THE IMPERFECT MATCH ILO International Conference on Jobs and Skills Mismatch Geneva 11-12 May 2017 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
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L enquête d Évaluation des Compétences des Adultes 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 Respondents with very low literacy skills were directed to a test of basic reading components The survey also collects a range of generic skills such as collaborating with others and organising one s time, required of individuals in their work.
What is mismatch? 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 English Lit How about you?
Three questions 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
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?
Over 1/3 workers are mismatched by qualifications The worker has higher (lower) qualifications than those needed to get the job On average: 21% over-qualified 13% under-qualified Slovak Republic Poland Denmark Czech Republic Flanders (Belgium) Finland Spain Korea United States Netherlands Germany Average Norway Austria Italy Estonia Japan Sweden Canada Australia England/N. Ireland (UK) Ireland France Incidence of Qualifications Mismatch PIAAC countries, 2012 0.00 10.00 20.00 30.00 40.00 50.00 Source: Survey of Adult Skills (PIAAC) (2012) Overqualification Underqualification
Around 1/7 workers are mismatched by literacy levels The worker has a higher (lower) skill level than those of workers who are wellmatched On average: 10% over-skilled 4% under-skilled Netherlands Poland Finland Canada France Sweden Flanders (Belgium) Estonia Australia Denmark Korea United States Japan Norway Average England/N. Ireland (UK) Germany Slovak Republic Cyprus¹ ² Italy Czech Republic Austria Spain Ireland Incidence of Skills Mismatch Literacy, PIAAC countries, 2012 Over-skilled Under-skilled 0 5 10 15 20 25 Source: Survey of Adult Skills (PIAAC) (2012)
Around 4/10 workers are mismatched by field of study 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) Finland Germany Austria Norway Sweden Netherlands Denmark Estonia Canada Slovak Republic Czech Republic Average Flanders (Belgium) Poland Ireland Russian Federation France Spain United States Japan Australia Italy England/N. Ireland (UK) Korea Incidence of Field of Study Mismatch PIAAC countries, 2012 0 20 40 60 Source: Survey of Adult Skills (PIAAC) (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, overqualification, 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 20 % 15 10 5 0-5 -10-15 -20-25 -30 Over-qualified (Ref: same qualifications, well-matched job) Field-of-study mismatched (Ref: same field of staudy, well-matched job) Overskilled in literacy (Ref: same skills, 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 Field-of-study alone does not carry wage penalty in most countries Note: Path analysis with country fixed effects. Source: Survey of Adult Skills (PIAAC) (2012).
Literacy mismatch and productivity 40 35 30 25 Percentage of workers with skill mismatch (LHS) Gains to labour productivity from reducing skill mismatch (RHS) 12 10 8 20 6 15 10 5 4 2 0 0
Mismatch can affect wage inequality 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 onto that of numeracy use 4 2.6 3.2 2 0.3 0.6 1.1 1.4 1.5 0-2 -4-6 -4.6-4.2-3.9-2.6-2.5-2.1-1.3-1.1-0.8-0.7-0.4-0.3-0.1-6.3-8 -7.9-10 NLD JPN KOR DNK EST ITA CAN IRL DEU POL USA BELᵇ FIN ESP AUT SVK CZE AUS FRA GBR ᵇ SWE NOR
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 Percentage of GDP 1.4% 1.2% 1.0% 0.8% 0.6% 0.4% 0.2% 0.0% The cost of field-of-study Highest share of mismatch costs comes can amount to more than 1% of GDP from productivity costs (wages), most of which result from the overqualification associated to FoS mismatch (assumes a 50- week work year) Productivity Education Unemployment Sunk education costs assume that lost education amounts to ½ a year for ISCED 3 and 1 year for ISCED 5.
What we know about mismatch 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 overqualification 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 But Michael, the labour market is awaiting you! field and a bigger one outside the field
What do we know about the causes of mismatch?
Under-qualified minus well-matched Over-qualified minus well-matched Russian Federation³ Finland Germany Netherlands Sweden Literacy proficiency and qualification mismatch 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 0 5 10 15 20 Score point difference
Labour market dynamics predict overqualification Workers fired or dismissed in the context of business closures are more likely to be over-qualified at reemployment 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
What causes field-of-study mismatch? 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
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).
The role of skills use at work 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
Index of use Use of skills at work by proficiency level Reading at work Writing at work Numeracy at work Most frequent use = 5 4.5 Most frequent use = 5 4.5 4.0 3.5 3.0 2.5 2.0 1.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 Level 1 or below Level 2 Level 3 Levels 4 and 5 1.0 Level 1 or below Level 2 Level 3 Levels 4 and 5 Literacy Numeracy Less frequent use = 1 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 60 Firm size Occupation Industry High-Performance Work Practices (HPWP) Skills proficiency Country fixed effects 50 40 30 20 10 0 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
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 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 Résultats More frequent skills use at work is associated with the use of High Performance Work Practices 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 A. HPWP - All factors Share of jobs with high HPWPᵅ and mean HPWP score 45 Percentage of jobs with high HPWP (left) Mean HPWP index (right) 3.1 40 35 30 25 20 15 10 5 3.0 2.9 2.8 2.7 2.6 2.5 2.4 0 2.3 a) Share of workers in jobs where the summary HPWP is above the top 25th percentile of the pooled distribution. Source: Employment Outlook (2016)
Policy-relevant messages 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
What the OECD is doing: 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
Thank you for your attention 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