The threat of oil market turmoils to food price stability in Sub-Saharan Africa

While the causal relationship between different types of oil shocks and food prices in the US and other developed countries has been extensively studied, the inter-dynamics between global oil market turmoils and food prices in Sub-Saharan Africa (SSA) remain unclear. This gap in the literature is particularly striking as populations in developing countries are much more vulnerable to food crises than those in developed countries. In this paper we use structural vector autoregressive (SVAR) models to investigate the impacts of global oil market shocks on local corn prices in several SSA countries. We estimate the structural shocks through independent component analysis, which allows for a more agnostic identification compared with conventional methods. Our key findings are that unlike US or global corn markets, African corn markets are much less sensitive to the impacts of oil-specific demand shocks, instead, disruptions in global oil supply can lead to an increase in food prices in several markets. Countries suffering from oil-supply shocks have neither strategic or natural oil reserves to buffer import shortages, nor efficient oil distribution systems that translate into food prices through higher transport costs. We show that a large share of corn price surges in 2011 and 2012 can be attributed to oil-supply shortages caused by the Libyan revolution and the oil embargo against Iran. Conversely, the shale oil boom in the US and the oil production expansion in the Middle East exerted downward pressures on corn prices in three African countries in 2014/15. Finally, political events related to the oil market, e.g. the tensions between the US and Iran or the recent oil price war between Saudi Arabia and Russia, have the potential to raise or lower corn prices by up to 25%. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

This study investigates the impacts of global oil market shocks on local corn prices in several Sub-Saharan African countries using structural vector autoregressive models. The findings reveal that African corn markets are less sensitive to oil-specific demand shocks but can experience price increases due to disruptions in global oil supply. Political events related to the oil market also have the potential to significantly influence corn prices in these countries.