This note sets forth a methodology for the evaluation of uncertainties related to the precision of a risk model. It is based on sensitivity and robustness analyses (assessment of output level variability from—respectively—one or multiple input parameters variations). The methodology is illustrated through the application to Africa RiskView (ARV), African Risk Capacity’s (ARC) risk model, for which a five-day support mission took place between November 2016 and January 2017.

Overall, the study concludes that whilst the analysis contained in this report only paves the way to further, more comprehensive studies, some preliminary results can already be extracted and provide orders of magnitude of the uncertainty involved in the modelling of Maize in Malawi, Millet in Niger and Rangeland in Mauritania. It identifies specific areas where uncertainty can be understood, controlled, and reduced. A number of limitations are raised and recommendations on future follow-up studies provided.