Putting Children First: Identifying solutions and taking action to tackle poverty and inequality in Africa. Addis Ababa, Ethiopia, 23-25 October 2017 This three-day international conference aimed to engage policy makers, practitioners and researchers in identifying solutions for fighting child poverty and inequality in Africa, and in inspiring action towards change. The conference offered a platform for bridging divides across sectors, disciplines and policy, practice and research.

1. Mechanisms behind inequality in educational
opportunities:
The case of Ethiopia
Ilze Plavgo
ilze.plavgo@eui.eu
European University Institute, Florence (EUI)
24/10/2017
Conference “Putting Children First: Identifying Solutions and Taking Action to Tackle
Child Poverty and Inequality in Africa”: 23-25 Oct 2017, Addis Ababa, Ethiopia 1

2. Outline of the presentation
• Motivation
• Research question
• Theory
• Data
• Methodology
• Findings
• Conclusions and policy implications

3. Motivation
Rational choice theory:
lifting school fees should
increase enrolment and promote
intergenerational mobility
of education (i.e., reduce
intergenerational inequality)
However:
– Primary school enrolment
rates increasing
BUT
– Primary school success
rates stagnating
AND
– Intergenerational education
inequality rising/
stagnating
Year of fee abolition reform:
2003 in Kenya
1997 in Tanzania, Uganda and Ethiopia
0%
20%
40%
60%
80%
100%
2000-2004 2005-2010 2011-2015
%ofchildrenattendingschool
(age7-12)
Year of survey
Educational expansion: school attendance
Kenya
Tanzania
Uganda
Ethiopia
0.00
0.10
0.20
0.30
0.40
0.50
2000-2004 2005-2010 2011-2015
Coefficientofassociation
Year of survey
Intergenerational education inequality: association of
caretaker-child educational attainment (age 14)
Kenya
Tanzania
Uganda
Ethiopia
Source: Own calculations based on DHS data

4. Research questions
Mechanisms behind inequality in primary school progression:
• Does primary school progression differ by socioeconomic status (SES)?
Is this association the same for urban and rural areas?
• Do chances to successfully progress in primary school vary by level of
cognitive ability at primary school starting age ?
• Does level of cognitive ability differ by SES?
(primary effects of SES)
• Do chances to successfully progress in primary school vary by families’ SES,
net of children’s cognitive ability ?
(secondary effects, compensatory effects of SES)

5. Raymond Boudon (1974): Theory of primary and secondary effects of social origin
Parental background seen as the main determinant of inequality in educational opportunities because of two
mechanisms: (1) family conditions affect children’s cognitive ability and scholastic achievement (primary effects), and
(2) families are the main agents making choices about children’s school attendance and continuation (secondary effects).
J. Goldthorpe (2007); Fabrizio Bernardi (2014): Compensatory advantage theory
Educational choices made by better-off families are less sensitive to children’s cognitive ability and scholastic
achievement compared to worse-off families. Main reasons:
• Preventing downward intergenerational social mobility
• Disposing more resources to cope with such prior disadvantageous events as low cognitive ability & health issues
Theory
Figure 1: Causal mechanism describing primary and secondary effects of social origin

6. Data
• Young Lives longitudinal survey data
• Ethiopia, younger cohort born in 2000
• Data collected in 2002, 2006, 2009, and 2013, when children of younger cohort were of
age 1, 4/5, 7/8, and 11/12.
Main outcome of interest:
Chances to successfully progress in primary school over 4 years (between age 7/8 and 11/12)
 Sample limited to children aged 7/8 enrolled in school (77%), analysing
primary school progression of these same children 4 years later (when aged 11/12)
School history for children between age 7/8 (survey: 2009) and age 11/12 (survey: 2013)
Total Rural Urban
Freq. Percent Freq. Percent Freq. Percent
Enrolled (at age 7/8 & 11/12) 1328 73 690 65 638 86
Drop-outs (enrolled at age 7/8, not at 11/12) 69 4 60 6 9 1
Latecomers (enrolled at 11/12 but not at 7/8) 382 21 290 27 92 12
Never enrolled 29 2 25 2 4 1
Total 1808 100 1065 100 743 100

