J. Jusmawati, Mustika Hadijati, Nurul Fitriyani
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引用次数: 1

摘要

印度尼西亚的通货膨胀和利率对该国的经济发展有重大影响。印度尼西亚的通货膨胀和利率数据是多元时间序列数据,显示了一定时期内的经济活动。向量自回归积分移动平均(VARIMA)是一种分析多元时间序列数据的方法。该方法是一个同时具有多个内生变量的联立方程建模方法。本研究旨在对2009年1月至2016年12月的通货膨胀和利率数据进行建模,并利用VARIMA方法预测通货膨胀和利率。得到的模型为VARIMA(0,2,2)模型,参数估计采用极大似然法。VARIMA(0,2,2)模型的选择基于最小的AIC值-4,2891,其预测通货膨胀和利率的MAPE值分别为6,04%和1,84%,表明预测效果很好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Penerapan Model Vector Autoregressive Integrate Moving Average dalam Peramalan Laju Inflasi dan Suku Bunga di Indonesia
The inflation and interest rates in Indonesia have a significant impact on the country's economic development. Indonesian inflation and interest rates data are multivariate time series data that show activity over a certain period of time. Vector Autoregressive Integrated Moving Average (VARIMA) is a method for analyzing multivariate time series data. This method is a simultaneous equation modeling that has several endogenous variables simultaneously. This study aimed to model the inflation and interest rates data, from January 2009 to December 2016 and predict inflation and interest rates by using VARIMA method. The model obtained was the VARIMA(0,2,2) model, with estimated parameters using the maximum likelihood method. The choice of the VARIMA(0,2,2) model was based on the smallest AIC value of -4,2891, with a MAPE value for the inflation and interest rates forecasting were 6,04% and 1,84%, respectively, which indicates a very good forecast results.
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