SKILLS USE AND MISMATCH AT WORK : WHAT DOES PIAAC TELL US? Glenda - - PowerPoint PPT Presentation

SKILLS USE AND MISMATCH AT WORK : WHAT DOES PIAAC TELL US?

Glenda Quintini

Senior Economist, Skills and Employability division Directorate for Employment, Labour and Social Affairs THE IMPERFECT MATCH ILO International Conference on Jobs and Skills Mismatch Geneva 11-12 May 2017

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Housekeeping

L’enquête d’Évaluation des Compétences des Adultes

Respondents with very low literacy skills were directed to a test of basic “reading components 33 countries – 215 thousand adults…

Representing 815 millions 16-65 year-olds 24 countries in 2012 + 9 countries in 2015

Internationally agreed assessment in literacy, numeracy and problem solving in technology-rich environments… The survey also collects a range of generic skills such as collaborating with others and organising

• ne’s time, required of individuals in their work.

What is mismatch?

“English Lit – How about you?”

• Mismatch points to an imbalance between the

skills a worker has or the training he/she has received and the skills or training required to perform his/her job – Qualifications mismatch: over/under – Skills mismatch: over/under – Field-of-study mismatch

–How pervasive is mismatch? –Why does it matter? –What causes it?

• Proficiency levels
• A field’s saturation and skills transferability
• The use of skills in the workplace

Three questions

Drawing from several studies

• Quintini, G. (2011), "Right for the Job: Over-Qualified or Under-

Skilled?", OECD Social, Employment and Migration Working Papers,

• No. 120, OECD Publishing, Paris.
• OECD (2016), “Skills Matter: Further results from the Survey of

Adult Skills”, OECD Publishing, Paris.

• Montt, G. (2015), "The causes and consequences of field-of-study

mismatch: An analysis using PIAAC", OECD Social, Employment and Migration Working Papers, No. 167, OECD Publishing, Paris.

• Adalet McGowan, M and D. Andrews (2015), “Labour market

mismatch and labour productivity: Evidence from PIAAC data”, OECD Economics Department Working Paper, No. 1209

• OECD (2016), OECD Employment Outlook, “Skills use at work: why

does it matter and what causes it?”, Chapter 2 , OECD Publishing, Paris

How pervasive is mismatch?

The worker has higher (lower) qualifications than those needed to get the job

• On average:

– 21% over-qualified – 13% under-qualified

Over 1/3 workers are mismatched by qualifications

Source: Survey of Adult Skills (PIAAC) (2012)

Incidence of Qualifications Mismatch

PIAAC countries, 2012

0.00 10.00 20.00 30.00 40.00 50.00 France Ireland England/N. Ireland (UK) Australia Canada Sweden Japan Estonia Italy Austria Norway Average Germany Netherlands United States Korea Spain Finland Flanders (Belgium) Czech Republic Denmark Poland Slovak Republic Overqualification Underqualification

The worker has a higher (lower) skill level than those of workers who are well- matched

• On average:

– 10% over-skilled – 4% under-skilled

Around 1/7 workers are mismatched by literacy levels

5 10 15 20 25 Ireland Spain Austria Czech Republic Italy Cyprus¹ ² Slovak Republic Germany England/N. Ireland (UK) Average Norway Japan United States Korea Denmark Australia Estonia Flanders (Belgium) Sweden France Canada Finland Poland Netherlands Over-skilled Under-skilled

Source: Survey of Adult Skills (PIAAC) (2012)

Incidence of Skills Mismatch

Literacy, PIAAC countries, 2012

The worker’s highest qualification is in a field that is not related to the job

• On average:

– 39% mismatch – (40% also mismatched by qualification)

Around 4/10 workers are mismatched by field of study

20 40 60 Korea England/N. Ireland (UK) Italy Australia Japan United States Spain France Russian Federation Ireland Poland Flanders (Belgium) Average Czech Republic Slovak Republic Canada Estonia Denmark Netherlands Sweden Norway Austria Germany Finland

Source: Survey of Adult Skills (PIAAC) (2012)

Incidence of Field of Study Mismatch

PIAAC countries, 2012

Why does mismatch matter?

