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Transcript of 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
Linear decomposition model – structural equations
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)
Linear decomposition model – structural equations
C = C(I)E(C| I) = I
is a n ×1 vector of coefficients
I(Income)
C(Characteristics)
Linear decomposition model – structural equations
I(Income)
I(Income)
PU
(Proximals - unobs)
P*(Proximals – obs.)
*
*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)
Linear decomposition model – structural equations
I(Income)
I(Income)
PU
(Proximals - unobs)
P*(Proximals – obs.)
*
*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)
Linear decomposition model – structural equations
I(Income)
I(Income)
PU
(Proximals - unobs)
P*(Proximals – obs.)
*
*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)
Linear decomposition model – structural equations
I(Income)
I(Income)
PU
(Proximals - unobs)
P*(Proximals – obs.)
*
*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)
Linear decomposition model – structural equations
I(Income)
I(Income)
PU
(Proximals - unobs)
P*(Proximals – obs.)
*
*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)
Linear decomposition model – structural equations
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)
P*(Proximals – obs.)
δ = ** + ** + UU + UU
Linear decomposition model – structural equations
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)
P*(Proximals – obs.)
δ = ** + ** + UU + UU
C(Characteristics)
Linear decomposition model – structural equations
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
Household characteristics
Social capital
Educational capital
Emotional capital
Child characteristics
Social capital variables:
Mother’s age at birth
Child’s race
Family structure and size
Social housing
Local neighbourhood
(IMD)
Household characteristics
Social capital
Educational capital
Emotional capital
Child characteristics
Emotional capital variables:
Maternal anxiety/depression
(CCEI)
Maternal locus of control
Mother’s social networks
Parental relationship
Household characteristics
Social capital
Educational capital
Emotional capital
Child characteristics
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
Maternal warmth/ discipline
Health-relatedbehaviours
Parenting behaviours (cognitive)
Childcare/ school quality
Observed proximal factors
Health-related behaviours variables:
Breastfeeding
Maternal smoking
Diet
Materialdeprivation
Maternal warmth/ discipline
Health-relatedbehaviours
Parenting behaviours (cognitive)
Childcare/ school quality
Observed proximal factors
Material deprivation variables:
Car and phone ownership
Noise and crowding
Damp, double-glazing and central
heating
Toys and books
Materialdeprivation
Maternal warmth/ discipline
Health-relatedbehaviours
Parenting behaviours (cognitive)
Childcare/ school quality
Observed proximal factors
Parenting behaviours (cognitive) variables:
Maternal teaching and reading
Paternal reading
Extra-curricular classes
Help with homework
Materialdeprivation
Maternal warmth/ discipline
Health-relatedbehaviours
Parenting behaviours (cognitive)
Childcare/school quality
Observed proximal factors
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)
Child characteristics
(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)
Child characteristics
(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)
Child characteristics
(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)
Child characteristics
(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)
Father’s ed (31.0)
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)
Mother’s locus (14.1)
G’parents ed (12.3)
Social housing (18.1)
Social housing (10.5)
Mother’s
locus (10.6)
Mother’s age (11.6)
CCEI (12.3)
Mother’s locus (16.2)
Social
networks (10.2)
Lone parenthood
(11.6)
Father’s ed (10.9)
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)
MaterialDeprivation (P*)
Maternal warmth/ discipline (P*)
Health-relatedBehaviours (P*)
Parenting behaviours (cognitive) (P*)
Childcare/ school quality (P*)
Path model: Table 8
Unobserved proximal factors (PU)
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)
MaterialDeprivation (P*)
Maternal warmth/ bonding (P*)
Health-relatedBehaviours (P*)
Parenting behaviours (cognitive) (P*)
Childcare/ school quality (P*)
Path model: Table 9
Unobserved proximal factors (PU)
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)
MaterialDeprivation (P*)
Maternal warmth/ bonding (P*)
Health-relatedBehaviours (P*)
Parenting behaviours (cognitive) (P*)
Childcare/ school quality (P*)
Path model: Table 10
Unobserved proximal factors (PU)
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)
MaterialDeprivation (P*)
Maternal warmth/ bonding (P*)
Health-relatedBehaviours (P*)
Parenting behaviours (cognitive) (P*)
Childcare/ school quality (P*)
Path model: Table 11
Unobserved proximal factors (PU)
δ = ** + UU + ** + UU
Table 11: Decomposition of part of income gradient explained by income correlation with cognitive parenting behaviours
Outcome(O)
Income(I)
MaterialDeprivation (P*)
Maternal warmth/ bonding (P*)
Health-relatedBehaviours (P*)
Parenting behaviours (cognitive) (P*)
Childcare/ school quality (P*)
Path model: Table 12
Unobserved proximal factors (PU)
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