Introducing the Africa RISING Research framework

Joseph Rusike IITA)

Africa RISING

East and Southern Africa Research Review and Planning Meeting, Arusha, Tanzania, 1-5 October 2012

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

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

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

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

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

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

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)

Research outputs• Situation analysis and program synthesis

• Integrated Systems Improvement

• Scaling and delivery of integrated innovation

• M & E (Program-wide synthesis and co-learning)

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

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

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

Output: M & E • Sakana’s presentation

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

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…

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

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 where unlikely to be adopted

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 where unlikely to be adopted

Methods: Roll out: MCC-GhanaChris Udry, Ernest Aryeetey, Dean Karlan, Isaac Osei-Akoto

Thank you!