Improving evidence for better policy making in Ethiopia’s livestock sector

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IMPROVING EVIDENCE FOR BETTER POLICY
MAKING IN ETHIOPIA’S LIVESTOCK SECTOR
Webinar
24 June 2020

ETHIOPIA’S EVOLVING LIVESTOCK SECTOR
Fantu Bachewe
24 June 2010
Improving evidence for better policy making in Ethiopia’s
livestock sector

INTRODUCTION
• Agriculture accounted for 29% of GDP growth during 2004-2014
• Crop accounted for 24% and livestock for 5% of the growth
o Importance of livestock in agriculture declined in all but two years
Figure 1 — Share in GDP and average contribution to GDP growth, 2004/5-2015/16
0
20
40
60
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Share in GDP (%)
Agriculture Crop Livestock Industry Services
Crop
24%
Livestock
5%
Other
primary
2%
Industry
16%
Services
53%
Average contribution to GDP growth

INTRODUCTION…CONTD.
Livestock number
• Livestock means of ASF production & are themselves end-products
• Cattle (58 million in 2015) largest & on average grew at 3.8% during 2004-2015
o Number of sheep (29 mill) grew at 4.6% and others at 5.6% or higher
• Livestock deaths significant and adversely affect productivity
o Over 3 million cattle, sheep, & goats lost to death annually since 2005
• Deaths as % of stock declined, e.g. cattle 16%
Supply and demand side factors indicate considerable potential in livestock production
1. Home to large stocks of many livestock types: means of ASF prod’n & end-products
• Cattle largest & grew at 3.8% during 2004-2015; sheep (4.6%), & others at ≥5.6%
• About 4 heads of cattle & poultry; No variation in size of ownership
• Real value of livestock 11.2 billion USD (720 USD/farm) in 2015,
o Grew by 58.4% (4.3% per year); similar to growth in TLU (56.4% or 4.2% per year)
2. Livestock/ASF produced by large number of farmers
• About 92% farm HHs owned at least one livestock in 2015
• Proportion of owners remained about same but number increased by 51%
3. Consumption spending on ASF as well as livestock exports grew
• Further increase in spending expected with growth in income

PRODUCTION AND PRODUCTIVITY
Live animal marketing
• Number sold for off-farm slaughter, net commercial off-take (NCOT), doubled in
cattle, grew at 56% in sheep and at 131% in goats
• NCOT rate (NCOT/average stock) grew in all animals except poultry but growth slow
Figure 2 — Net commercial off-take number (millions) and rate (%), 2005-2014
0
2
4
6
8
10
12
Cattle Sheep Goat Poultry Cattle Sheep Goat Poultry
NCOT (number) NCOT rate (%)
2005
2010
2014

PRODUCTION AND PRODUCTIVITY…CONTD.
Animal-sourced food (ASF) production and productivity
• ASF output grew considerably
o Egg output grew by 93% and milk output by 41% during 2005 – 2015
• Productivity (output per animal) stagnated
• Milk yields in Uganda, Kenya, & Malawi were 27%, 125%, & 239% higher than
Ethiopia in 2014
Figure 3 — Annual milk and egg production and productivity, 2005-2015
0
2
4
6
8
10
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Output
Eggs (million dozens) Milk (billion liters)
0
1
2
3
4
5
2005 2010 2015
Productivity
Milk (100 lts/cow/year) Egg (dozens/hen/year)

PRODUCTION AND PRODUCTIVITY…CONTD.
Real value of livestock output per TLU and per farmer
• Real livestock output in 2015 was 73% higher than in 2004
• Real output per TLU & per farmer was 11% & 15% higher in 2015 than 2004
Growth accounting analyses of the livestock subsector
• Labor and livestock most important, accounted for three-quarters of output growth
• Modern inputs contributed only 11% to livestock output growth
700
800
900
1,000
1,100
1,200
2,000
2,500
3,000
3,500
4,000
4,500
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Output/TLU
Output/holder
Value of output/farmer Value of output/TLU
Labor
49%
Grazing
land
9%
Livestock
25%
Improved feed
9%
RTS & rural roads
5%
Other factors
2%
∆ TFP
1%
Figure 4 — Real value of output per farmer and
per TLU, 2004-2015
Figure 5 — Average contribution as % of
livestock output growth (2004 – 2014)

INPUT USE AND INTENSIFICATION
Livestock feed
• Green fodder (grazing) important but share of users declining
o Consistent with decline in grazing area per farmer observed during the period
• Lower share use improved feed but share doubled
o Purchased, particularly Improved feed, increasing in importance
Livestock extension
• Number of dairy, meat, & poultry extension users increased by 28%, 11%, & 37%
• Proportion of extension users stagnant & considerably lower in livestock
Figure 6 — Number of farmers using livestock extension services, 2005 and 2014
0
40,000
80,000
120,000
160,000
Dairy Meat Poultry
2005 2014
0
10
20
30
40
50
2005 2014
Crop extension (%) Livestock extension (%)

