Presented by Joseph Rusike (IITA) at the Africa RISING East and Southern Africa Research Review and Planning Meeting, Arusha, Tanzania, 1-5 October 2012
1. Africa RISING
East and Southern Africa Research Review and Planning
Meeting, Arusha, Tanzania, 1-5 October 2012
Introducing the Africa RISING
Research framework
Joseph Rusike IITA)
2. Context
• Sustainably intensify household food, cash crop and
livestock production in FtF target areas (West Africa,
ESA, Ethiopian highlands)
• In line with USAID missions
• In line with the CRP 1.1 and 1.2
• Farm-level issues to landscape to markets (beyond the
plot and field to consumers)
• Integrate multiple stakeholders
• Staple foods within major farming systems with links to
nutrition and diversification
• Research backstops FtF investments
3. Purpose
• Provide pathways out of hunger and poverty for small holder
families through sustainably intensified farming systems that
sufficiently improve food, nutrition, and income security,
particularly for women and children, and conserve or enhance
the natural resource base
• Research contributes to the developmental aims FtF
4. Objectives: Research
• Identify & evaluate demand-driven options for sustainable
intensification that contribute to rural poverty alleviation,
improved nutrition and equity and ecosystem stability
• Evaluate, document & share experiences with approaches for
delivering and integrating innovation for sustainable
intensification in a way that will promote their uptake beyond
the Africa RISING action research sites
5. Objectives: Development
• Create opportunities for smallholders (within Africa RISING
action research sites) to move out of poverty and improve
their nutritional status – especially of young children and
mothers – while maintaining or improving ecosystem stability
• Facilitate partner-led dissemination of integrated innovations
for sustainable intensification beyond the Africa RISING action
research sites
6. Outcomes: Research
• Integrated innovations increase production & / or improve
productivity in a sustainable manner for targeted households
at Africa RISING research sites
• Aggregated impact of these farming practices at household
level contributes to an improved understanding of ecosystem
stability at the landscape level
• Dissemination of integrated innovations for SI leads to
impacts beyond the Africa RISING action research sites
7. Outcomes: Development
• Wider adoption of innovations identified and tested by the
program’s outputs within the Africa RISING action research sites
enhances livelihoods through increased agricultural output, income
diversity, reduced vulnerability to adverse environmental and
economic challenges and improved nutrition and welfare; especially
of young children and mothers
• Development community initiates programs, based on the
knowledge tools and innovations developed and promoted by Africa
RISING, that are directed at developmental goals that are consistent
with the Africa RISING program purpose
8.
9. Research design: hypotheses
• ADOPTION rates for any innovation (combinations of technologies and
management practices and knowledge) are enhanced by targeting on the
demand from and capacities of potential adopters
• INTEGRATION: Innovations with components that mutually reinforce whole
farm performance/productivity produce greater and more sustained benefits
than the joint adoption of equally effective single purpose technologies and
practices
• TRADE-OFF: Effective targeting of innovations also reduces the negative impacts
of trade-offs between farm productivity and environmental sustainability and
helps to identify potential “win-win” options for SI
• SEQUENCING: Adoption of innovations that lead to SI is affected by the
sequence in which the component technologies, practices and knowledge are
integrated and applied
• SCALABILITY: A research approach based on targeting and evaluating SI-related
innovations, in context, increases the relevance of findings from action research
sites and enhances their scalability to similar strata elsewhere (i.e. to similar
development domains and households typologies in other locations)
10. Research outputs
• Situation analysis and program synthesis
• Integrated Systems Improvement
• Scaling and delivery of integrated innovation
• M & E (Program-wide synthesis and co-learning)
11. Output: Situation analysis
• Determine development domains (agro-ecological potential, market
access, and population density)
• Prioritize target areas (welfare, sustainability, farming systems,
degradation, governments’ & USAID priorities)
• Develop farm household typologies
• Identify pathway entry points
• Inventory of innovations
• Ex-ante potential of innovations
• Priority setting and planning for integrated systems improvement
• Program-wide synthesis and co-learning
12. Output: Integrated systems
• Identify research teams within R4D platforms to lead
innovation activities related to system improvement
• Identify modeling/decision support tools for ex-ante
technology identification, trade-off analysis, evaluation
of the ex-ante sustainability and resilience of options,
and guiding future research
• Participatory evaluation and adaptation of appropriate
combinations of technologies and interventions
• Address new research challenges and opportunities
emerging from the activities
13. Output: Scaling
• Assess scalability of integrated innovations (meta-analysis of
options)
• Identify/develop scaling approaches for targeted integrated
innovations
• Pilot test scaling approaches from action sites within project
area
• Develop costed templates for scaling by development
investors
• Evaluate aggregated impact of household level interventions
at landscape scale and beyond
15. Methods: PTD, PRA,
• (de Janvry, A., Dustan, A., Sadoulet, E., 2010. Recent advances in
impact analysis methods for ex-post impact assessments of
agricultural technology: Options for the CGIAR. University of
California at Berkeley. < http://impact.cgiar.org/meetings-and-
events> ).
• Participatory technology evaluation and adaptation, Participatory
Action Research, FPR
• Pilot technology on small test plots allocated randomly to treatment
and controls (on-station/on-farm) to estimate gains of technology
• Farmers participating not representative of adopters
(placement/selection biases)
• Researchers/Extension agents/NGO staff induce different behaviour
from actual adopters
• Approach untenable for impact evaluation
16. Methods: Randomized
experiments (or natural)
• Natural or randomized experiments village,
community is unit of randomization/individuals
unit of observation
• Many villages in geographically distinct
areas=>scalability
• Withhold treatment from some villages but data
still collected…
17. Methods: RCT: Supply side
interventions
• Choose villages that do not have the technology
• Randomly choose a subset of treatment and control
villages
• Sell technology at market prices i.e. agro-dealers or
production and marketing contracts through
agribusiness firms
• Adopters farmers adopting technology when
available for purchase
18. Methods: Roll out over time
• Match villages in pairs based on observables (using
as many characteristics as possible)
• Randomize Treatment and Control within each pair
• Randomly choose say 5 pairs of villages
• Stratify the sample to obtain better randomization
results
• Rollout across villages can start from the most
favorable to the least favorable pair without
imposing a bias on measured impacts
• Do not sabotage technology by introducing to areas
19. Methods: Roll out over time
• Match villages in pairs based on observables (using as
many characteristics as possible)
• Randomize Treatment and Control within each pair
• Randomly choose say 5 pairs of villages
• Stratify the sample to obtain better randomization
results
• Rollout across villages can start from the most favorable
to the least favorable pair without imposing a bias on
measured impacts
• Do not sabotage technology by introducing to areas
20. Methods: Roll out: MCC-Ghana
Chris Udry, Ernest Aryeetey, Dean Karlan, Isaac Osei-Akoto