Post on 11-May-2015
description
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Agriculture and livelihoods in East Africa:
An overview from an economics perspective
Steffen Abele
April 2, 2008
IITA Headquarters, Ibadan, Nigeria
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Contents • Challenges in Eastern Africa
• Food security
• Agricultural commercialization
• Pests and diseases
• Impact of CMD and bxw
• CMD adoption study in Uganda
• Bxw impact study Uganda
• Cassava processing business in Tanzania
• C3P: Diseases, food security and GIS
• Other activities (CIALCA, impact in WA,
agronomy)
• Outlook: Activities in the coming years
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Challenges
in Eastern
Africa
Food security
Three categories of countries in Eastern Africa
Stably food secure (>2,100 kcal/cap/day):
Uganda (2,360)
Food secure but unstable (around 2,100
kcal/cap/day and slightly below):
Rwanda (2,100), Kenya (1,880), Tanzania
(1,960)
Food insecure (significantly below 2,100
Kcal/cap/day): Burundi (1,700), DRC (1,600)
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Challenges
in Eastern
Africa
Commercialization
Increase in cassava market (raw and
processed) from 2005-2010: Uganda: 11 %,
Tanzania 48 %
1 million mt required for cassava processing in
Uganda and Tanzania by 2010
10-15 % of the population could benefit from
cassava commercialization (raw and
processed) in Uganda and Tanzania
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Challenges
in Eastern
Africa
Pests and diseases
Banana xanthomonas wilt:
55 % production losses over a decade if
uncontained, major outbreaks in Uganda and
spreading westwards
Cassava mosaic disease:
Uganda and Western Kenya: CMD outbreak in
late eighties/early nineties with 80 percent
production losses, CMD spreading further
south-west
CBSD: Recent outbreaks, similar threats
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Variety Central
(%
farmers
adopting)
Eastern
(%)
Northern
(%)
N.Western
(%)
NASE 1 6 6 6 3
NASE 2 6 8 12 3
NASE 3 77 75 46 75
NASE 4 7 6 18 13
NASE 10 2 2 0 0
NASE 12 2 3 18 6
Adoption of
cassava
varieties in
Uganda
NASE 3 has in general lower yields than the other
varieties, but dominates through short maturity periods,
market demand and flour quality. Relatively lower
cyanide content and limited use seem to be of a lesser
influence
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Adoption of
cassava
varieties in
Uganda
Determinants of speed of adoption of
NASE 3
Variable Coefficient Std error Z stat
Distance 0.00091 0.00077 1.19
Age of Head -0.0076 0.0045 -1.69*
Educ of Head 0.00085 0.00067 1.28
Farm size -0.010 0.028 -0.37
H/hold size -0.0034 0.0010 -3.37***
FT Labor -0.0030 0.0024 -1.23
No. of hoes 0.0024 0.00087 2.83***
Ext. advice -0.0038 0.0022 -1.72*
Constant 4.36 0.33 13.00***
No. of obs = 216, LR chi2(8) = 26.20, Prob > chi2 = 0.0010, Pseudo R2 = 0.0158,
Log likelihood = -813.58
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Ex-ante
impact
assessment
of bxw in
Uganda
Price developments without and with bacterial
wilt
0
50
100
150
200
250
300
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Year
Ug
sh
s/k
g m
ato
ok
e
Baserun
Wilt
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Ex-ante
impact
assessment
of bxw in
Uganda
Potential economic losses through bxw
-350,000,000
-300,000,000
-250,000,000
-200,000,000
-150,000,000
-100,000,000
-50,000,000
0
50,000,000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Year
US
$
Total change Consumer welfare changes Producer welfare changes
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
•Welfare losses of 200 million $ p.a. (about
3 % of GDP) – a serious threat to economic
growth (which is 7 % p.a.)
