Predictive Model with Square-Root Variance Stabilizing Transformation for Nigeria Crude Oil Export to America

O. Adubisi, Titus Terkaa Mom, C. Adubisi, Phillip Luka
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引用次数: 2

Abstract

In the last few decades, crude oil has claimed the topmost position in Nigerian export list, constituting a very fundamental change in the structure of Nigerian international trade. In this study, secondary data on monthly crude oil export to the United States was obtained from the Energy Information Administration (EIA) database. Using the Box-Jenkins (ARIMA) methodology, the results showed that Seasonal ARIMA (0, 1, 1) (1, 0, 1)12 model had the least information criteria after the data was Square-Root transformed and non-seasonally first differenced in order to achieve series stationarity. The diagnostic tests on the selected model residuals revealed the residuals are normally distributed uncorrelated random shocks.
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尼日利亚原油对美出口的平方根方差稳定变换预测模型
在过去的几十年里,原油在尼日利亚的出口清单中占据了首位,这是尼日利亚国际贸易结构的一个非常根本的变化。在本研究中,从美国能源情报署(EIA)的数据库中获得月度原油出口到美国的二次数据。采用Box-Jenkins (ARIMA)方法,结果表明:为达到序列平稳性,经平方根变换后,季节性ARIMA(0,1,1)(1,0,1)12模型的信息准则最少,且非季节性先差。对所选模型残差的诊断检验表明,残差是正态分布的不相关随机冲击。
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