INPUT USE AND INTENSIFICATION…CONTD.
Veterinary services
• Share of vaccinated cattle, sheep, and goats more than doubled
• Share afflicted with diseases grew slightly in cattle & sheep and declined in goats
(excluding 2008 it declined in all 3 species)
• Sick cattle treated grew by 63% and by over 114% in sheep & goats
Figure 7 – Share of vaccinated and treated livestock, 2004-2015
0
20
40
60
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Vaccinated (% out of stock)
Cattle Sheep Goats
0
20
40
60
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Share of treated out of afflicted (%)
Cattle Sheep Goats

INPUT USE AND INTENSIFICATION…CONTD.
Artificial insemination
• Artificial insemination (AI) increasingly being adopted in the country
• Calves born using AI 11 times higher in 2016 (230,000) than in 2005, but still low
Dairy processing and livestock breed composition
• Number of dairy processors increased by 260% & processed milk output by 93%
• Share of cross-bred cows and poultry low but grew considerably
Figure 8 — Number of milk processing plants
and processed milk output, 2007-2015
Figure 9 — Share of cross-bred cows
and poultry (%), 2004-2014
0
2
4
6
8
10
0
10
20
30
40
2007
2008
2009
2010
2011
2012
2013
2014
2015
Monthlyprocessedmilk
output
Dairyprocessors
Dairy processors (number)
Monthly processed milk (million liters)
0
1
2
3
4
5
2004 2010 2014
Cross-bred cows (%)
Cross-bred poultry (%)

ASSOCIATES OF MODERN INPUT USE
Results of econometric analyses
• Period marked with rapid growth in % using vaccination, improved feeds & breeds,
• Intensification in use of such inputs need to drive future livestock output growth
• Study investigates factors associated with adoption of 3 inputs for cattle & shoats
Results indicate that:
• Education and household size positively associated with adoption,
• Adoption of all inputs positively associated with receiving extension advice
• Distance to urban centers negatively associated with adoption of inputs,
• Larger herd size positively associated with adoption of inputs,
• Adoption positively influenced by past levels of adoption in the woreda-
neighborhood effect and ease of access

CONCLUSIONS
• Rapid growth in number of livestock and livestock owners
o Livestock contributed little to GDP and importance declined
• Demand and supply factors imply considerable potential for livestock output growth
• Number sold for meat production increased considerably but share still low
• Milk and egg output grew considerably but productivity is stagnant
• Labor & livestock accounted for most of output growth
• Improved feed and purchased feed growing in importance but share still low
• Cross-bred cows & poultry growing in importance
• Share using livestock extension low and stagnant
• Vaccination & treatment increased considerably; share diseased overall declined
• Death rates declined slightly
o However, higher than twice proportion sold for meat are lost to deaths,

Transformation of Ethiopia’s livestock sector:
The role of income and prices
Bart Minten, IFPRI
May 24th, 2020

Quick transformation in
Ethiopia
• Rapid poverty reduction
• Rapid decline in stunting
• However, stunting levels
still very high
• Monotonous diets an
important issue
0
20
40
60
80
2000 2005 2011 2016
%
Stunting Poverty head count

Signs of increasing
diversification in the food
basket
• Share of cereals in
expenditures on the
decline
0
10
20
30
40
50
60
70
80
2000 2005 2011 2016
Shareinfoodexpenditures(%)
Cereals
Non-cereals

0
2
4
6
8
10
12
14
2000 2006 2011 2016Shareinfoodexpenditures(%)
Animal source foods
Fruits & vegetables
Increasing expenditures on
high-value and nutritious
crops
1/ Animal source foods
(dairy most important)
2/ Fruits and vegetables

However, part of increased expenditures to pay for
increased prices of ASF
-60 -40 -20 0 20 40 60 80
Grains, roots and tubers
Legumes and nuts
Dairy products
Eggs
Flesh foods and others/small animal…
Vitamin A dark green leafy vegetables
Other Vitamin A rich vegetables and fruits
Other fruits and vegetables
Oils and fats
Sugar and honey
%
Price changes (2018 compared to 2015, %)

Richer people spend significantly more on ASF
than poorer people
0
2
4
6
8
10
12
14
16
18
20
Poorest q2 q3 q4 Richest
%foodexpenditures

• Demand estimations based on national
household surveys (HICES)
• Estimates of price and income elasticities, i.e. if
prices/change change with x%, consumption
changes with y%
What is the impact of changes in prices and incomes on
consumption?

