Centre for Market and Public Organisation Decomposing the income gradients in child outcomes: What...

Centre for Market and Public Organisation

Decomposing the income gradients in child outcomes: What is it about low-income

households that’s bad for kids?

Paul Gregg, Lindsey Macmillan, Carol Propper and Elizabeth Washbrook

Family Background and Child Development Conference

LSE, 18th July, 2006

Introduction I

• Question: What is it that goes on in low-income households that leads to poorer child outcomes?

• Data: the AlSPAC cohort of children born in the Avon area of England in 1991/2 (very rich data)

• Method: a linear decomposition technique that unpacks raw income gradients in seven child outcomes at ages 6 to 9– Cognitive, socio-emotional and health outcomes

• Some evidence on:– Is the relationship between maternal education and child health mediated

by smoking?

– The association between asthma in children and their educational attainment

– The role of child’s diet in mediating the relationship between income and child outcomes

– The relationship between pre-school childcare and child behaviour

– The role of social mix in explaining the income gradients in child outcomes

Introduction II

• Motivation: Money doesn’t ‘buy’ better test scores – Income may be correlated with, but not (necessarily) cause, other

characteristics of the household that have a direct effect on child outcomes

– Along with other household characteristics, income defines the constraints under which parents choose the optimal mix of inputs into a ‘child quality production function’ – not a direct input but a proxy

• Conceptually, we make the distinction between

– Characteristics: features of the household that are not direct inputs into the child quality production process

– Proximal factors: inputs, or factors that are directly experienced by the child

• We cannot ‘prove’ causality but rather provide ‘suggestive evidence’

O(Outcome)

I(Income)

O = O(I)

Linear decomposition model – the income gradient

δ

O is a scalar outcome variable

I is a scalar (here log income)

δ is the (single-valued) parameter to be decomposed

Measure: Log average real equivalised disposable household income at 33 and 47 months

E(O | I ) = δ I

O(Outcome)

O = O(P* , PU)

Linear decomposition model – structural equations

PU

(Proximals - unobs)

P*(Proximals – obs.) *

U

E(O| P*, PU) = * P* + U PU

P* is a k* ×1 vector of observed proximal factors

* and U are 1 × k* and 1 × kU vectors of coefficients respectively

PU is a kU ×1 vector of unobserved proximal factors

I(Income)

C(Characteristics)

PU

(Proximals - unobs)

P*(Proximals – obs.)

*

*U

U


P = P(C , I)E(P*| C,I) = * C + * I

C is a n ×1 vector of characteristics of the household, parents and child

* and U are k* × 1 and kU × 1 vectors of coefficients respectively

* and U are k* × n and kU × n matrices of coefficients respectively

E(PU| C,I) = U C + U I

C(Characteristics)


C = C(I)E(C| I) = I

is a n ×1 vector of coefficients

I(Income)

C(Characteristics)


I(Income)

I(Income)

PU

(Proximals - unobs)


*

*U

U

O(Outcome)

*

U

E(O| P*, PU) = * P* + U PU

E(O| C, I) = * (* C + * I) + U (U C + U I)

= * (* ( I) + * I) + U (U ( I) + U I)= (** + * * + UU + UU) I

E(O| I)

= δ I

Using LIE:

δ = ** + ** + UU + UU

C(Characteristics)


I(Income)

I(Income)

PU

(Proximals - unobs)


*

*U

U

O(Outcome)

*

U

E.g. Income is negatively correlated with family size (α), which is negatively correlated with parental reading behaviours (*), which is positively correlated with cognitive outcomes (*)

δ = ** + ** + UU + UU

C(Characteristics)


I(Income)

I(Income)

PU

(Proximals - unobs)


*

*U

U

O(Outcome)

*

U

E.g. Income is positively correlated with educational expenditures (*), which are positively correlated with cognitive outcomes (*)

δ = ** + ** + UU + UU

C(Characteristics)


I(Income)

I(Income)

PU

(Proximals - unobs)


*

*U

U

O(Outcome)

*

U

E.g. Income is negatively correlated with family size (α), which is associated with poorer quality unobserved parent-child interactions (U), which are associated with poorer cognitive outcomes (U)

δ = ** + ** + UU + UU

C(Characteristics)


I(Income)

I(Income)

PU

(Proximals - unobs)


*

*U

U

O(Outcome)

