Risk spillover between climate variables and the agricultural commodity market in East Africa - Jean-Luc Mubenga-Tshitaka; John W. Muteba Mwamba; Johane Dikgang; Dambala Gelo (ZBW - Leibniz Information Centre for Economics, 2021)
This paper assesses the effect of extreme weather variability in predicting the impact on two agricultural crop-related variables: yield and production. We use a Markov-Switching time-varying copula to describe the joint dependence structure between extreme weather variability and crops in East Africa during the period 1961-2018. Understanding the risk associated with weather variability on agricultural production is crucial, as mitigation, and even adaptation, can then be made more effective. Climate data are divided into regimes: higher and lower regimes. The abnormal or higher regime is the period during which the temperature exceeds a certain threshold, while the lower regime is the period during which the rainfall is below a certain threshold. The findings show that there is strong dependence between weather variability and crops, meaning an increase in temperature or a decrease in rainfall is associated with a decrease in crop yield or production. The dependence is more significant when weather variability moves into either regime compared to the normal condition. The dependency in the higher regime tends to be more significant. This highlights the need to formulate policies that consider crop improvement strategies such as genetic crops, irrigation, and adaption under carbon dioxide (CO2) fertiliser to mitigate the impact on food supply in the region.
Keywords: Q1; Q2; Q10; Q54; 330; Dependence structure; weather variability; markov-switching; constant and time-varying copulas