OECD Employment Outlook 2016

OECD Employment Outlook 20167 July 2016

OECD Employment Outlook 20016 www.oecd.org/employment/outlook

http://www.oecd.org/employment/outlook

http://www.oecd.org/employment

The jobs recovery continues, but remains incompletein the majority of OECD countries

Evolution of the employment-to-population ratio as a percentage of the population aged 15-74


Note: Shaded area refers to the OECD projections. OECD is the weighted average for the 34 OECD member countries. Euro area is the aggregate of 15 OECD countries of the euro area.

Q4 2007

Q2 2008

Q4 2008

Q2 2009

Q4 2009

Q2 2010

Q4 2010

Q2 2011

Q4 2011

Q2 2012

Q4 2012

Q2 2013

Q4 2013

Q2 2014

Q4 2014

Q2 2015

Q4 2015

Q2 2016

Q4 2016

Q2 2017

Q4 2017

54

56

58

60

62

64

66

68

70

%

Projections

• Japan

• United States

• OECD

• Euro Area



Unemployment has been falling but remains above its pre-crisis level in most OECD countries

Evolution of the unemployment rate as a percentage of the labour force


Q4 2007

Q2 2008

Q4 2008

Q2 2009

Q4 2009

Q2 2010

Q4 2010

Q2 2011

Q4 2011

Q2 2012

Q4 2012

Q2 2013

Q4 2013

Q2 2014

Q4 2014

Q2 2015

Q4 2015

Q2 2016

Q4 2016

Q2 2017

Q4 2017

2

3

4

5

6

7

8

9

10

11

12

13

%

Projections

Note: OECD is the weighted average for the 34 OECD member countries. Euro area is the aggregate of 15 OECD countries of the euro area.

• Euro Area

• OECD

• United States

• Japan



Long-term unemployment has fallen more slowly than total unemployment

Long-term unemployed (12 months and over) as a percentage of total unemployed, Q4 2007-Q4 2015

Q4 2007

Q1 2008

Q2 2008

Q3 2008

Q4 2008

Q1 2009

Q2 2009

Q3 2009

Q4 2009

Q1 2010

Q2 2010

Q3 2010

Q4 2010

Q1 2011

Q2 2011

Q3 2011

Q4 2011

Q1 2012

Q2 2012

Q3 2012

Q4 2012

Q1 2013

Q2 2013

Q3 2013

Q4 2013

Q1 2014

Q2 2014

Q3 2014

Q4 2014

Q1 2015

Q2 2015

Q3 2015

Q4 2015

0

10

20

30

40

50

60

%

Note: OECD is the weighted average of 33 OECD countries excluding Chile.


• Euro Area

• Japan

• OECD

• United States



Real hourly earnings have grown slowlysince the onset of the crisis

Index base 100 in Q4 2007


Note: Total wages divided by total hours worked of employees deflated using the private consumption price index. OECD is the weighted average of 27 OECD countries (excluding Chile, Iceland, Korea, Mexico, New Zealand, Norway and Turkey).

Q4 2007

Q1 2008

Q2 2008

Q3 2008

Q4 2008

Q1 2009

Q2 2009

Q3 2009

Q4 2009

Q1 2010

Q2 2010

Q3 2010

Q4 2010

Q1 2011

Q2 2011

Q3 2011

Q4 2011

Q1 2012

Q2 2012

Q3 2012

Q4 2012

Q1 2013

Q2 2013

Q3 2013

Q4 2013

Q1 2014

Q2 2014

Q3 2014

Q4 2014

Q1 2015

Q2 2015

Q3 2015

Q4 2015

98

100

102

104

106

108

110

• Euro Area

• OECD

• United States

• Japan



The post-crisis surge in unemployment led to slower nominal wage growth, but this effect has now been reversed in some

countriesWage-Phillips curves: Relationship between nominal wage growth and change

in the unemployment rate since the start of the crisis, Q4 2007-Q4 2015


Note: Nominal wage growth: year-on-year percentage change in nominal hourly wage (defined as total wages divided by hours worked of employees); unemployment gap: percentage-points change in the unemployment rate since the start of the crisis in Q4 2007. OECD: Unweighted average of 27 OECD countries (excluding Chile, Iceland, Korea, Mexico, New Zealand, Norway and Turkey). Euro area: Unweighted average of the 17 euro area countries.

