International Food Policy Research Institute (IFPRI) and Ethiopian Development Research Institute (EDRI) in collaboration with Ethiopian Economics Association (EEA). Eleventh International Conference on Ethiopian Economy. July 18-20, 2013

1. Effect of Climate Shock on Cognitive Development of
Children in Ethiopia
Tilahun Asmare, WVE
and
Guush Berhane, ESSP, IFPRI
Addis Ababa, Ethiopia
1

2. PRESENTATION OUTLINE
Introduction
 Problem statement
 Objective
Research Methodology
 Data Source
 Conceptual framework
 Model Specification
Results and Discussions
 Descriptive Analysis
 Econometric Analysis
Conclusion and recommendation
 Conclusion
 recommendation 2

3. INTRODUCTION
• Climate-related shock, drought and flood threaten the
livelihood of nations specially developing countries that
have low coping mechanism and resilience capacity.
• Ethiopia faced by adverse climate shock (e.g drought) that
leads to a loss of household income, a reduction in
consumption, and/or a loss of productive asset (Darcon,
2005).
• Drought often defined as a continuous interval of time during
which actual moisture supply at a given place is consistently less
than normally expected (Roy and Hirway, 2007).
• Drought is covariant and slow onset shock
3

4. INTRODUCTION
 The short term impact of drought
 loss of food production and non-food production,
 loss of employment;
 shortage of water, fodder and fuel wood;
 indebtedness, migration etc
 long-term impact
 Low agriculture growth
 stunting,
 low cognitive development of children that it turn
negatively affects the development of the country as it
lost its children intelligence.
4

5. INTRODUCTION
 Cognitive development is the construction of thought
processes, including remembering, problem solving, and
decision making, from childhood through adolescent and
adulthood (cengage 2005).
 Many researchers used Peabody picture vocabulary test
(PPVT) as measurement of cognitive of children (desai
(1989), Bau (1999,McCullah &Joshi (2002), Duc (2009),
Nair (2009).
5

6. STATEMENT OF THE PROBLEM
‘notwithstanding major investments in improving the
numbers and the qualifications of teachers and the
availability of equipment, student achievement has not
sufficiently improved. (MOE, 2010).
 The Evolution of scores obtained in NLA shows the
composite score of grade 4 decreased to 40.9% in
2007/08 from its result 2000/01 that was 47.9% and the
composite score of grade 8 decreased from 41.1% of
2007/08 to 35.6% in 2000/01 (NOE, 2008).
6

7. STATEMENT OF THE PROBLEM:
 Though drought is the most frequent challenge of the country, the
national ESDP do not include it as a factor that determinants of
children academic achievement.
 Most researches undertake on cognitive development of children are
mainly focused on students/individual factors, household/ family
factors and school factors and give little or no attention to weather
related shocks.
 Most research is focused on the impact of idiosyncratic shocks (such
as child labor) on children educational outcomes (test scores)
(Woldehanna, 2012.
 As far as my knowledge there is no any related researches
undertaken in the country that can shows the impact of weather
related shock such as drought on PPVT test score
7

8. OBJECTIVES OF THE STUDY
The General objective of this study is to examine the effect of
climate related drought shocks on children cognitive
development and school outcomes. The specific objectives are:
 To investigate the impact of climate related shock such as
drought exposure on cognitive ability of children.
 To examine the impact of drought on other academic
achievement measurements such as reading and writing skills.
 To measure the impact of productive safety net (PSNP)
interventions on cognitive development of children aged 12
and 15.
8

9. RESEARCH METHODOLOGY
Data source
 Secondary data (Young Lives longitudinal dataset
 Second and third round old cohort
 Used purposive sampling strategy in selecting sentinel sites and a
random strategy used in the household selection within each sentinel
site (Woldehanna , 2011).
 The sampling was undertaken in five regions (namely Amhara, Addis
Ababa, Tigray, Oromia and SNNP
 3 to 5 woredas were selected in each region, gives total 20 woredas.
 50 old cohort children (of age 7.5 to 8.5 years) were selected randomly
in each sentinel site.
9

