Prioritizing Tanzania’s agricultural development policy to build smallholder climate resilience. Final report for the Bill & Melinda Gates Foundation Grand Challenges Explorations 22: Risk-explicit and Evidence-based Policy Prioritization (REAP)

Abstract

Faced with myriad options, Sub-Saharan Africa policy makers struggle to prioritize actions. Commonly used modeling approaches perform poorly in data scare conditions or focus intently on tools at hand. Policies, by consequence, report ‘wish lists’, making them a challenge to implement given resource constraints. Here, we evaluate the potential of using an alternative approach, Bayesian Networks (BNs), to prioritize agricultural policy actions, specifically modeling seven ‘Investment Areas’ listed in Tanzania’s Agriculture Sector Development Programme II