{"title":"使用自回归综合移动平均(ARIMA)模型建模和预测索马里GDP","authors":"Sadak Mohamud Hassan","doi":"10.37284/eajbe.6.1.1356","DOIUrl":null,"url":null,"abstract":"The Gross Domestic Product (GDP) is the total worth of all goods and services produced within a country's borders in a given year. The background of the study includes the importance of GDP as an important economic indicator reflecting the overall economic performance and growth of a country. As Somalia faces unique economic challenges, this research aims to provide insight into its GDP dynamics, trends, and potential future developments. In order to create the suitable Autoregressive-Integrated Moving-Average (ARIMA) model for the GDP data for Somalia, the Box-Jenkins method was used in this study. Data on the annual GDP of Somalia from 1972 through 2022 was taken from the Macrotrends database. ARIMA (3, 1, 8) was identified as the most suitable statistical model for the GDP of Somalia. The forecast for Somalia's GDP over the next five years was generated using this fitted ARIMA model. The findings indicated that a positive increase in Somalia's GDP over the next five years is expected. These forecasts line up with the historical trends and statistical correlations found by the ARIMA model","PeriodicalId":378318,"journal":{"name":"East African Journal of Business and Economics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modelling and Forecasting Somalia GDP Using Autoregressive Integrated Moving Average (ARIMA) Models\",\"authors\":\"Sadak Mohamud Hassan\",\"doi\":\"10.37284/eajbe.6.1.1356\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Gross Domestic Product (GDP) is the total worth of all goods and services produced within a country's borders in a given year. The background of the study includes the importance of GDP as an important economic indicator reflecting the overall economic performance and growth of a country. As Somalia faces unique economic challenges, this research aims to provide insight into its GDP dynamics, trends, and potential future developments. In order to create the suitable Autoregressive-Integrated Moving-Average (ARIMA) model for the GDP data for Somalia, the Box-Jenkins method was used in this study. Data on the annual GDP of Somalia from 1972 through 2022 was taken from the Macrotrends database. ARIMA (3, 1, 8) was identified as the most suitable statistical model for the GDP of Somalia. The forecast for Somalia's GDP over the next five years was generated using this fitted ARIMA model. The findings indicated that a positive increase in Somalia's GDP over the next five years is expected. These forecasts line up with the historical trends and statistical correlations found by the ARIMA model\",\"PeriodicalId\":378318,\"journal\":{\"name\":\"East African Journal of Business and Economics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"East African Journal of Business and Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37284/eajbe.6.1.1356\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"East African Journal of Business and Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37284/eajbe.6.1.1356","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modelling and Forecasting Somalia GDP Using Autoregressive Integrated Moving Average (ARIMA) Models
The Gross Domestic Product (GDP) is the total worth of all goods and services produced within a country's borders in a given year. The background of the study includes the importance of GDP as an important economic indicator reflecting the overall economic performance and growth of a country. As Somalia faces unique economic challenges, this research aims to provide insight into its GDP dynamics, trends, and potential future developments. In order to create the suitable Autoregressive-Integrated Moving-Average (ARIMA) model for the GDP data for Somalia, the Box-Jenkins method was used in this study. Data on the annual GDP of Somalia from 1972 through 2022 was taken from the Macrotrends database. ARIMA (3, 1, 8) was identified as the most suitable statistical model for the GDP of Somalia. The forecast for Somalia's GDP over the next five years was generated using this fitted ARIMA model. The findings indicated that a positive increase in Somalia's GDP over the next five years is expected. These forecasts line up with the historical trends and statistical correlations found by the ARIMA model