*

U

E.g. Income is positively correlated with the (unobserved) quality if a child’s toys (U), which is positively correlated with cognitive outcomes (U)

δ = ** + ** + UU + UU

C(Characteristics)


I(Income)

I(Income)

O(Outcome)

The total effect of I via Ci, via all observed and unobserved proximal factors (conditional on I and Cj i)

PU

(Proximals - unobs)


δ = ** + ** + UU + UU


The direct effect of I, via all observed and unobserved proximal factors (conditional on C)

C(Characteristics)

I(Income)

I(Income)

O(Outcome)

PU

(Proximals - unobs)


δ = ** + ** + UU + UU

C(Characteristics)


I(Income)

I(Income)

O(Outcome)

The total effect of I via P*i, direct effect plus effect via C (conditional on PU and P*j i)

PU

(Proximals - unobs)

P*(Proximals – obs.) ** + *

δ = ** + ** + UU + UU

Linear decomposition model – estimation

Identification of parameters (OLS):O = δ I + zC = I + xP* = * C + * I + w*

Substitute for PU inO = * P* + U PU + v

usingPU = U C + U I + wU

givingO = *P* + UU C + U U I + (U wU+ v)

Note: U, U and U cannot be identified separately Further assumption Cov(P*, PU | C, I) = 0 requiredStandard errors on combined path coefficients (will be) calculated by bootstrapping.

Table 1: Total income gradients in child outcomes in the ALSPAC cohort

All measures except asthma/wheeze are standardised to mean 100, SD 10.

Asthma/wheeze is 0/1 dummy (sample mean = 0.128)

ST = school-administered test; CC = child-completed during clinic; MQ = mother-completed postal questionnaire; TQ = teacher-completed postal questionnaire; AC = administered by ALSPAC staff during clinic

SDQ sub-scores: Hyperactivity, Emotional symptoms, Conduct problems, Peer problems

* Key Stage 1 completed Year 3, age 6/7; ALSPAC literacy score completed age 7

** Child ever had asthma/persistent wheeze between birth and 81 months

Household characteristics

Social capital

Educational capital

Emotional capital

Child characteristics

Educational capital variables:

Mother’s education

Father’s education

Maternal grandparents’

education

Mother’s attitudes to education


Social capital

Educational capital

Emotional capital


Social capital variables:

Mother’s age at birth

Child’s race

Family structure and size

Social housing

Local neighbourhood

(IMD)


Social capital

Educational capital

Emotional capital


Emotional capital variables:

Maternal anxiety/depression

(CCEI)

Maternal locus of control

Mother’s social networks

Parental relationship


Social capital

Educational capital

Emotional capital


Child characteristics:

Gender

Birth weight

SCU at birth

Month of birth

Materialdeprivation

Maternal warmth/ discipline

Health-relatedbehaviours

Parenting behaviours (cognitive)

Childcare/ school quality

Observed proximal factors

Maternal warmth/discipline

variables:

Frequency of smacking

Variation in types discipline method

Frequency of cuddling

Maternal confidence and enjoyment

Materialdeprivation






Health-related behaviours variables:

Breastfeeding

Maternal smoking

Diet

Materialdeprivation






Material deprivation variables:

Car and phone ownership

Noise and crowding

Damp, double-glazing and central

heating

Toys and books

Materialdeprivation






Parenting behaviours (cognitive) variables:

Maternal teaching and reading

Paternal reading

Extra-curricular classes

Help with homework

Materialdeprivation




Childcare/school quality


Childcare/school quality variables:

Types of care pre-3

Types of care 3 – school-age

School fixed effects (5+ children in

school)

Outcome(O)

Income(I)

Social capital

(C)

Income(I)

Educational capital

(C)

Emotional capital

(C)


(C)

δ = ** + UU + ** + UU

Path model: Table 2

Table 2: Decomposition of overall income gradients: direct income effects and parental capital

> 30% 20 - 30% 10 - 20% 5 - 10% < -5%

Outcome(O)

Income(I)

Social capital

(C)

Income(I)

Educational capital

(C)

Emotional capital

(C)


(C)

Path model: Table 3

δ = ** + UU + ** + UU

Table 3: Decomposition of part of income gradient explained by income correlation with educational capital

> 30% 20 - 30% 10 - 20% 5 - 10% < -5%

Outcome(O)

Income(I)

