Presentation by Dr. Bekele Shiferaw (CIMMYT) at Wheat for Food Security in Africa conference, Oct 8, 2012, Addis Ababa, Ethiopia.

1. Potential economic profitability and
competitiveness of wheat production
in SS Africa
Bekele Shiferaw, Asfaw Negassa, Jawoo Koo, Kai
Sonder, Melinda Smale, Stanley Wood, Hans Braun,
Thomas Payne, Zhe Guo, Sika,Gbegbelegbe
Wheat for Food Security in Africa Conference
8-10 October 2012, Africa Hall, UNECA, Addis
Ababa, Ethiopia

2. Outline
• Introduction –
– Widening gap and challenges to food security
– Can SS Africa produce some of its requirements to
reduce dependence on imports?
– How large is this potential?
• Methodology for analysis of SS Africa’s potential
• Main findings of the study
• Production potential
• Conclusions
• Policy implications

3. Widening gap – per capita consumption
and production
60
Wheat self-sufficiency (%),
2007-2009
60
50 53.3
50 46.1 45.8
40.7
40 40
30
30 20
10
2.6 1.6
20 0
Eastern Middle Western Northern Southern Africa
Africa Africa Africa Africa Africa
1960
1970
1980
1990
2000
2010
Per capita consumption Per capita production
Source: Based on FAOSTAT database.

4. Average area and production of wheat in
Africa (2008 - 2010)
Country Area (1000 ha) Production (1000 Self-sufficiency (%)
tons)
Algeria 1,585.1 2,388.1 29.33
Ethiopia 1,520.7 2,725.4 64.33
Egypt 1,283.2 7,889.7 45.78
South Africa 649.5 1,839.3 59.50
Tunisia 585.2 1,131.6 40.93
Sudan 308.8 543.9 25.38
Kenya 140.6 356.0 40.12
Libya 133.3 105.0 6.71
Tanzania 49.0 92.9 11.00
Rwanda 48.1 72.5 73.01
Nigeria 34.7 51.3 1.40
Others 141.8 340.9 5.24
Africa 9,376.0 22,542.3 38.8

5. Widening gap between wheat production and
consumption in Africa
All Africa Sub-Saharan Africa
25
Million tons
20
15
10 Gap
5
0
1977
1961
1965
1969
1973
1981
1985
1989
1993
1997
2001
2005
2009
Demand Production

6. Trends in wheat self-sufficiency ratio
for selected regions in Africa (1961-2010)
East Africa Middle Africa North Africa
90 60 80
80 40 70
70 60
60 20
0 50
50
40 40
-20
1960
1970
1980
1990
2000
2010
1960
1970
1980
1990
2000
2010
1960
1970
1980
1990
2000
2010
Southern Africa West Africa Africa
250 20 80
200 15 70
150 10 60
100 5 50
40
50 0
1960
1970
1980
1990
2000
2010
1960
1970
1980
1990
2000
2010
1960
1970
1980
1990
2000
2010
Source: Prepared by authors based on FAOSTAT database.

7. Challenges of reliance on import markets
• Weather induced supply disruptions
• Price spikes and price volatility in food markets
• Diversion of maize for biofuels production and pressure on
food prices
• Speculative selling and buying behaviors
• Wheat export restrictions by exporting countries
• Foreign exchange shortages by SSA countries
 Are African policy makers willing to take this risks for
national food security?
 Can this import dependence be reduced through
domestic production in SS Africa?

8. Objectives of the study
• Assess to what extent
domestic wheat production
in selected countries of SS
Africa would be agro-
ecologically feasible and
economically profitable and
competitive to imports
under rainfed systems using
existing varieties.
• Jointly conducted with IFPRI
(HarvestChoice) and
CIMMYT

9. Modeling approach
• GIS analysis. A number of biophysical suitability mapping
approaches were evaluated and utilized to delineate suitable
agro-ecologies as a basis for running the crop growth model.
• Crop growth simulation. CERES-Wheat model in the DSSAT was
used to estimate rainfed wheat yield responses at the pixel level:
• No fertilizer
• 50% of recommended fertilizers
• 100% of recommended fertilizers
• Fertilizer and grain transport cost modeling. Spatial analysis
using road network and land cover data to estimate pixel-specific
unit transport cost (for fertilizer and wheat produce).
• Net economic returns – computed using pixel level import parity
prices for wheat and imported inputs

10. GIS analysis – suitability mapping
Ecocrop map IIASA FAO GAEZ map

11. Economic profitability analysis

12. Aggregation and sensitivity analysis
• If pixel level production is profitable using imported fertilizer and
import parity prices, wheat production is considered profitable and
competitive to imports.
• National potential is then estimated at different levels of profitability
and competitiveness by aggregating returns from pixel level simulations.
• Sensitivity analysis. The robustness of the estimated potential was then
evaluated against plausible changes in:
– wheat prices,
– fertilizer prices,
– grain yields,
– marketing costs, and
– climate change.

