Africa RISING Research framework


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Presented by J. Rusike (IITA) at the Africa RISING West Africa Review and Planning Meeting Tamale, Ghana, 23-25 October 2012

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Africa RISING Research framework

  1. 1. Africa RISINGResearch framework J.Rusike (IITA) Africa RISING West Africa Review and Planning Meeting Tamale, Ghana, 23-25 October 2012
  2. 2. Context• Sustainably intensify 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 logic• Beyond the plot/field to consumers• Integrate multiple stakeholders• Staple foods + nutrition and diversification• Research backstops FtF investments
  3. 3. Purpose• Provide pathways out of hunger and poverty for SS families through sustainably intensified farming systems• Research contributes to development impacts of FtF
  4. 4. Objectives: Research • Identify & evaluate options for sustainable intensification • Evaluate, document & share experiences for delivering and integrating SI beyond research sites
  5. 5. Objectives: Development • Create opportunities for SS to move out of poverty and improve nutritional status • Facilitate partner-led dissemination of integrated innovations for sustainable intensification beyond sites
  6. 6. Outcomes: Research • Integrated innovations increase production & / or improve productivity in a sustainable manner • Aggregated impact contributes to ecosystem stability • Dissemination of integrated innovations for SI leads to impacts beyond sites
  7. 7. Outcomes: Development• Wider adoption of innovations identified and tested enhances livelihoods• Development community initiates programs on innovations by AR
  8. 8. Research design: hypotheses • INTEGRATION: Integrating technological components into SI systems more benefits to SS than single components • ADOPTION: Integrating technological components into SI systems stimulates adoption • TRADE-OFF: Offering interventions tailored to the context specific conditions lowers environmental damage • SEQUENCING: Right sequencing of integration of component technologies provides SI pathways • SCALABILITY: Agricultural SI interventions tailored to local context specific conditions are scalable to other settings
  9. 9. Research outputs• Situation analysis and program synthesis• Integrated Systems Improvement• Scaling and delivery of integrated innovation• M & E (Program-wide synthesis and co-learning)
  10. 10. 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 entry points for pathways• Inventory of innovations• Ex-ante potential of innovations• Priority setting and planning for integrated systems improvement• Program-wide synthesis and co-learning
  11. 11. Output: Integrated systems• Identify research teams within R4D platforms to lead innovation activities related to system improvement• Ex-ante technology evaluation, trade-off analysis, guide future research• Participatory evaluation and adaptation of appropriate combinations of technologies and interventions• New research challenges and opportunities emerging from the activities
  12. 12. 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 aggregate impact at landscape scale
  13. 13. Output: M & E• Sakana’s presentation
  14. 14. Methods• On-station/on-farm, FSR, Participatory technology evaluation and adaptation, PTD, FPR, FFS• 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• Move away from on-farm trials to design that allows farmers to select into adoption
  15. 15. Methods: Randomizedexperiments (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…
  16. 16. Methods: Platforms Premier Foods – AGRISERVE Ghana Grains Council Industrial maize Maize-soy processor Kumasi buyer Accra ADVANCE CANDEL Business plans & record Agrochemical keeping Sales importer Seed supplier supply CreditSTANBIC BANK Gundaa Trader Wumpini Services & agrochemicals inputs (ploughing, s Sales eed, fertilize r, thresher) USAID ADVANCE 2,686 farmer Training on outgrowers GAPs
  17. 17. 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
  18. 18. Thank you!