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Workers skills and_how_they_are_used_at_work Workers skills and_how_they_are_used_at_work Presentation Transcript

  • Workers’ skills and how they are used at work GLENDA QUINTINI Directorate for Employment, Labour and Social Affairs OECD 1
  • Paper motivation: • Proficiency matters for labour force participation and wages • Survey of Adult Skills (PIAAC) provides an opportunity to test how skills – not education – affect labour market outcomes; • PIAAC also has rich Job Requirement Module which allows distilling information on skills use at work; • Skills use at work influences labour productivity and reflects the distribution of workers across occupations • Combining information on skills proficiency and use helps assess incidence of skills mismatch and the extent to which it leads a “waste” of human capital; • PIAAC provides internationally comparable data to explore these issues in 24 countries
  • Paper content: • Explores how proficiency affects labour market outcomes: employment, labour force participation, hourly wages; • Assesses the use of information processing and other generic skills in the workplace and how it varies by socio-demographic and job characteristics; • Compares measures of competence – education and skills proficiency – with requirements at work to develop measures of qualification and skills mismatch; • Identifies consequences of mismatch on wages and skills use. Paper currently covers 21 countries – plans to add France and Russia to the final version
  • Proficiency and labour market outcomes • Proficiency (in literacy but also numeracy and problem solving) is positively and independently associated with: • • • The probability of participating in the labour force (employed + unemployed); The probability of being employed;* Higher hourly wages • YET, differences between mean literacy (or numeracy and problem solving) of employed, unemployed and inactive individuals are small pointing to pool of unexploited human capital;
  • Employment rate by proficiency level 100 90 80 70 60 50 40 Literacy level 1 and below Literacy level 3 Literacy level 2 Literacy levels 4 and 5
  • Unemployment to population ratios by proficiency level 20 15 10 5 0 Literacy level 1 and below2 Literacy level 3 Literacy level 2 Literacy levels 4 and 5
  • The effect of education and literacy on labour market participation 2 1.8 1.6 1.4 1.2 1 0.8 Odds ratio Statistically significant differences are marked in a darker tone Effect of 3 additional years of education Effect of 46 more points of literacy proficiency (close to 1 level)
  • Median hourly wages by proficiency level 25th, 50th and 75th percentiles of the wage distribution Literacy level 1 and below 25th percentile Literacy level 2 50th percentile Literacy level 3 75th percentile United States Ireland 0 Norway 0 Denmark 5 Canada 5 Germany 10 England/N. Ireland (UK) 10 Netherlands 15 Austria 15 Flanders (Belgiium) 20 Australia 20 Korea 25 Average 25 Finland 30 Spain 30 Sweden 35 Japan 35 Italy 40 Poland 40 Estonia 45 Czech Republic 45 Slovak Republic Hourly wages in USD Literacy levels 4 and 5
  • The effect of education and literacy on wages % 30 Effect of 3 additional years of education 25 Effect of 46 more points of literacy proficiency (close to 1 level) 20 15 10 5 0
  • Mean literacy score by labour force status 300% 290 280 270 260 250 240 230 220 210 200 Employed Unemployed Out of the labour force
  • Assessing skills use at work using PIAAC • Information on tasks carried out at work can be combined to obtain indices of skills use • The frequency of some tasks is used directly to measure skills use • One task for each skills use variable; • Varying from 1 (never use the skill) to 5 (skill used every day) • Composite indices – more than one underlying task – are created using sum-scales: • Cronbach’s Alpha is used to test that items are grouped appropriately. Resulting scale ranges from 1 to 5
