Open AccessForecasting Zambia’s Gross Domestic Product Using Time Series Autoregressive Integrated Moving Average (ARIMA) Model
Author(s) -
Chikumbe Evans Sankwa,
Sikota Sharper
Publication year - 2020
Publication title -
international journal of innovative science and research technology
Language(s) - English
Resource type - Journals
ISSN - 2456-2165
DOI - 10.38124/ijisrt20sep228
Subject(s) - autoregressive integrated moving average , akaike information criterion , gross domestic product , bayesian information criterion , recession , econometrics , autoregressive model , economics , time series , bayesian probability , volatility (finance) , statistic , statistics , mathematics , economic growth , macroeconomics
Gross Domestic Product is one of the social indicators of development. This study attempts to model Zambia’s Gross domestic product using the Autoregressive Integrated Moving Average (ARIMA) model. This model has proved to help many countries during economic recession or when there is any disruption in the economic system due to pandemics or natural disasters. The study utilized a time series dataset from 1960 to 2018. The best model that fit the data set, following the selection model criteria, was ARIMA (5,2,0) model with the lowest Akaike’s Information Criteria(AIC) and Bayesian Information Criteria (BIC) and smallest volatility. The study results showed that, on average, Zambia’s gross domestic product will continue to rise over the next eight years. However, few recession (decline) points are expected in the period 2020 to 2022. It is hoped that the forecasts would be useful for researchers in Zambia, including the fiscal and monetary policy makers.