Variation in the labour market rewards to vocational qualifications in the UK
| Published date | 01 November 2021 |
| Author | Steven McIntosh,Damon Morris |
| Date | 01 November 2021 |
| DOI | http://doi.org/10.1111/sjpe.12299 |
Scott J Polit Econ . 2021;68:535–552. wileyonlinelibrary.com/journal/sjpe
|
535
© 2021 Scottish Ec onomic Society
1 | INTRODUCTION
A huge variety of vo cational qualificatio ns exist in the UK. The Wolf Repor t (Wolf, 2011), into vocational educa-
tion for 14- to 19- year- olds, suggested th at there are around 13,00 0 different vocati onal qualifications in t he UK,
once we take into account different awarding bodies, levels and subject areas. There is therefore no reason to
expect a singl e answer to the questi on “what is the labour ma rket value of a vocationa l qualification in t he UK” and
rather, a great amount of v ariation should be expec ted. This paper is an attem pt to shed some light on this varia-
tion, looking i n particular at the subje ct area of qualificati ons, which has received lit tle attention in the liter ature.
Education in Engl and differs from tha t in many other developed cou ntries by having separate q ualifications by
subject to be taken at the end of compulsory full- time education at the age 16: the General Certificates of
Secondary E ducation (GCSEs). Follow ing these examination s, young people must, s ince 2015, continue to receive
some form of educ ation until the age of 18,1 either by remaining in full- time education, undertaking an apprentice-
ship or traineeship, or working in a job whilst studying part- time.
1This is not a requi rement in the oth er countries of t he UK, where in dividuals can s till complete ly leave educat ion and traini ng at age 16.
Accepted: 5 Augu st 2021
DOI: 10 .1111/sjpe.1 2299
ORIGINAL ARTICLE
Variation in the labour market rewards to
vocational qualifications in the UK
Steven McIntosh1| Damon Morris2
1Departme nt of Economics, Uni versity of
Sheffield, Sheffield, UK
2School of Heal th and Related Resea rch,
University of Sheffield, Sheffield, UK
Correspondence
Steven McIntosh, Department of
Economics, U niversity of Shef field,
Sheffiel d S1 4DT, UK.
Email: s.mcintosh@sheffield.ac.uk
Funding information
Department for Education
Abstract
We use UK Labour Force Survey data to estimate wage
differentials associated with the attainment of vocational
qualifications, relative to comparison groups qualified to at
best one level below. Our ma in aim is to show the variation
in the size of such differe ntials, according to the unobser ved
characteristics of the individual, via quantile regression and
also according to the characteristics of the qualifications
themselves, in terms of the level, type and subject area.
With respect to subject area, the key reason for variation
in differentials ac ross subjects is the differences in o ccupa-
tions to which qualifications lead.
KEYWORDS
vocational qualifications, wage differentials
536
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MCINTOSH aNd MORRIS
In order to help ind ividuals make such decisions abo ut which route and which qualifi cations to take, it is im-
portant for t hem to have information on the ec onomic value placed on tho se qualifications by the la bour market.
This paper provi des such information, by est imating wage differentia ls between a treatment gro up with a partic-
ular qualific ation, and a control group with out that qualification. Of m ost interest to individuals is t he change in
their wages if the y reach a new highest edu cation level via acquir ing a new qualificatio n, and so the control gro ups
we consider are mad e up of individuals one level be low the qualification b eing considered, to provi de an estimate
of the wages that woul d be received had the indiv idual not acquired that qual ification.
The “returns to ed ucation” literature is one of the la rgest in the applied economi cs field. Extensive work h as
been under taken looking at how earning s vary on average with an addit ional year of education, wit h much work
focussing on methodological approaches to obtaining unbiased estimates of t he coefficients on education vari-
ables.2 In parallel w ith this literature look ing at the effect of a single va riable, years of educati on, another has de-
veloped looking at the wage differentials associated with a range of qualifications, represented by a series of
dummy variable s in the wage equation. This app roach is perhaps most asso ciated with the UK, which has a l arge
number of qualif ications available, par ticularly on the vocationa l side, and a non- linear sys tem where individuals
do not progress at a co nstant rate each year, again par ticularly on the vocation al side. In such a system, it makes
less sense to der ive a single estimate of the wage g ain associated with one add itional year of education .
The most frequ ently used data set in researc h on wage differentials associat ed with UK qualifications is th e
Labour Force Su rvey (LFS), due to its detailed inf ormation on all qualificatio ns held by individuals, wide- r anging
labour market information, and large sample sizes allowing disaggregation by individual qualifications. Examples
of studies to have used such data for detailed analysis of vocational qualifications are Dearden et al. (2002),
Dearden et al. (2 004), Dickerson and Vigno les (2007), Jenkins et al. (20 07) and McIntosh (2006), with McInt osh
(2010) providing an overview of this body of work. These papers have consistently found similar findings. For
vocational qua lifications at Level 3, wage di fferentials are obser ved between individua ls who do and do not hold
the qualific ations of around 10% on average, with so me variation around this figu re by type of qualification (for
example somewhat higher for BTEC qualifications and somewhat lower for NVQ qualifications).3 Such figures a re,
however, a little lower th an the typical diff erentials earned by acad emic qualifications at t he same level.
At Level 2, the wage differentials associated with vocational qualifications are much smaller than those at
Level 3. For most qualifications, they are statistically insignificantly different from zero, and in some cases, for
example NVQs, the wage differential between those with and without the qualification has been observed as
negative and statistically significant. Dearden et al. (2004) further investigate the latter result and adjust the
control group ag ainst whom the differenti als are measured, from all thos e without the NVQ- 2 qualificat ion, to a
carefully sel ected control group, namel y individuals with either no q ualifications at all, or at be st very low (Level
1) qualificati ons. This group are chosen to be tter reflect “the sor t of people who would choos e to do an NVQ- 2.”
Even in this case, no s tatistically signif icant positive wage differ entials are observed for m ales, while for females,
a significant , though small, 3% different ial is observed, when NVQ- 2 hold ers were compared to individua ls with
no qualifications at all. The use of a particular and appropriate comparison group when considering vocational
qualificati ons is a methodology tha t will also be followed in this pap er.
More recent research has begun using alternative data sources to investigate the same issues, in particular
using administ rative data rather t han data based on samp le surveys. Administ rative data sets have t he advantages
of large sample size s as well as detailed informati on about type of qualific ations attained. Disa dvantages include
2For a review, see fo r example Card (1999) o r Harmon and Oos terbeek (20 00).
3BTEC (Busines s and Technology Ed ucation Coun cil) qualific ations are in mos t cases taken by f ull- t ime student s in colleges of Fur ther Educatio n,
most often in t he areas of busin ess and technol ogy, as suggeste d by their name. A f ull Level 3 qualif ication would t ypically inv olve two years of
study. NVQs (Nat ional Vocation al Qualificat ions) are typic ally work- based qualificati ons, in which the l earner has to de monstrate com petence in the
particul ar field, acqu ired through on - the- job t raining, day- release study at a c ollege, and/or simp ly learning th rough experi ence. They are ava ilable
in a wide range of a reas, most fre quently in ser vice areas, th ough also in manu al areas such as en gineering an d constructi on.
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