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‘Intergenerational Mobility in UK, life

chances and the Role of Inequality and

Education Paul Gregg

Presentation to IFS Poverty Review Workshop 7th Sept 2010

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Introduction & Background“Most people are willing to accept wide inequalities if they are coupled with equality of opportunities” – The Economist (Oct 2006)High profile policy area – previous gmt addressed both poverty and life chances and saw them as inherently linked but is new gmt decoupling them?

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Introduction & Background

Intergenerational mobility has been widely studied using Income, Education and Social ClassBut in a wider sense covers Social Gradients in children‘s life chances – how life chances differ by a measure of (permanent) social backgrounde.g. Marmot commission highlighting extent of social gradients in physical and mental health and how these emerge in childhood

Concepts Original concept of Intergenerational Earnings mobility is ideally comparison of life time (permanent) earnings of father and sonsThis is very data intensive so shorter tem earnings measures usedMore recently the question has shifted towards childhood experience and later life chances which has shifted emphasis toward family income in childhoodThis also allows for absentee fathers which varies across cohorts in a non-random way

Methodology – Income based

ln lnson parentsi i iY Y

parents son

ln

lnY , lnY ln = Corr ( )

parents

son

Y

Y

SDrSD

Intergenerational Income Mobility

Income/earnings NCDS BCS 0.205 (.026) 0.291 (.025)Partial correlation (r) 0.166 (.021) 0.286 (.025)

Measurement IEarly earnings based research had highlight high levels of mobility but concerns raised over biases generated by measurement error and life cycle stageSo using American data NLSY single period income = 0.32, average over 3 periods = 0.45 implies true estimate = 0.54 Life cycle bias comes from the age(s) at which earnings are measured and how good a proxy they are for lifetime earningsWhen earnings is measured early or late in life course it is a less good proxy for lifetime earnings (optimal is at about 40)

Life Cycle bias in UK

23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 460

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Age-beta profiles across cohorts

NCDS BCS

beta

coe

ffici

ent

PovertyIncome mobility and intergenerational poverty are not the same thingBlanden and Gibbons suggest the odds risk for poor children being poor adults rose from twice that of non-poor children to 3.5+ times between the NCDS and BCS cohorts All this work asks what happens to poor children not who become the poor parents in the next generation – including who has children from the earnings/employment distribution

Education/Inequality/GenesThe recent literature has been looking at the key patterns of mobility and beginning to look at the driversWhether mobility is high or low needs a benchmark so international comparisons and changes across time in countries have been widely investigated A natural next step was to explore how these patterns match on to inequality and education (for example Blanden, 2009)

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Estimated Intergenerational Income Persistence and Income Inequality Across Countries

CanadaGermany

USA

Sweden

GBrit

Italy

Norway

Denmark

Finland

France

Australia

.1.2

.3.4

.5

.2 .22 .24 .26 .28 .3inc_gini

Income beta Fitted values

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Estimated Intergenerational Income Persistence and Education Expenditure Countries

CanadaGermany

USA

SwedenGBrit

Italy

NorwayDenmark

Finland

France

Australia

Brazil

0.2

.4.6

.8In

com

e be

ta

.03 .04 .05 .06 .07 .08% GDP on education 1970-1974

Income beta Fitted values

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Educational TransmissionBlanden et al. (2007), following Solon, explore the

drivers of intergenerational mobility that are measured at earlier ages. The process of obtaining β can be thought of in two stages.

iparents

ii YEduc 11 ln

iichild

i uEducInY 11

)(ln)ln,( 1

parentsi

parentsii

YVarYuCov

-0.03

0.02

0.07

0.12

0.17

0.22

0.27

0.32

1 2 3 4 1 2 3 4

Pers

iste

nce

Specification

1958 - NCDS 1970 - BCS

Cross-cohort decomposition

Educational TransmissionIn data with moderately detailed education records, around 55% of intergenerational mobility in UK comes through educationFurther, around 80% of the rise in intergenerational income persistence comes from increased strength of the relationship between family background and education (Blanden et al. 2007)Following Heckman big interest in non-cog Mood et al. (2010) explore personality traits as well as education for Sweden and suggest that that about 45% of IGE is explained with 2/3 by cognitive/ed and 1/3 by personality measures