7. Variables
Dependent variable: success in primary school progression; Independent variables: SES
Success: Enrolled at age 7/8 and completed 3+ grades by age 11/12
Total Rural Urban
Freq. Percent Freq. Percent Freq. Percent
Failure (0-2 grades or dropped out) 280 20 222 30 58 9
Success (3+ grades) 1117 80 528 70 589 91
Total (excl. Latecomers + Never enrolled) 1397 100 750 100 647 100
Excluded: Latecomers + Never enrolled 411 23 315 30 96 13
Total 1808 100 1065 100 743 100
Economic capital: Household wealth (quartiles)
Total Rural Urban
Freq. Percent Freq. Percent Freq. Percent
1 Poorest 449 25 416 39 33 4
2 Poorer 459 25 361 34 98 13
3 Wealthier 455 25 226 21 229 31
4 Wealthiest 445 25 62 6 383 52
Total 1808 100 1065 100 743 100
Educational capital: Caretaker's education (in years)
Total Rural Urban
Freq. Percent Freq. Percent Freq. Percent
0 years 806 45 609 57 197 27
1-8 years 808 45 437 41 371 50
9-14 years 194 11 19 2 175 24
Total 1808 100 1065 100 743 100

8. 1. Descriptive analysis studying differences in primary school success rates by socioeconomic
status (SES) and the level of cognitive ability
2. Multivariate analysis studying the effect of primary and secondary effects of social origin on
school success/failure
Multivariate OLS probability model to estimate the effect of social origin on school progression:
𝑃 𝑅2013 = 𝛽0 + 𝛽1 𝑆𝑂2009 + 𝛽 𝑥 𝑋 + 𝜀 (1)
An additive linear OLS probability model to estimate the primary effects of social origin:
𝑃 𝑅2013 = 𝛽0 + 𝛽1 𝑆𝑂2009 + 𝛽2 𝐴2009 + 𝛽 𝑥 𝑋 + 𝜀 (2)
where 𝐴2009 is ability test z-score at age 7-8 (year 2009).
3. Multivariate analysis with an interaction term studying compensatory effects of social origin
A linear OLS probability model with an interaction term:
𝑃 𝑅2013 = 𝛽0 + 𝛽1 𝑆𝑂2009 + 𝛽2 𝐴2009 + 𝛽3 𝑆𝑂2009 × 𝐴2009 + 𝛽 𝑥 𝑋 + 𝜀 (3)
where 𝑆𝑂2009 × 𝐴2009 is an interaction term between prior cognitive ability level and social origin
Methodology

9. Does primary school progression
differ by SES?
Note: Only children who were in school at age 7/8
Own calculations; Source: Young Lives Ethiopia data. Obs. 1,397

10. Is the association between primary
school progression and SES the
same for urban and rural areas?
Own calculations; Source: Young Lives Ethiopia data. Obs. 1,397 (Urban N=647; Rural N=750)

11. Does cognitive ability differ by SES?
26
42
26
25
9
33
23
5
25
29
33
23
15
29
25
8
25
25
26
26
24
25
25
26
24
5
15
26
52
13
27
61
0 20 40 60 80 100
Total
Poorest
Poorer
Wealthier
Wealthiest
0 years
1-8 years
9-14 years
TotalWealth
Caretaker's
education
Cognitive ability distribution by family’s SES at age 7/8
Lowest
Mid-low
Mid-high
Highest

12. Does cognitive
ability differ by SES?
Does this differ by
area of residence?
Primary effects

13. Does primary school progression
differ by cognitive ability?
 Chances to successfully progress in primary school vary by level of
cognitive ability at primary school starting age

14. Does association between school progression
and ability differ by SES & area of residence?
Are there compensatory effects?
Association differs by SES, but not throughout the cognitive ability distribution
Chances to successfully progress in primary school are high for children of all SES if cognitive ability is high
Implication: Cognitive ability matters, also among children from poor socioeconomic backgrounds
In urban areas, chances to progress in school are high for children of high SES also when ability is low
Implication: High SES can compensate for low cognitive ability
Secondary effects Secondary effects
Compensatory effects

15. In Urban areas, differences substantial and statistically significant. Association with cognitive ability is
weaker for children from wealthier families (compensatory effects in urban areas!)
Does association between school progression
and ability differ by SES & area of residence?
Are there compensatory effects?

