A 72h exploration of the co-evolution of food insecurity and international migration

TL;DR

This work addresses the national-scale nexus between food insecurity and international migration by leveraging public datasets from FAO, the World Bank, and UNPD to explore how food insecurity, migration, remittances, and drivers like GDP, climate change, and political stability co-evolve. It develops three analytical strands—food insecurity vs. out-migration, migration vs. remittances, and remittances vs. food insecurity drivers—and derives a preliminary mechanistic framework that links these processes, including a log-log remittance relation with slope $\\gamma \\approx 0.87$ and a migration-change equation calibrated to $\\alpha = 0.0436$, $\\beta = 0.0846$. The study acknowledges significant data limitations and presents a conceptual model meant to be extended with longer time series and more robust validation, aiming to inform policies that stabilize food security amid migration dynamics. Overall, the paper offers a data-driven pathway to model the co-evolution of food insecurity and international migration, proposing equations that couple migration, remittances, and climate/economic factors for forward simulations.

Abstract

Food insecurity, defined as the lack of physical or economic access to safe, nutritious and sufficient food, remains one of the main challenges of the 2030 Agenda for Sustainable Development. Food insecurity is a complex phenomenon, resulting from the interplay of environmental, socio-demographic, and political events. Previous work has investigated the nexus between climate change, conflict, migration and food security at the household level, however these relations are still largely unexplored at national scales. In this context, during the Complexity72h workshop, held at the Universidad Carlos III de Madrid in June 2024, we explored the co-evolution of international migration flows and food insecurity at the national scale, accounting for remittances, as well as for changes in the economic, conflict, and climate situation. To this aim, we gathered data from several publicly available sources (Food and Agriculture Organization, World Bank, and UN Department of Economic and Social Affairs) and analyzed the association between food insecurity and migration, migration and remittances, and remittances and food insecurity. We then propose a framework linking together these associations to model the co-evolution of food insecurity and international migrations.

Figures (5)

• Figure 1: Data cleaning and aggregation flow. Data from FAO, WBG, and UNPD are combined by means of their ISO3 country codes and made consistent by computing 3-year averages from annual indicators. To produce this figure, we employed Creative Commons icons from thenounproject by the authors Rikas Dzihab and New icon.
• Figure 2: Relative changes in future total outgoing migration in function of relative changes in the origin country food insecurity situation. Each point represents a country and is coloured by its income group: Low (L), Lower-Middle (LM), Upper-Middle (UM), High (H).
• Figure 3: Relationship between the observed received average remittances of each country for the 2017-2019 period and the estimated average remittances for the same time period. Each point represents a country and is coloured by the its income group: Low (L), Lower-Middle (LM), Upper-Middle (UM), High (H).
• Figure 4: Schematic representation of the proposed framework to investigate the co-evolution of food insecurity and international migration. Food insecurity can drive individuals to leave their home country. Once people reach more secure countries, they tend to send remittances to relatives who remained in their home country, which can help them reduce their food insecurity. Finally, we propose to estimate changes in food insecurity in the origin country considering the known drivers of food insecurity (i.e., economic situation, conflict, and climate) as well as the positive effect of remittances (mediating the impact of outgoing migration). To produce this Figure, we employed Creative Commons icons from thenounproject by the authors: Sergey Novosyolov, Moch Rizki Eko Waluyo, UNKNOWN, bsd studio, Geni Alando, and yuni sarah.
• Figure 5: Migration route prevalence. Migration route prevalence is the migrant stock that is in one country as a proportion of the total migrant stock existing worldwide from the origin country. By comparing migration route prevalence at a time $t$ with a time $t+\Delta t$, we may observe variations in destination choice over time. All three comparisons display a strong correlation between two subsequent time periods, motivating our assumption that the likelihood of destination choice can be assumed to be static over time.