Education and Family Background – recent picture

GCSE year ‘88 ‘90 ‘91 ‘93 ‘95 ‘97 ‘99 ‘01 ‘03 ‘06 Birth year ‘72 ‘74 ‘75 ‘77 ‘79 ‘81 ‘83 ‘85 ‘87 ‘90

PARENTAL OCCUPATION (SEG)

Managerial/Professional 52 58 60 66 68 69 70 Other non-manual 42 49 51 58 58 60 59

Skilled manual 21 27 29 36 36 40 45 Semi-skilled manual 16 20 23 26 29 32 35

Unskilled manual 12 15 16 16 24 20 30 Top - Bottom 40 43 44 50 44 49 40

Ratio of top / bottom 4.3 3.9 3.8 4.1 2.8 3.5 2.3 PARENTAL

OCCUPATION (NS-SEC)

Higher professional 75 77 76 81 Lower professional 62 64 65 73

Intermediate 49 51 53 59 Lower supervisory 34 34 41 46

Routine 26 31 33 42 Top - Bottom 49 46 43 39

Ratio of top / bottom 2.9 2.5 2.3 1.9

Parental Educational and Genetics

Estimates of the impact these drivers is moving into causal analysisFor instance, looking at increased parental education on child education/earnings Results suggest raising a parents education by 1 year results in increase in child's education by 0.1-0.25

Parental Educational and Genetics

Studies of genetics using partialling out variances between identical twins, siblings etc suggest about 40-50% of IQ is heritable. For personality it is lower (20%) but measurement less well developedSimilar approaches being used in IGE estimation in Sweden (Bjorklund et al. 2006) Non-

adopteesBiological father

AdopteesAdoptee Father

AdopteesBiological father

Years of schooling

.24 .114 .113

Income .241 .173 .059

BCS intergenerational test scores from Claire Crawford, Alissa Goodman and Robert Joyce (IFS)

There is a strong link between the cognitive skills of parents and their children This remains even after controlling for

many detailed environmental factors Forms an important reason why

children from poor families do less well at school than richer ones (which the other studies could not capture)

Direct effect alone explains 17% of gap in rich-poor decomposition – this is an upward biased estimate of genetic influence

SES gradients are apparent across a range of outcomes at age 7 to 9

Income gradients in child outcomes in middle childhood

88

90

92

94

96

98

100

102

104

106

108

30 80 130 180 230 280 330 380 430 480 530 580 630

Equivalised disposable weekly household income age 3/4

Scor

e (m

ean

100,

SD

10)

IQ (5.85)

Key Stage 1 (5.46)

Locus of control (3.30)

Self esteem (1.71)

Behaviour (2.01)

Fat mass (1.34)

Source: Gregg, Propper and Washbrook (2008) (ALSPAC)

Attainment through childhoodfrom JRF funded research (CMPO and IFS)

20

30

40

50

60

70

80

Age 3 (MCS) Age 5 (MCS) Age 7 (ALSPAC) Age 11 (ALSPAC/LSYPE)

Age 14 (LSYPE) Age 16 (LSYPE)Perc

entil

e of

the

test

scor

e di

strib

ution

Highest Quintile 4 Quintile 3 Quintile 2 Lowest

How much of the socio-economic gap in cognitive outcomes at age 3 is explained by these factors?