-0.5 0 0.5 1 1.5 2 2.5 3 3.5 40

0.51

1.52

2.53

3.54

4.55

OECD

Unemployment gap, percentage-points change

Nominal hourly wage

growth, %

Q4 2015

Q4 2007

0 1 2 3 4 5 60

1

2

3

4

5

6

7

Euro area


Nominal hourly wage

growth, %

Q4 2007

Q4 2015

-1 -0.5 0 0.5 1 1.5 2-3

-2.5-2

-1.5-1

-0.50

0.51

1.52

Japan


Nominal hourly wage

growth, %

Q4 2007

Q4 2015

0 1 2 3 4 5 60

0.5

1

1.5

2

2.5

3

3.5

4

United States


Nominal hourly wage

growth, %

Q4 2007

Q4 2015



Youth unemployment has receded from its post-crisis peak,but remains very high in a few European countries

Percentage of youth (aged 15-24) labour force, Q4 2007- Q4 2015


Note: Youth aged 16-24 for the United States. Q1 2016 for Canada and the United States. Country-specific peak is defined as the maximum value of the youth unemployment rate since the start of the crisis (Q4 2007).

Jaapn

Germany

Mexico

Korea

United S

tates

Australi

a

Canada

United K

ingdom

OECDTurk

ey

Europea

n Unio

n

Euro ar

eaFran

ce Italy

Spain

0

10

20

30

40

50

60%

Q4 2007 Country-specific peak Q4 2015 ( )↗



The NEET rate has increased in the majority of OECD countries

Percentage of youth aged 15-29 who are neither employed nor in education or training, 2007-15


Note: 2008 and 2013 for Korea. OECD is the unweighted average of 33 OECD countries (excluding Israel).

Germany Jap

an

Australi

a

Canada

United K

ingdom

United S

tates

OECD

Europea

n Unio

n

Euro ar

eaFran

ceKore

aMexi

coSpai

nIta

lyTurk

ey0

5

10

15

20

25

30

35

40

45%

2007 2015 ( )↗2007 2015 ( )↗



Many NEETs have not finished upper-secondary schoolingPercentage distribution of youth aged 15-29 who are neither employed

nor in education or training by educational attainment, 2015


Note: 2013 data for Korea. OECD is the unweighted average for the 34 OECD member countries. High-skilled refers to NEETs with at least a tertiary degree and low-skilled to persons who have not finished upper secondary schooling.

Korea

Japan

United S

tates

Canada

France

Australi

aOECD

United K

ingdom Ita

ly

Europea

n Unio

n

Euro ar

ea

Germany Spai

nTurk

eyMexi

co0

10

20

30

40

50

60

70

80

90

100

%

• High-skilled

• Medium-skilled

• Low-skilled



Cumulative gaps in real hourly wage growth since the crisisPercentage shortfall of the Q4 2015 real hourly earnings with respect to a counterfactual value

calculated assuming the pre-crisis growth rate (Q1 2000 to Q4 2007) had continued after Q4 2007


Note: OECD is the weighted average of 27 OECD countries (excluding Chile, Iceland, Korea, Mexico, New Zealand, Norway and Turkey).

Germany Jap

anSpai

nFran

ceOECD

Italy

Canada

United S

tates

Australi

a

Greece

Hungary

United K

ingdom

Estonia

-20

-10

0

10

20

30

40



The majority of OECD countries still face a significant unemployment gap, a significant wage gap or both


Note: The unemployment gap is defined as the percentage-point change in the unemployment rate in Q4 2015 relative to its level in Q4 2007 (just before the crisis). The wage gap (real hourly earnings) is defined as the percentage shortfall of the Q4 2015 value with respect to a counterfactual value calculated assuming the pre-crisis growth rate during Q1 2000 to Q4 2007 (Q1 2002 to Q4 2007 for Poland) had continued after Q4 2007.

-6 -4 -2 0 2 4 6 8 10 12 14 16 18-20

-15

-10

-5

0

5

10

15

20

25

30

35

40

45

50

55

7.7

-2.1 -1.9

4.0

31.7

11.7

38.1

9.7

1.6

-14.6

22.524.8

20.4

3.3 3.9

-4.9

-0.6

4.9

-9.3

0.1

15.6 14.4

-1.0

7.2

1.0

26.3

4.0

-5.8

1.7

52.1

Unemployment gap (percentage-points change)

Real hourly wage gap (Per-centage change)

Unemployment gap of at least 2 percentage points and wage gap of

at least 5%

Unemployment gap of at least 2 percentage points, no/small wage

gap

No/small unemployment gap and no/small wage gap

No/small unemployment gap, wage gap of at least 5%



Skills proficiency explains a small part of the variation in skills use, while occupation and work organisation

explain a large partShare of skills use variance explained by individual and firm factors, OECD PIAAC countries