  • Assessing skills use at work using PIAAC Indicator Group of tasks Writing Writing documents (letters, memos, e-mails, reports, forms) Numeracy Calculating prices, costs or budgets; use of fractions, decimals or percentages; use of calculators; preparing graphs or tables; algebra or formulas; use of advanced math or statistics (calculus, trigonometry, regressions) ICT skills [workers who have used a computer before only] Using e-mail, Internet, spreadsheets, word processors, programming languages; conducting transactions on line; participating in online discussions (conferences, chats) Problem solving Facing hard problems (at least 30 minutes of thinking to find a solution) Choosing or changing sequence of job tasks, the speed of work; choosing how to do the job Learning at work Other generic skills Reading documents (directions, instructions, letters, memos, e-mails, articles, books, manuals, diagrams, maps) Task discretion Information-processing skills Reading Learning new things from supervisors or co-workers; learning-by-doing; keeping up-to-date with new products or services Influencing skills Instructing, teaching or training people; making speeches or presentations; advising people; planning others’ activities; persuading or influencing others; negotiating. Co-operative skills Co-operating or collaborating with co-workers Self-organising skills Organising one’s time and activities Dexterity Using skill or accuracy with one’s hands or fingers Physical skills (gross) Working physically for a long period Indicators in blue are derived from a single item
  • What skills are used most in the workplace • On average, writing skills and ICT are used more frequently at work than other information-processing skills (but only computer users answer ICT questions)* • Self-organising skills and dexterity used about once a week on average, although variance of dexterity use is rather high* • Influencing skills are least frequently used, reflecting their link with occupational status • Similar results when looking at high-frequency use as opposed to average • Information-processing skills often used in bundles – 20-25% of workers use them with above median frequency
  • The use of information-processing skills at work (selected countries)* Index of use Australia United States Average Italy Japan 5 Every day 4 At least once a week 3 At least once a month 2 Less than once a month 1 Never Reading at work Writing at work Numeracy at work ICT at work Problem solving at work
  • The use of generic skills at work (selected countries)* Index of use Australia 5 Every day 4 At least once a week 3 At least once a month 2 Less than once a month 1 Never United States Average Italy Japan
  • The relevance of skills at work • Skills use at work influences labour productivity* • Skills use at work reflects primarily the distribution of workers across occupations (job requirements) but proficiency and qualifications matter too (workforce competences)* • All things being equal, skills use is: • • • • Lower for women than men Lower for workers on fixed-term contracts and temporary workers Lower for part-timers than full-timers (but questions formulation?) Interesting – youth use ICT less than older counterparts at work but more at home* • Firm size matters for skills use, with larger firms using the skills of their workforce more efficiency, all things equal • Many jobs in most countries still require only basic qualifications*
  • Labour productivity and the use of reading skills at work 4.6 (log) Labour productivity 4.4 4.2 Estimates adjusted for proficiency in literacy and numeracy Slope = 1.118 (0.407) R2 = 0.296 Ireland Adjusted prediction Slope = 1.643 (0.504) R2 = 0.371 4 Spain Italy Norway Netherlands Denmark Germany United States Austria Sweden Australia 3.8 Finland Japan 3.6 3.4 Slovak Republic 3.2 Poland Korea Czech Republic Canada England/N. Ireland (UK) Estonia 3 1.5 1.6 1.7 1.8 1.9 2 Use of reading skills at work 2.1 2.2 2.3
  • Supply and demand determinants of skills use* Controls Reading Writing Numeracy ICT Problem solving Influence Learning Task discretion Selforganising Cooperative Physical Dexterit y Job requirements (occupations – ref. managers) Professionals 0.00 -0.27 -0.43 -0.29 -0.16 -0.39 0.00 -0.35 -0.17 -0.46 0.10 0.17 Technicians and associate professionals -0.18 -0.10 -0.40 -0.31 -0.26 -0.65 -0.06 -0.38 -0.28 -0.27 0.21 0.30 Clerical support -0.37 -0.21 -0.42 -0.22 -0.48 -1.01 -0.26 -0.46 -0.47 -0.44 -0.20 0.32 Service and sales -0.60 -0.70 -0.92 -0.93 -0.70 -0.80 -0.19 -0.64 -0.70 -0.08 1.26 0.34 Skilled agricultural -0.85 -1.13 -1.31 -1.00 -0.83 -1.15 -0.42 -0.55 -0.62 -0.11 2.03 0.80 Craft and trades -0.71 -1.00 -1.33 -1.23 -0.58 -1.25 -0.28 -0.73 -0.77 -0.23 1.87 1.14 Plant and machine operators -0.91 -1.00 -1.54 -1.58 -1.04 -1.55 -0.59 -1.11 -1.16 -0.53 1.49 0.70 Elementary -1.18 -1.44 -1.57 -1.43 -1.17 -1.59 -0.74 -0.80 -1.06 -0.37 1.90 0.41 Supply-side factors (proficiency and qualifications – ref. no qualifications) Literacy score *100 0.19 0.24 0.40 0.35 0.25 0.15 0.15 0.21 0.35 -0.24 -0.47 -0.27 Uppersecondary 0.21 0.24 0.16 0.16 0.17 0.19 0.17 0.11 0.20 0.05 -0.07 0.07 Postsecondary non tertiary 0.37 0.39 0.26 0.25 0.26 0.25 0.21 0.12 0.24 0.02 -0.09 0.11 Tertiary 0.43 0.39 0.36 0.35 0.35 0.34 0.26 0.15 0.31 -0.04 -0.36 -0.13