• Price elasticities (QUAIDS model):
- Beef: -0.73
- Mutton and goat: -0.12
- Dairy products: - 0.45
- Other meat and animal products: - 1.46
• High impacts of price changes. Noted price
increases in last decade ->25% reduction in
beef (ceteris paribus)…
Prices matter enormously for ASF

• Income elasticities (QUAIDS model):
- Beef: 0.465
- Mutton and goat: 2.702
- Dairy products: 0.511
- Other meat and animal products: 0.479
Income changes important drivers for
change of the livestock sector

Especially commercial ASF markets are expected to quickly
grow
0
5
10
15
2011 2030
Billion2011Birr
rural urban
0
5
10
15
2011 2030
Billion2011Birr
Beef Mutton Dairy Other

• Ethiopia successful in cereal sector
• Less so for nutritious crops, and more in
particular in livestock sector
• More attention needed:
1. Want to keep prices low - nutritional benefits
2. Massive demand changes are coming, esp.
leading to large changes in commercial
demand
3. Issue of inclusiveness

Trade and Value-Chain Assessment of
Live Animal Exports from Ethiopia
Tadesse Kuma, Endale Gebre, and Ashagrie Gibtan, PSI
June 24, 2020
Virtual Seminar
Improving evidence for better policy making in Ethiopia’s livestock sector
Co-Organized by IFPRI, the Livestock Systems Innovation Lab (LSIL), the Ethiopian Institute
of Agricultural Research (EIAR) and Policy Studies Institute (PSI)

1. INTRODUCTION
 Livestock sector has an important place in Ethiopian economy (12-16 percent
of total GDP; 30 percent of agricultural GDP)
 In the lowlands areas (with pastoral management), livestock is the principal
source of subsistence
 Export earning from live animal and animal products contributes substantial
share of national export earnings; however, its earnings declined in the
recent years: 400 million USD in 2011 to 252 million in 2018 (36 percent
drop)
 Similarly, live animal exports declined from 207 million in 2011; 148 million in
2015; 45 million in 2018/19 (a 17% drop per year).
 Purpose analysis is to understand: 1/ Reasons for this drop; 2/ Implications
on smallholder income

1. INTRODUCTION
Trends of live animal and animal products export
earnings (mill USD)
0.0
50.0
100.0
150.0
200.0
250.0
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
Value(inMilliionUSD)
Leather and Leather Products
Live Animals
Meat & Meat Products
Source: Ethiopia Revenue and Customs Authority, 2018

2. DATA AND METHOD
Data sources:
• Secondary data on production, price (producer, retail), access costs,
trade volume and value, livestock population, animal feed, etc. from
CSA, ERCA, NBE, Regional ECRA, and International sources.
• Primary data gathered through consultative meeting with Key
Informants
• Field visits to quarantine centers
Method of analysis:
• Both descriptive and simple statistical tools
• The MAFAP/FAO methodology

3. KEY CHALLENGES OF LIVE CATTLE EXPORT IN ETHIOPIA
(a) Lack of accredited quarantine center for Ethiopia - The efforts
GoE to put in place standard accredited quarantine centers;
 Since early 2000, the GoE made efforts to establish 5 export
quarantine centers (Mile, Jijiga, Metema, Humera, and
Almehal); 230 million Birr investment
 However, none of them are operational that relay on Djibuti QC
(a) Governance of quarantine in Djibouti (Live animals kept before
being exported to Middle East (re-certified Djibouti origin).
• Quarantine by the Government of Djibouti in hands of one
person (Mr. Abu Yasir), who seemingly manages at his will
• Excessive cost of quarantine services: USD 2/shots and USD 7-
8/cattle/per night plus cost of pre-quarantine health services
• Lack of transparency: rejection of live cattle from Ethiopia
without detection of sufficient defect or disease;

3. KEY CHALLENGES LIVE CATTLE EXPORT FROM ETHIOPIA
(c) Excessive and costly legal requirements for live animal
exporting which is also highly bureaucratic
 Export license
 Hiring a transitory company for custom clearance
 Currency regulation requirements (letter of credit (LC)
or Cash Against Document (CAD), or deposit an
advance payment in a bank)
 Health certificate from a quarantine service station (7-
21 days of quarantine during which the exporter is
responsible for all feed and watering expenses).

(d) Booming informal trade
 Informal cross-border trade practiced in the eastern, western, southern and
northwestern borderlands of Ethiopia (5 routs); 75-80% of total export
 Trade via Ethio-Somaliland, Djibouti, and Kenya account for lion’s share
Reasons:
 Excessive costs and inefficiencies of the export requirements
 Invisible hands of politicians – although it is difficult to prove, ICB live
animal trade backed by invisible/untouchable/powerful politicians
 High foreign exchange demand
 Lack of access to market infrastructure in the close proximity for border
communities
 Price difference (higher price at the border markets)
 Historical economic and social attachments of border community
 coordination failure of different tiers of government instituions
3. KEY CHALLENGES LIVE CATTLE EXPORT FROM ETHIOPIA

4. RESULTS
Access costs of feedlot operators (%) Trend of average feed price (Birr/Kg)
Cost of
Handling
1%
Feed cost at felots (75
days)
59%
Other cost at
feedlot (for 75
days)
4%
Transport
cost from
FG to PoC
8%
Taxes and
fees
4%
Capital cost
7%
Overhead cost
4%
Trader margin
13%
0.98 1.06
1.6
2.49 2.41
3.64
4.83
6.06
7.4
7.98
2003
2004
2006
2008
2009
2010
2015
2017
2019
2020
Value(Birr//Kg)

