Indian Agri-Exports to Select African Countries: A Machine Learning Approach to Gain Insights Towards Sustainable Food Security

This study focuses on agricultural exports from India to select African countries in order to mitigate food insecurity. As per the SDG Goal 2, the world should be hunger-free by 2030. With the onslaught of the pandemic, the Russia-Ukraine conflict and other consequences of climate change, domestic macroeconomic and socio-political concerns, large parts of Africa have been rendered severely food insecure. India has been a longstanding agri-trade partner with many African nations. While India and the African partners engage in bilateral agri-trade, it is clear that India has potential to trade specifically with countries around the Horn of Africa which has been the worst affected with respect to the recent global socio-economic and geopolitical developments. This study uses machine learning, employing panel regression, clustering and extrapolation to predict if India should indeed continue its efforts towards engaging in trade with its traditional African partners. The results show that it would be prudent to shift India’s attention towards the more food insecure African countries than continue in the same vein with the partners with whom agri-trade is predicted to trickle down over time due to various reasons. This insight will help in policy decisions that will optimise the utilisation of the surplus agri-produce that India has and also help to mitigate the severely food insecure situation in the wanting nations of Africa where India does not engage substantially yet.