Forecast Analysis of Ghana’s Gross Domestic Product in Economic Growth using Time Series ARIMA
B. S. Borbor *
Department of Mathematical Sciences, University of Mines and Technology (UMaT), Tarkwa, Ghana.
L. Brew
Department of Mathematical Sciences, University of Mines and Technology (UMaT), Tarkwa, Ghana.
*Author to whom correspondence should be addressed.
Abstract
This paper analyses Ghana’s gross domestic product using time series Autoregressive Integrated Moving Average (ARIMA). Time series analysis involves the application of statistical models to time series data and is useful for analysing the dynamics of Gross domestic product. The Ghana’s Gross domestic products (GDP) from 1980 to 2020 were obtained from the International Monetary Fund (IMF) datasets. Box Jenkins’s methodology of time series analysis was employed to analyse the data. The autocorrelation function (ACF) and partial autocorrelation function (PACF) plot suggested an Autoregression of order one AR(1). The (ARIMA) models were obtained using the minimum AIC criteria. Model diagnostics tests were performed using Ljung-Box test. The paper established that Ghana’s GDP will incline throughout the period of 2021-2025.
Keywords: Gross Domestic Product (GDP), Stationarity, ARIMA models, time series