Forecasting Nigeria’s Crude Oil Production Using Box and Jenkins Methodology

Modupe Stella Omotayo-Tomo Nwokeocha Divine Chinelo

doi:10.56201/ijasmt.vol.12.no9.2026pg77.81

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Forecasting Nigeria’s Crude Oil Production Using Box and Jenkins Methodology

Modupe Stella Omotayo-Tomo Nwokeocha Divine Chinelo

Abstract

This research analyzed and predicted the crude oil output of Nigeria utilizing the Autoregressive Integrated Moving Average methodology, rooted in the Box–Jenkins framework. The aim was to pinpoint a suitable time-series model for capturing production trends and producing dependable short-term predictions. To test for stationarity, the Augmented Dickey–Fuller unit root test was applied, while residual diagnostic assessments were conducted to check the suitability of the chosen model. Findings revealed that crude oil output was non-stationary at the levels, with an ADF statistic of −1.743 and a p-value of 0.6838. Nevertheless, upon first differencing, the series turned stationary, achieving an ADF statistic of −7.8812, suggesting integration of order one, I(1). The multiplicative ARIMA(4,1,4)12 model emerged as the most fitting model through the model selection criteria. Residual diagnostics demonstrated no considerable deviation from normal distribution at the 1% significance threshold (Shapiro–Wilk statistic = 0.98927, p = 0.1184) and no notable residual autocorrelation (Ljung–Box p = 0.8562). The model produced a root mean square error of 0.1058. Predictions spanning from July 2023 to June 2027 estimated monthly crude oil production to fall within the vicinity of 1.1 to 1.2 million barrels, based on the findings. The analysis advocates for the utilization of ARIMA modeling as an effective approach for forecasting and planning crude oil output in Nigeria.

Keywords

ForecastingCrudeOilProductionBoxJenkins & Methodology

References

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Forecasting Nigeria’s Crude Oil Production Using Box and Jenkins Methodology

Abstract

Keywords

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