Translating better skills into better economic and social outcomes (Lisbon Council15 September 2011)

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Translating better skills into better economic and social

outcomes

Lisbon Council15 September 2011

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rAgenda for this morning

Skills matter for individuals... because skills have an increasing impact on labour market

outcomes and social participation

…and for economies because failure to ensure a good skills match has both

short- term consequences (skills shortages) and longer-term effects on economic growth and equality of opportunities

…but better skills do not automatically translate into higher incomes and higher productivity

Success with converting skills into jobs and growth depends on whether

– we know what those skills are that drive economic outcomes– the right mix of skills is being taught and learned in effective,

equitable and efficient ways– economies and labour-markets fully utilize their skill potential– Governments build strong coalitions with the social partners to find

sustainable approaches to who should pay for what, when and where .

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Many systems have done well in getting more people to higher qualifications

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rAustraliaAustriaBelgiumCanadaChileCzech RepublicDenmarkEstoniaFinlandFranceGermanyGreeceHungaryIcelandIrelandIsraelItalyJapanKoreaLuxembourgMexicoNetherlandNew ZealandNorwayPolandPortugalSlovak RepublicSloveniaSpainSwedenSwitzerlandTurkeyUnited KingdomUnited States

A world of change – higher education

0 10 20 30 40 50 60 700.0

5,000.0

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Tertiary-type A graduation rate

Graduate supply

Cost

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United States

Finland

Japan

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Finland

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The composition of the global talent pool has changed…

Countries’ share in the population with tertiary education, for 25-34 and 55-64 year-old age groups, percentage (2009)

55-64-year-old population 25-34-year-old population

About 39 million people who attained tertiary level

About 81 million people who attained tertiary level

albiser_e

EAG 2011: chart A4.2OK

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United States, 35.8

Japan, 12.4

China, 6.9Germany, 6.3

United Kingdom, 5.3

Canada, 4.2

France, 3.5

Brazil, 3.5

Spain, 2.1Italy, 1.9

Mexico, 1.8

Australia, 1.7

Korea, 1.6other, 12.9

55-64-year-old population

United States, 20.5

Japan, 10.9

China, 18.3

Germany, 3.1United Kingdom, 4.4

Canada, 3.1France, 4.1

Brazil, 4.5

Spain, 3.5

Italy, 2.0

Mexico, 3.9

Australia, 1.6

Korea, 5.7

other, 14.5

25-34-year-old population

The composition of the global talent pool has changed…

Countries’ share in the population with tertiary education, for 25-34 and 55-64 year-old age groups, percentage (2009)

albiser_e

EAG 2011: chart A4.2OK

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r…and will continue to change

Share of new entrants into tertiary education in 2009 (all OECD and G20 countries)

China, 36.6%

United States, 12.9%

Russian Federa-tion, 10.0%

Indonesia, 4.9%Japan, 4.2%Turkey, 3.7%

United Kingdom, 3.3%

Mexico, 3.1%Korea, 3.1%

Argentina, 2.7%Germany, 2.5%

Poland, 2.1%

Spain, 1.6%Italy, 1.4%

Australia, 1.3%Chile, 1.3%

Netherlands, 0.5%

Other countries, 4.8%

OtherPortugal 0.5%Czech Republic 0.4%Israel 0.4%Sweden 0.4%Belgium 0.4%Hungary 0.4%Austria 0.4%New Zealand 0.3%Switzerland 0.3%Slovak Republic 0.3%Denmark 0.2%Norway 0.2%Ireland 0.2%Finland 0.2%Slovenia 0.1%Estonia 0.1%Iceland 0.0%

albiser_e

EAG 2011: Chart A1.4OK

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...but qualifications are not the same as skills...

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An

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in each country interview 5000 adults aged 16-65 in their homes and testing their skills

collect information on the antecedents, outcomes and contexts of skill development and use

… in order to… provide a comprehensive assessment

of the human capital stock show to what extent skills held by individuals are

actually used at work and identify the role skills play in improving labour market prospects

improve understanding of the labour market and social returns to education and training

help governments better understand how education and training systems can nurture these skills

help countries prioritise investment of scarce resources in education

contribute to building strategic partnerships for policy implementation .

