Abstract: Petroleum production and export play a dominant role in Nigeria's economy and account for about 90% of her gross earnings. This dominant role has pushed agriculture, the traditional mainstay of the economy, from the early fifties and sixties, to the background. In this research work we fitted a univariate Seasonal Autoregressive Integrated Moving Average model (SARIMA) to the monthly crude oil production in Nigeria between 2002 and 2016. Different Box-Jenskin Autoregressive Integrated Moving Average (ARIMA) models are fitted and diagnosed. However, ARIMA (2,1,0)(2,1,1)12 was the best model for the data. The model was further validated and it was discovered that autocorrelation between residuals at different lag times was not significant. Finally, the time plot of the in-sample forecast errors shows that the variance of the forecast errors seems to be roughly constant over time and the histogram of the time series shows that the forecast errors are roughly normally distributed and the mean seems to be close to zero, it seems plausible that the forecast errors are normally distributed with mean zero and constant variance.
Keywords: SARIMA, petroleum, Box-jenskin, model, residuals, autocorrelatiom.
Title: A STUDY OF THE SUITABLE TIME SERIES MODEL FOR MONTHLY CRUDE OIL PRODUCTION IN NIGERIA
Author: Sadeeq S. A., Ahmadu A. O.
International Journal of Mathematics and Physical Sciences Research
ISSN 2348-5736 (Online)
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