Access costs of exporter (% share)
Average composition of Market
Development Gap for live animal
export trade (2005-2019) (%)
Handling
costs, 22
Transport
cost from
PoC to
Djibouti ,
12
Taxes and
levies, 30
Trader
margin, 12
Capital
cost, 18
Overhead
costs &
Miscellane
ous , 6
35%
65%
Inefficiencies from
border to point of
competition
Inefficiencies from the
point of competition to
farm gate
4. RESULTS
Future market development in the sector needs
substantive reduction of excessive transaction/access
costs which account for current market inefficiencies

Producer, wholesale and export (f.o.b.)
prices, 2005 to 2019• Wholesales price is 28%
higher compared to fob
price throughout 2012-
2019, yet cattle is exported
• Under normal condition,
farmgate prices should be
lower than export (FOB)
price but here it was more
or less equal to FOB price
2017-2019
• Efforts to access exchange
rate accounts for these
abnormalities
0
5000
10000
15000
20000
25000
30000
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
Birr/headoflivecattle
Export price
Producer price
Wholesale price
Export price (parallel ER)
4. RESULTS

Wholesale price vs. observed and
adjusted reference FOB price at
wholesale market (Birr/head)
Farm gate price vs. observed and
adjusted reference FOB price at
farmgate (Birr/head)
0
5 000
10 000
15 000
20 000
25 000
30 000
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
Birr/headofcattle
Wholesale price
Observed FOB price
Adjusted FOB price
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
Price:Birr/headoflivecattle
Farmgate price
Observed FOB Price
Adjusted Fob Price
• Live cattle exporters make
substantial losses
Farmers receive disincentives 2005-
2011
4. RESULTS

5. CONCLUDING REMARKS
• Key findings
– booming informal trade in the recent years (mainly since 2015)
– High domestic demand for meat together with skyrocketing
access costs made livestock export trade uncompetitive (feed,
quarantine services, inefficient government system)
– Unmet demand for foreign exchange - exporters offer
generous prices to wholesalers; high prices passed on to
producers
– Exporters incur substantial loss, compensated through
importing goods with low import parity price and high
domestic prices (similar to what happened for coffee export);

Following policy measures required:
 Improve institutional arrangement for live animal export trade
 Strengthening quarantine services – meet international standard and
accredited
 Re-visiting causes of current foreign exchange misalignment
 Without prejudice of historical ties of cross border communities,
strengthening enforcement capacity of existing laws and regulation to
reduce current informal trade
 Improving access, availability and quality of animal feed has an important
implication for future development of the sector
5. CONCLUDING REMARKS

Alternative national development scenarios and
their implications for the livestock system in
Ethiopia
Emerta A Aragie
(with James Thurlow, Seneshaw Tamiru and Ermias Engida)
June 24, 2020
Virtual Seminar

PROBLEM
• IFPRI research shows that demand for ASF has
grown rapidly.
• Income growth and urbanization is driving
this change.
• The LMP lays out an ambitious and sizable
investment plan based on very high projected
demand growth for 2015-2020 period
• But income growth slowed down considerably
(from 10% to IMFs latest forecast of 6.5% )
• COVID and other risks could push this down even
further over the next five years
• This means the LMP is no longer appropriate for
the new economic trajectory.
 >35% annual increase in meat consumption
 >10% annual increase in meat production
 >10% annual increase in milk consumption
 >12% annual increase in milk production

SOLUTION
• For national planning and identifying
investment needs, it is crucial to reassess
projections and policy priorities.
• We developed a more sophisticated
integration of advanced economic
modeling with traditional herd dynamics.
• This tool allows us to quantify in a more
consistent way
• the linkages between economic growth
and agri-food system transformation, and
• develop trajectory of the livestock system.
Fig.: Integrated modeling framework with
information flows and outcome indicators
Herd
Dynamics
Model
(HDM)
Economy
wide
model
(CGE)
Microsim
ulation
module
(MSM)
Herd sizes, feed
needs, etc.
Consumer
demand
Changes in GDP
and employment,
etc.
Changes in poverty
and dietary
diversity
Incomes and
prices

HERD DYNAMICS MODEL
The HDM:
• Feature: tracks herd sizes disaggregated
by age, sex and breed.
• Inputs: utilizes baseline stock, indicative
birth, death, offtake and intake rates
• Outputs: system consistent births, deaths
and offtakes, meat, milk production.
• Nature of the data
• Currently focusing on cattle
• Ethiopia’s Agric. Sample Surveys (ASS).
• The data runs from 2003 – 2017
• Survey reports cattle by five major age
groups by sex
• We build the cattle database for 5 agro-
ecological zones.
Fig.: Schematic representation of herd
dynamics- e.g.: cattle
Figure: Schematic representation of herd dynamics
Survive Survive Survive
Survive Survive SurviveFemale
Birth
Male
Birth
Young
male
Young
female
Immature
male
Immature
female
Adult
male
Adult
female
Offtake
Male
deaths
Female
deaths
Life
expectancy
Milk
Manure
Manure
Hides
and
skins
Livestock
capital

LINKING TO ECONOMIC MODEL
• Data transformation and demographic variables computation
• 13 single-year age class cattle database – from 5 class
• Transform the data to create smoothed, demographically consistent life-table.
• Linking the demographic information to the gams based HDM
• Once internally consistent demographic parameters are computed, export to the
HDM.
• Smoothed baseline data – for 2016/17
• Fertility rate, death rate, offtake rate, etc
• Interacting the HDM and the core CGE model –> bi-directional
• From the HDM – feed demand, livestock capital trend for the meat and milk
activity
• From the CGE model – activity prices (meat and milk offtake rates), input
availability (live-weight, etc.)

