Presentación de Santiago Cueto en la 59 Conferencia Anual de Comparative and International Education Society (CIES), el 12 de marzo del 2015 en Washington DC, Estados Unidos.

1. Does pre-school improve cognitive abilities among
children with early-life growth faltering? A longitudinal
study for Peru
Santiago Cueto, Juan León, Alejandra Miranda (GRADE), Kirk Dearden (Boston
University), Benjamin Crookston (Brigham Young University) & Jere Behrman
(University of Pennsylvania)
March 2015

2. March, 2015
Introduction
• Many empirical studies have shown negative associations
between low height-for-age (HAZ), and school achievement.
• Empirical findings suggest that schooling (or other formal
educational programs) and nutrition may have independent but
also possibly interactive effects in promoting children.
• In Peru, stunting prevalence has gone down, currently about
18% of children under 5 years of age are stunted (UNICEF,
2011).

3. March, 2015
Types of pre-school in Peru
• For ages three to five years, there are two types of pre-school:
• PRONOEI (Programas no Escolarizados de Educación Inicial) :
– provided in marginal urban and rural area
– non certified teachers
– 3 to 4 days a week of classes
• Jardines:
– Set up in more populated areas
– Teachers are usually certified
– 5 days a week of classes
• Some research on these: Cueto & Diaz, 1999; Diaz, 2006

4. March, 2015
Objectives
• The present study seeks to determine whether there is an interaction
between low HAZ at age one year and attending pre-school from ages
three to five years on abilities by age five (PPVT, receptive vocabulary;
CDA, test on notions of quantity).
• Further, we explore if the type of pre-school is associated with
stunted children’s performance on these tests.
• Hypothesis: children who were stunted at one year of age and
attended Jardines are more likely than children who were stunted at
one year of age and attended PRONOEI to perform well on tests by
age five.

5. March, 2015
Methods
• Young Lives is a longitudinal study which follows 12,000 children in Vietnam,
India, Ethiopia and Peru over 15 years.
• Two cohorts: born around 1994 (older cohort) and 2001 (younger cohort).
This study uses data from the YC in Peru.
• Household and children´s information from 2002, 2006, 2009 and 2013 (two
first rounds included here).
• From the sample of 1963 childrenin R2, we only included the 72.5 percent
who attended either a Jardin or a PRONOEI pre-school or no pre-school.
Mixed cases (i.e. children who attended both) as well as children who
attended other types of childcare programs from ages three to five years
were excluded from the analysis.

6. March, 2015
Threats to validity
• Selection bias: we performed corrections for excluded children.
• Endogeneity: we performed both OLS and Two Stage Least Squares (2SLS)
regression models (instrumental variables).
• Good instruments predict well the endogenous variables (nutritional status,
number of years the child attended a Jardin and number of years the child
attended a PRONOEI) in the model and should have no direct impact on the
main dependent variable (cognitive abilities).

7. March, 2015
Instrumental variables
• For height-for-age z scores
Maternal height
• For years the child attended a Jardin pre-school
Education of the household head (proportion of household heads that had
completed at least secondary schooling in the district where the Young Lives
child lived; data from National Census of 2007).
• For years the child attended a PRONOEI pre-school
Ratio of PRONOEI pre-schools over total number of pre-schools in the district
(from the School Census 2006 administered by the Ministry of Education).

8. March, 2015
Results
CDA and PPVT mean scores by nutritional status and years of pre-school attendance
CDA PPVT
Not-
stunted
Stunted Difference
Not-
stunted
Stunted Difference
0 years 7.79 7.48 0.31 21.13 15.09 6.04*
(183) (125) (183) (125)
1 year 8.39 7.82 0.57* 28.44 21.45 6.99*
(349) (130) (349) (130)
2 years 8.74 7.62 1.12* 33.01 21.39 11.62*
(367) (105) (367) (105)
3 years 9.32 8.59 0.73 39.74 30.24 9.50*
(135) (29) (135) (29)
*Differences are statistically significant at 5% according to the t test for independent samples.
Note: Number of children reported in parentheses.
Source: Young Lives Study, Rounds 1 and 2.
Own Elaboration.

9. March, 2015
Results – MCO Model
Effect of attending pre-school and nutritional status on cognitive abilities using OLS,
standardized coefficients (N=1,423)
CDA PPVT
M1 M2 M1 M2
Main effects
HAZ adjusted to age one 0.03 0.03 0.05 * 0.05 **
Years attended JARDIN 0.08 * 0.08 * 0.09 ** 0.08 **
Years attended PRONOEI 0.00 0.00 0.05 + 0.05
Interaction effects
Years attended JARDIN*HAZ adjusted
to age one 0.01 0.05 *
Years attended PRONOEI*HAZ
adjusted to age one 0.01 0.01
R-squared 0.20 0.20 0.51 0.52
**p<0.01, *p<0.05, +p<0.10
Note: Standard errors are adjusted by possible covariance among children living in the same district. All models include as
control variables: child´s age, child´s mother tongue, child´s sex, maternal schooling attainment, mother´s age, place of
residence, and household wealth index. Standard errors were calculated using bootstrapping with 100 replications.

10. March, 2015
Results – 2SLS Model
Effect of attending preschool and nutritional status on cognitive abilities using 2SLS,
standardized coefficients (N=1,423)
CDA PPVT
M1 M2 M1 M2
Main effects
HAZ adjusted by age one 0.17 ** 0.15 * 0.34 ** 0.28 **
Years attended JARDIN 0.21 ** 0.20 ** 0.33 ** 0.25 **
Years attended PRONOEI -0.04 -0.04 + 0.00 0.00
Interaction effects
Years attended JARDIN*HAZ adjusted by
age one
0.11 0.46 *
Years attended PRONOEI*HAZ adjusted
by age one
-0.13 -0.43 **
R-squared 0.18 0.18 0.44 0.45
**p<0.01, *p<0.05, +p<0.10
Note: Standard errors are adjusted by possible covariance among children living in the same district. All models include as control
variables: child´s age, child´s mother tongue, child´s sex, maternal education, mother´s age, place of residence, and wealth index.
Standard errors were calculated using bootstrapping with 100 replicates.

11. March, 2015
Discussion
• Preschool may be crucial for achievement, but we need to know more
about their quality.
• Targeting children at risk of poor achievement (e.g. stunted) could be
a priority to consider.
• Comprehensive interventions (i.e. health and nutrition, plus work with
their parents) might also be a priority, even from an early age.
• What are the interactive effects on other aspects of children´s
development (e.g. motor, social, emotional)?
• What interactions may we find between stunting at an early age,
catching up and quality of primary school?

12. March, 2015
Results
Correlation among cognitive measures and main independent variables (N=1,423)
PPVT score CDA score
HAZ adjusted
to age one
CDA score
0.56 - -
(0.00)
HAZ adjusted to age one
0.32 0.19 -
(0.00) (0.00)
Years attending a JARDIN
0.37 0.25 0.22
(0.00) (0.00) (0.00)
Years attending a PRONOEI
-0.11 -0.10 -0.06
(0.00) (0.00) (0.02)
Note: P-values in parenthesis
Source: Young Lives Study, Rounds 2 and 3
Own Elaboration.