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ETHIOPIAN DEVELOPMENT
RESEARCH INSTITUTE
Cows, missing milk markets and nutrition in
rural Ethiopia
John Hoddinott, Derek Headey and Mekdim Dereje
IFPRI ESSP
Ethiopian Economics Association (EEA) and the Econometric Society
19th Annual Conference of the African Region Chapter of the Econometric Society
12th International Conference on the Ethiopian Economy
July 16-19, 2014
Addis Ababa
1
2
Structure of Presentation
 Introduction
 Data
 Estimation strategy
 Results and Discussion
 Summary
 Policy recommendations
3
Introduction
 In rural areas, is child nutrition affected by what goods the household
produces?
 Conceptually, if there are complete markets, production and consumption
decisions are separable
=> production decisions do not affect consumption
 But if markets are missing, this will no longer be true
4
Introduction, cont’d
 Milk is an instructive good to consider
 Missing markets are widespread because product is perishable
• In Ethiopia, 85% of all milk produced is consumed by the producing household
• Domestically processed milk is largely available only in urban areas
 Milk is important for growth in early life
• Cow’s milk contains insulin-like growth factor I (IGF-I) which plays a key role in
growth in early life.
• Also important source of animal-sourced protein, amino acids, calcium, iron, B-
12 and other micronutrients
 Reducing undernutrition is important for both intrinsic and instrumental
reasons
5
Data
 This study is based on Agricultural Growth Programme (AGP) baseline
survey data
 Very large (n=7,930) household survey fielded in 2011.
 Sample is drawn from high potential agricultural localities
 Data collected on agricultural assets, agricultural production, foods
consumed by children in previous seven days, anthropometry of children 0-
60 months
• Around one quarter of children consumed milk in the last 7 days; one of the
most important sources of protein for young children, in what is otherwise a
highly undiversified diet
• About 64% of households own at least one cow
• High level of stunting (47%)
6
AGP enumeration areas(red) , major markets (yellow) and population density
Source: http://www.gafspfund.org/content/ethiopia. Market towns (light circles) are from FEWSNET, and population density at the woreda level is
from the 2007 National Census of Ethiopia.
Notes: Population density categories (in persons per square kilometer) from lightest to darkest are 0-31, 31-101, 101-139, 139-195, 195-537, 537 and
above.
7
The model and estimation strategy
 Starting from the basic agricultural household model, we consider
dimensions of nutrition.
 The resulting basic model is given by :
𝑉 = 𝑣(𝐾 𝐶𝐴𝑅𝐸
,  𝐶, 𝑧, , 𝑤, 𝑃 𝐴
, 𝑃 𝑁
, 𝑃 𝑋
, 𝐾 𝐴
, 𝐾 𝐹𝐴𝑅𝑀
) where,
 V( 𝐻𝑐, 𝑁𝑐) represent the outcome variables(frequency of milk consumption and
nutritional status)
 𝐾 𝐶𝐴𝑅𝐸
is Knowledge of good care practices (care givers education and age
  𝐶 is for genetic endowments (child sex and age
 Z is local characteristics that might affect nutritional status (region dummy)
  represents taste variables ( religion, ethnicity) that might affect consumption.
 𝑤, 𝑃 𝐴
, 𝑃 𝑁
, 𝑃 𝑋
, 𝐾 𝐴
are respectively wage rate, prices of nutrients, other goods
and prices of agricultural goods produced by households.
 𝐾 𝐴
, 𝐾 𝐹𝐴𝑅𝑀
are farm capital and farm knowledge (land holding & cow ownership)
8
Estimation strategy , cont’d
We use our cross sectional data to look at associations between owning at
least one cow and:
1. Whether a child 6-24m consumes milk in the 7 days prior to the survey
2. The number of days that the child consumes milk in the 7 days prior to the
survey
3. Anthropometry, HAZ and stunting
We use regression techniques:
1. Probit for the first
2. OLS (and poisson) for the second
3. OLS and Probit for the third, respectively
Endogeneity concerns as the association we seek to establish might potentially be due
to other factors in the regression. We run different sensitivity test for this.
But this is not an experimental study and hence can’t completely rule out endogeneity
9
Basic results
Household owns at least one cow: Impact on:
Marginal impacts on Anthropometry: 6-
24m
Anthropometry: 12-
24m
Any milk consumption
in last 7 days
# days milk consumed
in last 7 days
Stunted Stunted
22.5%*** 1. 3 *** -5.5%* -9.9%***
10
Basic results: Looking for missing markets
Food Market in village No food market in village
Any milk
consumption
# days
milk
consumed
Stunted
12-24m
Any milk
consumpti
on
# days
milk
consumed
Stunted
12-24m
Household
owns cow
18.9*** 0.7** 11.4% 22.2%*** 1.3*** -12%***
11
Discussion of the results
1. Cow ownership considerably increases the likelihood of milk
consumption and also the frequency of milk consumption per
week.
