Measuring skills mismatch: sheepskins or banana skins?

Mark KeeseEmployment, 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?

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

What should we be measuring?

There are many ways to measure skill mismatch: Use of Beveridge curves (vacancies vs job seekers)

o Using admin datao 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

How should we measure skill mismatch?

Each measure of skill mismatch has advantages and disadvantagesType of measure Advantages Disadvantages Beveridge curves Available in many countries.

Relatively “cheap” to produce if based on admin data.

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 of recruitment difficulties

Provides a direct measure of unmet skill demands.

Does not provide an indicator of mismatch for incumbent workers (if no other questions). 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 over- and under-education

Provides a useful measure to judge performance of national education and training systems. Can be obtained relatively easily for many countries from existing national surveys.

Benchmark for determining “required” education or method for determining mismatch is arbitrary. Measures qualifications rather than skills. May need “specialised” survey to capture field of study, wages and to study persistence.

Matching of measured (as tested) and required skills

Provides objective measure of skills possessed by individuals.

Limited number of skills that can be tested nationally. Determination of skill requirements is not straightforward.

Self-assessment Can cover a wide range of skills and be linked to wages, work history, etc.

Subjective measure influenced by age, gender, level of education, cultural background, etc.

1. 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 over-education 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?

2. 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. 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?

4. 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

What remains to be done?

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

Conclusions