A general framework for the generation of probabilistic socioeconomic scenarios: Quantification of national food security risk with application to the cases of Egypt and Ethiopia

In this work a general framework for providing detailed probabilistic socioeconomic scenarios as well as estimates concerning country-level food security risk is proposed. Our methodology builds on (a) the Bayesian probabilistic version of the world population model and (b) on the interdependencies of the minimum food requirements and the national food system capacities on key drivers, such as: population, income, natural resources, and other socioeconomic and climate indicators. Model uncertainty plays an important role in such endeavours. In this perspective, the concept of the recently developed convex risk measures which mitigate the model uncertainty effects, is employed for the development of a framework for assessment, in the context of food security. The proposed method provides predictions and evaluations for food security risk both within and across probabilistic scenarios at country level. Our methodology is illustrated through its implementation for the cases of Egypt and Ethiopia, for the time period 2019-2050, under the combined context of the Shared Socioeconomic Pathways (SSPs) and the Representative Concentration Pathways (RCPs).