文章基本信息

标题：Dynamic Modeling Data Export Oil and Gas and Non-Oil and Gas by ARMA(2,1)-GARCH(1,1) Model: Study of Indonesian’s Export over the Years 2008-2019
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作者：Nairobi Nairobi ; Edwin Russel ; Ambya Ambya 等
期刊名称：International Journal of Energy Economics and Policy
电子版ISSN：2146-4553
出版年度：2020
卷号：10
期号：6
页码：175-184
DOI：10.32479/ijeep.9892
出版社：EconJournals
摘要：It is well known that a country's economy is very dependent on the export of goods and services produced by that country. This depends on exporting either mining products such as oil and gas or non-oil and gas. This paper will study the data export of oil and gas and data export of non-oil and gas of Indonesian over the years 2008 to 2019. The aim of this study is to obtain the best model that can describe the pattern of the data export of oil and gas and data export of non-oil and gas. From the results of the analysis, researchers found that the best models that can describe the pattern of data export of oil and gas and data export of non-oil and gas are the same, namely: ARMA (2.1) -GARCH (1.1) models. These models for both data are very significant with P-values < 0.0001 and < 0.0001, respectively, R-squares are 0.8797 and 0.7604, respectively and Mean Average Percentage Errors (MAPE) are 12.41 and 6.92, respectively. These models are very reliable, and they can be used to predict (forecast) for the next 12 periods (months).
关键词：Akaike’s Information Criterion;Autoregressive Moving Average;Generalized Autoregressive Conditional Heteroscedasticity;Mean Average Percentage Error.