Stochastic modelling of food insecurity risk in Africa: Use of Vine Copulas and cointegration approaches

Demand for rice in Africa has been steadily increasing due to population and economic growth and changing preferences. However, low production growth has led to major gaps between rice supply and demand leading to import reliance. Given the concerns on long term food security and availability that comes with import reliance, many studies have focused on evaluating how shocks in the global markets and exporting countries are transmitted to import reliant countries. With this development, our paper furthers this endeavour by developing an econometric predictive framework to identify dependency relationships for forecasting purposes, which provides information not only on the relationship between African countries and its import sources, but also how current prices impact future prices. The novelty of our study lies in integrating the Vine Copula into cointegration analysis to forecast future rice prices using monthly time series data from three sub-Saharan African countries between 2018 and 2024. The results demonstrate a high predictive performance from the proposed approach and finds that food insecurity dynamics are both asymmetric and path dependent. Additional insights are obtained through sensitivity and impulse response analyses.