_GLOBAL FOOD INSECURITY OUTLOOK_ _7_ resilience strategies. An important distinction from a policy perspective is that when food insecurity is primarily chronic, markets are typically still functional so that a wider range of economic interventions may still be considered as part of a prevention and resilience strategy.<sup>7</sup> A challenge in using the data to track global developments is that the regional totals cannot be traced back to the underlying country figures. First, the annual figures are not available at the individual country level. Second, the moving averages are not published for all countries that make up the aggregated totals. For instance, 70% of the 2018-2020 average of the global number of severely food insecure people cannot be accounted for after summing up all available data points. This is mostly because the data is not available for several countries with high population counts like China, India, and Pakistan, and several of the major ongoing food crises including those in the Sahel region, the Syrian Arab Republic, and the Republic of Yemen.<sup>8</sup> In some of these countries, particularly the Sahel countries, other harmonized food insecurity assessments are available from the Cadre Harmonis ́e and the Integrated Phase Classification system. For a small set of countries, these data are utilized to produce proxies for the prevalence of severe food insecurity using linear regression scaling. The details are in the appendix, section A.A1.

A second challenge is that the data is produced following a deliberate sampling and measurement process that is not designed for monitoring rapid developments and guiding actions during crisis situations. There is a typical delay in the individual country figures of 2 years due to the 3-year averaging plus the typical publication delay of any country figure. For policy purposes, it would be beneficial to have preliminary estimates and future expectations and be able to track changes therein. As an example, upward or downward revisions in economic growth expectations are typically more informative for setting a new course of action than the official growth rate from one or more years ago.

# _B. Modeling Framework_

In order to help evaluate shifts in food insecurity during a rapidly evolving crisis environment and provide adjustable forward guidance, the analysis takes a model-based approach to producing preliminary estimates, filling historical data

> 7Focus on the more chronic measure is grounded in a rhetoric of prevention, adapted to the geographical and temporal scale at which development finance decisions take place. This proposes that long-term aspects of food insecurity can be tackled through long-term development assistance, while acute food insecurity situations may require direct humanitarian assistance. This also implies that humanitarian objectives may benefit from a different modeling objective that have already been pioneered in earlier work, for instance the 1 to 12 months ahead subnational food crisis risks forecast by Andr ́ee et al. (2020) or the 36 months ahead projections at national scale by Wang et al. (2020, 2022).

> 8The number of countries for which data are available varies over time (96 in 2015, 120 by 2019). It is unclear to what extent trends in country coverage of the assessments is associated with global totals, which, by itself, is another motivation to this work. It is worth noting that the need for this complex modeling work, and imputation in general, is in part a result of chronic underinvestment in transparent data collection and dissemination systems. The overall availability of reliable data, without which investments are difficult to justify, remains low, particularly in lower income countries.