Author(s)

Dwumah Barbara^1*, Chenlong Li¹, Yingchuan Jing¹, Aning Samuel²

¹Department of Statistics, Taiyuan University of Technology, Taiyuan, China.
²Institute of Computer Science, University of Silesia in Katowice, Katowice, Poland.

GDP is frequently used as a way of national evaluations, as well as a way of measuring economic progress. This paper analyses a combination of time series models that are both linear and non-linear in making forecast of Ghana’s GDP. Ghana’s GDP current prices data from 1980 to 2019 were used in the analysis. Based on the AIC values, the best model was determined to be ARIMA (2, 2, 2) in modeling our data, except that it is heteroscedastic. The combination with non-linear GARCH (1, 1) model is used to capture these variances over time. The diagnostics test further shows that the presented model is stable and quite reliable. The results of the study reveal that the GDP of Ghana will continue to increase for the next 10 years and this goes to show that the nation is moving forward.

Gross Domestic Product (GDP), Heteroscedasticity, ARIMA, GARCH, Volatility

Barbara, D., Li, C.L., Jing, Y.C. and Samuel, A. (2022) Modeling and Forecast of Ghana’s GDP Using ARIMA-GARCH Model. Open Access Library Journal, 9, 1-16. doi: 10.4236/oalib.1108335.