promising agricultural technologies: what evidence do we ... · how we can generate reliable...
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Promising agricultural technologies: What
evidence do we need on the profitability of
new technologies?
Bekele Shiferaw
CIMMYT
Evidence Summit Agenda (Detailed Draft)
June 1-2, 2011 – Washington, DC
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Outline
● Current challenges in estimating profitability of new technologies
● Some evidence on the profitability of maize and other crop varieties in Africa
● Need for broader view of profitability – need to look at ‘adoptability’
● Profitability and farmer variety adoption
● How we can generate reliable evidence
– Profitability/adoptability
–Adoption constraints
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CGIAR Technologies for Africa
Maize
● High yielding varieties
– Hybrids
– Open pollinated
● Drought tolerant maize
(DTM) varieties
● Quality protein maize
(QPM)
● Insect resistant maize
Other cereals (wheat, rice,
sorghum, pearl millet, etc):
● High yielding
● Pest and disease resistant
Legumes (pigeonpea, groundnut,
beans, chickpea, etc)
● High yielding
● Disease and pest resistant
Roots and tubers (potatoes,
cassava, etc)
Livestock and agroforestry
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Current challenges in estimating profitability of new technologies
● Yield and cost estimation
dependent on cross-
sectional small sample
and recall surveys
● No actual measurement of
land area, yield and input
use
● Poor representation –
agro-ecology, markets etc
● Poor data on risk and
inter-seasonal yield
variation
● Panel surveys with
repeated visits
● Actual measurement of
land area, yield and key
inputs (e.g. fertilizer)
● Representative sampling
to capture variation in
agroecology, markets etc
● Capture effect of weather
and growing conditions
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What we have on the on-farm yield and profitability of new DT varieties in Africa - Maize
Maize yield (tons/ha) and variance for different varieties
1.2
0.9
1.7
1.1
1.2
1.0
1.3
1.2
-0.5
0.0
0.5
1.0
1.5
2.0
Improved
(N=390)
Local
(N=521)
Improved
(N=764)
Local
(N=937)
Improved
(N=402)
Local
(N=490)
Improved
(N=475)
Local
(N=731)
Kenya Tanzania Malawi Uganda
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Maize - Returns to family labor and land
Net margins for maize by variety in selected ESA countries
(US$/ha)
217
143
312
187
239
177
85 57
-700
-500
-300
-100
100
300
500
Improved
(N=390)
Local
(N=521)
Improved
(N=738)
Local
(N=934)
Improved
(N=402)
Local
(N=491)
Improved
(N=475)
Local
(N=731)
Kenya Tanzania Malawi Uganda
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What we have on the on-farm yield and profitability of new varieties in Africa - Wheat
Yield of different wheat varieties in
Ethiopia (tons/ha)
2.72.4
-0.5
0.5
1.5
2.5
3.5
4.5
5.5
Improved (N=347) Local (N=638)
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Pigeonpea - Returns to family labor and land
Yields of pigeonpea by variety in selected
countries (tons/ha)
0.20.2
0.4
0.6
0.20.2
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
Improved
(N=262)
Local
(N=183)
Improved
(N=322)
Local
(N=1113)
Improved
(N=579)
Local
(N=363)
Kenya Tanzania Malawi
Net margins of pigeonpea by variety in selected
countries (US$/ha)
2831
150200
5164
-200
-100
0
100
200
300
400
Improved
(N=262)
Local
(N=183)
Improved
(N=316)
Local
(N=1106)
Improved
(N=579)
Local
(N=363)
Kenya Tanzania Malawi
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Groundnut - yields
Yields of groundnut by variety in selected ESA countries
(ton/ha)
0.450.43
0.81
0.330.35 0.33
0.87
0.64
-0.7
-0.2
0.3
0.8
1.3
Improved
(N=314)
Local
(N=299)
Improved
(N=20)
Local
(N=210)
Improved
(N=323)
Local
(N=502)
Improved
(N=1428)
Local
(N=1002)
Kenya Tanzania Malawi Uganda
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Broader view of ‘profitability’
● Adoptability of the technology is a function of market value plus other factors valued by farmers
● Other non-market traits may include:
– Risk (stress tolerance and stability of yield)
– Taste and nutrition
– Grain color
– Storage pests and storability
– Value of stover for feeding livestock
– Soil fertility restoration (e.g. legumes)
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Profitability per se does not explain adoption: Seed supply, credit, information, etc
Adoption constrains
82
59
18
6 8 10
56
34
23
44
0
10
20
30
40
50
60
70
80
90
Demand (+) Adopted Lack seed
supply
Lack credit Information Profitability
Want to adopt Not know
technology
Do not want
to adopt
Pe
rce
nt fa
rme
rs
Groundnut (Uganda) Pigeonpea (Tanz)
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How we can generate reliable evidence on adoption constraints for new technologies?
● Regional on-farm trials for promising varieties– Randomized control trial design
– Using local varieties as checks
– Representative systems (agroecology, etc)
– Actual measurement of yields, crop area, inputs, etc
● Technology adoption and impact studies– Panel data (plot, household, village)
– Experimental (RCTs, natural experiments) and quasi-experimental designs
– Representative and large scale