Transcript Mark Keese - Measuring skill mismatch

Measuring skills mismatch:
sheepskins or banana skins?
Mark Keese
Employment, Labour and Social Affairs, OECD
Cedefop Workshop on “Skill Mismatch: Identifying Priorities
for Future Research”, 30 May 2008, Thessaloniki
Outline of presentation
• What should we be
measuring?
• How should we be
measuring this?
• What remains to be done?
What should we be measuring?

Concept of skill mismatch is straight forward: a
gap between the skills required in jobs and the
skills possessed by workers or the non-employed

Skill shortages or mismatch is not the same as
labour shortages which may arise because of:

Limited geographical mobility

Ageing populations

Economic boom

But which type of skills should we be measuring?

Depends on the policy issues at stake

For use by public employment services

For career guidance

For assessing performance of education and
training systems
How should we measure skill mismatch?

There are many ways to measure skill mismatch:

Use of Beveridge curves (vacancies vs job seekers)
o
Using admin data
o
Or survey data

Employer reports of recruitment difficulties

Matching of actual educational qualifications of workers
with “average” or “required” qualifications in their jobs

Matching of measured generic skills (e.g. literacy,
numeracy) with use of these skills in jobs

Self-assessment by workers of own skill adequacy
Each measure of skill mismatch has advantages and disadvantages
Type of measure
Beveridge curves
Advantages
Available in many countries.
Relatively “cheap” to produce if
based on admin data.
Disadvantages
Does not provide an indicator of mismatch for
incumbent workers.
Requires long time series to disentangle structural
and cyclical trends.
Coverage of admin data on vacancies is low and
varies by occupation.
Employer reports Provides a direct measure of unmet
Does not provide an indicator of mismatch for
of recruitment
skill demands.
incumbent workers (if no other questions).
difficulties
Limited information on skills as opposed to
occupations or job tasks.
May be difficult to distinguish skill shortage from
other reasons for recruitment difficulties.
Measures of
Provides a useful measure to judge
Benchmark for determining “required” education
over- and under- performance of national education
or method for determining mismatch is arbitrary.
education
and training systems.
Measures qualifications rather than skills.
Can be obtained relatively easily for
May need “specialised” survey to capture field of
many countries from existing national study, wages and to study persistence.
surveys.
Matching of
Provides objective measure of skills
Limited number of skills that can be tested
measured (as
possessed by individuals.
nationally.
tested) and
Determination of skill requirements is not
required skills
straightforward.
Self-assessment Can cover a wide range of skills and
Subjective measure influenced by age, gender,
be linked to wages, work history, etc. level of education, cultural background, etc.
What remains to be done?
1.
2.
Need to do further work on improving and
testing the theory behind skill mismatch

Policy implications will differ according to the theoretical
basis for why skill mismatch arises and for why it may
persist

Has a consensus been reached on whether overeducation reflects “sheepskin effects” or other
unmeasured skills, etc.?

How robust are our measures of skill mismatch over
time, across countries and according to changes in
method and? Or do we risk stepping on a banana skin by
drawing firm policy conclusions on the basis of any one
study?
Need to develop and improve comparisons of
skill mismatch within countries

Better longitudinal data is required to examine
persistence in mismatch at the individual level

Time series at the national level are required to examine
trends over time and the impact of the business cycle
What remains to be done?
3.
4.
Develop and improve international comparability
of skill mismatch measures to isolate the impact
of institutional and policy settings:

Which features of national education and training
systems are associated with better or worse outcomes in
terms of skill mismatch?

Do strict employment protection rules, minimum wages
or family-unfriendly employment policies generate labour
rigidities, reduce labour mobility and worsen skill
mismatch?
Need to improve our measures of skill

More direct measures of skill are required

Surveys of adult skills such as the OECD’s PIAAC survey
will be of considerable help here

The PIAAC survey will not only test literacy and
numeracy skills but will also provide measures of other
generic skills being used in jobs
Conclusions
 Measuring and understanding skill mismatch is a highly
policy-relevant area for research
 But first we need to answer the fundamental questions of
what do we want to measure, for whom and why
 We also need to carefully distinguish structural trends
from “fads”, e.g. see the swings in the US policy debate
about over-education, the bursting of the “dotcom” bubble
along with expectations of severe shortages in IT
specialists