1. Association Between Parental Resources and Child Development in Peru
From  Parent to Child
Association Between Parental Resources and Child Development in Peru
Milo Vandemoortele
DSA Conference
November, 2013

2. Overarching Research Question
How and to what extent are parental resources associated with child development? A case study of Peru

3. Why do research on this topic?
A “conservative estimate that more than 200 million children under 5 years fail to reach their potential in cognitive development because of poverty…” and its attendant problems.1
Long term consequences2
Poor children are more likely to remain poor
Limited research on the topic
1 Grantham-McGregor et al., 2007:60; 2 Walker et al., 2011

4. Research Questions
How and to what extent are parental resources associated with child development? Particularly focusing on:
Parental resources at birth and each subsequent stages of life
Changes in parental resources
Differential effect of parental wealth versus parental expenditure
Shape of the association – is it linear?
Does the effect of parental resources differ for poorer children versus wealthier children

5. Analytical Framework
Source: Adapted from Haveman and Wolfe (1995), Grantham-McGregor et al. (2007)

6. Data: Young Lives
Four countries: Ethiopia, Andhra Pradesh (India), Peru and Vietnam
Total sample of 12,000 children followed over a period of 15 years
Sample size used here, younger cohort in Peru ~2000 children born in 2001/02
Three survey rounds (birth, 5/6 yrs and 7/8 yrs)
Extremely low attrition rates (7% in Peru)
Limitations

7. Analytic Approach Models
Challenge: Omitted variable bias and endogeniety leads to biased estimates
Several approaches available to address this
Latent Trait Modeling to recalculate the wealth index
Models
1) OLS with Community Fixed Effects
2) Spline with Community Fixed Effects
3) Child Level Fixed Effects (First-Differences)

8. Control Variables Child specific: Household level: gender
race/ethnicity
birth weight
chronic health problems
stunting
age
subjective socio-economic status (at age 7/8 yrs)
Household level:
siblings
caregivers level of education
proxies for household non-cognitive environment:
maternal depression
caregiver’s educational aspirations of child
negative child rearing experience
network/social capital
main language spoken at home

9. Model 1: OLS with Community Fixed Effects
𝑆 𝑖𝑗,𝑡 𝐶 = 𝑎 0 + 𝑛=0 2 𝛽 𝑛 log(𝑌) 𝑖𝑗,𝑡−𝑛 + 𝑛=0 2 𝜏 𝑛 W 𝑖𝑗,𝑡−𝑛 + 𝑘=1 𝐾 𝜆 𝑘 𝑥 𝑖𝑗𝑡 𝑘 + 𝛼 𝑗 + 𝑙=1 𝐿 𝛾 𝑙 𝑦 𝑖𝑗𝑡 𝑙 + 𝜇 𝑖𝑗,𝑡 1
Where:
𝑆 𝑖𝑗,𝑡 𝐶 is the cognitive outcome observed in Round 𝑡 for child 𝑖 in community 𝑗
log(𝑌) 𝑖𝑗,𝑡−𝑛 is expenditure (logged) in Round 𝑡−𝑛 (𝑛=0,2)
W 𝑖𝑗,𝑡−𝑛 is household wealth
𝑥 𝑖𝑗𝑡 𝑘 are observed child-level factors, where there are 𝐾 number of variables (𝑘=1,𝐾)
𝛼 𝑗 represents the community fixed effects.
𝑦 𝑖𝑗𝑡 𝑙 are the unobserved exogenous factors affecting child development, where L is the number of variables (𝑙=1, 𝐿).
𝜇 𝑖𝑗𝑡 1 captures measurement error 

