This document summarizes a study on the role of livestock in the Ethiopian economy using a dynamic computable general equilibrium (CGE) model. The study develops a herd dynamics module and couples it with an existing CGE model of Ethiopia. Simulation results show that livestock sector growth increases incomes, particularly for the poor, through factor markets. Livestock growth has marginally smaller effects on food consumption than cereal growth but still significantly improves welfare. The study finds that accounting for crop-livestock interactions is important and extensions could further examine environmental and demographic linkages.

1. THE ROLE OF LIVESTOCK IN THE
ETHIOPIAN ECONOMY: A DYNAMIC CGE
ANALYSIS
Ayele Gelan, ILRI
Ermias Engida, IFPRI/ESSP
Stefano Caria, DRMFSS
Taking Stock of the Economics of The Livestock
07/11/2011
Sector in Ethiopia, Addis Ababa, Ethiopia 1
November 4, 2011

2. TOPICS OF DICUSSION
 Study contexts and motivations
 Approaches and methods
 Overview of existing model and its
modifications
 Simulation results

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Concluding remarks and future research 2

3. IMPORTANCE OF LIVESTOCK IN A
DEVELOPING ECONOMY
 Livestock’s macro roles are not often recognized
• Growing demand for meat and dairy products
• Crop-livestock interactions (e.g., draft power, manure, crop
residue feed, etc)
• Livestock products and agro-processing
(e.g., dairy, leather, etc)
 How high are macro multipliers from livestock
sector growth?
• How much income growth and poverty reduction can we
generate with livestock sector growth?
• General equilibrium analysis needed to capture these

4. POLICY AND RESEARCH PRIORITIES
 NEPAD (2006) recognized the importance of
integrating the livestock sector into the CAADP
framework
 Diao and Pratt (2008) conclude that “growth in
staples is the priority for poverty reduction”
• Combining growth in staples and livestock has high economic multipliers
& strong poverty reduction gains in food deficit areas
 Dorosh and Thurlow (2009) - poverty-growth
elasticities
• Cereals have highest rural poverty reduction potential

5. CURRENT STUDY - APPROACHES
 Developing a herd dynamic module
 Coupling/integrating the herd dynamics module
with the economy-wide model
 Nesting the biological and the economic processes
 Establishing stock-flow relationships in existing
economy-wide models (e.g. livestock as capital and
livestock products)
 Revising and improving the system of economic
accounts in existing models (e.g., draft power as
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capital in cropping, breeding stocks as capital in
5
livestock, etc)

6. Male
Deaths
Young Immature Mature Other
economic
male male male uses
+
Births Sale of live
Off-takes animals
+
Young Immature Mature Yields/ Sales of
female female female animal products
=
Female
TR
deaths
-
costs of keeping
costs of keeping + costs of keeping +
= TC
mature animals
young animals immature animals
=
Production and economic flows (off-take, in-takes and others)
Reproduction and growth (growth, births, deaths) Gross margin

7. Condensed and adapted SAM for Ethiopia
(ETH birr million, 2005)
Live Pro (P-1)
Poultry (P-2)
Institutions
Milk (P-3)
Non-ag-C
Nonag-A
oth facts
Liv cap
Oag-A
Oag-C
AEZ-1
AEZ-2
AEZ-3
AEZ-4
AEZ-5
Total
S-I
AEZ-1 0 0 0 0 0 0 0 0 0 114 6 71 0 0 0 0 191
Livestock AEZ-2 0 0 0 0 0 0 0 0 0 5553 180 1907 0 0 0 0 7640
activities AEZ-3 0 0 0 0 0 0 0 0 0 983 26 754 0 0 0 0 1763
by AEZs
AEZ-4 0 0 0 0 0 0 0 0 0 3372 128 942 0 0 0 0 4442
AEZ-5 0 0 0 0 0 0 0 0 0 745 18 3205 0 0 0 0 3968
Oag-A 0 0 0 0 0 0 0 46974 19 0 0 0 0 0 0 0 46993
Nonag-A 0 0 0 0 0 0 0 234 121985 0 0 99 0 0 0 0 122318
Oag-C 0 0 0 0 0 2791 4610 0 0 0 0 0 0 0 48984 -173 56213
Non-ag-C 4 171 39 100 87 3025 52861 0 0 0 0 0 0 0 104730 31295 192314
Live Pro (P-
1) 0 0 0 0 0 0 940 0 0 0 0 0 0 0 7969 2229 11138
Livestock
products Poultry (P-2) 0 0 0 0 0 0 32 0 0 0 0 0 0 0 343 8 383
Milk (P-3) 0 0 0 0 0 0 430 0 0 0 0 0 0 0 7042 0 7473
Liv cap 59 2313 540 1352 1210 880 0 0 0 0 0 0 0 0 0 0 6353
Factors
oth facts 128 5155 1184 2990 2671 40297 63444 0 0 0 0 0 0 0 453 0 116323
Institutions 0 0 0 0 0 0 0 9005 70309 371 25 495 6353 116323 37153 0 240036
S-I 0 0 0 0 0 0 0 0 0 0 0 0 0 0 33360 2945 36305
Total 191 7640 1763 4442 3968 46993 122318 56213 192314 11138 383 7473 6353 116323 240036 36305

