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MAIZE AFS: Monitoring, Evaluation,
Learning and Impact Assessment
Paswel Marenya
Impact Assessment Focal Point Meeting
Standing Panel on Impact Assessment
(SPIA)
Boston Marriott Copley Place
Boston MA, July 29, 2016
Will MAIZE deliver on SLOs and IDOs (1)?Maize is an important staple:
Grown on
184 million hectares (M ha)
globally (FAOSTAT, 2013) Contributes over
20% of total
calories in human
diets in 21 low-
income countries
over 30% of calories
in 12 countries with
310 million people
16 of 22 most maize dependent countries are in Africa
Maize is to Africa and Central America what rice is to Asia
Will MAIZE deliver on SLOs and IDOs (2)?
Focusing on MAIZE AFS holds much promise for
positive impact
SLO 3: Improved natural resource systems and ecosystem services: water and nutrient use efficiency
SLO1: Reduced Poverty: yield enhancement, value addition, reduced post-harvest losses
SLO 2: Improved food and nutrition security for health: nutrient dense maize varieties available to 20 M people
How will it be done (1)?
• Emphasis on learning, feedback loops, pathways
– evaluate impact of “embryonic” technologies on limited
scale (e.g. targeted RCTs)
– consumer surveys, risk analysis and willingness to pay
• Macro level impact tracking:
– Focus on global MAIZE AFS (developing world)
– germplasm development, variety pipelines and release
– Global Maize impact assessment ongoing to track:
• Variety releases and catalogues
• Attribution of varieties to CGIAR/MAIZE
• Economic impacts
How will it be done (2)?
Expand the frontiers of adoption and impact
assessment
1. Cross-sectional surveys (micro-econometrics and
allied)
2. Panel surveys and panel econometrics (Adoption
Pathways, SIMLESA)
3. Policy and institutional pre-conditions for adoption
4. Broader, economy-wide impacts of variety
adoption
5. RCTs (DTMass, NuME)
6. Adoption dynamics and behavioral aspects
7. DNA fingerprinting
8. GIS, Bio Economic Modelling, Big Data Analysis
Where will the data come from? • Developing baselines and subsequent datasets
• Existing data or piggyback on an ongoing surveys: .
DT/STMA, DTMass, RCT on DT with insurance,
Adoption Pathways
• Household income and expenditure surveys
• Living Standards Measurement Studies-Integrated
Surveys on Agriculture (LSMS-ISA)
• Population and agricultural census and surveys
• Specialized surveys conducted by NARS and ARI
partners
• Case studies and data collected by individual
projects
• MAIZE and CGIAR commissioned impact
evaluations.
How will this feed into RBM?
• Agricultural research competes for resources with other investments
– MAIZE research will be no exception
• To prove it deserves the investments: MAIZE research should demonstrate impact
– individual farmers, their communities and national economies.
• From the CGIAR perspective
– important to demonstrate benefits and costs of delivering the products of MAIZE.
Value for Money in MAIZE Research
How will this feed into RBM (2)?
Core principles of RBM
1. Strategic planning
2. Outcome focus
3. Learning and adaptation based on performance
4. Accountability and transparency
5. Defining and revising the impact pathways at
CRP and FP levels
Who will do all this?
• Establishment of multi-disciplinary teams:
– foresight, impact assessment, gender, business,
anthropology, geography, geo-spatial sciences and bio-
economic
• Work with ARIs and NARs
– scientific contribution and achievement of ,
complementarities and synergies with in-house capacity
and needs.
• Work with Regional Organizations
– ASARECA and CARDESSA in eastern and southern
Africa; regional assessments in Asia, SSA and LA in
Phase-I
Some Examples (1)
Adoption/Impact
Assessment Publication
Topic/Theme of Paper Key Method
Abate et al., 2015
How sustained investment in
agricultural research and
development and policy
support by the national
government revolutionized
maize sector in Ethiopia
Review
Alene et al., 2009
Adoption of modern maize
increased from less than 5% of
the maize area in the 1970s to
about 60% in 2005, with return
on (R&D) of 43% in West and
Central Africa.
Economic Surplus
Beyene and Kassie,
2015
Social capital and networks
crucial in speeding up the
adoption in Tanzania
Duration analysis
Some Examples (2)Adoption/Impact
Assessment Publication
Topic/Theme of Paper Key Method
Erenstein et al., 2015
Optimal resource stewardship
possible with tradeoffs. E and S
Africa, Mesoamerica, North
Africa, S. Asia
Crop and system models,
econometrics etc
de Groote et al., 2016
MLN cost $180 worth of damage
in Kenya , showing potential
impact of tolerant maize
varieties
GIS, Surveys
Fisher et al., 2015
Determinants of Drought
tolerant maize adoption in
Eastern and southern Africa
Econometrics (cross sectional
data)
Kassie et al., 2015
Impacts of maize varieties most
prominent when farmers adopt
multiple practices in East and
Southern Africa
Econometrics (cross sectional
data)
Kathage et al., in press
In regions where returns to
hybrids are small, adoption is
low in Tanzania
Econometrics (cross sectional
data)
Some Examples (3)Adoption/Impact
Assessment Publication
Topic/Theme of Paper Key Method
Micheni et al., 2016
Yield increase, water use
efficiency and higher revenue
possible for maize farmers if
conserving practices
implemented in Kenya
Field Experiments
Zeng et al., 2015 (SPIA
sponsored DIIVA project)
The impact of maize yield
varieties on poverty positive in
Ethiopia. 0.8–1.3% drop of
poverty headcount ratio
Econometrics, Economic
surplus
Raghu et al., 2015
Stress tolerant varieties impact
positively on yield enhancement,
per-unit cost reduction and risk
reduction in marginal
environments of India
Econometrics (cross sectional
data)
Snapp and Fisher, 2015
Education, income, market
access, and availability of
improved storage technologies
had higher influence on dietary
diversity among maize growers in
Malawi.