Social capital

(C)

Income(I)

Educational capital

(C)

Emotional capital

(C)


(C)

Path model: Table 4

δ = ** + UU + ** + UU

Table 4: Decomposition of part of income gradient explained by income correlation with social capital

> 30% 20 - 30% 10 - 20% 5 - 10% < -5%

Outcome(O)

Income(I)

Social capital

(C)

Income(I)

Educational capital

(C)

Emotional capital

(C)


(C)

Path model: Table 5

δ = ** + UU + ** + UU

Table 5: Decomposition of part of income gradient explained by income correlation with emotional capital

> 30% 20 - 30% 10 - 20% 5 - 10% < -5%

COGNITIVE SOCIO-EMOTIONAL HEALTH

KS1 & ALS WISC SDQ (mum) SDQ (teacher) Locus Asthma/ wheeze

DXA

Father’s ed

(21.5) Father’s ed

(24.9) CCEI (29.8)

Mother’s locus (27.5)

Father’s ed (30.3)

Social housing (49.1)


Income (16.8)

Mother’s ed (20)

Income (19.4)

Social networks (15.5)

Mother’s ed (20.5)

N’hood IMD (17)

N’hood IMD (18.3)

Mother’s ed (13)

Income (19.3)

Ed attitudes (12.4)

Father’s ed (15)


G’parents ed (12.3)



Mother’s

locus (10.6)

Mother’s age (11.6)

CCEI (12.3)


Social

networks (10.2)

Lone parenthood

(11.6)


G’parents’ ed (15.0)

Social housing

(10.9)

Social networks (12.1)

Mother’s ed

(11.8)

Table 6: Characteristics than can singly account for 10% or more of the income gradient

Outcome(O)

Income(I)

MaterialDeprivation (P*)

Maternal warmth/ bonding (P*)

Health-relatedBehaviours (P*)

Parenting behaviours (cognitive) (P*)

Childcare/ school quality (P*)

Path model: Table 7

Unobserved proximal factors (PU)

δ = ** + UU + ** + UU

Table 7: Decomposition of overall income gradients: observed and unobserved proximal factors

> 30% 20 - 30% 10 - 20% 5 - 10% < -5%

Outcome(O)

Income(I)


Maternal warmth/ discipline (P*)




Path model: Table 8


δ = ** + UU + ** + UU

Table 8: Decomposition of part of income gradient explained by income correlation with maternal warmth/discipline

> 30% 20 - 30% 10 - 20% 5 - 10% < -5%

Outcome(O)

Income(I)






Path model: Table 9


δ = ** + UU + ** + UU

Table 9: Decomposition of part of income gradient explained by income correlation with health-related behaviours

> 30% 20 - 30% 10 - 20% 5 - 10% < -5%

Outcome(O)

Income(I)






Path model: Table 10


δ = ** + UU + ** + UU

Table 10: Decomposition of part of income gradient explained by income correlation with material deprivation

> 30% 20 - 30% 10 - 20% 5 - 10% < -5%

Outcome(O)

Income(I)








δ = ** + UU + ** + UU

Table 11: Decomposition of part of income gradient explained by income correlation with cognitive parenting behaviours

Outcome(O)

Income(I)








δ = ** + UU + ** + UU

Table 12: Decomposition of part of income gradient explained by income correlation with childcare/school quality

> 30% 20 - 30% 10 - 20% 5 - 10% < -5%

Conclusions I

Low-income children are disadvantaged across a number of dimensions and the factors underlying this advantage differ substantially across outcomes – no ‘magic bullet’

Differential education between high- and low-income parents is a major factor in explaining the attainment gap in cognitive outcomes, but plays a much smaller role in accounting for gaps in behaviour.

The poorer emotional resources of low-income mothers have little implication for their children’s cognitive outcomes, but play a large role in explaining their greater behaviour problems.

The fact that low-income children are much more likely to live in social housing and in deprived neighbourhoods has an important role in explaining their poorer health outcomes.

Conclusions II

We find evidence of systematic differences in the factors associated with teacher and mother reports of children’s behaviour.

Not all the characteristics of low-income families are associated with poorer outcomes. Lack of car ownership and colder homes are associated with reduced risk of obesity; childcare choices between 3 and school entry are associated with fewer behavioural problems.

Next steps:

•Standard errors

•Three-part pathways

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