Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Measuring Over-education
Data
Determinants
Wages
Arnaud Chevalier
Conclusions
Economica
2003
Arnaud Chevalier
Measuring Over-education
Economica
Introduction
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
Past fifty years, a cosiderable increase in participation in
higher education in UK
In particular, in 1985 a cohort attending tertiary education
has soared from 15% to 33%
Evidence of an excess supply; 40% of UK graduates have
too much education for their job
Evidence of 62% of male graduates, over-educated in their
first job remained in a sub-graduate position six years after
graduation
Aim: measure over-education, analyse how it affects
wages, propose policy recommendations
Economica
Definitions of Over-education
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Some definitions of over-education used in some empirical work
⇒ jobs are homogeneous in their skill requirements
a job analyst definition of the skill/educational requirement
for each occupation (as available e.g. Dictionary of Titles)
a measure of a worker’s self-assessment of educational
requirements
a distribution of education calculated for each occupation,
employees generally one standart deviation more than the
mean ⇒ over-educated
Arnaud Chevalier
Measuring Over-education
Economica
Definitions of Over-education
Measuring
Overeducation
Arnaud
Chevalier
Alternative Definition: heterogeneity of graduates
two types of graduates, clever (g) and under-achiever (u)
three types of job differing by their skill requirments:
1
Introduction
2
Definitions
Data
Determinants
Wages
3
graduate (G),
non-graduate jobs with intermediate skill level (upgraded
job, U),
non-graduate job with low skill level (L)
possible outcomes:
Conclusions
Arnaud Chevalier
Measuring Over-education
Economica
Definitions of Over-education
Measuring
Overeducation
Arnaud
Chevalier
How the dichotomy of the over-educated population was made:
Introduction
Definitions
Data
Determinants
Wages
Conclusions
A measure of over-education:
using the standard occupation code (2-digit), occupations
that require degrees (graduate jobs) are:
1
2
3
Arnaud Chevalier
Measuring Over-education
managers and administrators
professional occupations
associate professional and technical occupations
Economica
Definitions of Over-education
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
A measure of job satisfaction:
”How dis/satisfied are you with the match b/w your work
and your qualifications?”
⇒ classifies the graduates in a non-graduate job as
genuinely or apparently over-educated
six possible answers ranging from very dissatisfied to very
satisfied
very dissatisfied and disatisfied answers are grouped to
generate a dichotomous variable
apparently over-educated: over-educated workers in
upgraded jobs, satisfied with their match
genuinely over-educated: clever graduates in upgraded
jobs and under-achievers in low-skill jobs
Economica
Data
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Collected by postal survey in winter of 1996:
a sample of two cohorts of UK graduates from 1985 and
1990
graduates from 30 higher education institutions
⇒ sample of 15.000 individuals
only first-degree graduates
younger than 25 on graduation
full-time employees in 1996
living in UK
without health problems
⇒ sample of 4844 individuals
Arnaud Chevalier
Measuring Over-education
Economica
Data
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
Questionnaire covers wide range of topics: schooling,
academic information, family background, employment
history (1, 6 and 11 years after graduation ⇒ longitudinal
component)
dis/satisfaction with the match b/w education and
employment ⇒ allows for introduction of heterogeneity in
graduates and jobs(apparently and genuinely
over-educated)
”Was the degree gained in 1985/1990 a requirement in
the job specification for your main employment?” ⇒
includes self-assessment measure
Economica
Data
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
Economica
Data
Measuring
Overeducation
Arnaud
Chevalier
Distribution of answers to question:
”On reflection and in general, in what ways has your degree
contributed to your getting an interesting job?”
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
Economica
Data
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
Economica
Data
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Some conclusions:
Within the over-educated population, apparently
over-educated have better academic credentials than
genuinely over-educated
⇒ suggests that latter group is composed mostly of (Lu)
rather than (Uu)
the skill differential observed b/w groups confirms that
over-education originates from a lack of skills
Arnaud Chevalier
Measuring Over-education
Economica
Determinants of Over-education
Measuring
Overeducation
Arnaud
Chevalier
Hypothesis: over-education stems from heterogeneity in
the skills of graduates
Latent Model:
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
OE ∗ = βX + η
X: a vector of educational characteristics
η: normally distributed term of unobservable components
of over-education
This latent model is unobserved, so we have the ordinal
variable:
Economica
Determinants of Over-education
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
Economica
Determinants of Over-education
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
Economica
Determinants of Over-education
Measuring
Overeducation
1
Introduction
Definitions
Data
Model 1:
selection between a matched job and a job for which a
graduate is over-educated is based on educational skills
differences between apparent and genuine over-education
are not significant
Arnaud
Chevalier
2
Determinants
Model 2: marginal effects of over-education including 12
dummies for subject of graduation
inclusion of dummies has no effect on previous results
subjects in high demand (medical science, mathematics,
education, engineering): safeguards against over-education
students from biology, agriculture, languages and
humanities are more at risk than economists of being
over-educated
Wages
Conclusions
3
Arnaud Chevalier
Measuring Over-education
Model 3: subsequent qualifications ⇒ more qualification
reduces the likelihood of over-education
Economica
Determinants of Over-education
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
One step further: including unobserved skills
identification relies on individuals that change category
from one period to the next
estimation of earning in the first job
deviation between the expected and observed earning ⇒
proxy for unobservable skills affecting productivity
Determinants
ln(w ) = βX 1 X1 + βS1 S1 + 1
Wages
OE ∗ = βX + b
1 + η
Conclusions
Result:
50% of graduates, over-educated in their first job, made
the transition to a graduate job
the effect of is small but significant; graduates with a
higher score are less likely to be genuinely over-educated
matched graduates and apparently over-educated
graduates have similar unobserved skills
Arnaud Chevalier
Measuring Over-education
Economica
Determinants of Over-education
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Some conclusions:
The selection into the different types of job appears to be
based on both educational achievements and unobservable
skills
Graduates with better education credentials obtain
matched jobs
For the less talented graduates, the selection between
upgraded and non-graduate jobs is based on their
unobservable skills
⇒ graduate population is not homogeneous in skills
Arnaud Chevalier
Measuring Over-education
Economica
Over-education and Wages
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
Economica
Over-education and Wages
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
Economica
Conclusions
Measuring
Overeducation
Arnaud
Chevalier
Introduction
Definitions
Data
Determinants
Wages
Conclusions
Arnaud Chevalier
Measuring Over-education
Over-educated can be divided in three groups: matched
graduated, apparently and genuinely over-educated
Over-educated (standing for the two last groups) have less
academic credential than matched graduates
Apparently over-eduacated have similar unobserved skilled
as matched graduates
Genuinely over-graduated have a much lower skill
endowment
Over-education is associated with a pay penalty of
5%-10% for apparently over-educated and 22%-26% for
genuinely over-educated
Economica