1. THE ROLE OF LIVESTOCK IN THE KENYAN
ECONOMY: Policy
Analysis Using a Dynamic Computable
General Equilibrium
Model for Kenya
09/09/2013
Ermias Engida
CONFERENCE ON MAINSTREAMING LIVESTOCK
VALUE CHAINS
ACCRA, GHANA
NOVEMBER 05-06, 2013
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2. IMPORTANCE OF LIVESTOCK IN A
DEVELOPING ECONOMY
 Livestock’s macro roles are not often recognized
• “Livestock revolution” - 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 can we generate with livestock
sector growth?
• General equilibrium analysis needed to capture these

3. 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

4. The existing Model
DYNAMIC CGE MODEL FOR KENYA
» We use Thurlow and Benin’s (2008) model
(“Agricultural Growth and Investment Options for Poverty Reduction in
Kenya”)
• General equilibrium: the model represents different
markets, all reaching equilibrium
• Dynamic: the model is solved recursively
 The model is calibrated on a SAM for 2007
Kenyan economy (Mabiso et al., 2012).
 53 activities; 24 AEZ specific agri. activities, and 29
non-agri., 53commodities, 19 factors, and 45
households (disaggregated by location and income level)

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

6. ...Modifications



09/09/2013 /


Developing a separate herd dynamic module
Coupling the herd dynamics with the economywide 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 the existing models (e.g. breeding
stocks as capital in livestock)
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7. Simulation and Results
Simulation specification
 Four sim. scenarios; BASE, CEREAL, LIVESTOCK and AGRIC
 Total Factor Productivity (TFP) shocks are applied on three
agricultural subsectors: cereals, livestock and other-agrilture
214.4
111.5
86.5
Cereal
Livestock
Other-agri
 Initial shares in total agricultural GDP: cereals
(27%), livestock (21%), and other-agriculture (52%)
 The TFP growth rates are adopted from Mabiso et al.
(2012)

8. ...Simulation specification
Simulation
2.87
3.04
SIM_AGRIC
0.90
BASE
3.67
4.48
2.87
3.04
SIM_LIVESTOC
K
Services
0.90
manufacturing
3.67
1.68
Other-AGRI
2.87
3.04
SIM_CEREAL
Livestock
0.90
0
4.48
cereal
2.87
3.04
SIM_BASE
0.90
0
1.68
The weighted average annual TFP growth
across all agricultural activities in;
CEREAL is 1.68 percent,
LIVESTOCK is 1.70 percent, and
AGRIC is 2.45 percent
CEREAL
Shocks
All Ag activities grow
at the previous trend
Maize, Wheat, Rice,
Sorghum, Millet
including root crops
grow faster
LIVESTOCK Beef, Dairy, Poultry,
Shoats and Other
livestock activities
grow faster
Agric
CEREAL + LIVESTOCK
activities grow faster

9. Results
09/09/2013
» The results reveal the importance of the livestock
sector in increasing various macro measures
(GDP, export earnings, factor returns) and combating
food insecurity
» Livestock TFP growth spurs overall economic growth
by both promoting livestock GDP and by supporting
the cereal sector.
» significantly strong growth potential in contrast to
previous thoughts
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10. …Results
» A 1% point of CEREAL sector growth impacts Ag and overall
GDP less than similar growth rates in LIVESTOCK
» Accelerated agricultural TFP expansion thus results in
significant export growth.
» In LIVESTOCK demand for imports is the largest, thus lower
real exchange rate appreciation is needed. As a result, total
export growth is the largest.
BASE
CEREAL
6.1
6.26
7
LIVESTOCK
AGRIC
6.57
6.59
6
5
Export pct
change
4
Real
exchange pct
change
3
2
1
0
-0.37
-1
-0.43
-0.24
-0.2

11. …Results
» In LIVESTOCK, demand for existing livestock factor
increases the least and so does its price and returns.
However, demand for land is instead quite strong.
» Returns to land held by poor households rises the
most in the LIVESTOCK simulation.
» Cereal activities are intensive in the use of land and
labor
fliv
LIVESTOCK
flnd
CEREAL
BASE
flab
0.0%
2.0%
4.0%
6.0%
8.0%

12. …Results
» factor returns increased for all factors in all the
simulations
» significant positive growth in households’ income
» Rural households gain the faster growing income as
compared to their urban counter parts.
» Semi arid areas are getting better as compared to
the others.
» Livestock simulations are still exhibiting strong
effects on households’ income too. It is stronger in
Arid and Semi-arid areas as households in these
areas got 95% of their income from livestock
activities.

13. Policy recommendations
» Importantly, as factors are dynamically re-allocated
between agricultural activities, the inefficiency of
strategies focusing on cereal sector development
alone was highlighted.
» Investing more in enhancing livestock activities’
growth has huge implication in poverty reduction
and narrowing the income gap.
» Thus it is better to give equal policy priority emphasis
to the livestock sector and plan livestock – cereal
sub-sectors joint growth instead of cereal sub-sector
growth alone.
» Thus, balanced agricultural growth, in which
productivity gains are more evenly distributed across
sub-sectors, is preferable.

14. 09/09/2013
THANK YOU!
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