10. RESEARCH METHODOLOGY
 Children test score broadly depend on their initial skill endowment,
income and Time (Millett & Shah, 2012) .
 Initial skill endowments include biological or initial characteristics of
children such as sex, birth order, race, birth weight etc.
 HH income has direct effect, determine the amount of investment on
cognitive development children goods and services such as books that
increases students test results up on consumption.
 To increase household income the household needs many inputs such labor
that can be own or hired agricultural labor.
 The decision to use either of the two sources depends on the wage rate.
 When the wage is high households may use own labor including child labor that
in turn reduce children test score. 10

11. RESEARCH METHODOLOGY
 Children time consumption: hours spent on study or school
time positively affects children test score.
 The biological effect of drought on cognitive development is
very straightforward.
 Drought exposed children (either prenatal or postnatal exposure) are
simply lower ability, so conditional on the same level of schooling, they
still score lower on achievement tests because they attend less
efficiently (Bryce & Manisha , 2012).
 Drought also negatively affects the income of household.
 Hence any food or cash support to the drought affected
households helps to reduce the negative impact of drought.
11

12. RESEARCH METHODOLOGY

12

13. RESEARCH METHODOLOGY
We used Panel data that have following advantages over pooled
data (Baltagi 2004)
(1) account for heterogeneity across individual units which is assumed
away in pooled data
(2) deal with time-invariant omitted variables as we can and in pooled data
(3) are less likely to have problems with autocorrelation and
multicollinearity as time series data
 There are basically two types of panel models, the fixed effects
and the random effects model.
 They differ by their assumptions how the heterogeneity is
captured and estimation techniques.
13

14. RESEARCH METHODOLOGY
 The fixed effect model assumes that individual
heterogeneity is captured by the intercept term.
 The random effects model assume in some sense that the
individual effects are captured by the intercept and a
random component.
 This random component is not associated with the
regresses on the right hand side and part of the error term.
14

15. RESEARCH METHODOLOGY
 The critical difference between Fixed Effect and Random Effect is that FE
allowed for correlation between the unobserved individual specific effect
and the explanatory variables whereas RE requires these to be
uncorrelated.
 Having this, we run a basic fixed effect regression and random effect
regression of independent variables cognitive achievement outcome of
interest (standard score in PPVT test).
 To choose from FE and RE we used Hausman
 In this case, Random effects (RE) is preferred under the null hypothesis due
to higher efficiency, while under the alternative fixed effects (FE) is at least
consistent and thus preferred.
 Using the test of Hausman test we rejected the null hypothesis and
accepted the alternative hypothesis that is fixed effect model preferred.
15

16. DATA AND DESCRIPTIVE EXPLANATIONS
Variable Obs Mean Std dv Min Max
Standard PPVT test core 1648 91.17658 26.38066 40 160
Dummy for drought affected 1663 .3968731 .4893964 0 1
Dummy for PSNP participation 1663 .439567 .4964837 0 1
Rural PSNP participating 1663 .3505713 .4772924 0 1
rural drought affected PSNP beneficiaries 1662 .2178099 .4128817 0 1
dummy for Child health worse 1660 .086747 .2815488 0 1
Hours spent on paid work 1659 .2932188 1.339566 0 11
Dummy for missed more than a week 1511 .1250827 .3309222 0 1
Dummy for land ownership 1664 .9206731 .2703296 0 1
Hours spent on study 1659 1.794039 1.158055 0 8
Grade completed 1504 4.746676 1.917542 0 11
School distance in minute 1505 25.45116 19.5518 0 130
dummy for credit access 1663 .2958509 .4565616 0 1
Dummy household condition poor 1664 .6790865 .4669679 0 1
16

