This paper proposes a new composite index to measure the multidimensional concept of food security. Although other indicators with the same objective exist, they come with several methodological shortfalls. The Proteus index makes a twofold contribution: a) we apply all the steps needed to tackle the uncertainty sources inherent to building a composite indicator (variable selection, data imputation, normalization, weighting and aggregation) and test the assumptions through a Monte Carlo procedure that applies a variance-based sensitivity analysis of model output; and b) the results are robust over time and are comparable within and between countries, thus allowing a measure that can track the country progress towards food security. We demonstrate that the main sources of output variability are weighting, normalization, data imputation, variable selection, and aggregation in descending order of importance, but interaction effects between the uncertainty sources also play a key role. The index provides a contribution to food security monitoring. While it identifies countries requiring priority attention for their chronic situation, it proves flexible enough to capture sudden onset crises. It also reflects the main drivers that can dramatically affect a country’s food security in the short run, insofar suggesting potential areas of intervention for policy makers.