Mismatch can have various adverse effects

For individuals, firms and the economy:

• Lower aggregate productivity
• Lower wages for mismatched workers (field of study, over-

qualification, over-skilling)

• Lower job satisfaction
• Sunk costs in skills system

Qualification, literacy and field-of-study mismatch affect wages

Percentage difference in wages between overqualified, overskilled or field-of-study mismatched workers and their well-matched counterparts

• 30
• 25
• 20
• 15
• 10
• 5

5 10 15 20

Over-qualified (Ref: same qualifications, well-matched job) Overskilled in literacy (Ref: same skills, well-matched job) Field-of-study mismatched (Ref: same field of staudy, well-matched job)

%

Source: Skills Matter (OECD, 2016)

Does field-of-study mismatch imply a wage penalty?

The short answer: Yes, when it also involves overqualification

Note: Path analysis with country fixed effects. Source: Survey of Adult Skills (PIAAC) (2012).

Field-of-study alone does not carry wage penalty in most countries

Literacy mismatch and productivity

2 4 6 8 10 12

5 10 15 20 25 30 35 40 Percentage of workers with skill mismatch (LHS) Gains to labour productivity from reducing skill mismatch (RHS)

Ensuring a balance between the supply and demand for skills can help reduce wage inequality

• Wage inequality is lower in countries that are better at

matching skill demand and supply

The impact of skills use on wage inequality Percentage change in wage inequality (Gini) after imposing the distribution of numeracy proficiency

• nto that of numeracy use

Mismatch can affect wage inequality

• 7.9
• 6.3
• 4.6
• 4.2
• 3.9
• 2.6
• 2.5
• 2.1
• 1.3
• 1.1
• 0.8
• 0.7
• 0.4
• 0.3
• 0.1

0.3 0.6 1.1 1.4 1.5 2.6 3.2

• 10
• 8
• 6
• 4
• 2

2 4 NLD JPN KOR DNK EST ITA CAN IRL DEU POL USA BELᵇ FIN ESP AUT SVK CZE AUS FRA GBR ᵇ SWE NOR

0.0% 0.2% 0.4% 0.6% 0.8% 1.0% 1.2% 1.4%

Estonia England/N. Ireland (UK) Korea Ireland Poland Canada United States Spain Germany Country Average Japan Czech Republic Italy Slovak Republic Netherlands Denmark Austria Flanders (Belgium) France Australia Norway Sweden Finland Productivity Education Unemployment

The cost of field-of-study mismatch can amount to more than 1% of GDP

Percentage of GDP

Highest share of costs comes from productivity costs (wages), most of which result from the

• verqualification associated to

FoS mismatch (assumes a 50- week work year) Sunk education costs assume that “lost” education amounts to ½ a year for ISCED 3 and 1 year for ISCED 5.

“But Michael, the labour market is awaiting you!”

• Skills mismatch appears to be less common than

qualification or field of study mismatch

– Related to lower productivity levels – But this could be a methodological artifact

• Field of study mismatch is quite common, though

not really problematic unless it leads to

• verqualification

– Workers who move horizontally without having to downgrade do not suffer any penalty and may not be less productive in the other field

• Over-qualification brings a sizeable penalty in the

field and a bigger one outside the field

What we know about mismatch

What do we know about the causes of mismatch?

Literacy proficiency and qualification mismatch

Russian Federation³ Finland Germany Netherlands Sweden Japan Denmark Austria Spain Slovak Republic United States Cyprus¹ ² Ireland Estonia Average England/N. Ireland (UK) Italy Norway Australia Poland Czech Republic Canada Korea France Flanders (Belgium)

• 15
• 10
• 5

5 10 15 20

Under-qualified minus well-matched Over-qualified minus well-matched

Score point difference

Labour market dynamics predict over- qualification

• Workers fired or dismissed in the context of business

closures are more likely to be over-qualified at re- employment than workers who quit – Effect stronger if job separation occurs at times of rising unemployment

• The longer the time spent out of work between two

jobs, the higher the risk of over-qualification, suggesting skills obsolescence

• Saturation: there are too many graduates from

this field and fewer jobs in the corresponding sector – Roughly: Number of graduates from the field

Number of workers in that sector

• Skill transferability: skills from the field are

transferrable / valued in other sectors – Roughly: Number of skills well-matched in that sector

Number of FoS mismatched in that sector

What causes field-of-study mismatch?