FOUR FUTURE SCENARIOS
• Baseline – using a core CGE model for Ethiopia - 8 livestock products.
• 6.5% GDP growth with current pace of urbanization (+5 %-points by 2030)
• Four future economic-demographic scenarios
• Rate of economic growth (4.0% vs. 9%)
• Rate of urbanization (no change in pop share by 2030 vs. +5%-points by 2030)
• Hypothetical growth and urbanization scenario to provide a risk-based
approach to the prospects of the livestock sector.
• Results reported as deviations from baseline trajectory.

RESULTS | LIVESTOCK IN THE ECONOMY
• Demand for ASF heavily depends on economic-demographic changes
• Income growth main driver of overall livestock system expansion
• Urbanization shifts the composition of livestock system towards proc. ASF
Fig.: Percentage points deviation from baseline growth Fig.: Percentage points deviation from baseline
change in livestock product consumption
2.7%
2.1%
2.0%
5.5%
2.4%
-2.8%
-2.2%
-2.2%
-6.5%
-2.6%
Total GDP
Cattle
Milk
Meat processing
Dairy processing
Fast growth & fast urbanization Fast growth & slow urbanization
Slow growth & fast urbanization Slow growth & slow urbanization
1.9%
1.8%
2.0%
1.2%
2.5%
1.6%
-1.2%
0.8%
-0.6%
-1.9%
1.5%
-1.0%
Rural
Urban
National

RESULTS | HERD DYNAMICS
• Consistent results within the HDM framework
• High economic growth is linked to high meat and milk offtake levels
• High urbanization leads to higher meat offtake rate, but not to a clear
increase in milk offtake.
Fig.: Percentage points deviation from baseline change in meat and milk offtake
1.2%
0.8%
-0.6%
-0.7%
Fast growth & fast urbanization
Fast growth & slow urbanization
Slow growth & fast urbanization
Slow growth & slow urbanization
Meat offtake
1.1%
1.0%
-1.1%
-1.1%
Milk offtake

CONCLUSION
• Demand for ASF heavily depends on economic-demographic changes
• Income growth main driver of overall livestock system expansion
• Urbanization shifts the composition of the livestock system towards
processed ASF product
• Livestock development plans should reflect economic reality & potential
risks
• Previous LMP may have overestimated economic growth & hence resource
needs (but not priorities)
• Integrating economywide & livestock systems models can strengthen basis
for planning
• Modeling component of the IFPRI project continues until August
• Identifying future development scenarios for Ethiopia’s livestock system
• Evaluating drought damages and recovery scenarios

Thank you!
For further questions and comments: e.aragie@cigar.org

Transformation in the dairy sector
Seneshaw Tamru (IGC)
June 24, 2020

INTRODUCTION
• Transformation in
Ethiopia
• Drivers:
GDP growth
Urbanization
Infrastructure
• Dairy sector?
Policy
Lack of good data

DATA
• Primary data: survey fielded in
January – February 2018
• Focus: major producing areas
supplying Addis
• Stratified by distance to Addis:
• Addis Ababa: 97 farms;
• Suburban: 256 farms;
• Rural (North and West
Shewa): 602 farms

DATA
• Look at :
• 1/ Remote vs non-remote farms
• 2/ Small vs large dairy farms

Upstream
- Yields
- Access to services
- Adoption of modern inputs

Yield
200400600800
1000
0 50 100 150
Travel costs (birr/person)
at time of survey 10 years earlier
0
200040006000
yield(l/year/cow)
1-2 cows 3-24 cows >24 cows

Services
- Extension:
0
.2.4.6.8
1
0 50 100 150
0
.2.4.6.8
1
ShareDAs(mostly)available

Adoption
- Cross bred cows
0
.1.2.3
0 50 100 150
.2.4.6.8
1
sharecross-bredcows

Feed
-Purchased Wheat Bran
0
.1.2.3.4.5
0 50 100 150
.2.4.6.8
1
Shareusingpurchasedwheatbran

Health
-Distance to nearest pharmacy
406080
100120140
0 50 100 150
20406080
100
Walkingtime(minutes)togetmedicine

Conclusion
• Large changes in the dairy sector in Ethiopia
• Implications:
(1) Positive dynamics, but from a low base - more effort
needed to further stimulate dynamics
(2) Increasing importance of purchased feed
(3) The role of market access
(4) Inclusiveness of remote and small dairy farms

