PSNP Presentation 2014

1. Guush Berhane, IFPRI
John Hoddinott, IFPRI
Neha Kumar, IFPRI
May 13, 2014
Page 1
The Productive Safety Net Programme and the
nutritional status of pre-school children in Ethiopia:
Preliminary Results

2. • Ethiopia has high levels of chronic undernutrition. DHS (2011)
– 44% of children under five are stunted (Have a height for age z (HAZ) score < -2)
• Why does this matter?
– Intrinsic. Chronic undernutrition is a marker of high levels of deprivation. Healthy, well-
nourished children is an important development objective in itself.
– Instrumental. Children who are undernourished are less likely complete school, have poorer
cognitive skills in adulthood and are less economically productive. Evidence from other
countries shows that a one SD reduction in HAZ increases the likelihood of being poor in
adulthood by 10 percentage points
If you care about economic growth and poverty reduction in Ethiopia, you should care deeply
about reducing undernutrition
Page 2
Introduction and Context

3. • Ethiopia operates one of the largest social protection programmes in Africa: The
Productive Safety Net Programme (PSNP).
• The PSNP reaches more than 7 million people in drought-prone woredas in Afar,
Amhara, Oromiya, SNNP, Somale and Tigray
• The objective of the PSNP is to stabilize household asset levels (thereby preventing
recurrent shocks from forcing households into destitution) and improve household food
security
• The PSNP:
– Is well targeted
– Delivers significant resources (cash and food) to beneficiaries
– Reduces the food gap
– Stabilizes assets
Page 3
Introduction and Context

4. • The PSNP is “loosely meshed” with direct efforts to reduce undernutrition in rural
Ethiopia
• Health Extension Workers should be part of PSNP’s administrative structures that
oversee beneficiary selection and that hear appeals
• PSNP woredas are co-located in areas where the Community Based Nutrition Program
has been rolled out. In our data:
Page 4
Introduction and Context
Year CBN established Percent children <5 in sample
2008 13
2009 29
2010 20
2011 12
2012 26

5. • This presentation discusses results that are:
PRELIMINARY
PRELIMINARY
• We use data collected as part of the PSNP evaluation in 2008, 2010 and 2012
– Participation in the PSNP
– Anthropometry (heights and weights), ~7,500 observations across three years
– More limited data on child diet, 6-24m, interaction with HEW and community health volunteers,
knowledge of good nutrition practices
– Household characteristics affecting both PSNP participation and pre-school nutrition
• We explore preliminary associations between PSNP participation, duration of operation
of CBN and anthropometric outcomes, mindful that reductions in chronic
undernutrition are not a specific objective of the PSNP
• We discuss implications of these preliminary results
Page 5
Introduction and Context

6. Page 6
Trends in undernutrition
(children 6-59m)
HAZ Stunting (%)
2008 2010 2012 2008 2010 2012
Tigray -2.18 -2.29 -2.17 58.6 60.7 57.8
Amhara -1.79 -1.86 -1.92 47.5 50.3 49.2
Amhara HVFB -1.94 -2.05 -1.92 53.6 55.0 51.9
Oromiya -1.71 -1.80 -1.53 46.1 47.9 42.8
SNNP -1.94 -1.69 -1.76 50.2 46.2 47.3
Total -1.90 -1.91 -1.81 51.1 51.4 48.9
Sample size 3041 2845 2482

7. Page 7
Trends in undernutrition by beneficiary status
(children 6-59m)
HAZ
2008 2010 2012
HH is PSNP beneficiary -1.98 -2.04 -1.88
HH is non-beneficiary -1.85 -1.79 -1.78

8. • Look at association between being a PSNP participant and anthropometric outcomes
controlling for:
– Child characteristics (age, sex)
– Caregiver characteristics (age, schooling)
– Characteristics of the household head (sex, age)
– Wealth (livestock holdings)
– Housing quality (materials used to construct roof, walls)
– Access to towns
– When CBN began in woreda
– Region
• In each survey year, we find no association between being a PSNP participant and:
– HAZ
– Stunting
– WHZ
– Wasting
Page 8
Regression analysis

9. • Results do not change when we do the following robustness checks :
– Including or dropping different sets of control variables
– Changing variables (eg maternal age v log maternal age)
– Running estimates separately by region
– Restricting age ranges (eg 6-24m, 12-24m etc)
– Measuring PSNP participation (eg Public Works beneficiary, duration of participation)
• There are a number of extensions to be considered (which is why results are
preliminary)
– Improved accounting of selection into PSNP (eg thru use of matching methods)
– Assess competing effects of PSNP transfers (which might ↑HAZ) and work effort (which
might ↓HAZ)
• But there are also reasons to expect that these extensions will not change these basic
results
Page 9
Regression analysis

10. Page 10
HAZ and maternal schooling
-2.4-2.2
-2
-1.8-1.6-1.4-1.2
-1
0 1 2 3 4 5 6 7 8
Grades of schooling, mother
95% CI lpoly smooth
kernel = epanechnikov, degree = 0, bandwidth = 1.08, pwidth = 1.62

11. In the last month:
PSNP Beneficiary
status in 2012
Have you been
visited by a
Health Extension
Worker
Have you been
visited by
someone from
the Women’s
Development
Army
Have you been
given
information
about foods to
feed young
children
Have you heard
about
information
about foods to
feed young
children on the
radio
Does household
boil drinking
water before
use?
PSNP beneficiary 33.3% 18.2% 26.0% 14.9% 11.4%
Non-beneficiary 33.4 14.5 28.5 20.2 11.2
Page 11
Access to information about nutrition
No difference in access to information by PSNP status

12. Percent consuming any:
Region Pulses Dark, leafy
vegetables or
Vitamin A rich fruits
Other fruit
or
vegetables
Milk or
other dairy
products
Eggs Meat,
poultry or
fish
Fats or oils
Tigray 22.5 14.7 8.5 12.4 20.9 3.9 17.1
Amhara 16.0 16.0 12.3 21.7 7.5 6.6 21.7
Amhara
HVFB
15.5 7.7 4.5 13.5 3.9 5.8 8.4
Oromiya 7.5 14.5 13.7 48.6 9.8 3.5 15.7
SNNP 4.0 30.5 12.0 37.5 5.5 2.5 15.5
All 11.5 17.3 10.7 30.7 9.1 4.1 15.3
Page 12
Foods consumed by children 6-24 months, previous day, by
region, 2012
46 percent consumed none of these food groups
11 percent consumed three or more
four percent consumed four or more
Oromiya has highest % of dairy
consumption and highest mean HAZ

13. • We see no association between PSNP participation and measures of undernutrition in
these data
• Important to remember that results are preliminary but also consistent with
international experience
• This is suggestive that an assumption that the PSNP alone can reduce undernutrition in
rural Ethiopia may well be incorrect. Instead, a more powerful approach may well be
one where the PSNP is “tightly wedded”
– To direct nutrition interventions
– Expansion of access to a wider range of foods
Page 13
Summary and discussion