1. SUPPORTING STRATEGIC INVESTMENT CHOICES IN AGRICULTURAL TECHNOLOGY DEVELOPMENT AND ADOPTION 1. HarvestChoice & Technology Platform 2. Household data 3. Africa RISING M&E BELIYOU HAILE monitoring and evaluation CARLO AZZARRI microeconomics, poverty ELODIE VALETTE participatory GIS, spatial analysis CINDY COX technical writer, technology evaluation CLEO ROBERTS farming systems characterization IVY ROMERO administrative coordinator JAWOO KOO crop/technology modeling, MARIA COMANESCU web development, programming MELANIE BACOU project management, microeconomics QUEENIE GONG data management, SPAM S A R A S I G N O R E L L I Microeconomics, impact evaluation HO-YOUNG KWON crop and soil process modeling ULRIKE WOOD-SICHRA data management, SPAM, DREAM ZHE GUO GIS coordinator, market accessibility, remote sensing

2. HarvestChoice FIVE GUIDING QUESTIONS 1.Where are the poor, and what are their welfare status? 2.On what farming systems do the poor most depend? 3.What are the constraints affecting the productivity and market integration of those farming systems? 4.What present or prospective investments in technologies and practices might best address those constraints? 5.What will be the benefits of investment on productivity, income, and the reduction of poverty and hunger?

3. Production System & Market Access Analysis MESO SCALE Pixels as Units of Analysis Production System Ecosystem Services Infrastructure/Market Access Investment/Policy Analysis MACRO SCALE Aggregate, market-scale (geo-political) units Fixed Geographies of Analysis e.g., IMPACT/WATER, GTAP derivatives Flexible Geographies/Units of Analysis e.g., DREAM, MM models Aggregation By Commodity Urban/RuralConsumptionInputsProductionIncome tercileRegion Household Characterization MICRO SCALE Change (e.g., policy) Change (e.g., climate, technologies)

4. Data harmonization Up/down scaling Calibration HarvestChoice CELL5M (400+ 10 km spatial layers) Data API MAPPR TABLR 3 rd -party tools Web Map Service (WMS) BMGF Project Mapping Tool Africa RISING FAO HarvestChoice website Try: harvestchoice.org/mappr harvestchoice.org/tablr

5. Flagship Datasets SUB-NATIONAL POVERTY MAPPING Updated version using 24 nationally representative household surveys conducted in years circa-2008. SPAM 2005 Updated version including 42 crops to values centered around the year 2005, using more recent primary data from national statistics offices, ministries of agriculture, publications from other various organizations, and targeted internet searches. Underlying model is being developed as a customizable web application, in collaboration with GEOSHARE.

6. Ex-ante Modeling TECHNOLOGY EVALUATION Potential impact of agricultural technology adoption on productivity, globally simulated for maize, rice, and wheat. MODELING CONSTRAINTS Model-estimated rainfall variability impacts on yield variability, under intensification scenarios LOW INPUT HIGH INPUT

7. Ex-ante Modeling STRATEGIC ANALYSIS OF POTENTIAL INTERVENTIONS Spatially-explicit modeling of multiple management interventions in Gates focus countries

8. Data & Tools TECHNOLOGY PLATFORM* Providing evidences for the New Alliance partners and national stakeholders to make informed investment decisions for scaling-up technology adoption * HarvestChoice MINI in Country

9. Partner Supports PARTNERING WITH AGRA: SCALING SEEDS AND TECHNOLOGY PARTNERSHIP 1.Specifying and prioritizing and value-chains to focus; validating the selection of technologies to scale 2.Identifying the target areas to scale the technologies 3.Estimating potential impacts of the technologies, in terms of productivity and socio-economic aspects 4.Assessing the need for complementary technology investments to maximize the benefits from the technology 5.Help developing the M&E baseline through survey and/or existing databases 6.Evaluating the impact of subsidies on the attractiveness of identified technologies to the private sector 7.Monitoring and mapping the Partnership-invested activities of grantees and partners on the ground 8.Developing investment strategy to reduce the average distance from farmers to input agro-dealers SPECIFIC RESEARCH AREAS WE AGREED TO SUPPORT:

10. HOUSEHOLD SURVEY DATA

11. Poverty -> flagship, the most downloaded Consumption Subnational per-capita total consumption (in PPP$), extracted from 24 nationally representative household consumption and expenditure surveys conducted in various years circa-2005 (+-2 years) Nutrition Information collected from 60 DHS (Demographic and Health Survey) Phase 4, 5, and 6 (1999-2013) worldwide; 29 in Sub-Saharan Africa. Highly comparable across countries, wide spatial coverage, over time representation 1. Sub-national mapping (poverty, consumption, nutrition) 2. Agriculture Farming system characterization (crop mix) Use of inputs (land, fertilizers, seeds, irrigation, labor) and their combination Yield, production Livelihoods

