_GLOBAL FOOD INSECURITY OUTLOOK_ _27_ composition of economies. Future efforts may however still be taken to enrich the list of covariates with climate variables for which climate models can produce annual projections.

A final shortcoming is that the list of variables related to pre-existing vulnerabilities seems rather short, with only historical child mortality providing a proxy that allows distinguishing between the quality of governance and social systems.<sup>29</sup> The choice of the variable was primarily motivated by data availability, but it is reasonable to believe that a country that has ranked worse on child mortality in the recent past also ranked worse on a wide variety of other indicators that are predictive of weak socio-economic systems. Vastly superior indicators of the quality of governance in particular could be obtained from the estimates of Kaufmann et al. (2011) who maintain the annual Global Governance Indicators. The technical challenge would again be that these data may be predictive, but no outlooks can be produced without introducing new assumptions about the future. Forecasting government breakdown, after all, is at least as difficult as forecasting food crises.<sup>30</sup>

# **V. Conclusion**

This paper developed a statistical model to estimate and project global food insecurity conditions up to 6 years ahead using macro-economic outlooks. The long-term nature of the outlook aligns with the slow replenishment cycle of development finance, but the results can be revised on a semi-annual basis following the periodical assessments of broader economic outlooks. Extreme food insecurity situations are multifaceted in nature and frequently develop as part of multiple interlocking challenges. The paper’s approach anchors the food insecurity outlook to economic assumptions in an attempt to contribute to broader foresight that is internally consistent so that multiple policy actions can be informed jointly by a cohesive set of expectations. The paper concludes that the proposed framework provides a robust and low-cost approach to maintain reliable projections and scenario analyses that can be interpreted within the context of available economic outlooks, contributing to the capacity to monitor global food insecurity trends.

The model is based on historical associations between the prevalence of severe food insecurity and covariates that capture economic and structural drivers of food insecurity. All the data can be obtained from official public sources, and outlooks are available for the key predictors. The model was validated using holdout data that explicitly tested the model’s ability to forecast new data from

> 29One could argue that in order to be more accurate, the model should also include data on aid or supportive measures. However, since the modeling effort is itself motivated by a desire to trigger action, any resulting forecasts themselves should not bake in the assumed effect of assumed protective measures not yet taken. In a related early-warning early-action effort, Andr ́ee et al. (2020) provide more discussion on isolating the impacts of humanitarian action from forecast risk signals.

> 30A secondary challenge is that governments notoriously push back on governance indicators and no official data are widely available across countries. Since the objective of this paper is to produce outlooks that could help with resource allocation, the overall preference would be to reach sufficient accuracy using official or measured data that cannot be disputed alone.