10. Model 2: Spline with Community FE
Are there non-linear effects?
A prototypical model is represented as follows:
𝑆 𝑖𝑗𝑡 𝐶 = 𝑎 0 + 𝑛=0 2 𝑠(log(𝑌) 𝑖𝑗,𝑡−𝑛 ) + 𝑛=0 2 𝑠( W 𝑖𝑗,𝑡−𝑛 ) + 𝑘=1 𝐾 𝜆 𝑘 𝑥 𝑖𝑗𝑡 𝑘 + 𝛼 𝑗 + 𝑙=1 𝐿 𝛾 𝑙 𝑦 𝑖𝑗𝑡 𝑙 + 𝜇 𝑖𝑗𝑡 1
The only difference between Equation 2 and Equation 1 is the spline function around the household resources variables 𝑠(log(𝑌) 𝑖𝑗,𝑡−𝑛 ) and 𝑠( W 𝑖𝑗,𝑡−𝑛 )

11. Model 3: First-difference model
Controls for differences between households and communities
Allows to examine the effect of changes in parental resources on child development
𝑆 𝑖,𝑡+1 𝐶 − 𝑆 𝑖𝑡 𝐶 = 𝑎 0 + 𝑛=0 2 𝛽 𝑛 log 𝑌 𝑖,𝑡+1−𝑛 − log 𝑌 𝑖,𝑡−𝑛 ) + 𝑛=0 2 𝜏 𝑛 W 𝑖,𝑡+1−𝑛 − W 𝑖,𝑡−𝑛 𝛽 3 log 𝑌 𝑖,0 + 𝜏 3 𝑊 𝑖,0 + 𝛽 4 𝑛=0 2 log 𝑌 𝑖,0 ∗ log 𝑌 𝑖,𝑡+1−𝑛 − log 𝑌 𝑖,𝑡−𝑛 𝜏 4 𝑛=0 2 𝑊 𝑖,0 ∗ W 𝑖,𝑡+1−𝑛 − W 𝑖,𝑡−𝑛 𝛽 5 𝑇 𝑖 + (𝜇 𝑖,𝑡+1 1 −𝜇 𝑖,𝑡 1 )
𝑆 𝑖𝑡 𝐶 − 𝑆 𝑖,𝑡−1 𝐶 : changes in the developmental outcome between age 5/6 yrs and 7/8 yrs

12. Results: OLS with Community FE (1)
Consumption appears to have a positive and contemporaneous effect. Wealth too, but also a lagged effect.

13. Results: OLS with Community FE (2)
Wealth is a better predictor of children’s math and reading skills at 7/8 yrs old than consumption.

14. Results: Spline with Community FE (1)
The effect of wealth on vocabulary scores at age 5/6 yrs is non-linear, whereas the effect of expenditure is linear.
This is differs with math scores at 5/6 yrs, where the effect of wealth and expenditure in the same time period are broadly linear.

15. Results: Spline and Community FE (3)
With maths and reading scores at 7/8 yrs, wealth in the previous period (5/6 yrs) appears to have a nonlinear effect.

16. Results: First-Differences (1)
Changes in expenditure between 5/6 and 7/8 years appear to benefit the poorest children more than the better off children.
Vocabulary
Math

17. Summary
Consumption appears to have a contemporaneous effect, while wealth has both a contemporaneous and lagged effect on vocabulary test scores.
Data on parental wealth are a better predictor of children’s maths and reading skills at 7/8 yrs old than consumption data.
The assumption that wealth is linearly associated with cognitive development does not hold.
A change in wealth appears to have a lagged effect, while changes in expenditure an immediate effect on both math and vocabulary test scores.
This effect appears to benefit poorer children more than better off children.

18. Thank you! m.vandmoortele@lse.ac.uk

19. Mechanisms Goods inputs and under-nutrition
Stunting - negative and significant effect generally
Long term health problems – no significant effect
Birth weight – no significant effect
Time inputs / under-stimulation
Caregiver’s depression – positive with reading at age 7/8 yrs
Parental aspirations – positive and significance with vocabulary at age 7/8 yrs
Demographic
Gender - significant differences in math and vocabulary at age 7/8 yrs, but small
SES
Subjective SES – small, positive and significant with reading at age 7/8 yrs only

20. Results: First-Differences (2)
Changes in wealth between birth and 5/6 yrs appears to benefit poorer children more than wealthier children in both maths and vocabulary scores.
Math
Vocabulary