时间序列回归分析在评估新冠肺炎病例对印度尼西亚经济影响中的作用

U. Mukhaiyar, Devina Widyanti, Sandy Vantika
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引用次数: 6

摘要

本研究旨在利用传递函数模型和外生回归向量自回归移动平均(VARMAX)模型确定印度尼西亚COVID-19病例对美元/印尼盾汇率的影响。本文使用了2020年3月1日至6月29日期间印度尼西亚COVID-19病例、美元/印尼盾汇率和印尼盾x综合指数的每日数据。分析表明:(1)印尼新增新冠肺炎病例数越高,美元兑印尼盾汇率就越弱;(2)6天前印尼新增新冠肺炎病例数增加1%,美元兑印尼盾汇率就越弱0.003%;(3)7天前印尼新增新冠肺炎病例数增加1%,美元兑印尼盾汇率就越弱0.17%;(4) 8天前印度尼西亚新冠肺炎病例数增加1%将使美元兑印尼盾汇率下跌0.24%。
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The time series regression analysis in evaluating the economic impact of COVID-19 cases in Indonesia
This study aims to determine the impact of COVID-19 cases in Indonesia on the USD/IDR exchange rate using the Transfer Function Model and Vector Autoregressive Moving-Average with Exogenous Regressors (VARMAX) Model. This paper uses daily data on the COVID-19 case in Indonesia, the USD/IDR exchange rate, and the IDX Composite period from 1 March to 29 June 2020. The analysis shows: (1) the higher the increase of the number of COVID-19 cases in Indonesia will significantly weaken the USD/IDR exchange rate, (2) an increase of 1% in the number of COVID-19 cases in Indonesia six days ago will weaken the USD/IDR exchange rate by 0.003%, (3) an increase of 1% in the number of COVID-19 cases in Indonesia seven days ago will weaken the USD/IDR exchange rate by 0.17%, and (4) an increase of 1% in the number of COVID-19 cases in Indonesia eight days ago will weaken the USD/IDR exchange rate by 0.24%.
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来源期刊
Model Assisted Statistics and Applications
Model Assisted Statistics and Applications Mathematics-Applied Mathematics
CiteScore
1.00
自引率
0.00%
发文量
26
期刊介绍: Model Assisted Statistics and Applications is a peer reviewed international journal. Model Assisted Statistics means an improvement of inference and analysis by use of correlated information, or an underlying theoretical or design model. This might be the design, adjustment, estimation, or analytical phase of statistical project. This information may be survey generated or coming from an independent source. Original papers in the field of sampling theory, econometrics, time-series, design of experiments, and multivariate analysis will be preferred. Papers of both applied and theoretical topics are acceptable.
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