17. RESULTS AND DISCUSSION
Drought shock and PPVT test score by region and year
Source: Author’s calculations based on Young Lives data
Standard PPVT score Amhara Oromia SNNP Tigray Total
not affected
round 2 83 96 88 96 90
round 3 96 99 104 115 101
Change rate (%) 15.66 3.13 18.18 19.79 12.2
affected
round 2 76 76 76 88 80
round 3 79 82 84 98 88
Change rate (%) 3.95 7.89 10.53 11.36 10
Gap between affected and
non-affected
round 2 7 20 12 8 10
round 3 17 17 20 17 13
17

18. ‹#›

19. RESULT AND DISCUSSION
Drought enrolment and grade completed
Source: Author’s calculations based on Young Lives data
outcomes
Full
sample
(R2)
Non
Affected
(R2)
Affected
(R2)
Full
sample
(R3)
non
Affected
(R3)
Affected
(R3)
Enrollment (%) 97.37 97.30 97.50 89.60 92.16 85
grade completed
(progress)
4.25 4.3 3.54 5.74 5.7 5.15
school Attendance 5.32 5.24 5.52 10.64 9.53 14.09
Taken grade 8 21% 27% 11%
19

20. RESULT AND DISCUSSION
old cohort children time use on typical day by drought shock
Source: Author’s calculations based on Young Lives data
on a typical days
hours spent on
Round 2 Round 3
Full
sample
non
Affected
Affected
Full
sample
non
Affected
Affected
caring for others 0.65 0.65 0.66 0.7 0.75 0.74
Domestic work 2.3 2.34 2.2 2.7 2.67 2.75
Farming activity 1.69 1.42 2.17 1.57 1.31 1.88
Paying work 0.15 0.11 0.25 0.42 0.36 0.51
School 5.15 5.27 4.93 5.52 5.31 5.05
Study outside
school
1.72 1.81 1.56 1.86 2 1.7
Sleep 9.04 8.91 9.26 8.65 8.56 8.77
Leisure 2.71 2.91 2.33 2.81 3.02 2.52
child labor 4.79 4.52 5.28 5.39 5.09 5.88
20

21. RESULT AND DISCUSSION
old cohort children reading and writing skill by drought incidence
Source: Author’s calculations based on Young Lives data
9% 12% 12%
67%
9%
29%
62%
14%
19% 19%
47%
16%
39%
45%
0%
10%
20%
30%
40%
50%
60%
70%
80%
can't read reads
letters
reads
words
reads
sentence
No with
difficulty
without
difficult
Reading level Writing skills
not Affected
by drought
Affected by
drought
21

22. RESULT AND DISCUSSION
 Households affected by drought and PSNP participation
Source: Author’s calculations based on Young Lives data
Region
Affected
PSNP
participate
d R2)
affected
but
supported
(R2)
cohort
mean
PPVT
(R2)
Affected
PSNP
participat
ed (R3)
affected
but
supporte
d (R3)
cohort
mean
PPVT
(R3)
response
capacity
growth
Amhara 77% 78% 80.57 20% 72% 88.31 -7.60%
Oromia 70% 73% 88.29 53% 97% 99.33 32.60%
SNNP 61% 73% 85.69 7% 86% 95.54 18.70%
Tigray 93% 93% 91.82 69% 97% 102.95 5.00%
Total 78% 81% 91.29 40% 89% 102.95 8.90%
22

23. RESULT AND DISCUSSION
 During round two more than 78 percent of the
households was PSNP participants but reduced to 40
percent during round three that partly may be due
graduation.
 drought responding capacity almost fifty percent
reduction.
 other food/cash support from small projects (may be
as emergency relief programs) increased as a result
percentage of drought affected but supported
households increased in round three.
23

