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

Guy Merlain Djakou, Xuemei Jiang
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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.
基于Arima的喀麦隆GDP建模与预测实证研究
国内生产总值(GDP)是用来描述和评估经济活动和增长水平的重要指标。决策者也经常使用它来规划金融报道。本文的目标是对喀麦隆的GDP进行建模和预测。目前的调查从1980年到2020年采用了Box- Jenkins (JB)技术。基于这些结果,ARIMA(2,1,2)被发现是估算GDP的最优模型。桌面约束和识别指南时间收集测试的结果,以及aic和bic标准的使用,验证了结果,模式内预测显示,相对和模式内预测,相对值和预测值都在5%的范围内。该模型的预测有效性在喀麦隆的年度GDP建模中是特殊和高效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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