12. 1. POVERTY, CONSUMPTION, NUTRITION Nutrition indicators child anthropometric indicators (stunting, wasting, underweight) BMI for women hemoglobin for women percentage of women and children with anemia DDS for women and children antenatal care infant/young child breastfeeding practices iron and vitamin A supplementation of women and <5 y.o. infant and child under 5 mortality rate percentage of children with diarrhea Various education decision power asset ownership (incl. livestock) wealth index dwelling conditions (drinking water, sanitation facilities, wall and roof material, cooking fuel, bednets) Poverty indicators poverty headcount ratio at $1.25 and $2 PPP/day poverty gap at $1.25 and $2 PPP/day poverty severity at $1.25 and $2 PPP/day std. dev. of poverty headcount ratio at $1.25 and $2 PPP/day number of poor at $1.25 and $2 PPP/day poverty density at $1.25 and $2 PPP/day Consumption indicators per-capita total consumption expenditure Gini index per-capita food consumption expenditure (in progress) …by region, urban/rural, household headship

13. Farming System Characterization Top 15 systems in Tanzania derived from AC 2007/08: HS analysis provides high granularity compared to Dixon farming system map. 2. AGRICULTURE

14. …by AEZ …by farming system 3. COMBINATION

15. consumption and child undernutrition

16. Maize yield production

17. Millet yield production

18. cattle stunting wasting

19. elevation wheat-> production yield

20. Low BMI LGP

21. Maize production yield

22. Rice production yield

23. Sorghum production yield

24. stunting poultry cattle

25. AFRICA RISING

26. How is Africa RISING linked to HarvestChoice?  AR needs to be spatially-informed, requiring granular information on a large suite of indicators  Both seek integration among different disciplines (agronomy, biophysical&crop modeling, economics)  Both are focused on farming system, ex-ante modeling, adoption study and scaling-up plan of agricultural technologies and innovation  HarvestChoice data need groundtruthing, indeed AR is an excellent opportunity for testing

27. Monitoring & Evaluation Support Africa RISING  Feed the Future Compliance: Conform to the FtF core indicators  Multi-scale, multi-site reporting: Meet stakeholder needs and support multi-scale/multi-site M&E  Monitoring and projection: Provide monitoring reports and short-term projections (targets) of key M&E indicators for intervention sites  Open-access data and analysis platform: Maintain a user-friendly, open-access M&E data management and analysis platform to serve the needs of SI stakeholders.  Quasi-RCTs design and implementation: Use randomization of control sites within the same stratum (identified by homogeneous agriculture potential) as intervention sites for Impact Evaluation Eastern & Southern Africa Maize-based Systems Sudano-Sahelian Zone Ethiopian Highlands Systems Sub- Systems + + + + + + Action Sites Three AR Mega-sites Fostering multi-scale spillover by design

28. Monitoring & Evaluation Support Africa RISING HIGHLIGHTS  Site Stratification and Selection/Re- Selection: Evidence-based, participatory approach to select intervention sites  Baseline Surveys: Design and development of survey toolkit using remote cloud-storing, tablets and intensive training  Project Mapping and Monitoring Tool: Web-based tool to provide spatially- disaggregated M&E analysis and support decisions and adjustments over project lifecycle, as well as data repository Site selection Survey design and training in Malawi Monitoring of activities and indicators of sites in Ethiopia

29. IE Design Beneficiary HHs Non-beneficiary HHs Control HHs Action Sites Control Sites Spillover effects Program impact BACK

30. ARBES Household summary contents TLocation info, GPS TRoster nEducation nLabor nHealth nWomen and child anthropometrics Agriculture -general- Crop inputs (Conservation Agr.) Crop production Crop inputs (costs) Crop inputs (labor time use) Crop inputs (seeds) Crop sales Crop storage Livestock ownership and income Livestock feed  Problems and coping strategies Agricultural extension and AR program Other income Credit Housing, utilities, assets, distance to services Subject welfare and food security Food Expenditures/ Consumption Non-Food Expenditures Shocks Re-contact info FIRST VISIT HeadIndividualBest Informed SECOND VISIT BACK

31. ARBES Qx Community summary contents 5 to 8 key community informants  Location info, GPS  Informants’ roster  Access to basic services  Agricultural labor, extension services, agricultural problems  Land use  Demographics, cooperatives, migration  Water access, shocks, food consumption  Market prices  Conversion of non-standard units