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 work0

10

20

30

40

50

60

Firm size Occupation Industry

High-Performace Work Practices (HPWP) Skills proficiency Country fixed effects



Higher skills use at work is associated with higher wages, over and above the effect of skills

proficiencyPercentage change in wages associated to a standard deviation increase in skills use, proficiency

and years of education


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 work0

0.04

0.08

0.12

0.16

0.2

Years of education



High-Performance Work Practices (HPWP) can positively influence the use of information-processing

skills at workAverage skills use at work, by HPWP intensity


Reading

Writing

Numeracy

ICT at work

Problem solving

1 1.5 2 2.5 3 3.5 4

A. Work flexibility - Sequence of tasks

Reading

Writing

Numeracy

ICT at work

Problem solving

1 1.5 2 2.5 3 3.5

B. Work flexibility - Speed of work

Reading

Writing

Numeracy

ICT at work

Problem solving

1 1.5 2 2.5 3 3.5

C. Work flexibility - How to do work

Reading

Writing

Numeracy

ICT at work

Problem solving

1 1.5 2 2.5 3 3.5

E. Instructing, teaching and training others

Reading

Writing

Numeracy

ICT at work

Problem solving

1 1.5 2 2.5 3 3.5

F. Sharing information with co-workers

Reading

Writing

Numeracy

ICT at work

Problem solving

1 1.5 2 2.5 3 3.5 4

G. Organising own time

Reading

Writing

Numeracy

ICT at work

Problem solving

1 1.5 2 2.5 3 3.5

H. Planing own activities

Reading

Writing

Numeracy

ICT at work

Problem solving

1 1.5 2 2.5 3 3.5 4

D. Co-operating with co-workers

• To a high extent and more

• Up to some extent

• Not at all

• At least once a week

• At least once a month

• Never



The use of bonuses, training and flexible working hours can promote skills use by enhancing workers’ motivation

to make full use of their skills at work

Reading

Writing

Numeracy

ICT at work

Problem solving

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Flexible working hours minus no flexibility Training last year minus no training Bonus minus no bonus




Structural reforms can boost the economy in the long run: the case of product market regulation

Aggregate employment gains from competition-enhancing reforms, in percentage


Mexico

Israel

Korea

Japan

Luxem

bourg

New Zeal

andIce

landPola

ndFinla

ndGree

ce

United S

tates

SpainFran

ceOECD

Norway Ita

ly

Hungary

Switzerlan

d

Slovak

Republic

Belgium

Czech R

epublic

Canada

Portuga

l

Irelan

d

Netherla

ndsAust

ria

Sweden

Germany

Denmark

Australi

a

United K

ingdom

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0%



Structural reforms can boost the economy in the long run: the case of labour market regulation

Aggregate labour market effects of flexibility enhancing EPL reforms


Wage and salary employment(%)

Wages(%)

Wages, composition corrected(%)

Low-skilled share in hours worked (percentage points)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.1443

0.372 0.3681

0.1845

Note: ***, ** denote estimated impacts that are significant at the 1% , 5% level, respectively.



In the short-run reforms can entail job lossesCumulative percentage change in employment up to 4 years following reform


Before 1 2 3 4Time since reform (years)

-2.5

-2

-1.5

-1

-0.5

0

0.5

A. Barriers to Firm Entry


-1.5

-1

-0.5

0

0.5

B. Dismissal regulations



Short-term job losses from EPL reforms are minimized in dual labor markets

Cumulative percentage change in employment up to 4 years following reform



- 1.2

- 0.8

- 0.4

0.0

0.4

0.8

15% of fixed-term contracts 10% of fixed-term contracts 5% of fixed-term contracts




Many countries are converging to low gender participation gaps, but progress is uneven

Percentage-point difference in labour force participation rates between men and women of working-age

0

10

20

30

40

50

60

A. Countries experiencing strong decline in the gender participation

gap

ArgentinaBrazilChileColombiaCosta RicaMexicoPeruOECDp.p

1990

1993

1996

1999

2002

2005

2008

2011

2014

0

10

20

30

40

50

60

B. Countries experiencing no change in the gender participation gap at a

low level

China

Russian Federation

South Africa

OECDp.p

1990

1993

1996

1999

2002

2005

2008

2011

2014

0

10

20

30

40

50

60

C. Countries experiencing no change in the gender participation gap at a

high level

EgyptIndiaIndonesiaMoroccoTunisiaTurkeyOECDp.p

Note: OECD is the unweighted average of the 34 OECD member countries.




Top management positions are dominated by men, but progress has often been sizable

Women’s share of top management or executive positions as a percentage of all top management or executive positions, 2000 and 2014

EgypMorocco

TurkeyIndia

TunisieIndonesia

PeruChina

South AfricaOECD

ArgentinaCosta Rica

MexicoBrazil

Russia FederationColombia

Chili

0 5 10 15 20 25 30 35 40 45 50

2014

2000

Note.: OECD is the unweighted average of the 33 OECD member countries (Israel not included).




The gender pay gap remains substantial in most countries

Difference between male and female median earnings divided by male median earnings

Costa Rica Colombia Mexico Argentina Turkey OECD Chile Brazil Indonesia Peru South Africa

Russian Federation

India0

10

20

30

40

50

60

1990s 2000s 2010s ( )↗

%

Notes: Earnings refer to the monthly earnings of full-time employees (usually persons working at least 30 hours per week). The pay gap has been averaged over the available years within each decade. OECD is the unweighted average of the 34 OECD member countries



Data & Analytics

OECD Employment Outlook 2016