www.skope.ox.ac.uk

Education, social mobility and earning inequality: towards a

new model Craig Holmes, Oxford University

“Social mobility: what has been said and what hasn’t?” ESRC Festival of Social Science, November

6th 2012

www.skope.ox.ac.uk

Introduction

• The creation of a highly educated workforce has long been seen as the key to improving social mobility and lowering inequality– “Education goes to the heart of all we stand for...to make Britain a

fairer and more equal society” Tony Blair, speech to the Fabian Society, 2004

– “As a result of low skills, Britain risks increasing inequality...skills are increasingly the key lever” Leitch Review of Skills final report, 2006

– “Education is critical to our hopes of a fairer society” – Nick Clegg, speech to the Sutton Trust, 2012

– “Education is the silver bullet. Education is everything” – Sam Seabourn, ‘The West Wing’, 1999

www.skope.ox.ac.uk

Policy models

• New Labour:

“We must transform...aspirations...through helping people get the skills they need for better jobs...only in this way will we drive up social mobility, the great force for equality in dynamic market economies.” Tony Blair, speech on welfare reform, June 9th 2002

Educational attainment

Social mobility

Earnings inequality

www.skope.ox.ac.uk

Policy models

• Coalition:

“Myth 1 is that social mobility is simply a sub-set of income inequality. According to this myth, mobility will follow automatically in the wake of greater equality...[b]ut unfortunately it’s not the straightforward route to social mobility that its proponents suggest.” – Nick Clegg, speech to Sutton Trust, May 24th 2012

Educational attainment

Social mobility

Earnings inequality

www.skope.ox.ac.uk

Education and inequality

Correlation = -0.36 (p-value = 0.002)

Sources: World Bank, OECD

0.0% 2.0% 4.0% 6.0% 8.0%0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

CAF

LAO

AZE

KAZ

PER

GEO

PAKARMJPN

SVK

NER

SLV

THA

EGY

COL

CHL

MRT

CZE

RUS

AUSITA

DEU

CIV

ESPCAN

KORSRB

MEX

PRT

LTU

CRI

POL

HUN

SVN

VNM

CHE

ARG

GBR

BRA

AUT

NLD

USA

FRA

NZLESTIRL

LVAKGZISR

FIN NORBEL SWE

ISL

DNK

MDA

Education expenditure (%GDP), 2008

Gini

, 200

8

www.skope.ox.ac.uk

Education and inequality

Correlation = -0.28 (p-value = 0.063)

Sources: World Bank, OECD

0.0% 2.0% 4.0% 6.0% 8.0%0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

KOR CHEISL

SVK SWE

SVNDNK

NORCZE

ESTNLDJPN NZL

FIN

ESP

AUT BEL

CANAUSDEU

HUNFRA

POL

USAGBRPRT

ITAISR

Education expenditure (%GDP), 2008

Gini

, 200

8

www.skope.ox.ac.uk

Education and mobility

Correlation = -0.59 (p-value=0.003)

Sources: World Bank, Corak (2006)

2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0%0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

DNKNORFINCAN

SWENZL

DEUJPN

ESP FRA

CHEPAK USAARGITA GBR

CHL

BRA

PER

Education expenditure (%GDP), 2008

Inte

rgen

erati

onal

inco

me

elas

ticity

(tak

en fr

om C

orak

, 200

6)

www.skope.ox.ac.uk

Education and mobility

Correlation = -0.41 (p-value = 0.007)

Sources: World Bank, Blanden (2009)

2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0%0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

BGDPHL

PER

IDN

PAK

SVK

EGY

PAN

NPL

COLCHL

CZE

MYS

ITA

POLZAF

HUNSVN

VNM

CHE

GBR

BRA

ETH

NLD

USA

NZL

EST

IRL

GHA

KGZ

FINNOR

BEL SWE

DNK

Education expenditure (%GDP), 2008

Year

s of s

choo

ling

corr

elati

on (t

aken

from

Bla

nden

, 20

09)

www.skope.ox.ac.uk

Inequality and mobility

Correlation = 0.78 (p-value=0.0004)

Sources: World Bank, OECD

0.15 0.17 0.19 0.21 0.23 0.25 0.27 0.29 0.31 0.33 0.350

0.1

0.2

0.3

0.4

0.5

0.6

DNKNORFIN CAN

SWENZL

DEUJPN

ESPFRA

USAGBRITA

Gini, 1985

Inte

rgen

erati

onal

inco

me

mob

ility

(tak

en fr

om C

orak

, 20

06)

www.skope.ox.ac.uk

Education, inequality and mobility

• There is obviously correlations between these variables• The causal links are less clear

– If key causal relationship is between inequality and mobility, which then drives educational attainment, current policy is misplaced

• Each of the three elements may mediate the relationships between the other two– e.g. level of inequality in an economy may affect how expansion of

education affects mobility

• Remainder of this paper discusses some important issues and hints towards what a better model might look like

www.skope.ox.ac.uk

Education, inequality and mobility

• Human capital (supply side) view:– Earnings and employment prospects depends on education and

training– Therefore, the strength of correlations between the generation’s

educational attainment is key– Strong correlations maintain a distribution of education based on

family background, which replicates a distribution of earnings and jobs– Weak correlations lead to a distribution of education based on ability

(more efficient)– This does not necessarily, in itself, lead to falling inequality– Increased equality of outcomes result from increased equality of

educational attainment

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Education, inequality and mobility

• Demand side view:– The supply of jobs creates a constraint on the earnings-education link– One role of education is to sort young people into these jobs (Thurow,

1975)– As under HC, strength of correlation of educational attainment would

be predicted to affect social mobility– However, increased equality of educational attainment does not lead

to increased equality of outcomes– The process of recruitment and the structure of occupations directly

affects mobility and inequality, regardless of educational attainment• May feedback into educational attainment

