Multi-stakeholder platforms have become mainstream in projects, programmes and policy interventions aiming to improve innovation and livelihoods systems, i.e. research for development interventions in low-and middle-income contexts. However, the evidence for multi-stakeholder platforms' contribution to the performance of research for development interventions and their added value is not compelling. This paper focuses on stakeholder participation as one of the channels for multi-stakeholder platforms' contribution to the performance of research for development interventions, i.e.
Farmers in the Lake Victoria crescent zone have over the years struggled with pests and diseases in a country full of fake agricultural inputs, access to markets, post-harvest losses, declining soil fertility and the changes of weather. The production for most farmers is rain fed and is greatly affected by climatic changes. The Mukono Wakiso innovation platform (IP) was formed to help farmers find solutions to these issues.
Mobile phone based money services have spread rapidly in many developing countries. We analyze micro level impacts using panel data from smallholder farmers in Kenya. Mobile money use has a large positive net impact on household income. One important pathway is through remittances, which contribute to income directly but also help to reduce risk and liquidity constraints, thus promoting agricultural commercialization. Mobile money users apply more purchased inputs, market a larger proportion of their output, and have higher farm profits.
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.