Predictive Modelling and Analysis of Petroleum Prices (PMS, AGO, DPK) Using the Non-Linear Logistic Approach

The study investigated the use of mathematical equations to predict and analyze the unit pump price of petroleum products in Nigeria. A logistic model was developed and solved into its analytic solution. Fuel pump prices from all over Nigeria for PMS, AGO, and DPK were obtained from the statistical facts sheet of the Nigerian Upstream Petroleum Regulatory Commission (NUPRC) and plotted into a scatter diagram. The analytic solution of the model developed was superimposed on the scatter diagram to see its fitness. The model fitted into the scatter diagram excellently, with R² values reaching 0.996 for PMS, 0.9915 for AGO, and 0.9984 for DPK, confirming its robustness in predicting future prices and the meandering of the profile among the points of the scatter diagram. The model showed that the pump price phenomenon was model-able and predictive and revealed a projected saturation point for AGO prices at NGN 2062.25 by 2058, which indicated a gradual stabilization of the market. The Nigerian unit pump prices of petrol, diesel, and kerosene from 1992 to 2016 obey the model equation up to a degree of accuracy. The logistic model employed effectively captured the non-linear behaviour of petroleum prices and offered a more accurate representation compared to traditional linear models. However, the rate of price increases was projected to decline over time, suggesting a potential mitigation of the burden of rising fuel costs in the long run. The study's findings have implications for policymakers, consumers, and industry stakeholders and provide valuable insights for informed decision-making. Received: 11 September 2024 | Revised: 20 December 2024 | Accepted: 21 January 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data available on request from the corresponding author upon reasonable request. Author Contribution Statement Chinemerem Jerry Chukwu: Conceptualization, Writing - original draft, Supervision. Lawal Kunle Adam: Conceptualization, Writing - original draft. Obasi Daniel Ebubechi: Methodology, Investigation, Writing - review & editing. Akoma Ugochukwu Chibuzo: Methodology, Investigation, Writing - review & editing. Ajadalu Samson Oseiwe: Software, Visualization. Ogamba Chidube: Software, Visualization. Olaremi Samuel Oluwasijibomi: Validation, Project administration. Sunday Abayomi Joseph: Validation, Supervision, Project administration. Mohammed Sherif Ali: Formal analysis, Data curation. Chukwuma Richard Chukwudi: Formal analysis, Data curation. Eze Simeon Okechukwu: Investigation, Resources. Saifullahi Abdullahi Abubakar: Investigation, Resources.

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Journal
Archives of Advanced Engineering Science
Published
2025-02-18
DOI
https://doi.org/10.47852/bonviewaaes52024316
Primary Topic
Market Dynamics and Volatility
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article
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article

Predictive Modelling and Analysis of Petroleum Prices (PMS, AGO, DPK) Using the Non-Linear Logistic Approach

M. Ali, S. J. Sathish Aaron Joseph, S. Abubakar, Chinemerem Jerry Chukwu et al.
Archives of Advanced Engineering Science
Market Dynamics and Volatility
article

Predictive Modelling and Analysis of Petroleum Prices (PMS, AGO, DPK) Using the Non-Linear Logistic Approach

M. Ali, S. J. Sathish Aaron Joseph, S. Abubakar, Chinemerem Jerry Chukwu, Chukwuma Richard Chukwudi, Eze Simeon Okechukwu, Obasi Daniel Ebubechi, Akoma Ugochukwu Chibuzo, Ajadalu Samson Oseiwe, Ogamba Chidube, Olaremi Samuel Oluwasijibomi
article en

Abstract

The study investigated the use of mathematical equations to predict and analyze the unit pump price of petroleum products in Nigeria. A logistic model was developed and solved into its analytic solution. Fuel pump prices from all over Nigeria for PMS, AGO, and DPK were obtained from the statistical facts sheet of the Nigerian Upstream Petroleum Regulatory Commission (NUPRC) and plotted into a scatter diagram. The analytic solution of the model developed was superimposed on the scatter diagram to see its fitness. The model fitted into the scatter diagram excellently, with R² values reaching 0.996 for PMS, 0.9915 for AGO, and 0.9984 for DPK, confirming its robustness in predicting future prices and the meandering of the profile among the points of the scatter diagram. The model showed that the pump price phenomenon was model-able and predictive and revealed a projected saturation point for AGO prices at NGN 2062.25 by 2058, which indicated a gradual stabilization of the market. The Nigerian unit pump prices of petrol, diesel, and kerosene from 1992 to 2016 obey the model equation up to a degree of accuracy. The logistic model employed effectively captured the non-linear behaviour of petroleum prices and offered a more accurate representation compared to traditional linear models. However, the rate of price increases was projected to decline over time, suggesting a potential mitigation of the burden of rising fuel costs in the long run. The study's findings have implications for policymakers, consumers, and industry stakeholders and provide valuable insights for informed decision-making. Received: 11 September 2024 | Revised: 20 December 2024 | Accepted: 21 January 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data available on request from the corresponding author upon reasonable request. Author Contribution Statement Chinemerem Jerry Chukwu: Conceptualization, Writing - original draft, Supervision. Lawal Kunle Adam: Conceptualization, Writing - original draft. Obasi Daniel Ebubechi: Methodology, Investigation, Writing - review & editing. Akoma Ugochukwu Chibuzo: Methodology, Investigation, Writing - review & editing. Ajadalu Samson Oseiwe: Software, Visualization. Ogamba Chidube: Software, Visualization. Olaremi Samuel Oluwasijibomi: Validation, Project administration. Sunday Abayomi Joseph: Validation, Supervision, Project administration. Mohammed Sherif Ali: Formal analysis, Data curation. Chukwuma Richard Chukwudi: Formal analysis, Data curation. Eze Simeon Okechukwu: Investigation, Resources. Saifullahi Abdullahi Abubakar: Investigation, Resources.

Archives of Advanced Engineering Science
University of Nigeria (NG), University of Ilorin (NG), Niger Delta University (NG), Federal University of Technology Owerri (NG), Federal University of Technology (NG), Ashland University (US), University of Lagos (NG), Adekunle Ajasin University (NG), University of Petroleum (ID), University of Benin (NG), Erciyes University (TR)
Openalex Percentile: Top 96%
Market Dynamics and Volatility
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