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Measures of adult competencies

Test-based measures in areas where methodologies exist

Indirect measures in other areas that support PIAAC‘s policy objectives

Measures of key social and economic outcomes Labour-market experience

, status and transitions, earnings, adult learning, social outcomes

Measures of the utilisation of competencies at the workplace

Through a job-requirement survey

A background questionnaire

To contextualise and analyse determinants of competencies, their development, and their use

Surveyed: individuals

Assessment: direct and

indirect


Assessment: indirect


Assessment: indirect, e.g. JRA


Assessment: indirect

Key elements of PIAAC

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No

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d s

ch

oo

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Up

pe

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co

nd

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Un

ive

rsit

y

No

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d s

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Up

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Un

ive

rsit

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No

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Up

pe

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Un

ive

rsit

y

Country A Country B Country C

150

200

250

300

350

Skill score

Source: PIAAC Field trial

Measuring the value of qualificationsInterquartile range in skill distribution by educational qualification

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rPIAAC participating countries Round

1Round 2

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Skills matter for individuals……because skills have an increasing impact on labour

market outcomes and social participation

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0 1 2 3 41.0

1.5

2.0

2.5

3.0

3.5

In lowest two quin-tiles of personal income

Unemployed

Received social assistance in last year

Did not receive in-vestment income in last year

Number of skills domains with low performance

Increased likelihood of failure (16-65 year olds)

Low skills and economic outcomes

Odds are adjusted for age, gender and immigration status.

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rMarginal probability of being unemployed by skill decile

Adjusted for age, gender, foreign language status, and country.

1 2 3 4 5 6 7 8 9 10

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

0.12

f(x) = − 0.00772664172839507 x + 0.11537928664903

f(x) = − 0.0047602224691358 x + 0.0751142450088183

Skill decile

Prob

abili

ty o

f bei

ng u

nem

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ed

Level 1 Level 2 Level 3 Level 4/5

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Low skills and social outcomes

Odds are adjusted for age, gender, pand immigration status.

Level 5 Level 4 Level 3 Level 2 Level 11.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6Has fair to poor health

Does not volunteer for charity or non-profit organizations

Poor understanding of po-litical issues facing coun-try

Poor level of general trust

Higher propensity of be-lieving people try to take of advantage of others

Lower propensity to reciprocate

Poor political efficacyPIAAC skill level

Odds ratios

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Low skills and ICT outcomes

Source: PIAAC Field trialOdds are adjusted for age, gender, education, parents' education and immigration status.

Level 5 Level 4 Level 3 Level 2 Level 10.0

0.5

1.0

1.5

2.0

2.5

3.0

In bottom half of computer engagement at home in-dex

Do not use internet at work

Proxy skill level

Odds ratios

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Producing an effective skill mix

Drivers of current and future demand of skills

Instruments to ensure responsiveness of education provision to labour demand

Optimising access to education and training throughout life

Impact of migration and international labour mobility on skill formation systems

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rDemographic challenges

Skills by age

15 25 35 45 55 65225

235

245

255

265

275

285

295

305

No adjustmentAdjusted for immigrant status and educationAdjusted for immigrant status, education and reading engagement

Age

Skill score

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rKeeping learning beyond school

Cross-sectional skill-age profiles for youths by education and work status

16 17 18 19 20 21 22 23 24 25220

230

240

250

260

270

280

290

300

310

320

Age

Mean skill score

Youth in education

Youth in education and work

Youth in work

Not in education, not

in work

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Optimising the use of skills

Which measures help optimise the utilisation of skills on the job?

How can workforce participation be boosted?

Which tools facilitate the recognition of skills?

How can transparency of skills systems be ensured?

What information is necessary to facilitate matching of skills?

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rHow the demand for skills has changed

Economy-wide measures of routine and non-routine task input (US)

1960 1970 1980 1990 200240

45

50

55

60

65

Routine manual

Nonroutine manual

Routine cognitive

Nonroutine analytic

Nonroutine inter-active

(Levy and Murnane)

Mean t

ask

inp

ut

as

perc

en

tile

s of

the 1

960

task

dis

trib

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The dilemma for education and training:The skills that are easiest to teach and test are also the ones that are easiest to digitise, automate and outsource

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rChanges in employment shares by

occupation1960-2009, selected OECD countries

Australia, Austria, Belgium, Canada, Chile, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Japan, Korea, Luxembourg, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom and United States.

Prof. and Tech.

Admin. and Manag.

Clerical Sales Service Farm Prod. and labour.

-30

-25

-20

-15

-10

-5

0

5

10

15

20

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Skill use by occupational groups


Problem solvingTeamwork

Oral communication

Influence others

Plan own time

Plan others time

Fine motor skills

Gross motor skillsRead prose type texts

Read document type texts

Write

Advanced numeracy

Basic numeracy

Internet use

Computer use

-1.00

0.00

1.00

Total Service (low-skill) Goods Information (low-skill) Information (high-skill)

Managers Knowledge (expert)

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HIGH-SKILL MATCH

MISMATCH-SKILL SURPLUS

LOW-SKILL MATCH

MISMATCH-SKILL DEFICIT 0%

10%

20%

30%

40%

50%

60%

Goods Service (low-skill) Information (low-skill)

Information (high-skill) Managers Knowledge (expert)

Skill mismatch by occupational groups


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Imp

act

of

inte

rnat

ion

al A

sse

ssm

en

ts

Making investment in skill development and utilisation more

efficient

Who should pay for what, when and how?Which is the right level of intervention

(regional and local dimension)?