THANK YOU
DISCUSSION PAPER (ESSP WP 129):
“TRANSFORMING AGRI-FOOD SYSTEMS IN ETHIOPIA: EVIDENCE FROM THE DAIRY SECTOR”
BART M. (IFPRI), YETIMWORK H. (PSI), SENESHAW T.(KULEUVEN) AND AGAJIE TESFAYE (EIAR)

Fasting, food and farmers:
The case of dairy
Eline d’Haene, University of Gent
Senne Vandevelde, EU
Bart Minten, IFPRI
May 24th, 2020

Introduction
The role of religion in shaping food choices, nutrition,
and food value chains not well understood.
 Ethiopia:
1. Large group of Orthodox Christians
2. Multiple Orthodox fasting periods - abstinence from
animal-source foods
3. Low overall consumption of milk in the country,
especially by children, and underdevelopment of the
dairy sector

Research questions
1. What is the effective number of fasting days adhered
to by Orthodox Christians?
2. How do milk producing households and markets cope
with these cycles of religious fasting?
3. What is the impact of fasting on children’s milk
consumption?

 Milk production and output data are recorded using a one-
month recall period
 Consumption data: one-week and one-day recall period
 The timing of the data collection good to evaluate influence
fasting
Data and methods

Fasting participation
Fasting reduces annual dairy consumption at national
level by 12%

Impact fasting on dairy sector
 Prices fall during fasting
– good for consumption of
those that do not fast.
Production goes down
during (long) fasting
periods
 Price swings larger for
storable dairy
commodities compared to
liquid milk

Adaptation strategies
To cope with fasting, dairy farmers adopt different
strategies:
They reduce milk output at the farm by aligning
number of cows in milk with fasting periods (esp.
remote)
They increasingly channel surplus milk to children
(esp. non-remote)
They expand home processing activities

Milk Butter
Prices
(1) Lent; (2) Easter; (3) Easter-May; (4) Jun-Advent; (5) Advent; (6) Christmas; (7) Christmas-current

Dairy consumption
 Reduction of consumption of dairy products at the
household level
 Generally, higher milk consumption by children during
fasting
 Differential effect of remoteness.
 In accessible areas, consumption of children:
- Non-fasting: 2 l/week
- Fasting: 3 l/week

Implications
 Fasting matters but availability and affordability important
impediments to increased dairy consumption in Ethiopia
 further investments in the dairy sector needed
 A small number of children participates in fasts
 awareness creation is needed
 To smoothen effects of demand swings, further efforts are
needed towards
 enhancing processing practices (UHT and powdered
milk)
 improving transportation/chilling facilties to assure
better market integration

Food safety, modernization and food prices:
Evidence from milk in Ethiopia
Yetimwork Habte, ESSP/PSI
June 24, 2020
Addis Ababa

Introduction
• Assuring food safety is a challenge in many developing countries.
• Typically a problem with milk value chains (perishability, adulteration)
• Modern processing and marketing mechanisms to solve this issues
• However, there is lack of evidence on how these modern
arrangements perform in early stages of roll-out.
• We study this issue in the case of rural-urban milk value chain in
Ethiopia focusing on answering the following three questions:
1) To what extent modern processing companies linked to improved
hygienic practices?
2) Does improved practices reflected in prices?
3) What is the role of modern retail?

Data
• Survey fielded in January - February 2018
• 955 dairy producers (97 Addis Ababa, 256 Sub-urban and 602 Rural
areas (North and West Shewa zones)
 Modern channel: Milk producers normally sells to agents or
traders of processing companies.
 Traditional channel: producers selling to traditional traders or
directly to consumers, institutions, or service sector
• 208 outlets in Addis Ababa that sells liquid milk (28 modern mostly
supermarket, 113 Minimarket and regular shop 67 Dairy shops)

Hygienic practices, testing and milk handling
0 20 40 60 80 100
Udder and teats are
cleaned
Stored milk kept in a
fridge
Morning and evening
milk are put together
Different use of milk
when cows are sick
Hygienic practices (%)
Modern channel Traditional channel
0 20 40 60 80 100
quality is checked
through lactometer
quality is checked
through alcohol test
buyer uses stainless
steel/aluminum
buckets/cans
Testing and milk handling (%)
Modern channel Traditional channel

Prices at the producer level
Density function of prices modern versus traditional value chain
• Prices paid to modern
channel suppliers are
overall lower than in
traditional ones
• However, prices similar
when controlling for
other factors (e.g.
suppliers located
further from city)

Modern channels rely more on non-price mechanism to bind producers to buyers
0 10 20 30 40 50 60 70
advice on improved milk production
advice on hygienic milk handling
advice on health risks inflicted by adulteration
keeps buying milk during fasting periods
provides medecine/veterinary services/AI
supplies milk storage cans
supplies feed
provides credit/loans
Service delivery by the most important buyer (%)
Modern channel Traditional

Prices at the retail level – Pasteurized milk
Density function of prices pasteurized versus raw
• No large differences
between pasteurized
and raw milk
• The price difference
vanishes once we
control for type of retail
outlet, fasting period
dummy & location

Prices at the retail level – Modern retail
Price density function modern versus traditional retail
• Not much difference of
price for modern
compared to traditional
outlets.
• In regression, modern
retailers sell milk at a price
that is 3% lower than in
traditional shops.