9. DYNAMIC CGE MODEL FOR ETHIOPIA
 We use Dorosh and Thurlow’s (2009)
model
• General equilibrium: the model represents different
markets, all reaching equilibrium
• Dynamic: the model is solved recursively
 Model is calibrated for Ethiopia using
2005/06 EDRI Social Accounting
Matrix
• 5 AEZs, 97 activities, 66 commodities, 27 factors

10. SIMULATION SCENARIOS
Simulation Shocks
 We simulate Total
Factor Productivity
BASE All Ag commodities grow at
(TFP) shocks to various 98-07 trend
subsectors CEREAL Cereals + vegetable/fruit +
(38%) enset grow faster
 Base growth follows
1998-2007 trend CASH CROP Cash crops and pulses
(29%) + oilseeds grow faster
 Additional shocks as in LIVESTOCK Livestock activities grow
Dorosh Thurlow 2009 (33%) faster
(obtained in discussions CAADP All Ag commodities grow
with MoA and CAADP) faster

11. … AGRI. SUB-SECTORS
Weighted average of TFP shocks
Size of sub-sector in 2005 to subsectors
22,000
Percentage
20,000 0.0% 2.0% 4.0% 6.0%
18,000 2.2%
Cereal only
Million Birr
4.3%
16,000
14,000 0.6%
Cash crop only
2.4%
12,000
0.5%
10,000 Livestock only
3.1%
Base Accerelated

13. 90000
85000
80000
Million Birr
75000
70000
65000
60000
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Base Cereal only Cash crop only Livestock only
Agricultural GDP 2006-2015

14. INTERSECTORAL LINKAGE EFFECTS
• CEREAL has the highest
Average growth rates 2009-15 sub-sector growth
Sub-sector Ag sector GDP GDP
BASE 3.7% 6.4%
CEREAL 6.4% 4.6% 6.6% • But about the same
aggregate agri. and GDP
CASH CROP 4.1% 4.2% 6.5%
growth effects
LIVESTOCK 5.5% 4.5% 6.7%
CAADP 5.9% 7.0%
• Different economic
linkages at wor

15. LIVESTOCK AND EXPORT
PERFORMANCE
Shares of agricultural export
value 2005-15 % change in total
1% export and real exchange
rate
15% 10.5%
10.4%
-1.0%
-0.9%
10.3% -0.8%
Percentage
Percentage
10.2% -0.7%
10.1% -0.6%
CEREAL 10.0% -0.5%
9.9% -0.4%
9.8% -0.3%
9.7% -0.2%
CASH CROP 9.6% -0.1%
9.5% 0.0%
LIVESTOCK
84%
Export pct change
Real EXR pct change (right axis)

16. RELATIVE FACTOR INCOME EFFECTS
% increase 2009-15 in factor
income: poor HH
Factor income of the poor Percentage
0% 20% 40% 60% 80% 100% 0% 10% 20% 30% 40% 50%
humid lowland
Labour
humid cereal
humid enset Land
drought prone
Livestock
pastoralist
Land Labour Livestock CEREAL CASH CROP LIVESTOCK

17. REAL CONSUMPTION EFFECTS
 The evolution of poor HHs Average growth rate 2009-15 of
rural poor HHs food consumption
consumption similar for Percentage
each simulation 0.00% 1.00% 2.00% 3.00% 4.00% 5.00%
BASE 3.58%
 Price effects more than
compensate lower income CEREAL 4.36%
effect of CEREAL
CASH CROPS 3.89%
• Cereals about 25pct of whole
consumption basket
LIVESTOCK 4.02%
• Rural poor HHs consumption
thus grows faster

19. KEY FINDINGS
 Livestock has important economic linkages, esp.
when we take into account complementarities
with crop production
 Livestock growth increases incomes of the
poor, particularly labor and land
 Livestock has marginally smaller
consumption effects and with smaller
productivity shocks, which means livestock
needs to be taken seriously in food security
policies

20. FUTURE EXTENSIONS
 By far the most important extension (in both
modelling contexts) - strengthening crop-livestock
interactions (e.g. crop residue)
 From social accounting to environmental accounting
(i.e., a third level nesting: biological => economic =>
environment)
 Livestock-environment interactions (the “long
shadow” story)
 Livestock-demographic-economic relationships (the
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livestock revolution story) 20

21. THANK YOU!
07/11/2011
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