16. Primary and secondary effects of SES
on successful school progression
URBAN Economic capital
M 1
Wealth quartiles at age 7-8: 2nd
(ref. 1st
) 0.13
Wealth quartiles at age 7-8: 3rd
(ref. 1st
) 0.21***
Wealth quartiles at age 7-8: 4th (ref. 1st
) 0.23***
Cognitive ability PPVT test score, age 7-8 (std.)
Child's gender: boy (ref. girl) -0.01
Child is the oldest (no other child aged 13-17 in hh)
0.06***
Number of children aged 0-5 in household -0.04**
Number of children aged 6-12 in household -0.03**
Caretakers' educ: 1-8 years; ref.. 0 years
Caretakers' educ: 9-14 years; ref. 0 years
Constant 0.73***
Observations 637
R-squared 0.06

17. Primary and secondary effects of SES
on successful school progression
URBAN Economic capital
M 1 M 2
Wealth quartiles at age 7-8: 2nd
(ref. 1st
) 0.13 0.11
Wealth quartiles at age 7-8: 3rd
(ref. 1st
) 0.21*** 0.18**
Wealth quartiles at age 7-8: 4th (ref. 1st
) 0.23*** 0.18**
Cognitive ability PPVT test score, age 7-8 (std.) 0.04***
Child's gender: boy (ref. girl) -0.01 -0.02
Child is the oldest (no other child aged 13-17 in hh)
0.06*** 0.05**
Number of children aged 0-5 in household -0.04** -0.03
Number of children aged 6-12 in household -0.03** -0.02*
Caretakers' educ: 1-8 years; ref.. 0 years
Caretakers' educ: 9-14 years; ref. 0 years
Constant 0.73*** 0.74***
Observations 637 637
R-squared 0.06 0.08

18. RURAL Economic capital Educational capital
M 1 M 2 M 1 M 2
Wealth quartiles at age 7-8: 2nd
(ref. 1st
) 0.07* 0.05
Wealth quartiles at age 7-8: 3rd
(ref. 1st
) 0.08* 0.06
Wealth quartiles at age 7-8: 4th (ref. 1st
) 0.03 -0.01
Cognitive ability PPVT test score, age 7-8 (std.) 0.12*** 0.12***
Child's gender: boy (ref. girl) -0.05 -0.05* -0.06* -0.05*
Child is the oldest (no other child aged 13-17 in hh)
0.01 0 0.02 0.01
Number of children aged 0-5 in household -0.02 -0.02 -0.02 -0.02
Number of children aged 6-12 in household -0.02 -0.01 -0.02 -0.01
Caretakers' educ: 1-8 years; ref.. 0 years -0.01 0
Caretakers' educ: 9-14 years; ref. 0 years 0.16 0.09
Constant 0.72*** 0.76*** 0.77*** 0.79***
Observations 760 760 760 760
R-squared 0.01 0.05 0.01 0.05
Primary and secondary effects of SES
on successful school progression

19. Summary
1. For children from the poorest families, only 66% successfully progress in primary school
between age 7/8 and 11/12 (wealthiest: 91%)
2. For children from the lowest quartile of cognitive ability at age 7/8, only 65% successfully
progress in primary school (highest: 96%)
3. Among poorest children, 42% belonged to the lowest and 5% to the highest quartile of
cognitive ability at age 7/8
Among wealthiest, 9% from lowest and 52% from highest quartile of cognitive ability.
 Inequality already in the initial stage when entering primary school (age 7/8)
4. In urban areas:
Differences in cognitive ability at primary school starting age only part of the story:
Life chances differ by SES.
Different coping mechanisms: Compensatory effects for children from better-off families.
Among poor, only children with high cognitive ability succeed to the same extent as
children with average-low cognitive ability but from wealthier families.
5. In rural areas:
Inequality in educational opportunities predominantly a primary effect of SES

20.  Even the most egalitarian education system alone is unlikely to weaken much the impact
of social origin on opportunities
(initial inequality in cognitive ability and differences in costs throughout primary school)
 Class differentials in school preparedness are already manifest when children first enter
the education system, and schools are not well equipped to remedy the problem
 Conditions during early childhood are decisive:
Primary cause of disadvantage in early childhood stems from inadequate cognitive and
behavioural stimulus, linked to lack of financial and educational capital
 Social investment case [A. Hemerijck, 2017] :
equality of opportunity can be achieved by equalizing childhood living conditions by:
– “Stock” policies: Cognitive stimulus through parental education and high-quality pre-school institutions; and
– “Buffer” policies: Reducing child poverty, offsetting opportunity costs for having and schooling children
Policy implications

21. 22
Thank you!

22. 23
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23. 24
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