UNIVARIATE MODELLING AND FORECASTING OF ENERGY DEMAND
Main Article Content
Abstract
A thorough assessment of energy sources and long-term energy demand predictions are crucial to the development of sustainable energy planning and policy for any country. However, these are uncommon practices in Nigeria, thereby resulting in shortage of energy supplies required by the economy and its growing population. In this study, energy demand in the commercial and public services, industrial, and residential sectors of the Nigerian economy is examined using Autoregressive Conditional Heteroskedasticity, Markov Switching, and Unobserved Component models. The results of the comparative study show that Markov Switching model performs better than Autoregressive Conditional Heteroskedasticity and Unobserved Component Model for energy demand forecasting. The outcomes further suggest that the energy demand in Nigeria will grow at an average annual rate of less than 2% from 2018 to 2050 in all the three sectors investigated. In view of these findings, the Nigerian Government should have made effort to collaborate with relevant stakeholders, aiming at harnessing the abundant energy resources needed to meet the future energy consumption with a guarantee of energy security and sustainability in the country.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0 DEED).
You are free to:
- Share — copy and redistribute the material in any medium or format
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes .
- NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
Rights of Authors
Authors retain the following rights:
1. Copyright and other proprietary rights relating to the article, such as patent rights,
2. the right to use the substance of the article in future works, including lectures and books,
3. the right to reproduce the article for own purposes, provided the copies are not offered for sale,
4. the right to self-archive the article.