34%

16%25%

4%

3%

1% 16%

1% Residual Gap

Parental Education

Family Background/Demograph-ics

Family Interactions

Health and Well-Being

Childcare

Home-Learning Environment

Parenting Style/Rules

Missing Data

© Institute for Fiscal Studies

Total gap to be explained:

23 percentile points

Evolution of the socio-economic gap in cognitive outcomes at ages 7 to 11

7%

13%4%

6%6%

-1%

63%

Residual GapParental Education and Family BackgroundChild's attitudes and behavioursParent's attitudes and behavioursPre-school envi-ronmentsSchoolsMissing DataPrior Ability

© Institute for Fiscal Studies

Total gap to be explained:

31 percentile points

Evolution of the socio-economic gap in cognitive outcomes at ages 11 to 16

7%6%

15%

8%1%

4%

59%

Residual GapParental Education and Family BackgroundChild's attitudes and behavioursParent's attitudes and behavioursSchoolsMissing DataPrior Ability

© Institute for Fiscal Studies

Total gap to be explained:

33 percentile points

Key messages1. Educational achievement persists strongly over the

course of childhood. Those who start a developmental stage ahead generally finish it ahead. This implies earlier interventions are likely to be more effective than later ones.

2. Low SES children exhibit poorer social and emotional development. These skills matter and lead low SES children to fall further behind at school, even conditional on prior academic ability.

3. Parental behaviours and values play an important role in the transmission of family background to educational achievement and other outcomes.

ConclusionsRather speculatively

Societies with higher inequality have lower mobility for two reasons – 1) higher inequality gives parents greater incentives/different resource to invest in children. 2) the educational inequalities get higher pay offs in high inequality countriesSchool environment is more equal than home environment and tends to generate mobility but this will depend on the extent of resources in the schooling system and the degree of inequality in schooling experience as the conflict with inequalities in the broad home learning environment incl. parenting

Additional slides

Permanent Income Decomposition

Components of Permanent Childhood and Current Income in the BHPS

Percentage

share of variance

Correlation with permanent childhood income

Permanent childhood income, components associated with:

Fathers’ social class ( ˆp pSC ) 15.67 0.431

Other income predictors ( ˆp pX ) 22.26 0.615

Residual permanent income ( ˆp ) 62.07 0.716

Current income, components associated with:

Fathers’ social class ( pp SC ) 7.54 0.398

Other income predictors ( pp X ) 17.41 0.514

Transitory and measurement error (ˆ ˆp pu e )

40.55 -0.041

Residual permanent income (ˆˆ ˆp p p )

34.52 0.706

Error and residual unmeasured income, (ˆˆ ˆ ˆ ˆp p p p pu e )

75.06 0.487

Current income ( py ) ˆ ˆ( ) ( )p p p p p p p p pSC X u e 0.735

Current income without error = permanent childhood income

ˆ ˆ( ) ( )p p p p p p pSC X

1.000

Ed-Income recent evidence

Variable

NCDS 1958

BCS 1970

BHPS 1 1975-1980

BHPS 2 1981-1986

BHPS 3 1987-1990

LSYPE 1989/1990

Number of O-levels (A*-C)

0.7165 [0.036]***

1.1315 [0.046]***

1.0647 [0.155]***

0.7958 [0.258]***

0.9880 [0.249]***

0.9336 [0.035]***

N 7841 5428 815 515 345 10935 Stay on post – 16

0.0963 [0.006]***

0.1360 [0.006]***

0.1110 [0.019]***

0.0846 [0.031]***

0.0885 [0.029]***

0.0463 [0.005]***

N 7196 6420 964 583 386 8205 Number of A-levels (any)

0.1618 [0.010]***

0.4164 [0.023]***

0.4703 [0.075]***

0.4512 [0.128]***

N 7841 3769 638 373 Stay on post – 18

0.0621 [0.004]***

0.1047 [0.006]***

0.0697 [0.021]***

0.0730 [0.033]**

N 7196 5529 946 568 Degree 0.0553

[0.004]*** 0.1158 [0.006]***

0.0916 [0.017]***

0.0884 [0.033]***

N 7949 5520 932 484 Proportion time NEET

-0.0049 [0.002]***

-0.0197 [0.003]***

-0.0676 [0.009]***

N 5907 5546 949