Electricity has proved to be a vital input to most developing economies. As the Kenyan government aims at transforming Kenya into a newly-industrialized and globally competitive, more energy is expected to be used in the commercial sector on the road to 2030. Therefore, modelling and forecasting of electricity costs in Kenya is of vital concern. In this study, the monthly costs of electricity using Autoregressive Integrated Moving Average models (ARIMA) were used so as to determine the most efficient and adequate model for analysing the volatility of the electricity cost in Kenya. Finally, the fitted ARIMA model was used to do an out-off-sample forecasting for electricity cost for September 2013 to August 2016. The forecasting values obtained indicated that the costs will rise initially but later adapt a decreasing trend. A better understanding of electricity cost trend in the small commercial sector will enhance the producers make informed decisions about their products as electricity is a major input in the sector. Also it will assist the government in making appropriate policy measures to maintain or even lowers the electricity cost.
| Published in | Science Journal of Applied Mathematics and Statistics (Volume 3, Issue 2) |
| DOI | 10.11648/j.sjams.20150302.14 |
| Page(s) | 47-57 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Electricity, ARIMA, Forecast, Kenya
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APA Style
Mohammed Mustapha Wasseja, Samwel N. Mwenda. (2015). Analysis of the Volatility of the Electricity Price in Kenya Using Autoregressive Integrated Moving Average Model. Science Journal of Applied Mathematics and Statistics, 3(2), 47-57. https://doi.org/10.11648/j.sjams.20150302.14
ACS Style
Mohammed Mustapha Wasseja; Samwel N. Mwenda. Analysis of the Volatility of the Electricity Price in Kenya Using Autoregressive Integrated Moving Average Model. Sci. J. Appl. Math. Stat. 2015, 3(2), 47-57. doi: 10.11648/j.sjams.20150302.14
AMA Style
Mohammed Mustapha Wasseja, Samwel N. Mwenda. Analysis of the Volatility of the Electricity Price in Kenya Using Autoregressive Integrated Moving Average Model. Sci J Appl Math Stat. 2015;3(2):47-57. doi: 10.11648/j.sjams.20150302.14
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Download@article{10.11648/j.sjams.20150302.14,
author = {Mohammed Mustapha Wasseja and Samwel N. Mwenda},
title = {Analysis of the Volatility of the Electricity Price in Kenya Using Autoregressive Integrated Moving Average Model},
journal = {Science Journal of Applied Mathematics and Statistics},
volume = {3},
number = {2},
pages = {47-57},
doi = {10.11648/j.sjams.20150302.14},
url = {https://doi.org/10.11648/j.sjams.20150302.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20150302.14},
abstract = {Electricity has proved to be a vital input to most developing economies. As the Kenyan government aims at transforming Kenya into a newly-industrialized and globally competitive, more energy is expected to be used in the commercial sector on the road to 2030. Therefore, modelling and forecasting of electricity costs in Kenya is of vital concern. In this study, the monthly costs of electricity using Autoregressive Integrated Moving Average models (ARIMA) were used so as to determine the most efficient and adequate model for analysing the volatility of the electricity cost in Kenya. Finally, the fitted ARIMA model was used to do an out-off-sample forecasting for electricity cost for September 2013 to August 2016. The forecasting values obtained indicated that the costs will rise initially but later adapt a decreasing trend. A better understanding of electricity cost trend in the small commercial sector will enhance the producers make informed decisions about their products as electricity is a major input in the sector. Also it will assist the government in making appropriate policy measures to maintain or even lowers the electricity cost.},
year = {2015}
}
TY - JOUR T1 - Analysis of the Volatility of the Electricity Price in Kenya Using Autoregressive Integrated Moving Average Model AU - Mohammed Mustapha Wasseja AU - Samwel N. Mwenda Y1 - 2015/03/30 PY - 2015 N1 - https://doi.org/10.11648/j.sjams.20150302.14 DO - 10.11648/j.sjams.20150302.14 T2 - Science Journal of Applied Mathematics and Statistics JF - Science Journal of Applied Mathematics and Statistics JO - Science Journal of Applied Mathematics and Statistics SP - 47 EP - 57 PB - Science Publishing Group SN - 2376-9513 UR - https://doi.org/10.11648/j.sjams.20150302.14 AB - Electricity has proved to be a vital input to most developing economies. As the Kenyan government aims at transforming Kenya into a newly-industrialized and globally competitive, more energy is expected to be used in the commercial sector on the road to 2030. Therefore, modelling and forecasting of electricity costs in Kenya is of vital concern. In this study, the monthly costs of electricity using Autoregressive Integrated Moving Average models (ARIMA) were used so as to determine the most efficient and adequate model for analysing the volatility of the electricity cost in Kenya. Finally, the fitted ARIMA model was used to do an out-off-sample forecasting for electricity cost for September 2013 to August 2016. The forecasting values obtained indicated that the costs will rise initially but later adapt a decreasing trend. A better understanding of electricity cost trend in the small commercial sector will enhance the producers make informed decisions about their products as electricity is a major input in the sector. Also it will assist the government in making appropriate policy measures to maintain or even lowers the electricity cost. VL - 3 IS - 2 ER -
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