•Most of the losses on the consumer side
•BXW is a macro-economic threat
•Threat could easily scale out to Burundi,
Rwanda, Eastern DRC – it becomes a
regional threat with possibly similar effects
Ex-ante
impact
assessment
of bxw in
Uganda
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Business
planning
• Comparison of profits in the initial setup
stages of processing sites
Zogowale
(flour)
Chisegu
(flour)
Mtimbwani
(starch)
Bungu
(chips)
Profits -1,640 1,876 6,448 2,212
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Business
planning
Bottlenecks to small scale businesses
• Low and erratic inflow of raw material (daily,
seasonal)
• Inefficient use of inputs (e.g. water), indicated
by volatile costs per unit processed
• Unstable demand at the beginning, project
members as “brokers”
• Difficult finance schemes (processors/farmers
want cash transactions, clients want bank
transactions)
• Diseconomies of small scale (see next slide)
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Business
planning
• Economies of scale
0
200
400
600
800
1,000
1,200
Status quo Full press capacity Full grater capacity Full mill capacity
Technology setup
Perf
orm
ance
Investment (100 $) Fixed costs (100 $) Costs of production (100 $) Revenues (100 $) Profits (100 $)
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Business
planning
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
C3P Objectives of the C3P food security
assessment
Link food security to crop diseases (bxw and
CMD)
Support GIS to target food insecure and
disease threatened areas
Support targeting across social strata
Shed some light on the economics of food
security
Create tools that allow short term surveys
on/assessments of food security (< 1 year)
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
C3P
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
C3P
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
C3P
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
C3P
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
C3P
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
C3PValidation of map indicators
Correlation coefficients
(significance levels)
Calorie production Maize equivalent of
income
Temporary and
permanent food
insecurity
-0.452
(.000)
-.179
(.109)
Regression
Variable
Coefficient t-value Significance level
Temporary and permanent
food-insecure people (%)
DEP
Calorie production -0.00892 -4.452 .000
Income square -0.00183 -1.837 .070
Constant 65.93800 16.276 .000
Adj. R2 0.218, n = 81. Source: Own data
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
C3P
Factors determining food production and
indicators for social targeting
Country Uganda Kenya Tanzania Burundi Rwanda DRC
Variable Sign
(t-value)
Sign
(t-value)
Sign
(t-value)
Sign
(t-value)
Sign
(t-value)
Sign
(t-value)
EXP +
(2.10)
+
(1.79)
+
(2.13)
+
(4.30)
+
(11.31)
+
(2.69)
EXP2 -
(-1.97)
-
(-1.86)
-
(-1.95)
-
-4.32
-
(-2.25)
-
(-2.32)
EDUCHEAD -
(-0.61)
+
(1.85)
-
(-1.03)
+
2.63
0.003
(0.16)
+
(17.80)
AGEHEAD -
(-0.41)
+
(0.87)
-
(-0.96)
+
4.11
+
(2.38)
+
(14.60)
HHSIZE -0.79
(-1.53)
-0.73
(-0.23)
-
-5.05
+
(0.88)
CASSLOSS -
(-3.63)
-
(-1.73)
-
(-1.65)
-
-2.06
-
(-2.35)
-
(-1.66)
SEXHEAD +
(2.78)
+
(0.54)
-
(-0.24)
+
3.94
-
(-3.17)
FARMLAB +
(0.39)
+
(7.83)
+
(2.90)
+
0.06
-
(-0.59)
LANDOWN +
(4.81)
-
(-0.14)
+
1.26
+
(0.13)
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
C3P –food
security
economics
Impact of cassava losses on food
expenditures
Variable Coefficient p-value
Per capita monthly hh food exp.
dependent
EXP 0.54 0.005
Caloric consumption 0.001 0.589
hdd 0.05 0.854
EDUCHEAD 0.05 0.613
AGEHEAD -0.11 0.296
HHSIZE -4.32 0.048
Cmdloss 0.01 0.097
SEXHEAD 0.11 0.543
FARMLAB 0.18 0.924
LANDOWN -0.44 0.042
Ky 55.48 0.007
Tz 39.68 0.04
Bu 25.03 0.030
Rw 44.00 0.000
DRC 126.9 0.000
CONSTANT 18.3 0.614
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Other
activities
• DGDC/CIALCA baseline surveys: 2,600 farm
datasets in Central Africa (Rw, Bu, DRC)
• Co-authoring papers on:
•Ex ante impact assessment of ag-research
in Nigeria
•Adoption meta study
• Some basic cassava agronomics in Kenya
and Uganda (as PhD supervisor)
International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
Outlook • Final econometrics and publication of C3P
results
• Publication of a synthesis of cassava impact
in Eastern Africa
• Publication of business planning study in
Tanzania
• Publication of Marketing Unit studies in
Southern Africa
• Backstopping DGDC CIALCA economics
• Impact assessment of Market Information
Systems in Uganda
• Continue food security and impact studies in
GLCI: Depict impact pathways