These primary data are taken from a mixture of quantitative and qualitative methods employed over two years in three countries in East Africa: Kenya, Sudan and Uganda. In each of the three countries research teams worked in four sites which were split across two districts (Uganda), counties (Kenya) or states (Sudan). The methodology progressed from inductive qualitative tools from which hypotheses were developed to deductive qualitative and quantitative investigation. Inductive methods included key informant interviews (not included in these data due to issues with confidentiality), agricultural timelines, innovation histories and communication maps – a mixture of textual and visual data. Inductive methods included quantitative tools: a household survey of more than 400 households in each country and participatory budgets and qualitative tools: innovation behaviour case studies, wealth ranking and local economy chain analysis (protocols for all methods are included with this submission). This project’s aim is to understand how different institutional arrangements for supporting smallholder farmers affect the innovation activity and livelihoods of female and male farmers in Kenya, Sudan and Uganda, and the impact of this innovation on growth in the local economy. From interviews with key informants and a document review the research team will build up a detailed picture of organisations and institutions that support and provide services to smallholder farmers in Kenya, Sudan and Uganda. They will then carry out a detailed investigation of recent innovation activity in four sites in each country and of the factors that have constrained and those that have supported innovation. Participatory research tools will include innovation histories, communication maps, value chain analysis and timelines. The analysis will generate hypotheses linking institutional arrangements, innovation activity, and changes in farm output, livelihoods, and incomes. These hypotheses will be tested using data from further participatory research and a sample survey in each of the research sites. The team will develop evidence-based conclusions on the potential and limitations for enhancing support for smallholder farmers’ innovation through new institutional arrangements and different ways of implementing support programmes at local level.

These data are a mixture of quantitative and qualitative. Collected using a range of methods, the data are split between three folders, objective 2 data, objective 3 quantitative data and objective 3 qualitative data. Objective 2 data were collected using qualitative tools which included agricultural timelines, innovation histories and communication mapping (the protocols for each of these activities are included in the objective 2 data folder). Objective 3 quantitative data were collected through a household survey. Sampling strategy for each country is outlined in the objective 3 quantitative data folder. Objective 3 qualitative data were collected using a range of tools which included participatory budgets, livelihood maps, wealth ranking, local economy chain analysis and innovation behaviour case studies. The protocols for each of these activities are included in the objective 3 qualitative data folder.