1. Priority-Setting for Agricultural Biotechnology in West Africa USAID/EGAT March 9, 2005 William A. Masters Purdue University

2. DSS’S” Price Quantity J (output gain) I (input change) QQ’ K (cost reduction) Variables and data sources Market data P,Q National ag. stats. Field data J Yield change×adoption rate I Input change per unit Economic parameters K Supply elasticity (=1 to omit) ΔQ Demand elasticity (=0?) ΔQΔQ P The economic gains from new technology are proportional to output before adoption (PxQ) times the probability of cost reduction (“K”) Figure 1. Economic impact assessment in one picture

3. Table 1. Concordance and the allocation of R&D investment in Mozambique (1990s) Share of Agricultural GDP Share of research expenditure Research intensity ratio Cassava44150.3 Maize16120.7 Pulses950.5 Peanuts750.6 Sorghum6101.6 Rice441.0 Cotton2156.4 Cashew273.7 Sweet potato11414.2 Source: Uaiene, Rafael, 2002. “Priority setting and resource allocation in the National Agronomic Research Institute, Mozambique” (Dec. 2002). Strategic targeting can be much improved through concordance…

4. Figure 2. Prevalence of stunting in Sub- Saharan Africa (latest available, includes sub- national data) Strategic targeting aims for large problems that are being missed by other investors

5. Fig. 3. Share of food production by crop, 1961-2002 Source: Calculated from data in FAOStat (2005), reproduced in Annex 1. The biggest needs are in cereals, cassava, and oilcrops

6. Source: Calculated from data in FAOStat (2005), reproduced in Annex 1. Fig. 3. Share of protein output by crop, 1961-2002 Cereals and oilcrops are especially important for food quality

7. Figure 5. Average yield of all cereals by region, 1961-2004 Source: Figures 5-10 calculated from FAOStat (2005) data There are huge catch-up opportunities for Africa to do what Asia did

8. Figure 6. Average yield of maize by region, 1961-2004 The catch-up opportunities are large in maize

9. Figure 7. Average yield of millet by region, 1961-2004 …but catch-up opportunities are big in small grains also!

10. Figure 9. Average yield of cassava by region, 1961-2004 There are huge catch-up opportunities in cassava

11. Figure 10. Average yield of other root crops by region, 1961-2004 and also catch-up opportunities in other root crops

12. Figure 8. Average yield of seed cotton by region, 1961-2004 Africa has already done relatively well in cotton

13. Figure 11. Public agricultural R&D per unit of agricultural land, 1971-91 (1985 PPP dollars per hectare) Africa’s lag is mainly driven by the relatively low level of R&D spending

14. Figure 12. Agricultural R&D intensity in West and Central Africa, 1971-2001 There is huge variation but no growth in R&D expenditure across the region

15. Can build on experience of seven Sahel regional workshops (1994-2002)  all participants use common spreadsheet methods formulas derived directly from graphical model using each kind of data in sequence for intermediate results with “open architecture” to facilitate adaptation  participants have access to small grants to implement priority-setting exercises to report their results at follow-on workshops From Priority-Setting to Capacity Building

16. Results and methods are well-tested across West Africa Strategic Targeting for Economic Gains