  • Mean ICT use at work and at home, by age group* 16-24 1 1.2 2.4 1.4 1.6 55-65 1.8 2 2.2 2.4 2.4 England/N. Ireland (UK) Australia United States Netherlands Estonia Canada Italy United States Denmark Flanders (Belgium) Ireland Czech Republic Slovak Republic Korea Flanders (Belgium) Spain Czech Republic Australia Norway Slovak Republic Poland Netherlands Slovak Republic Finland England/N. Ireland (UK) Estonia Denmark Italy Canada Norway Flanders (Belgium) Germany Austria Germany Spain Estonia Poland Sweden Finland Sweden Ireland Poland Japan England/N. Ireland (UK) Czech Republic Italy Austria Spain 2.2 2 ICT use at work 25-54 Korea 1.8 Japan 1.6 Korea 2.2 2 1.8 United States Austria Australia Ireland 1.6 Germany Canada Netherlands 1.4 1.4 Denmark Sweden Norway Finland 1.2 1.2 Japan 1 1 1 1.2 1.4 1.6 1.8 ICT use at home 2 2.2 2.4 2.6
  • Workers in high-skilled and unskilled jobs Austria Italy Czech Republic Slovak Republic Japan Germany England/N. Ireland (UK) Australia Poland Average Ireland United States Netherlands Spain Sweden Estonia France Norway Denmark Korea Canada Finland Flanders (Belgium) Low-skilled jobs: jobs requiring primary education or less High-skilled jobs: jobs requiring tertiary education or more Based on the respondent’s view of what qualification is required to get his/her job today 30 20 10 0 10 20 30 40 50 60 %
  • The discrepancy between skills proficiency and use • The discrepancy between skills proficiency and use generates pervasive mismatches which affect wages • PIAAC provides options to derive several measures of qualification mismatch as well as skills mismatch • In this paper: • Qualification mismatch = difference between worker’s qualification and qualification that she thinks are needed to get her job (+ over-qual. ; - under-qual); • Skills mismatch = worker’s proficiency compared with proficiency of workers reporting that they are neither over-skilled nor underskilled for their job (>max over-skilled; <min under-skilled)
  • Percentage of workers who are over or under qualified over- or under-skilled in literacy Sweden Finland Canada France Netherlands Estonia Poland Denmark Flanders (Belgium) England/N. Ireland (UK) Norway United States Australia Cyprus Japan Average Korea Italy Slovak Republic Germany Ireland Czech Republic Spain Austria Under-qualification Over-qualification % 40 % 30 20 10 0 Under-skilling Over-skilling 0 5 10 15 20 %
  • Socio demographic determinants of mismatch Little overlap between qualification and skills mismatch* Literacy proficiency within qualification level explains some qualification mismatch*: • Over-qualified workers are less skilled than their well-matched counterparts other things being equal (education, gender, age, foreign-born status) • Under-qualified workers are more skilled than their well-matched counterparts, other things being equal Over-qualification: • Is higher for foreign-born workers; • Youth are more likely to be over-qualified than prime-age workers but this is often not statistically significant; • No evidence on gender or marital status; • Is less likely among workers in large-firms, among full-time workers and workers on permanent contracts No patterns for under-qualification and skills mismatch, except: • Likelihood of over-skilling declines with age; • Older workers are more likely to be under-qualified than prime-age workers with same education and proficiency*
  • Overlap between qualification and skills mismatch* Percentage 30 Over-qualified who are over-skilled 25 Over-qualified who are under-skilled Under-qualified who are under-skilled Under-qualified who are over-skilled 20 15 10 5 0
