Modeling inflation volatility and uncertainty in selected african economies using garch type model

Abstract

Inflation volatility and uncertainty pose persistent challenges to macroeconomic stability in African economies, where structural vulnerabilities and external shocks often amplify price fluctuations. This study models inflation volatility in selected African countries using Generalized Autoregressive Conditional Heteroskedasticity (GARCH) type models. Monthly inflation data are analyzed through symmetric GARCH and asymmetric EGARCH and TGARCH specifications following preliminary tests for non normality, stationarity, and ARCH effects. The results reveal strong volatility clustering and high persistence of inflation shocks across all countries. While the GARCH(1,1) model confirms long run persistence, asymmetric models provide superior performance, indicating that adverse inflation shocks generate disproportionately larger increases in uncertainty. Model selection criteria identify EGARCH as the preferred specification for Nigeria and Ghana, while TGARCH better captures volatility dynamics in South Africa and Kenya. These findings highlight the importance of accounting for asymmetry and nonlinearity in modeling inflation dynamics in African economies and provide policy relevant insights for strengthening inflation management and monetary credibility