REAP: Risk-Explicit Agricultural Policy Prioritization

Christine Lamanna and Todd Rosenstock of the World Agroforestry Centre in Kenya will develop a strategy that combines local knowledge and a Bayesian network model to prioritize agricultural policy using Tanzania’s Agriculture and Food Security Investment Plan as a case study. Agriculture is responsible for nearly one third of Africa’s gross domestic product, yet productivity suffers from limited infrastructure and lack of access to markets and financing. Many policy options exist to stimulate agricultural transformation, however countries struggle to prioritize them and progress is limited. They will develop a Bayesian network to model the cost and risks of implementing specific agricultural policies as well as the economic, social and environmental benefits. Using the Tanzanian plan as a case study, they will develop a data-driven model for policy prioritization that incorporates risk (financial, climate, logistical, political) and reflects stakeholder perspectives to create a sense of ownership over the process. This strategy will allow for direct and transparent comparison of diverse policy options and provide decision-makers with clear prioritization information.