On Forecasting Nigeria’s GDP: A Comparative Performance of Regression with ARIMA Errors and ARIMA Method (Published)
This paper examines the application of autoregressive integrated moving average (ARIMA) model and regression model with ARIMA errors for forecasting Nigeria’s GDP. The data used in this study are collected from the official website of World Bank for the period 1990-2019. A response variable (GDP) and four predictor variables are used for the study. The ARIMA model is fitted only to the response variable, while regression with ARIMA errors is fitted on the data as a whole. The Akaike Information Criterion Corrected (AICc) was used to select the best model among the selected ARIMA models, while the best model for forecasting GDP is selected using measures of forecast accuracy. The result showed that regression with ARIMA(2,0,1) errors is the best model for forecasting Nigeria’s GDP.
Citation: Christogonus Ifeanyichukwu Ugoh, Udochukwu Victor Echebiri, Gabriel Olawale Temisan, Johnpaul Kenechukwu Iwuchukwu, Emwinloghosa Kenneth Guobadia (2022) On Forecasting Nigeria’s GDP: A Comparative Performance of Regression with ARIMA Errors and ARIMA Method, International Journal of Mathematics and Statistics Studies, Vol.10, No.4, pp.48-64
Keywords: AICc, ARIMA, GDP, Measures of Forecast Accuracy, Nigeria, Regression with ARIMA errors