Guush Berhane, IFPRIJohn Hoddinott, IFPRINeha Kumar, IFPRI

May 13, 2014

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The Productive Safety Net Programme and the nutritional status of pre-school children in Ethiopia:

Preliminary Results

• 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

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Introduction and Context

• 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

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Introduction and Context

• 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:

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Introduction and Context

Year CBN established Percent children <5 in sample

2008 13

2009 29

2010 20

2011 12

2012 26

• This presentation discusses results that are:

PRELIMINARYPRELIMINARY

• 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

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Introduction and Context

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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 48.9Sample size 3041 2845 2482

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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

• 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

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Regression analysis

• 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

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Regression analysis

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HAZ and maternal schooling

-2.4

-2.2

-2-1

.8-1

.6-1

.4-1

.2-1

Len

gth/

heig

ht-f

or-

age

Z-s

core

0 1 2 3 4 5 6 7 8Grades of schooling, mother

95% CI lpoly smooth

kernel = epanechnikov, degree = 0, bandwidth = 1.08, pwidth = 1.62

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

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Access to information about nutrition

No difference in access to information by PSNP status

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 17.1Amhara 16.0 16.0 12.3 21.7 7.5 6.6 21.7Amhara

HVFB15.5 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 15.7SNNP 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

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Foods consumed by children 6-24 months, previous day, by region, 2012

46 percent consumed none of these food groups11 percent consumed three or morefour percent consumed four or more

Oromiya has highest % of dairy consumption and highest mean HAZ

• 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

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Summary and discussion