使用自回归综合移动平均(ARIMA)模型建模和预测索马里GDP

Sadak Mohamud Hassan
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摘要

国内生产总值(GDP)是一个国家在某一年生产的所有商品和服务的总价值。研究的背景包括GDP作为反映一个国家整体经济表现和增长的重要经济指标的重要性。由于索马里面临着独特的经济挑战,本研究旨在深入了解其GDP动态、趋势和潜在的未来发展。为了建立适合索马里GDP数据的自回归综合移动平均(ARIMA)模型,本研究使用了Box-Jenkins方法。索马里从1972年到2022年的年度GDP数据取自Macrotrends数据库。ARIMA(3、1、8)被确定为最适合索马里国内生产总值的统计模型。对索马里未来五年国内生产总值的预测是使用这个拟合的ARIMA模型生成的。调查结果表明,索马里的国内总产值在今后五年可望有积极增长。这些预测与ARIMA模型发现的历史趋势和统计相关性一致
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
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