Modeling and Forecasting Nigerian Crude Oil Exportation: Seasonal Autoregressive Integrated Moving Average Approach
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064



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Research Paper | Statistics | Nigeria | Volume 2 Issue 12, December 2013

Modeling and Forecasting Nigerian Crude Oil Exportation: Seasonal Autoregressive Integrated Moving Average Approach

Kayode Ayinde, Habib Abdulwahab

In the last few decades, crude oil (petroleum) has claimed the topmost position in Nigerian export list, constituting a very fundamental change in the structure of Nigerian international trade. This paper is intended to model and forecast Nigerian monthly crude oil exportation (in barrels) by applying seasonal autoregressive moving average (SARIMA) into the same data collected between January, 2002 to December, 2011. Result reveals an upward trend of the series which became stationary at 1st difference, a sharp drop between 2007 and 2009 and autocorrelation function with significant spikes at lag 1, 7 and 12 suggesting the presence of seasonality in the series. Based on Akaike Information Criterion (AIC), Schwartz Bayesian Information Criterion (SBIC) and Hannan-Quinn Information Criterion (HQC), the best model was SARIMA (1, 1, 1) x (0, 1, 1) 12. The diagnosis on such model was confirmed, the error was white noise, presence of no serial correlation and a forecast for current and future values within 24 months period was made which indicates that the crude oil exportation is fairly unstable.

Keywords: SARIMA Model, BIC, Forecasting, Crude Oil Exportation

Edition: Volume 2 Issue 12, December 2013

Pages: 245 - 249

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How to Cite this Article?

Kayode Ayinde, Habib Abdulwahab, "Modeling and Forecasting Nigerian Crude Oil Exportation: Seasonal Autoregressive Integrated Moving Average Approach", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=02013401, Volume 2 Issue 12, December 2013, 245 - 249

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