13. Map of study countries

14. Results and discussion

15. Yield under low
intensification (all pixels)
Country Average
(kg/ha)
Angola 1055
Burundi 2886
Ethiopia 2348
Kenya 3087
Madagascar 2175
Mozambique 1052
Rwanda 3681
Tanzania 1986
DRC 1655
Uganda 2861
Zambia 1462
Zimbabwe 911

16. Yield under medium
intensification (all pixels)
Country Average
(kg/ha)
Angola 1542
Burundi 3208
Ethiopia 2972
Kenya 3410
Madagascar 2605
Mozambique 1287
Rwanda 3986
Tanzania 2219
DRC 2059
Uganda 3383
Zambia 1933
Zimbabwe 1394

17. Yield under High
intensification (all pixels)
Country Average
(kg/ha)
Angola 1886
Burundi 3395
Ethiopia 3395
Kenya 3617
Madagascar 2874
Mozambique 1444
Rwanda 4151
Tanzania 2372
DRC 2325
Uganda 3728
Zambia 2252
Zimbabwe 1744

18. NER under Low
intensification (for pixels
NER>0)
Country Average NER Pixels with
(US$/ha) positive NERs
(%)
Angola 195 22
Burundi 905 100
Ethiopia 618 71
Kenya 802 91
Madagascar 524 73
Mozambique 111 15
Rwanda 1314 96
Tanzania 347 68
DRC 270 53
Uganda 742 99
Zambia 301 63
Zimbabwe 250 35

19. NER under Medium
intensification (for pixels
NER>0)
Country Average Pixels with
NER positive
(US$/ha) NERs (%)
Angola 250 28
Burundi 1010 100
Ethiopia 670 88
Kenya 885 92
Madagascar 651 76
Mozambique 128 19
Rwanda 1416 96
Tanzania 371 70
DRC 275 71
Uganda 898 100
Zambia 385 80
Zimbabwe 271 58

20. NER under High
intensification (for pixels
NER>0)
Country Average Pixels with
NER positive
(US$/ha) NERs (%)
Angola 275 32
Burundi 1061 100
Ethiopia 771 90
Kenya 931 92
Madagascar 731 76
Mozambique 145 21
Rwanda 1461 96
Tanzania 384 71
DRC 302 76
Uganda 994 100
Zambia 444 86
Zimbabwe 309 76

21. Potential area (>$200/ha) and production
(medium level of intensification)
Area (million ha) Production (million tons)
10% 25% 10% 25%
Mozambique 0.1 0.26 0.27 0.67
Burundi 0.14 0.34 0.45 1.11
Rwanda 0.14 0.36 0.61 1.51
Uganda 0.2 0.51 0.69 1.72
DRC 0.25 0.62 0.76 1.89
Kenya 0.67 1.67 2.65 6.63
Zimbabwe 0.81 2.03 1.72 4.3
Angola 0.92 2.31 2.67 6.67
Tanzania 1.21 3.02 3.62 9.05
Madagascar 1.27 3.17 4.74 11.85
Zambia 1.73 4.32 4.26 10.64
Ethiopia 2.6 6.5 9.42 23.55
All 10.04 25.11 31.86 79.59

22. Sensitivity analysis:
25% wheat price
decrease
Change in percentage of pixels with positive net economic returns
from baseline
DRC-44
Zambia -29
Tanzania -23
Zimbabwe -23
Madagascar -21
Mozambique -15
Angola -13
Ethiopia -13
Kenya -8
Burundi -3
Rwanda -1
Uganda -1
-40 -30 -20 -10 0
Change

23. Sensitivity analysis:
25% wheat yield
decrease
Change in percentage of pixels with positive net economic returns
from baseline
DRC -28
Zambia -23
Zimbabwe -21
Madagascar -15
Mozambique -14
Tanzania -14
Angola -8
Ethiopia -8
Kenya -7
Burundi -3
Rwanda -1
Uganda -1
-30 -20 -10 0
Change

24. Conclusions
• Strong evidence that there is large potential for
economically profitable wheat production in SSA to meet
the growing consumption demand
• Results are generally robust to plausible shocks.
– Low world prices of wheat and high fertilizer costs will
reduce the relative competitiveness of domestic production
– Fall in domestic yield will reduce competitiveness
– investment in R&D to increase yields and to reduce
production and marketing costs will increase it
• The limiting factors are not agro-ecological, they are rather
socio-cultural, institutional and policy impediments.

25. Policy implications
• How can Africa exploit this potential?
– Paradigm shift – policy dialogue with an open mind
to explore opportunities
– Action plan will vary by country/region and need to
analyze farming system constraints and other crops
– Adaptive research and extension to enhance farmer
awareness, access to seeds, inputs and knowledge of
improved practices
– Development of value chain opportunities
– Better food aid and import policies to reduce
negative effects on domestic producers

26. • Thank you!
• Asante sana!
• Merci
beaucoup!
• Shukran!
• Ameseginalehu!
Bekele Shiferaw:
b.shiferaw@cgiar.org

27. Per capita consumption of main cereals in Africa (kg/year)
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
1961 1964 1967 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009
Maize Wheat Rice

28. 0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
1961 80.0
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
Maize
1981
1982
1983
1984
1985
1986
1987
Wheat
1988
1989
1990
1991
1992
(kg/capita/year), 1961 - 2010
Rice
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Trends in annual per capita consumption of main cereals in Sub Saharan Africa
2007
2008
2009
2010

29. Import of main cereals into Africa (million tons)

30. Trends in Sub Saharan Africa's net export of main cereals (million tons), 1961 - 2010

31. Sensitivity analysis:
25% fertilizer cost
increase
Change in percentage of pixels with positive net economic returns
from baseline
DRC -2
Zambia -2
Ethiopia -1
Madagascar -1
Mozambique -1
Tanzania -1
Zimbabwe -1
Angola 0
Burundi 0
Kenya 0
Rwanda 0
Uganda 0
-2 -1.5 -1 -.5 0
Change

32. Sensitivity analysis:
25% marketing cost
increase
Change in percentage of pixels with positive net economic retur
from baseline
DRC-21
Zambia -14
Madagascar -11
Mozambique -9
Angola -8
Zimbabwe -7
Ethiopia -2
Burundi -1
Kenya 0
Rwanda 0
Tanzania 0
Uganda 0
-20 -15 -10 -5 0
Change