Modeling and Forecasting of Ghana’s Inflation Volatility

Abstract

In this paper, we assessed volatility of Ghana's inflation rates for 2000 to 2018 using the auto-regressive conditionally heteroskedasticity (ARCH), generalized ARCH (GARCH), and the exponential GARCH (EGARCH) models. The inflation data were obtained from the Ghana Statistical Service (GSS). The proposed model should be able to provide projections of inflation volatility from 2019 and beyond. The results showed that higher order models are required to properly explain Ghana's inflation volatility and the EGARCH(12, 1) is the best fitting model for the data. The EGARCH(12, 1) model is robust to model and forecast volatility of inflation rates. Also, the results suggest that we are forecasting increasing volatility and there is increasing trend in general prices of goods and services for 2018 and beyond. The forecasts figures revealed that Ghana's economy is likely to be unstable in 2018 and 2019. This study therefore recommends that policy makers and industry players need to put in place stringent monetary and fiscal policies that would put the anticipated increase in inflation under control. The models were implemented using R software.

Exploring the causality between economic growth, financial development and inflation in sixteen high-income countries

“…We find a bidirectional relationship between stock market development and inflation. Similar results were found for African countries where inflation brought volatility to the capital market (Iddrisu et al, 2019), and European countries (Fuinhas et al, 2019). Any economy with high inflation refers to a time of instability.…”

Modelling and Forecasting Volatility of Crude Oil Returns in Nigeria based on Six Error Innovations

“…A plethora of literature has studied volatility in some time series variable such as crude oil price (Suleiman et al, 2015Alhassan & Kilishi, 2016Muhammed & Faruk, 2018;Zhang et al, 2019;Nguyen & Walther, 2020;;Boitumelo et al, 2020), exchange rate (Kuhe & Agaigbe, 2018;Abdullah et al, 2017;Okoro & Osisiogu, 2017;Dritsaki, 2019), stock prices (Al Rahahleh & Kao, 2018;Iwada et al, 2018;Lin, 2018;Aliyev et al, 2020), inflation (Fwaga et al, 2017;Nyoni, 2018;Iddrisu et al, 2019) amongst others. Modeling PVCO by some authors has reported varying outcomes over the years.…”