Duration dependence and dynamic conditional covariance of seasonal food price shocks in semi-arid African countries

Abstract

Every year in the months preceding harvests several African regions register higher malnutrition and morbidity levels, severe water shortages, and food price jumps. A previous study, focused on Niamey (Niger) with ‘hunger’ and ‘normal’ seasons modelled as a latent Markov process, found that in the last two decades the risk of food crises has tended to spread over longer periods and to shift forward in timing. To help better devise support programmes, it would be beneficial to test for this finding in other locations in Africa and extend the focus beyond conditional mean analysis. This paper first reviews measures of food insecurity/crisis risk, and considers determinants of spatial and temporal food price variability in drought-prone countries. Duration-dependent Markov-switching VAR models are then formulated and applied to monthly staple prices of food markets in Niger, Ethiopia and Somalia. This is complemented with multivariate GARCH models of volatility and dynamic correlations of food price shocks in major urban centres of five Sahel countries. In Niger, seasonal shocks in surplus-producing regions often anticipate by nearly 1 month those in deficit regions. ‘Steep’ regime probability switches are of concern especially in recent years. However, across semi-arid countries in East and West Africa, no systematic variation over time was detected in terms of onset and length of seasonal food insecurity periods, nor between seasons relative to food price volatility.