This paper considers the analyses and forecasting of the monthly All-items (Year-on-Year change) Inflation Rates in Nigeria. The data used for this study are monthly All-items Inflation rates from 2000 to 2015 collected from the Central Bank of Nigeria. Analyses reveal that the Inflation rates of Nigeria are seasonal and follow a seasonal ARIMA Model, (0, 1, 0) x (0, 1, 1)12. The model is shown to be adequate and the forecast obtained from it are shown to agree closely with the original observations.
| DOI | 10.11648/j.sjams.20160403.13 |
| Published in | Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 3, June 2016) |
| Page(s) | 101-107 |
| 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. |
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Copyright © The Author(s), 2024. Published by Science Publishing Group |
Inflation Rates, Seasonal Time Series, SARIMA Model, Forecasting
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APA Style
Ekpenyong Emmanuel John, Udoudo Unyime Patrick. (2016). Short-Term Forecasting of Nigeria Inflation Rates Using Seasonal ARIMA Model. Science Journal of Applied Mathematics and Statistics, 4(3), 101-107. https://doi.org/10.11648/j.sjams.20160403.13
ACS Style
Ekpenyong Emmanuel John; Udoudo Unyime Patrick. Short-Term Forecasting of Nigeria Inflation Rates Using Seasonal ARIMA Model. Sci. J. Appl. Math. Stat. 2016, 4(3), 101-107. doi: 10.11648/j.sjams.20160403.13
AMA Style
Ekpenyong Emmanuel John, Udoudo Unyime Patrick. Short-Term Forecasting of Nigeria Inflation Rates Using Seasonal ARIMA Model. Sci J Appl Math Stat. 2016;4(3):101-107. doi: 10.11648/j.sjams.20160403.13
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Download@article{10.11648/j.sjams.20160403.13,
author = {Ekpenyong Emmanuel John and Udoudo Unyime Patrick},
title = {Short-Term Forecasting of Nigeria Inflation Rates Using Seasonal ARIMA Model},
journal = {Science Journal of Applied Mathematics and Statistics},
volume = {4},
number = {3},
pages = {101-107},
doi = {10.11648/j.sjams.20160403.13},
url = {https://doi.org/10.11648/j.sjams.20160403.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20160403.13},
abstract = {This paper considers the analyses and forecasting of the monthly All-items (Year-on-Year change) Inflation Rates in Nigeria. The data used for this study are monthly All-items Inflation rates from 2000 to 2015 collected from the Central Bank of Nigeria. Analyses reveal that the Inflation rates of Nigeria are seasonal and follow a seasonal ARIMA Model, (0, 1, 0) x (0, 1, 1)12. The model is shown to be adequate and the forecast obtained from it are shown to agree closely with the original observations.},
year = {2016}
}
TY - JOUR T1 - Short-Term Forecasting of Nigeria Inflation Rates Using Seasonal ARIMA Model AU - Ekpenyong Emmanuel John AU - Udoudo Unyime Patrick Y1 - 2016/05/25 PY - 2016 N1 - https://doi.org/10.11648/j.sjams.20160403.13 DO - 10.11648/j.sjams.20160403.13 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 - 101 EP - 107 PB - Science Publishing Group SN - 2376-9513 UR - https://doi.org/10.11648/j.sjams.20160403.13 AB - This paper considers the analyses and forecasting of the monthly All-items (Year-on-Year change) Inflation Rates in Nigeria. The data used for this study are monthly All-items Inflation rates from 2000 to 2015 collected from the Central Bank of Nigeria. Analyses reveal that the Inflation rates of Nigeria are seasonal and follow a seasonal ARIMA Model, (0, 1, 0) x (0, 1, 1)12. The model is shown to be adequate and the forecast obtained from it are shown to agree closely with the original observations. VL - 4 IS - 3 ER -
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