24. RESULT AND DISCUSSION
 Economic Estimation
 PPVT test estimation
Dependent variable standard PPVT test score Fe model Re model
Dummy for drought affected -6.732429*** -8.048916***
-2.92 -4.93
dummy for Child health worse -4.658618 -5.031659**
-1.53 -2.31
Hours spent on paid work -2.010522* -2.463492***
-1.75 -3.26
rural drought affected PSNP beneficiaries 6.428558** 3.934902**
2.28 2.02
Dummy for missed more than a week -3.907601 -2.166414
-1.59 -1.21
Dummy for landownership 3.887701 -11.25698***
0.88 -4.88
Hours spent on study per day 2.248315 2.562031***
2.74 4.36
Grade completed 3.503539*** 4.636148***
3.91 12.86
School distance in minute -0.0535196*** -0.0553434*
-1.04 -1.74
24

25. RESULT AND DISCUSSION
 Economic Estimation
 PPVT test estimation
Dependent variable standard PPVT test score Fe model Re model
dummy for credit access 2.29007 0.1541255
1.31 0.12
Dummy household condition poor -4.268674*** -3.525394***
-2.22 -2.76
R-sq: within 0.137 0.1193
between 0.2468 0.3153
overall 0.1974 0.2425
Number of obs 1484 1484
Number of groups 812 812
F test that all u_i=0 1.71
sigma_u 19.439141 10.434154
sigma_e 19.718549 19.718549
Rho 0.49286489 0.21875258
Hausman test of FE vs. RE; 2(17)=28.81, p=0.0024
Robust z statistics and t value in parentheses for RE and Fe respectively
* significant at 10%; ** significant at 5%; *** significant at 1% 25

26. RESULTS AND DISCUSSION
 We found that drought shock affected cognitive
development of children negatively. (Similar to the findings
of Aderman, 2006 and Mill and Shah (2012)
 The PPVT test score of old cohort children affected by
drought shock reduced by almost 7 points than that of old
cohort children not affected by drought shock.
26

27. RESULTS AND DISCUSSION
 We found that child health worse has negative effect on PPVT
score similar to the findings of Spernak 2006
 hours spent on paid work, land ownership,
 hours spent on study and grade completion have positive effect
test score similar to the findings of Ray and Lancaster, 2003
 Meanwhile old cohort children from poor household registered
lower results than that of non-drought affected old cohort children.
 The impact of drought dummy for missed class more than a week
with PPVT test score is negative thought it is not statistically
significant.
27

28. RESULTS AND DISCUSSION
 We found that drought affected rural children whose household
participated in the productive safety nets program scores 6 points higher
than of non participant drought affected rural children .
 We found that child health hours spent on paid work, land ownership,
hours spent on study, grade completion have a significant and positive
relationship with standard PPVT test score.
 Meanwhile old cohort children from poor household registered lower
results than that of non-drought affected old cohort children.
 The impact of drought dummy for missed class more than a week with
PPVT test score is negative thought it is not statistically significant.
 dummy credit access has positive relationship children.
28

29. CONCLUSIONS AND RECOMMENDATIONS
Conclusions
 Drought shock has a negative impact on children PPVT test score. Old
cohort children affected by drought scores PPVT test score 7 point lower
than those not affected.
 Household condition poor and school distance in minutes negatively
affect PPVT score
 Drought also negatively affects school enrollment , grade completion
school attendance, hours spent on study outside school.
 Children who are exposed to drought shock score significantly worse in
reading and writing skills.
29

30. CONCLUSIONS AND RECOMMENDATIONS
Conclusions
 productive safety net programme participation has a positive and
significant impact on drought affected children cognitive development.
 Moreover productive safety improves children cognitive development by
improving household economic condition. So drought mitigation
measures such as food aid reverses help to improve cognitive
development of children affected by the drought.
30

31. CONCLUSIONS AND RECOMMENDATIONS
Recommendations
 Strengthening prevention and mitigation measures (DRR)
 the identification of efficient agricultural management practices, and
provision of timely advice to farmers
 improving drought responding capacity/ emergency response (especially
Amhara region)
 as strengthen their early warning systems such as Short message
system (SMS) throughout all woredas of the region.
 Moreover microfinance institution can also create access for credit
service to the drought affected households.
 National Learning Assessment has to include as factor that affects
children academic achievement.
31

32. Thank you!
32