{"title":"基于Arima的喀麦隆GDP建模与预测实证研究","authors":"Guy Merlain Djakou, Xuemei Jiang","doi":"10.58970/ijsb.2094","DOIUrl":null,"url":null,"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.","PeriodicalId":297563,"journal":{"name":"International Journal of Science and Business","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GDP Modelling and Forecasting using Arima: An Empirical Study for Cameroon\",\"authors\":\"Guy Merlain Djakou, Xuemei Jiang\",\"doi\":\"10.58970/ijsb.2094\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":297563,\"journal\":{\"name\":\"International Journal of Science and Business\",\"volume\":\"87 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Science and Business\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.58970/ijsb.2094\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Science and Business","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.58970/ijsb.2094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GDP Modelling and Forecasting using Arima: An Empirical Study for Cameroon
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.