Does saturation and transferability predict field of study mismatch?

The short answer: YES Graduates from more saturated fields are more likely to be mismatched (and overqualified) Graduates from fields with more transferability are more likely to be mismatched and well qualified

Note: Path analysis with country fixed effects. Source: Survey of Adult Skills (PIAAC) (2012).

• Demand-side factors often less well understood

than supply-side ones

• Findings on skills use are in line with findings on

mismatch:

• More frequent skills use associated with higher wages
• More frequent skills use associated with higher job

satisfaction

• Higher skills use associated with higher labour

productivity at the sector/country level

The role of skills use at work

1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Level 1 or below Level 2 Level 3 Levels 4 and 5 Literacy Index of use Reading at work Writing at work

Use of skills at work by proficiency level

1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Level 1 or below Level 2 Level 3 Levels 4 and 5 Numeracy Numeracy at work

Most frequent use = 5 Less frequent use = 1 Most frequent use = 5 Less frequent use = 1

OECD Average

Factors explaining the variance of skills use at work

The contribution of skills proficiency and other factors to the variance of skills use at work

10 20 30 40 50 60 Use of reading at work Use of writing at work Use of numeracy at work Use of ICT skills at work Problem solving skills at work Firm size Occupation Industry High-Performance Work Practices (HPWP) Skills proficiency Country fixed effects

Skills use is associated with the use of High Performance Work Practices at work Definition

Aspects of work organisation – team work, autonomy, task discretion, mentoring, job rotation, applying new learning; Management practices – employee participation, incentive pay, training practices and flexibility in working hour

Résultats

• More frequent skills use at

work is associated with the use

• f High Performance Work

Practices Variables used in PIAAC: Flexibility in the sequence, order, speed of tasks Organising own time and activities Co-operating with others Instructing, teaching or training others Sharing information with others Management practices: working time flexibility, training participation, bonuses

Reverse causality : many HPWP enable and/or motivate workers to use their skills better, but employers may apply HPWP particularly to jobs requiring intense use of information processing skills.

The use of HPWP varies significantly across countries

2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 5 10 15 20 25 30 35 40 45

• A. HPWP - All factors

Share of jobs with high HPWPᵅ and mean HPWP score

Percentage of jobs with high HPWP (left) Mean HPWP index (right) a) Share of workers in jobs where the summary HPWP is above the top 25th percentile of the pooled distribution. Source: Employment Outlook (2016)

• Promote linkage between education provision and

labour market needs

– Skills assessment and anticipation systems linked to the definition of vacancies

• Promote skill transferability so that FoS mismatch

does not bring about over-qualification

– Competency-based occupational frameworks – Flexible re-skilling programmes – General education

• Encourage firms to adopt High Performance Work

Practices that:

– Increase internal flexibility to adapt job tasks to the skills of new hires; – Promote a better allocation of workers to tasks; and – Provide incentives for workers to deploy their skills at work more fully

Policy-relevant messages

• Getting Skills Right: Country reviews on skills anticipation

systems and policies to address mismatch and shortage

• Getting Skills Right: Indicator of skills imbalances

– Follow wage, employment and talent pressures – Link occupations to specific skills

• Survey of Adult Skills: Development work for Second Cycle

– Improve measures of skills mismatch – Improve measures of skills use – Better understand work organisation through expanded module and employer survey

What the OECD is doing:

Contact: Glenda.Quintini@oecd.org

Pour plus de renseignments: Suivez-nous sur Twitter: @OECD_Social

Website: www.oecd.org/els BLOG: https://oecdskillsandwork.wordpress.com

Thank you for your attention