Conclusions
• Adoption levels of hygienic practices and practices leading to safer milk
by dairy producers in Ethiopia low
• No major differences between traditional and modern milk value chains;
• Modern processing companies do more formal milk testing; no price
premiums paid by them at the producer level for the adoption of improved
practices.
• At urban retail level, no prices difference for pasteurized and raw milk.
• Modern retail sells pasteurized milk at lower prices ceteris paribus,
possibly driven by shorter value chain.
• Modern value chains to better reward hygiene and food safety in these
settings are therefore called for.

The quest for safe food:
The COVID-19 crisis and dairy value chains in
Ethiopia
Agajie Tesfaye (EIAR), Yetimwork Habte (ESSP-PSI), and Bart Minten (ESSP-IFPRI)
Presenter: Agajie Tesfaye
Date: 24 June 20
Venue: Webinar

INTRODUCTION
• COVID-19 pandemic started in Ethiopia since mid-March 2020
• A rapid qualitative appraisal was made on the dairy value chain
supplying the city of Addis Ababa
• Purpose was to understand the effects that COVID-19 might have on
the dairy sector
• Interviews to nearly 100 key informants/Value chain actors:
• Telephone interviews with dairy farmers and institutes, milk
collectors, processing companies
• Face-to-face interviews to supermarkets markets, retails shops,
commercial service centers, consumers

COVID-19 EFFECTS ON INPUTS IN DAIRY SECTOR
Effects on dairy feeds
• Large scale concentrate feed processing companies had stocks of raw materials –
few impacts (no noticeable changes on supplies)
• Some of the dairy farms attempted to keep stocks of feeds at the beginning of the
pandemic because of uncertainty
• Most of the dairy farms in the city of Addis Ababa faced no supply shortages and
price changes on the feed market
• Instead, suburban dairy farms faced short lived price rise (about 30 – 40%) for
wheat bran and nugcake because of restricted transportation access
• Overall, no noticeable effects on feed supply, demand and prices on dairy feeds
because of COVID-19

Effects on dairy labor
• Most of the medium and small-scale dairy farms depend on family labor
• Almost no labor lay-offs reported on commercial dairy farms
• Dairy labor not yet affected noticeably
Effect on veterinary medicines
• International supply chains interrupted
• Prices of vet medicines increased by 20%
COVID-19 EFFECTS ON INPUTS IN DAIRY SECTOR

COVID-19 EFFECTS ON MILK PRODUCTION
• More than 90% of the dairy inputs not disrupted by the pandemic
• Overall milk demand not yet noticeably affected
• Farm-gate whole-milk prices not noticeably affected by COVID-19
• Because of these, the supply side of milk has not been noticeably
affected by COVID-19 in the short run
• Instead, fasting season affected milk demand, supplies and prices
temporarily

COVID-19 EFFECTS ON MIDSTREAM VALUE CHAINS
Effect on large and medium-scale milk suppliers
• Milk collectors collect the milk from suburb dairy farms (commercial and family
dairy) and supply to the city of Addis Ababa (5,000 – 20,000 liters/day per collector)
• These milk collectors supply whole-milk directly for milk processors
• Temporary disruption of milk demand at the beginning because of mis-
information by mass-media (not to drink/eat animal source foods)
• Corrections made later to consume safest/pasteurized products, but raw milk still
not advised.
• Prices remained unaffected
• COVID-19 pandemic has not much affected the milk collectors in the short run

Effect on small-scale milk collectors and distributors
• Small-scale collectors aggregate <5000 liters of milk/day per collector from urban and
peri-urban dairy farms
• Supply raw-milk to households, coffee houses, pastries, café’s & restaurants
• House-to-house supplies was affected: fear that milk distributors will spread the virus
as they are in contact with many clients, travel in public transport
• Most of the consumers deserted commercial service enters because of stay-at-home
and physical distancing guidelines:
• Whole-milk demand dropped in the range of 50 – 70%
• Overall, whole-milk supply to households and commercial service centers adversely
affected by COVID-19 pandemic

Effect on milk processing sector
• They process milk and produce safest products (pasteurized milk and yogurt)
• At the beginning of the pandemic, temporary disruption of demand because
of mass-media mis-information
• Corrections made (panel discussions held on safety of pasteurized products)
• Prices were not affected and demands for pasteurized milk and yogurt
returned to normal cycle
• COVID-19 little impact on milk processing sector
• Instead, fasting season did affect the demand, supplies and prices

COVID-19 EFFECTS DOWNSTREAM IN VALUE CHAINS
Effect on shift in demand
• The demand for unsafe products declined:
• raw milk
• local yogurt prepared from raw milk (local yogurt houses adversely affected)
• The demand for safest products highly increased:
* Pasteurized milk and yogurt
* Powdered milk
• So, there is a shift in demand:
Unsafe products
*Raw milk
*local yogurt
Safest products
• Pasteurized milk
• Pasteurized yogurt
• Powdered milk
Price rise
• Pasteurized milk (7%)
• Powder milk (20%)

