GDP Modelling and Forecasting using Arima: An Empirical Study for Cameroon

Guy Merlain Djakou and Professor Xuemei Jiang
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Guy Merlain Djakou: School of Economics, Capital University of Economics and Business (CUEB), Beijing, China.
Professor Xuemei Jiang: School of Economics, Capital University of Economics and Business (CUEB), Beijing, China.

International Journal of Science and Business, 2023, vol. 22, issue 1, 41-52

Abstract: Gross domestic product (GDP) is a significant metric used to describe and assess economic activities and levels of growth. It's also regularly used by decision-makers to plot financial coverage. This paper's objective is to model and expect GDP in Cameroon. The current investigation employed the Box- Jenkins (JB) technique from 1980 to 2020. Based on the consequences, ARIMA (2, 1, 2) changed into discovered to be the optimal model for estimating GDP. The results of the desk-bound and identification guidelines time collection tests, as well as the use of aic and bic criteria, validated the outcomes, and an in-pattern forecast revealed that the relative and an in-pattern forecast, the relative and anticipated values were in the 5% area. This model's forecasting effectiveness is exceptional and efficient in modelling Cameroon's annual GDP.

Keywords: GDP; Box-Jenkins methodology; Forecasting; ARIMA model; Cameroon. (search for similar items in EconPapers)
Date: 2023
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