age group.
The two fields of
engineering and manufacturing technology, and business administration and law
show large levels of enrolment among males and lead to large positive returns.
For instance, the typical young male learner who chooses engineering and
manufacturing technology as his main field of study will earn, on average,
almost 7% more five years after finishing education when compared to earnings
before attending FE college, after adjusting for inflation. For adult male learners specialising in this
field, earnings rise by 1.5% five years after leaving college. In contrast, young
male learners specialising in retail and commercial enterprise do not see any
increase in earnings five years after attending FE college. These results take
into account that earnings increase with experience, irrespectively of which
field one specialised in. Business administration and law, and health, public
services and care are the two fields that show high levels of enrolment and
consistent positive returns for women across age groups.
While we find
consistently higher returns to fields of study for women than for men, this
does not mean that overall, they have higher earnings post FE-college
attendance. It means that compared to before enrolment, they experience steeper
increases in earnings after completing their education at FE colleges. We
also find that many specialisations present negative
returns immediately after leaving college that turn positive five years after
graduation, indicating that it takes time for positive returns to be reflected
in wages. The fact that timing matters suggests that policy makers should be
extremely cautious about evaluating colleges in terms of the labour market
performance of their students.
Our
findings also have relevant practical implications for students since they
could help them to get a better understanding of the variation in FE college
quality and to compare the returns to different fields of study. This
information is likely to be particularly important considering the evidence
suggesting that students tend to be misinformed about the labour market returns
of VET qualifications.
Table 1. Top 3 Fields of
study by proportion of learners who specialise in them
|
Mean GLH
|
Estimated Return
|
Share specialising
|
|
|
main field
|
1 year post-FE
|
5 years post-FE
|
in the field
|
Young male learners
|
|
|
|
|
Engineering and
Manufacturing Technology
|
632
|
0.04
|
0.068
|
20.60%
|
Construction, Planning
& Built Environment
|
621
|
-0.001
|
0.023
|
16.60%
|
Arts, Media and
Publishing
|
942
|
-0.064
|
-0.003
|
10.70%
|
Adult male learners
|
|
|
|
|
Health, Public
Services and Care
|
77
|
-0.006
|
0.004
|
19.00%
|
Engineering and
Manufacturing Technology
|
206
|
-0.008
|
0.015
|
18.90%
|
Business
Administration and Law
|
131
|
0.003
|
0.009
|
14.20%
|
Young female learners
|
|
|
|
|
Health, Public
Services and Care
|
525
|
-0.002
|
0.045
|
25.20%
|
Retail and Commercial
Enterprise
|
597
|
0.036
|
0.115
|
23.40%
|
Business
Administration and Law
|
430
|
0.040
|
0.118
|
13.60%
|
Adult female learners
|
|
|
|
|
Health, Public
Services and Care
|
142
|
-0.008
|
0.020
|
34.30%
|
Business
Administration and Law
|
189
|
0.004
|
0.019
|
14.80%
|
Education and Training
|
143
|
-0.007
|
0.027
|
12.70%
|
Note. The estimated returns reported are the
marginal effects, one and five years after leaving the college, respectively,
of choosing the field as the main field. This is a summary table. The complete
tables can be found in Tables 9 to 12 of CVER DP 030