Effect on shift in mode of consumption
Consumption in commercial
service centers
• Pastries
• Coffee houses
• Café’s & restaurants
Consumption at
home
Deserting of commercial
service centers
Stay-at-home and
physical distancing
A shift in mode of
consumption

CONCLUSION
• The dairy sector has proven resilient in the face of the pandemic in the
short run
• However, COVID-19 might start negatively impacting the dairy sector as
the pandemic persists:
• Feed supplies will decline & prices will rise
• Imports of feed ingredients, vet. medicines will decline
• Imports of powdered milk will be affected
• Purchasing power of consumers will decline & demand for milk products will
start dropping
• Following decline in demand, milk supply will also be reduced
• Therefore, corrective measures need to be planned at the outset to minimize the
impact

Trade, value chain technology, and prices for
dairy in East Africa
Liz Ignowski (KU Leuven)
June 24, 2020

DAIRY SECTOR TRANSFORMATION
-20
-10
0
10
20
30
40
50
60
2005 2010 2015
NetExportValue(MillionUSD)
Ethiopia Uganda
0
1000
2000
3000
4000
5000
2005 2007 2009 2011 2013 2015
1000Tonnes
Production Ethiopia Production Uganda
Consumption Ethiopia Consumption Uganda
Sources: Production data: FAOstat; Consumption data:
Minten et al. (2018); Van Campenhout et al. (2019);
Trade data: Comtrade
Production and Consumption Net Exports

DATA
Ethiopia
• Collected in January/February2018 around Addis
 870 Farmers (317 sell fresh milk)
 50 Traders
 254 Retailers
Uganda
• Collected in September 2018 in the central milk shed north of Kampala
 1,264 Farmers
 440 Traders
 55 MCCs

TECHNOLOGY AND THE VALUE CHAIN

CROSSBRED COWS
Adoption of Crossbred Cows Price of Crossbred Cows

CONCLUSION
• Between country price differences  trade position
• Within country price differences  value chain structure and
use of modern technology
• Shorter value chains not necessarily more efficient than longer
value chains
• Use of technology improves milk quality and reduces the impact of
farmer's remoteness on prices

Leading the way – FDI and dairy value chain
upgrading in Uganda
Bjorn Van Campenhout
Wednesday, June 24, 2020

BACKGROUND
DVC in Uganda have transformed dramatically over the last few decades
• Increase in local consumption and exports
• Increase in production and processing capacity
• Facilitated by policy reforms
• => vibrant sub-sector with dairy becoming the third most important
export commodity
Describe endogenous technological and institutional innovations that
both:
• Enabled VC up-grading
• Resulted from modernizing value chains
Observational data collected at different nodes – compare modern value
chains to traditional ones.

STUDY AREA
• Uganda is organized in milk
sheds
• Two types of value chains:
– Southwestern milk shed =
modern export oriented VC
– Central milk shed =
traditional local market
oriented VC
• Data collected on 4 actors
– Producers -1600
– Traders - 700
– Milk collection centers - 100
– Processors - 2

MILK COLLECTION CENTERS
• 60 MCCs in Central – 160
MCCs in Kiruhura alone!
• Average distance to MCC is 10
km in Central versus 5.4 km in
SW
• Offer a range of mid-stream
services
• Medicines and vaccinations
(acaricides!)
• Milk cans (sanitation)
• Credit/loans
• training

PRODUCTION
Other innovations at
this level include:
• Paddocking
• Dams for water
• Cooperative
membership
• Access to
credit/financing for
investment
• Participate in trainings

CONCLUSION
• MCCs are central, providing many of the support services that
enable other actors to produce enough milk and maintain milk
sanitation levels necessary for an export sector to emerge.
• But MCCs cannot do it alone:
– Ticks become resistant to acaricides and there are signs of
disadoption – R&D is beyond capacity of MCCs
– Artificial insemination too complex to organize
– Feed sector needed to increase yields of cross-bred cows
• Lack of support service sector also at processor level
– Knowledge on processing is scarce – experts need to be flown in
– Lack of industrial base – packaging material needs to be imported
from Kenya

MORE INFORMATION
Van Campenhout, Bjorn; Minten, Bart; and Swinnen,
Johan. 2019. Domestic versus export-led agricultural
transformation: Evidence from Uganda’s dairy value chain.
IFPRI Discussion Paper 1883. Washington, DC:
International Food Policy Research Institute (IFPRI).
https://www.ifpri.org/publication/domestic-versus-export-
led-agricultural-transformation-evidence-ugandas-dairy-
value

IFPRI-ESSP: http://essp.ifpri.info/
EIAR: http://www.eiar.gov.et/
PSI: https://psi.gov.et/
IMPROVING EVIDENCE FOR BETTER POLICY MAKING IN
ETHIOPIA’S LIVESTOCK SECTOR
Virtual Seminar | June 24, 2020

Improving evidence for better policy making in Ethiopia’s livestock sector

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