Exploring the Dynamic Interrelationships of Major Cereal Prices in Northern Ghana: An Empirical Analysis Using VAR Modeling

Cereals are the most types of crops produced worldwide. They have received particular deliberation because of their large shares in the diets of most developing countries. Hence, cereal prices have a considerable impact on food security. Understanding therefore the dynamics of cereal prices and examining the feasibility of econometric models to forecast their dynamics is essential to improve economic decisions. This study employed a Vector Autoregressive (VAR) model to investigate the dynamic relationship between the returns of the cereals. VAR (2) and VAR (3) models were fitted to the data. Based on the Likelihood Ratio Test, VAR (3) model was the best for modeling the dynamic relationship between the returns of the cereals. The diagnostic checks revealed that VAR (3) model was adequate. The VAR (3) model was then used to make inference about the relationship between the returns of these cereals. The Granger causality test revealed a bilateral relationship between the returns of rice and that of millet whiles the returns of maize was independent of the returns of rice and millet. The Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD) analysis both affirm that there exists a dynamic relationship between the returns of the three cereals. Future research could be carried out to understand the sources of price volatility of cereal markets in the Northern Region.