This chapter assesses the potential of farmer-to-farmer extension (F2FE) as a low-cost approach for promoting CSA. It is based on surveys of extension program managers and farmer-trainers in Cameroon, Kenya and Malawi who are involved in promoting a wide range of agricultural practices, including CSA. In the F2FE approach, extension programs provide education for farmer-trainers, who in turn educate other farmers, typically 17–37 per year. Extension program managers find this approach to be effective in boosting their ability to reach large numbers of farmers.
A decline in public sector extension services in developing countries has led to an increasing emphasis on alternative extension approaches that are participatory, demand-driven, client-oriented, and farmer centered. One such approach is the volunteer farmer-trainer (VFT) approach, a form of farmer-to-farmer extension where VFTs host demonstration plots and share information on improved agricultural practices within their community. VFTs are trained by extension staff and they in turn train other farmers.
The Unites States Agency for International Development (USAID) Feed the Future De-veloping Local Extension Capacity (DLEC) project conducted a three-country study on youth and EAS in Rwanda, Niger and Gua-temala. These case studies provided a land-scape analysis to inform actions to strengthen the inclusion of youth in EAS to improve their livelihoods and increase the effective-ness of EAS systems.
This chapter starting presenting the current status of agricultural research systems in SSA at national and regional levels against a backdrop of key policy changes and progressive elaboration of agricultural knowledge frameworks registered in the last decade or so. The section argues for endogenous mechanisms to encourage sustainable funding of agricultural research in the region. Section 2 discusses key trends and some innovative approaches that are helping bridge the supply and demand mismatch in AAS.
This study analyse how agricultural extension can be made more effective in terms of increasing farmers’ adoption of pro-nutrition technologies, such as biofortified crops. In a randomised controlled trial with farmers in Kenya, the authors implemented several extension treatments and evaluated their effects on the adoption of beans biofortified with iron and zinc. Difference-in-difference estimates show that intensive agricultural training can increase technology adoption considerably.
While education access has improved globally, gains are uneven, and development impacts driven by increases in education continue to be left on the table, especially in rural areas. Demand-driven extension and advisory services (EAS) – as a key institution educating rural people while providing agricultural advice and supplying inputs – have a critical role to play in bridging the education gap. This can help ensure that millions of young people successfully capitalise on opportunities in agriculture markets, as surveys in Rwanda and Uganda demonstrate.
Background
Weather risk is a serious issue in the African small farm sector that will further increase due to climate change. Farmers typically react by using low amounts of agricultural inputs. Low input use can help to minimize financial loss in bad years, but is also associated with low average yield and income. Increasing small farm productivity and income is an important prerequisite for rural poverty reduction and food security. Crop insurance could incentivize farmers to increase their input use, but indemnity-based crop insurance programs are plagued by market failures.
Classical innovation adoption models implicitly assume homogenous information flow across farmers, which is often not realistic. As a result, selection bias in adoption parameters may occur. We focus on tissue culture (TC) banana technology that was introduced in Kenya more than 10 years ago. Up till now, adoption rates have remained relatively low.
Most micro-level studies on the impact of agricultural technologies build on cross-section data, which can lead to unreliable impact estimates. Here, we use panel data covering two time periods to estimate the impact of tissue culture (TC) banana technology in the Kenyan small farm sector. TC banana is an interesting case, because previous impact studies showed mixed results. We combine propensity score matching with a difference-in-difference estimator to control for selection bias and account for temporal impact variability.