This study investigates the relationship between climate variables such as rainfall amount, temperature, and carbon dioxide (CO₂) emission and the triple dimension of food security (availability, accessibility, and utilization) in a panel of 25 sub-Saharan African countries from 1985 to 2018. After testing for cross-sectional dependence, unit root and cointegration, the study estimated the pool mean group (PMG) panel autoregressive distributed lag (ARDL). The empirical outcome revealed that rainfall had a significantly positive effect on food availability, accessibility, and utilization in the long run. In contrast, temperature was harmful to food availability and accessibility and had no impact on food utilization. Lastly, CO₂ emission positively impacted food availability and accessibility but did not affect food utilization. The study took a step further by integrating some additional variables and performed the panel fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) regression to ensure the robustness of the preceding PMG results. The control variables yielded meaningful results in most cases, so did the FMOLS and DOLS regression. The Granger causality test was conducted to determine the causal link, if any, among the variables. There was evidence of a short-run causal relationship between food availability and CO₂ emission. Food accessibility exhibited a causal association with temperature, whereas food utilization was strongly connected with temperature. CO₂ emission was linked to rainfall. Lastly, a bidirectional causal link was found between rainfall and temperature. Recommendations to the national, sub-regional, and regional policymakers are addressed and discussed.

This article analyzes the impact of agricultural support measures on food import dependency for a 52-country sample from 1985 to 2017 using databases from the World Bank, the Center for Systemic Peace and the Groningen Center for Growth and Development. We apply a continuous treatment effect and control for endogeneity to describe the extent of food import dependency in response to domestic support for agriculture. Our results show strong evidence of heterogeneous impacts on aggregate food import dependency at different levels of political aid intensity. Estimates of dose-response functions confirm that countries providing moderate support to agriculture tend to do better in reducing their use of agri-food imports.

In this article, we analyze the relationship between agricultural support measures and food import dependency for a 52-country sample from 1985 to 2017 using databases from the World Bank, the Center for Systemic Peace, and the Groningen Center for Growth and Development. Using an instrumental variable framework, we apply a continuous treatment effect and control for endogeneity to describe the extent of food import dependency in response to domestic support for agriculture. Our results suggest heterogeneous associations for aggregate food import dependency at different levels of political aid intensity, while our analysis further reveals nonlinear dose–response patterns, suggesting that moderate levels of agricultural support are associated with lower food import dependency, whereas very high support intensities are not systematically associated with additional reductions. Although estimates of dose–response functions confirm that countries providing moderate support to agriculture tend to exhibit lower levels of agri-food import dependency, these findings should nevertheless be interpreted cautiously given the potential limitations regarding instrument validity and data availability. The primary contribution of our study is the explicit modeling of heterogeneous treatment intensity effects and potential endogeneity. These findings should therefore be interpreted as conditional empirical associations rather than definitive causal effects.

The authors would like to make the following corrections to the published paper