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Modeling and Forecasting of Nigeria Crude Oil Production

Author

Listed:
  • Chigozie Kelechi Acha

    (Department of Statistics, Michael Okpara University of Agriculture Umudike, Abia State, Nigeria)

  • Christain Chinenye Amalahu

    (Department of Mathematics, Faculty of Sciences, University of Agriculture and Environmental Sciences, Umuagwo, Imo State, Nigeria)

  • C. Emmanuel Eziokwu

    (Departments of Mathematics, College of Physical and Applied Science, Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria)

Abstract

This paper assessed comprehensively and systematically the predictive capabilities of the Nigerian Monthly Crude Oil Production forecasting models. To obtain the generality of the empirical results, ARIMA model was used. Some of the frequently used measures of forecast adequacy such as Mean Error (ME), Mean Absolute Error (MAE), Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) were used to evaluate the forecast performance of the chosen models. This study reveals the fact that ARIMA (1, 1, 1) model is the best or optimal model for the period forecasted. The study fitted an appropriate time series models of crude oil production in Nigeria (2005-2022) which provided a useful forecast for quantity of crude oil production and export for the purpose of making reliable budget for the sustenance of the economy. This study reveals the fact that ARIMA (1, 1, 1) model is the best or optimal model for the period forecasted.

Suggested Citation

  • Chigozie Kelechi Acha & Christain Chinenye Amalahu & C. Emmanuel Eziokwu, 2023. "Modeling and Forecasting of Nigeria Crude Oil Production," Journal of Mathematics and Statistics Studies, Al-Kindi Center for Research and Development., vol. 4(1), pages 58-67, February.
    • Handle: RePEc:alk:jmss00:v:4:y:2023:i:1:id:6604
    DOI: 10.32996/jmss.2023.4.1.5
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