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Education, inequality and mobility

• Policy to increase educational attainment at the low end may not weaken intergenerational correlation in schooling (Goldthorpe, 2012)

• Richer families can attempt to maintain the gap in education in response:– Move to expensive areas near best schools– Private tutors– Entry to Russell Group/pre-1992 universities

• Family background (social capital and networks) – Possible disincentive effects on educational attainment at low end

• Inequality education (and social mobility)

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Towards a new model

• Expanding secondary education has coincided with rising inequality

Correlation = -0.13 (p-value = 0.239)

Source: World Bank, OECD

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0%

-0.10

-0.05

0.00

0.05

0.10

0.15

0.20

AUTUSA

JPN

FINDNKCAN

SWE

POL

GBRNORISR

IRL

LUX

ITANLDARG

FRA

PER

ESP DOM

NZL

MEX

CRI

TUR

Increase in enrollment rate, secondary education, 1981-2008

Chan

ge in

Gin

i, 19

85-2

008

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Towards a new model

• Depending on sample, expansion of secondary education is correlated with smaller increases in inequality

Correlation = -0.47 (p-value = 0.003)

Source: World Bank, OECD

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0%

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

AUTUSA

JPN

FIN

DNKCAN

SWE

POL

GBRNORISR

IRL

LUX

ITANLD

ARG

FRA

PER

ESP DOM

NZL

MEX

TUR

Increase in enrollment rate, secondary education, 1981-2008

Chan

ge in

Gin

i, 19

85-2

008

www.skope.ox.ac.uk

Towards a new model

• However, expansion of tertiary education is not associated with falling inequality

Correlation = 0.05 (p-value = 0.387)

Source: World Bank, OECD

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0%

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

LUXHND

MEX

JPN

ISR

FRA

USA

NLD

AUT

TUR

GBR

ITA

SWE

IRL

ARGNOR

DNK

ESP

NZL

POL

FIN

Increase in enrollment rate, tertiary education, 1981-2008

Chan

ge in

Gin

i, 19

85-2

008

www.skope.ox.ac.uk

Towards a new model

• Potentially a positive correlation between HE expansion and inequality (removing Honduras, Mexico and Luxembourg)

Correlation = 0.38 (p-value = 0.017)

Source: World Bank, OECD

25.0% 30.0% 35.0% 40.0% 45.0% 50.0% 55.0% 60.0% 65.0%

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

JPN

ISR

FRA

USA

NLD

AUT

TUR

GBR

ITA

SWE

IRL

ARGNOR

DNK

ESP

NZL

POL

FIN

Increase in enrollment rate, tertiary education, 1981-2008

Chan

ge in

Gin

i, 19

85-2

008

www.skope.ox.ac.uk

Towards a new model

• Composition effect from expansion of education increased inequality in the UK between 1987 and 2001

Source: UK Family Expenditure Survey, adapted from Holmes and Mayhew (2012)

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.000.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00%

9.00%

Percentile of UK gross hourly earnings distribution

Chan

ge in

wag

e att

ribut

able

to in

crea

sed

educ

ation

al

attai

nmen

t, 19

87-2

001

www.skope.ox.ac.uk

Towards a new model

• Little evidence of changing patterns of wage returns that would counteract this:

Source: UK Family Expenditure Survey

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

-1.00%

-0.50%

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

3.50%

4.00%

Percentile of UK gross hourly earnings distribution

Chan

ge in

wag

e att

ribut

able

to g

radu

ate

earn

ings

pr

emia

, 198

7-20

01

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Towards a new model

• Institutional changes – independent of education but occuring simultaneously – also matter:

Source: UK Family Expenditure Survey

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

-4.00%

-3.00%

-2.00%

-1.00%

0.00%

1.00%

2.00%

Percentile of UK gross hourly earnings distribution

Chan

ge in

wag

e att

ribut

able

to d

eclin

ing

unio

n m

embe

rshi

p, 1

987-

2001

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Towards a new model

• Focus of the discussion is largely on intergenerational mobility (parents to children)

• Intragenerational mobility (throughout working life) is also important:– If low-wage work is a persistent reality, progression reduces its effects

from a lifecycle perspective– Not all educational interventions targeted at young people– Many structural or institutional changes affect those in the workforce

rather than those yet to enter – ability to move within labour market in response to these changes affects earnings and employment outcomes

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Towards a new model• Structural change in work towards more non-routine jobs:

• Age and progression opportunities are not constant over time:

Source: Holmes and Tholen (forthcoming)

Probability of staying in routine jobs (5 year period) A-Levels and equivalent Graduates

Decline of routine jobs: 0% 10% DISP 0% 10% DISP

NCDS (1958 cohort) 95% 85% 10%*** 88% 67% 20%***

BCS (1970 cohort) 82% 78% 3%*** 62% 57% 5%***

Probability of staying in routine jobs (5 year period)

25 year old male 35 year old male

Routine experience: 5 years 5 years 15 years

NCDS 91% 96% 98%

BCS 96% 50% 61%

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Towards a new model

• Internal labour markets and recruitment practices create:– additional demand side barriers to mobility – increase earnings inequality at the top end

• The signalling role of education becomes increasingly important here:– Skills are specific to firms and require further training – and career ladders within firms– Linked to the issue of ‘talent’ and the ways top firms recruit

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Towards a new model?

Educational attainment

Social mobility (inter- and intra-)

Earnings inequality

Everything else?

www.skope.ox.ac.uk

Contact Details

Craig HolmesESRC Centre on Skills, Knowledge and Organisational

Performance (SKOPE), Department of Education,

Norham Gardens,Oxford

Email: craig.holmes@education.ox.ac.uk