Building A Suitable GARCH Model for Accuracy Measurement of Selected Components of The Somalia Agro-Economy

Abstract

This study investigates the volatility patterns in Somalia’s agro-economy by applying GARCH models to key economic indicators, including GDP rate, livestock production index, and crop production index. Using time series data, the study assesses stationarity, estimates model parameters, and compares various GARCH specifications based on information criteria to identify the most suitable model for forecasting economic trends. The findings reveal significant fluctuations in agricultural productivity and GDP, with the APARCH (2,1) model emerging as the best fit for capturing volatility. The forecast results indicate periods of economic uncertainty, highlighting potential external shocks such as climate change and geopolitical instability. This study provides critical insights for policymakers, emphasizing the need for strategic interventions to enhance economic resilience and sustainable agricultural development in Somalia. A key recommendation is for the Somali government to implement robust risk management strategies, such as climate adaptation policies and financial support systems, to mitigate the adverse effects of agro-economic volatility.