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

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

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

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

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

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

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)

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

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

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)

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)

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