Semiparametric econometrics,
PSM
Some Examples (4)
Adoption/Impact
Assessment Publication
Topic/Theme of Paper Key Method
Mutenje et al., 2016
Spouse's education , women's
intra-household
decision-making power, religious
affiliation predicted adoption.
Risk management was a motive
for adopting CA for maize
production in Malawi
Econometrics
Tesfaye et al. 2016
DT varieties could give a yield
advantage of 5–40% over the
commercial check variety across
drought environments in Malawi,
Mozambique, Zambia and
Zimbabwe
Bio economic crop modelling
using big data
Papers 2015
• Abate et al., 2015. Factors that transformed maize productivity in Ethiopia. Food
Security 7, 965-981.
• Beyene, A.D., Kassie, M., 2015. Speed of adoption of improved maize varieties in
Tanzania: An application of duration analysis. Technological Forecasting and Social
Change 96, 298–307.
• Fisher et al., 2015. Drought tolerant maize for farmer adaptation to drought in sub-
Saharan Africa: Determinants of adoption in eastern and southern Africa. Climatic
Change 133, 283-299.
• Fisher, M., Carr, E.R., 2015. The influence of gendered roles and responsibilities on
the adoption of technologies that mitigate drought risk: The case of drought-
tolerant maize seed in eastern Uganda. Global Environmental Change 35, 82-92.
• Holden, S.T., Fisher, M., 2015. Subsidies promote use of drought tolerant maize
varieties despite variable yield performance under smallholder environments in
Malawi. Food Security 7, 1225-1238.
• Jaleta et al., 2015. Determinants of maize stover utilization as feed, fuel and soil
amendment in mixed crop-livestock systems, Ethiopia. Agricultural Systems 134, 17-
23.
2015 (cont.)
• Khonje et al., 2015. Analysis of Adoption and Impacts of Improved Maize Varieties
in Eastern Zambia. World Development 66, 695-706.
• Liben et al., 2015. Dry Soil Planting of Maize for Variable Onset of Rainfall in
Ethiopia. Agronomy Journal 107, 1618-1625.
• Raghu et al., 2015. Adoption and outcomes of hybrid maize in the marginal areas
of India. Quarterly Journal of International Agriculture 54, 189-214.
• Smale et al, 2015. The Changing Structure of the Maize Seed Industry in Zambia:
Prospects for Orange Maize. Agribusiness 31, 132-146.
• Snapp, S., Fisher, M., 2015. “Filling the maize basket” supports crop diversity and
quality of household diet in Malawi. Food Security 7, 83-96.
• Tesfaye et al., 2015. Maize systems under climate change in sub-Saharan Africa:
Potential impacts on production and food security. International Journal of Climate
Change Strategies and Management 7, 247-271.
• Zeng et al., 2015. Ex post impacts of improved maize varieties on poverty in rural
Ethiopia. Agricultural Economics 46, 515-526.
Papers 2016 to date
• De Groote et al., 2016. Measuring rural consumers’ willingness to pay for quality
labels using experimental auctions: the case of aflatoxin-free maize in Kenya.
Agricultural Economics 47, 33-45.
• De Groote et al., 2016. Community-survey based assessment of the geographic
distribution and impact of maize lethal necrosis (MLN) disease in Kenya. Crop
Protection 82, 30-35.
• Gunaratna et al., in press. Women's and children's acceptance of biofortified quality
protein maize for complementary feeding in rural Ethiopia. Journal of the Science of
Food and Agriculture.
• Kathage et al., in press. Big Constraints or Small Returns? Explaining Nonadoption
of Hybrid Maize in Tanzania. Applied Economic Perspectives and Policy.
• Manda et al., 2016. Adoption and Impacts of Sustainable Agricultural Practices
on Maize Yields and Incomes: Evidence from Rural Zambia. Journal of Agricultural
Economics 67, 130-153.
• Manda et al., in press. Determinants of child nutritional status in the eastern
province of Zambia: the role of improved maize varieties. Food Security, 1-15.
• Micheni et al., 2016. On-Farm Experimentation On Conservation Agriculture In
Maize-Legume Based Cropping Systems In Kenya: Water Use Efficiency And
Economic Impacts. Experimental Agriculture 52, 51-68.
Thank you
for your
interest!
Photo Credits (top left to bottom right): Julia Cumes/CIMMYT, Awais
Yaqub/CIMMYT, CIMMYT archives, Marcelo Ortiz/CIMMYT, David
Hansen/University of Minnesota, CIMMYT archives, CIMMYT archives (maize),
Ranak Martin/CIMMYT, CIMMYT archives.