Agriculture-related research and innovation for growth and poverty reduction in Rwanda

Agricultural productivity growth plays a particularly important role in achieving sustainable pro-poor growth in Rwanda. With 75 percent of Rwanda's land and labour force in agriculture, there is clearly large scope for increasing national income and reducing poverty by improving productivity in agriculture and supporting sectors.

Research shows that the rate of return on resources allocated to agricultural research and development typically has very high social rates of return. However, how scarce research resources should be allocated is unclear. One key is to identify sectors in which Rwanda’s research and development activity can be expected to achieve large increases in productivity, and hence, in national incomes and exports. Knowledgeable policymakers can make informed assessments about these impacts based on past experimental evidence and information from researchers located in similar agro-ecological zones to Rwanda. Another important criterion is the extent to which gains in productivity benefit the poorest people in Rwanda. These ex-ante assessments are particularly difficult to make since they require information on where poor people obtain and spend their incomes and how they will respond to productivity-increasing innovations.

If research and development resources are allocated most effectively, they will be able to generate much larger improvements in economic, social and nutritional outcomes than if poorly allocated. The purpose of this project is to provide a structured approach for guiding policymakers in making ex-ante allocations of scarce research resources between different crops and activities. Additionally, the researchers will aim to identify areas in which reductions in off-farm costs could have particularly large impacts on poverty reduction.

The impacts of productivity improvements on poverty depend on the extent to which poor people participate in the production of the good; the way they affect returns to the factors sold by poor households; and their impacts on commodity prices (which affect poor households both as producers and consumers). The researchers' methodology uses economy-wide models linked to household models to capture poverty impacts.