How should financing and incentives (to employers and individuals)

be structured?

What are good models of policy evaluation to ensure efficiency/continuity of skills policies?

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Individuals are getting a good return…

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DenmarkSwedenTurkey

New ZealandNorway

SpainAustralia

NetherlandsBelgiumFinland

JapanFrance

GermanyAustria

OECD AverageCanada

United KingdomPoland

SloveniaHungary

Czech RepublicIreland

KoreaItaly

United StatesPortugal

-400,000 -200,000 0 200,000 400,000 600,000 800,000

55,946 62,481

64,177 74,457

92,320 95,320

100,520 112,928

115,464 135,515 143,018

144,133 147,769

173,522 175,067

175,670 207,653

215,125 225,663 230,098

240,449 253,947

300,868 311,966

323,808 373,851

Foregone earnings Income tax effect Social contribution effectTransfers effect Grosss earnings benefits Unemployment effectNet Present value

USD equivalentC hart A9.3

Components of the private net present value for a man with higher education (2007 or latest available

year)

Net present value in USD equ.

albiser_e

EAG 2011: chart A9.3OKEAG 2010: Data updated but for female instead of male (as in EAG 2010)

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…Taxpayers are getting a good return too

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TurkeyDenmark

SpainSweden

New ZealandNorwayFranceJapan

CanadaCzech Republic

ItalyAustralia

IrelandKorea

PortugalAustria

OECD AveragePoland

NetherlandsUnited Kingdom

FinlandSloveniaHungaryBelgium

GermanyUnited States

0 50,000 100,000 150,000 200,000 250,000

21,724

28,621

29,58237,542

46,482

43,41963,701

67,411

79,77481,307

82,93284,532

85,91789,034

89,46489,705

91,036

94,12595,030

95,322

100,177155,664

166,872167,241

168,649

193,584

Public benefits Public costs

Chart A9.5 In equivalent USD

Public cost and benefits for a man obtaining tertiary education (2007 or latest available year)

Net present value

albiser_e

EAG 2011: chart A9.5 (tertiary)OK

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The crisis hit the least educated hardest

Lack of relevant skills/experience brings higher unemployment risk for recent entrants

to the labour force

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When the crisis hitPercentage-point change between 2008-09 in unemployment rate for 15-29

year-olds

Norway

Switzerland

United Kingdom

Korea

Australia

Denmark

Slovenia

Japan

Belgium

France

Poland

Germany

Finland

Portugal

Greece

Slovak Republic

Turkey

Spain

- 10 20 30 40 C3.1Norway

Switzerland

United Kingdom

Korea

Australia

Denmark

Slovenia

Japan

Belgium

France

Poland

Germany

Finland

Portugal

Greece

Slovak Republic

Turkey

Spain

- 10 20 30 40

Tertiary education (%) Below upper secondary education

(%)

2008 2009

albiser_e

EAG 2011: use chart A7.2 insteadOKEAG 2010: new slide: Chart C3.1 This chart is based on a quick survey to gather data on 2009. Lower educated substantially more vulnerable than higher educated...

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We can do better(probably a lot)

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rWhat we need to resolve…

Some people have poor foundation skills Shortages, skills gaps exist Skills are underutilised (unemployment, low

rates of labour market participation) There is evidence of mismatch Are we skilling for future jobs

(quantity and quality)?

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rWhat we can do

Mobilise and develop comparative intelligence on skills and skill utilisation

Prioritise investment of scarce resources in skills development

Foster peer learning and look at skills beyond the nation state

Contribute to building strategic partnerships for policy implementation .

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Pillar 1: Labour market responsiveness

• Curricula and provision is informed by labour market needs

• Education systems are flexible and responsive

• Preparing for future labour market needs

Pillar 2:Attention to quality

• Setting high performance standards

• Quality assurance at all levels of education

• Preparing, attracting and retaining good quality teachers

Pillar 3:Adequateskills use

• Good quality career guidance

• Transparent skills systems (recognition, assessment, qualification frameworks)

• Effective HRM in firms

• High demand

Pillar 4: Open/equal

access

• No barriers to participation in education

• easy re-entry and second chance options

• Labour market participation (including marginalised groups)

Pillar 5: Effective

partnerships

• Co-ordination at all levels of government

• Engagement of social partners and education stakeholders

• Co-ordinating policy fields (skills, labour, family, migration)

In Conclusion

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Thank you !