  • Literacy proficiency scores among over- and under-qualified * Finland Germany Netherlands Sweden Japan Denmark Austria Spain Slovak Republic United States Average Ireland Estonia England/N. Ireland (UK) Italy Norway Australia Poland Czech Republic Canada Korea Flanders (Belgium) Score difference Under-qualified minus well-matched Over-qualified minus wellmatched -15 -10 -5 0 5 10 15 20
  • Impact of qualification and skills mismatch Qualification and skills mismatch have impact on skills use: • Over-qualification and over-skilling associated with under-use of information processing skills* • BUT no under-use associated with over-skilling once other factors are controlled for (not in the paper; controls are socio-demographic, job characteristics, proficiency etc.) Over-qualified earn*: • Less than equally-qualified well-matched workers • More than well-matched workers in similar jobs (not shown, 4% on average) Under-qualified earn: • More than equally-qualified well-matched workers • Less than well-matched workers in similar jobs (not shown, 17% on average)) Skills mismatch has small impact on wages suggesting employers may adjust job content or skills other than information processing skills contribute to mismatch*
  • Use of numeracy at work, by mismatch status* Netherlands Czech Republic Germany Denmark Estonia Canada Finland Austria Slovak Republic Korea Ireland United States Australia Average England/N. Ireland (UK) Sweden Spain Japan Norway Cyprus1 Poland Italy Score difference Values are obtained by controlling for proficiency in numeracy and literacy over-skilled minus well-matched under-skilled minus well-matched overqualified minus well-matched underqualified minus well-matched -2 -1 0 1 2
  • Difference in wages between over-/under-qualified and well-matched employees* Statistically significant differences are marked in a darker tone Over-qualification Under-qualification United States Sweden Spain Slovak Republic Poland Norway Netherlands Korea Japan Italy Ireland Germany Flanders (Belgium) Finland Estonia England/N. Ireland (UK) Denmark Czech Republic Canada Austria Australia 20% 15% 10% 5% 0% -5% -10% -15% -20% -25%
  • Difference in wages between employees who are over-/under-skilled and well-matched in numeracy* Over-skilling (numeracy) Under-skilling (numeracy) 40% Statistically significant differences are marked in a darker tone 30% 20% 10% 0% -10% United States Sweden Spain Slovak Republic Poland Norway Netherlands Korea Japan Italy Ireland Germany Flanders (Belgium) Finland Estonia England/N. Ireland (UK) Denmark Czech Republic Canada Austria Australia -20%
  • Conclusions • Skills proficiency is positively and independently associated with labour market outcomes but the strength of the relationship varies across countries; • Educational qualifications and skills proficiency reflect different aspects of individuals’ human capital that are separately identified and valued in the labour market. • The use of skills in the workplace influences a number of labour-market phenomena, including labour productivity, the gender wage gap and the wages gap between temporary and permanent workers. • The distribution of workers across occupations is found to be important in shaping the distribution of skills use but workers’ qualifications and skill proficiency matter too.
  • Conclusions • Mismatches between skills proficiency and the use of skills in the workplace are pervasive, affecting just over one in seven workers. • • Young people are particularly affected by over-skilling; Over-skilling has a relatively small negative effect on wages, suggesting most employers succeed in identifying their employees’ real skills and adapt job content or that wages are negotiated based on skills other than those measured by PIAAC. • On average across countries, about 28% of workers report that they are over-qualified and 13% report that they are under-qualified for their jobs. • • Over-qualification is particularly common among young and foreign-born workers and those employed in small establishments, in part-time jobs or on fixed-term contracts; Over-qualification has a significant impact on wages, even after adjusting for proficiency
  • Find Out More About PIAAC at: www.oecd.org/site/piaac All national and international publications Email Glenda.Quintini@OECD.org The complete micro-level database Thank you