Measuring cognitive capacity in food systems
Food systems transformation depends not only on finance, technology, and formal policy commitments, but also on whether countries can convert evidence into coordinated, implemented, and adaptive action. This paper develops the Food Systems Cognitive Capacity Index (FSCCI) as a policy diagnostic covering six system-level capacities: sensing and information, transparency and feedback, policy framing, collective action and coordination, administrative implementation, and anticipatory resilience. Using country-year data for the 2000–2023 period, the study constructs equal-weighted, principal component analysis (PCA)-weighted, and interdependence-adjusted versions of the FSCCI, alongside a Food Systems Cognitive Failure Index and a Food Systems Transformation Performance Index. The results show that cognitive capacity is measurable and policy-relevant, but its association with transformation performance depends on index construction and model specification. In the preferred one-year-lagged models, the equal-weighted estimate is positive but imprecise, whereas the PCA-weighted and interdependence-adjusted estimates remain positive and statistically significant. Additional controls preserve the positive direction of the association but reduce its precision. Regional and interaction analyses also reveal important contextual variation: the association is stronger in Latin America and the Caribbean, positively moderated by climate readiness, and negatively moderated by food-import dependence.
The policy implication is that food systems strategies should be accompanied by investments in the institutional capacities required for implementation. The FSCCI can help governments and development partners diagnose whether the binding constraint lies in weak data systems, limited feedback, fragmented coordination, poor implementation, or inadequate preparedness. It is therefore best used as a capacity-development tool rather than as a country-ranking instrument. Although the findings are associational rather than causal, they support a practical shift from measuring policy presence to assessing whether food systems can perceive problems, learn, coordinate, implement, and adapt.
Authors
Ulimwengu, John M.
Citation
Ulimwengu, John M. 2026. Measuring cognitive capacity in food systems. IFPRI Discussion Paper 2440. Washington, DC: International Food Policy Research Institute. https://hdl.handle.net/10568/185339
Keywords
Capacity Development; Mental Ability; Learning Capacity; Food Systems; Policies; Large Language Models; Generative Artificial Intelligence; Artificial Intelligence; Measurement; Ethics; Econometrics
Access/Licence
Open Access
