Open AccessForecast Analysis of Ghana’s Gross Domestic Product in Economic Growth using Time Series ARIMA
Author(s) -
Bridget Sena Borbor,
Lewis Brew
Publication year - 2022
Publication title -
asian research journal of mathematics
Language(s) - English
Resource type - Journals
ISSN - 2456-477X
DOI - 10.9734/arjom/2022/v18i230359
Subject(s) - autoregressive integrated moving average , partial autocorrelation function , autocorrelation , box–jenkins , gross domestic product , time series , econometrics , autoregressive model , series (stratigraphy) , statistics , mathematics , moving average model , moving average , economics , macroeconomics , paleontology , biology
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.