2. Cow ownership greatly reduces the likelihood of stunting
3. When there is missing foods market in the village, we see higher
effect of cow ownership on both milk consumption and nutritional
status.
4. To test the validity of the basic results, we run different tests:
 Including additional controls
 Different specifications
 Different estimation strategy
 Different data set (EDHS-2000)
 Increase probability of daily milk consumption by 28 per.points
 Reduced stunting by 5.8 percentage points
12
Summary
 We present evidence that ownership of cows is associated with higher milk
consumption by children 6-24m and in this age group, and especially in
children 12-24m, improvements in HAZ and reductions in stunting
 Magnitudes of effects are large – reduction in stunting of approximately 6-
10 percentage points
 Some evidence that the existence of food markets can partially substitute
for own production
 Need to be cautious; not an experimental study, though results are robust
to a number of checks and alternative model specifications
13
Policy recommendation
 Chronically undernourished children accumulate less human capital in
school and are more likely to be economically less productive as adults
 This implies that interventions that reduce chronic undernutrition have
high economic returns
 Given our results, we see three possible classes of intervention:
1. Intervention to increase cow ownership
 Rural households commonly have the skill to keep milk cows
 The nutritional value of cow ownership is large.
 But with continued human population growth and increasing
competition for feed and water, this is not sustainable.
14
Policy recommendation
2. Intervention to increase dairy productivity
 More researches on the sector; the current budget allocated to the
livestock sectors is relatively very low.
Encourage adoption of foreign breeds and hybrids
3. Intervention to increase dairy market development
Introduction of technologies for reducing perishability and
health risks of milk products
Encouraging establishment of milk cooperatives and
monitoring the quality of their products.
15
Policy recommendation
Investments in improving dairy production and
value chains may be a “win-win” proposition:
Providing higher incomes to producers
Making milk more widely available for consumption by
pre-school children
16
Thank you!

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Cows, missing milk markets and nutrition in rural Ethiopia

  • 1. ETHIOPIAN DEVELOPMENT RESEARCH INSTITUTE Cows, missing milk markets and nutrition in rural Ethiopia John Hoddinott, Derek Headey and Mekdim Dereje IFPRI ESSP Ethiopian Economics Association (EEA) and the Econometric Society 19th Annual Conference of the African Region Chapter of the Econometric Society 12th International Conference on the Ethiopian Economy July 16-19, 2014 Addis Ababa 1
  • 2. 2 Structure of Presentation  Introduction  Data  Estimation strategy  Results and Discussion  Summary  Policy recommendations
  • 3. 3 Introduction  In rural areas, is child nutrition affected by what goods the household produces?  Conceptually, if there are complete markets, production and consumption decisions are separable => production decisions do not affect consumption  But if markets are missing, this will no longer be true
  • 4. 4 Introduction, cont’d  Milk is an instructive good to consider  Missing markets are widespread because product is perishable • In Ethiopia, 85% of all milk produced is consumed by the producing household • Domestically processed milk is largely available only in urban areas  Milk is important for growth in early life • Cow’s milk contains insulin-like growth factor I (IGF-I) which plays a key role in growth in early life. • Also important source of animal-sourced protein, amino acids, calcium, iron, B- 12 and other micronutrients  Reducing undernutrition is important for both intrinsic and instrumental reasons
  • 5. 5 Data  This study is based on Agricultural Growth Programme (AGP) baseline survey data  Very large (n=7,930) household survey fielded in 2011.  Sample is drawn from high potential agricultural localities  Data collected on agricultural assets, agricultural production, foods consumed by children in previous seven days, anthropometry of children 0- 60 months • Around one quarter of children consumed milk in the last 7 days; one of the most important sources of protein for young children, in what is otherwise a highly undiversified diet • About 64% of households own at least one cow • High level of stunting (47%)
  • 6. 6 AGP enumeration areas(red) , major markets (yellow) and population density Source: http://www.gafspfund.org/content/ethiopia. Market towns (light circles) are from FEWSNET, and population density at the woreda level is from the 2007 National Census of Ethiopia. Notes: Population density categories (in persons per square kilometer) from lightest to darkest are 0-31, 31-101, 101-139, 139-195, 195-537, 537 and above.
