AFRICAN POTATO ASSOCATION CONFERENCE 2013

Naivasha, Kenya, June 30 – July 4, 2013

Ex-ante Evaluation of Improved Potato Varieties for Sub-Saharan

AfricaUlrich Kleinwechter, Guy Hareau, Merideth Bonierbale,

Manuel Gastelo and Dieudonne HarahagazweInternational Potato Center (CIP)

Outline

1. Introduction2. Methodology: The IMPACT model3. Scenario: Improved potato varieties for SSA4. Results5. Conclusions

1. Introduction

• Strong expansion of potato production and consumption in SSA (Low et al., 2007)

• Multiple and important roles in local food systems• Increase food availability and aggregate efficiency of

food systems• Short vegetation cycle and suitability to marginal environment

• Provision of income generation opportunities • Cash crop and processing

• Grown in regions with high incidence of poverty, undernutrition and food insecurity and high population density

1. Introduction

• Steady but slow yield growth in the past, main production increases from area expansions

• High potential of technological innovations to increase productivity• Potentially high returns on investment and strong impacts on poverty

and hunger (Anderson et al. 2010)

Technological improvements in potatoes “an underexploited resource” (Alexandratos, 1997)

• Ongoing breeding efforts by CIP and NARS in the region• What potential impacts can be expected from future

improvement of potato varieties for SSA?

Ex-ante assessment of potential impacts using an agricultural sector simulation model

2. Methodology: The IMPACT model

• Integrated modeling framework which combines an economic global agricultural sector model with a water simulation model• Food module

• Projections of agricultural production, demand, trade flows and prices on a regional scale (countries or aggregates)

• Partial-equilibrium model• 40 agricultural commodities• 155 regions and 126 water basins, which combine into 281 “food

production units” (FPUs)• Water module

• Simulation of water availability for agriculture and other uses• Multi-period model: 2000-2050

2. Methodology: The IMPACT model

2. Methodology: The IMPACT model

• Agricultural production depicted by area and yield functions:

Yield shifterIntegration of new technologies via shifters in yield functions

3. Scenario- Description of the technology

• Improved potato varieties for SSA• Higher yield potential• Late-blight and virus resistance• Heat tolerance• Processing quality

• 30% higher yields• Nine target countries• Total investment: 9.8m US$ (4.29m NPV,

2000 constant prices)• Project duration: 12 years Source: Theisen and Thiele (2008).

EthiopiaUganda

Rwanda

Burundi

DR Congo

Kenya

Tanzania

MozambiqueMalawi

3. Scenario- Project description and cost

Activity Description Output Duration Total cost1. Breeding at CIP

One breeding cycle, starting from LBHT population

Advanced clones with improved traits

4 years 3.5m US$

2. Breeding and seed multiplication at NARS

Further selection, seed multiplication

Improved potato varieties, potato seeds for dissemination

4 years 3.5m US$

3. Dissemination Dissemination of potato seeds, extension

New varieties adopted by farmers

4 years 2.1m US$

Total 12 years 9.1m US$

3. Scenario - Dissemination and adoption

• Release: 2020• Four tier model of adoption

• Very low: 5% after 10 years (MLW, MOZ)• Low: 10% (DRC,TZA)• Middle: 20% (BUR, ETH, KEN, UGA)• High: 30% (RWA)

• Analysis of three adoption cases• “High”: as above• “Medium”: 2/3 of “high”• “Low”: 1/3 of “high”

0

20

40

60

80

100

% o

f cul

tivat

ed a

rea

High adoption

Traditional varieties Improved varieties

0

20

40

60

80

100

% o

f cul

tivat

ed a

rea

Low adoption

Traditional varieties Improved varieties

0200400600800

100012001400160018002000

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

2020

2022

2024

2026

2028

2030

2032

2034

2036

2038

2040

2042

2044

2046

2048

2050

Kenya

Traditional (High adoption) Improved (High adoption)

Tota

l sup

ply

of p

otat

oes

[100

0 m

t]4. Results- Production

4. Results- Production

Cha

nge

agai

nst b

asel

ine

[%]

0123456789

10Total potato supply in target countries, 2050

Low adoption Medium adoption High adoption

4. Results - Prices

-0.14

-0.12

-0.1

-0.08

-0.06

-0.04

-0.02

0

Potato Sweet potato Cassava Rice Wheat

World market prices of selected commodities, 2050

Low adoption Medium adoption High adoption

Cha

nge

agai

nst b

asel

ine

[%]

4. Results - Consumption

0

0.02

0.04

0.06

0.08

0.1

0.12Per-capita potato consumption, 2050

Low adoption Medium adoption High adoption

Cha

nge

agai

nst b

asel

ine

[% ]

4. Results - Economic welfare

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0Net welfare changes

Low adoption Medium adoption High adoption

NP

V

[m U

S$

at 2

000

cons

tant

pric

es]

4. Results - Returns on investment

00.10.20.30.40.50.60.70.8

IRR

Low adoption Medium adoption High adoption

4. Results - Global effects

-800-600-400-200

0200400600800

10001200

∆ Producer surplus ∆ Consumer surplus ∆ Net welfare Net benefits

Welfare and global benefits

Low adoption Medium adoption High adoption

NP

V

[m U

S$

at 2

000

cons

tant

pric

es]

5. Conclusions and outlook

• Positive production impacts in target countries• Positive net welfare effects and high ROI in target

countries • Comparable with findings from previous impact

evaluations of improved varieties• Investment in improved potato varieties justified from

economic point of view• Global analysis

• Consumers benefit • Producers lose • Positive net benefit

5. Conclusions and outlook

• Pivotal role of adoption levels• Importance of market acceptance and sufficiently good

seed systems for quick dissemination and adoption• Complementary investments in seed systems

• Showcase application of IMPACT modeling framework for ex-ante assessment of agricultural technologies

• Advantages• Global geographic coverage, comprehensive commodity

coverage• Capture complex market-mediated interactions across

commodities and countries• Scope for improvement:

• Assumptions on costs, adoption and dissemination• Combination of IMPACT with biophysical modeling tools

(crop models, pest and disease models)• Improvement of baseline data (FAO!)

Thank you for your

attention!

References

Alexandratos, N. (1997). World agriculture: towards 2010 : an FAO study. Chichester, New York, Brisbane: Wiley.

Anderson, P., Barker, I., Best, S., Bonierbale, M., Crissman, C., Hareau, G., & Leon Velarde, C. (2010). Importance of roots and tubers in the world food system; digging up the evidence. Unpublished manuscript, Lima, Peru, International Potato Center (CIP).

Low, J., Barker, I., Bonierbale, M., Crissman, C., Forbes, G., Lemaga, B., & Priou, S. (2007). Emerging trends and advances in potato research relevant to defining the way forward for the potato sector in Sub-Saharan Africa. African Potato Association Conference Proceedings, Vol . 7 (pp. 1-17). Alexandria, Egypt.

FAO. (2012). FAOSTAT database.Theisen, K., & Thiele, G. (2008). Implementing CIP’s Vision: Impact targeting.

Lima, Peru.