  • 7. 7 The model and estimation strategy  Starting from the basic agricultural household model, we consider dimensions of nutrition.  The resulting basic model is given by : 𝑉 = 𝑣(𝐾 𝐶𝐴𝑅𝐸 ,  𝐶, 𝑧, , 𝑤, 𝑃 𝐴 , 𝑃 𝑁 , 𝑃 𝑋 , 𝐾 𝐴 , 𝐾 𝐹𝐴𝑅𝑀 ) where,  V( 𝐻𝑐, 𝑁𝑐) represent the outcome variables(frequency of milk consumption and nutritional status)  𝐾 𝐶𝐴𝑅𝐸 is Knowledge of good care practices (care givers education and age   𝐶 is for genetic endowments (child sex and age  Z is local characteristics that might affect nutritional status (region dummy)   represents taste variables ( religion, ethnicity) that might affect consumption.  𝑤, 𝑃 𝐴 , 𝑃 𝑁 , 𝑃 𝑋 , 𝐾 𝐴 are respectively wage rate, prices of nutrients, other goods and prices of agricultural goods produced by households.  𝐾 𝐴 , 𝐾 𝐹𝐴𝑅𝑀 are farm capital and farm knowledge (land holding & cow ownership)
  • 8. 8 Estimation strategy , cont’d We use our cross sectional data to look at associations between owning at least one cow and: 1. Whether a child 6-24m consumes milk in the 7 days prior to the survey 2. The number of days that the child consumes milk in the 7 days prior to the survey 3. Anthropometry, HAZ and stunting We use regression techniques: 1. Probit for the first 2. OLS (and poisson) for the second 3. OLS and Probit for the third, respectively Endogeneity concerns as the association we seek to establish might potentially be due to other factors in the regression. We run different sensitivity test for this. But this is not an experimental study and hence can’t completely rule out endogeneity
  • 9. 9 Basic results Household owns at least one cow: Impact on: Marginal impacts on Anthropometry: 6- 24m Anthropometry: 12- 24m Any milk consumption in last 7 days # days milk consumed in last 7 days Stunted Stunted 22.5%*** 1. 3 *** -5.5%* -9.9%***
  • 10. 10 Basic results: Looking for missing markets Food Market in village No food market in village Any milk consumption # days milk consumed Stunted 12-24m Any milk consumpti on # days milk consumed Stunted 12-24m Household owns cow 18.9*** 0.7** 11.4% 22.2%*** 1.3*** -12%***
  • 11. 11 Discussion of the results 1. Cow ownership considerably increases the likelihood of milk consumption and also the frequency of milk consumption per week. 2. Cow ownership greatly reduces the likelihood of stunting 3. When there is missing foods market in the village, we see higher effect of cow ownership on both milk consumption and nutritional status. 4. To test the validity of the basic results, we run different tests:  Including additional controls  Different specifications  Different estimation strategy  Different data set (EDHS-2000)  Increase probability of daily milk consumption by 28 per.points  Reduced stunting by 5.8 percentage points
  • 12. 12 Summary  We present evidence that ownership of cows is associated with higher milk consumption by children 6-24m and in this age group, and especially in children 12-24m, improvements in HAZ and reductions in stunting  Magnitudes of effects are large – reduction in stunting of approximately 6- 10 percentage points  Some evidence that the existence of food markets can partially substitute for own production  Need to be cautious; not an experimental study, though results are robust to a number of checks and alternative model specifications
  • 13. 13 Policy recommendation  Chronically undernourished children accumulate less human capital in school and are more likely to be economically less productive as adults  This implies that interventions that reduce chronic undernutrition have high economic returns  Given our results, we see three possible classes of intervention: 1. Intervention to increase cow ownership  Rural households commonly have the skill to keep milk cows  The nutritional value of cow ownership is large.  But with continued human population growth and increasing competition for feed and water, this is not sustainable.
  • 14. 14 Policy recommendation 2. Intervention to increase dairy productivity  More researches on the sector; the current budget allocated to the livestock sectors is relatively very low. Encourage adoption of foreign breeds and hybrids 3. Intervention to increase dairy market development Introduction of technologies for reducing perishability and health risks of milk products Encouraging establishment of milk cooperatives and monitoring the quality of their products.
  • 15. 15 Policy recommendation Investments in improving dairy production and value chains may be a “win-win” proposition: Providing higher incomes to producers Making milk more widely available for consumption by pre-school children