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Short-Term Forecasting of Nigeria Inflation Rates Using Seasonal ARIMA Model

Received: 29 March 2016     Accepted: 29 April 2016     Published: 25 May 2016
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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.

Published in Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 3)
DOI 10.11648/j.sjams.20160403.13
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.

Copyright

Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Inflation Rates, Seasonal Time Series, SARIMA Model, Forecasting

References
[1] Adebiyi, M. A., Adenuga, A. O., Abeng, M. O., Omanukwe, P. N., and Ononugbo, M. C. (2010): Inflation forecasting models for Nigeria. Central Bank of Nigeria Occassional Paper No. 36, Abuja, Research and Statistics Department.
[2] Aidan, M., Geoff, K. and Terry, Q. (1998): Forecasting Irish Inflation using ARIMA Models. CBI Technical Papers 3/RT/98: 1-48. Central Bank and Financial Services Authority of Ireland.
[3] Alan, P. (1983): Forecasting with univariate Box and Jenkins Models: Concepts and Case. Wiley and Sons. New York.
[4] Box, G. E. P. and Jenkins, G. M. (1976): Time series Analysis, Forecasting and Control. Holden Day, San Francisco.
[5] David, F. H. (2001): Modeling UK Inflation (1875 – 1991). Journal of Applied Econometrics, 16 (3), 255-275.
[6] Doguwa, S. I. and Alade, S. O. (2013): Short-term Inflation Forecasting Models for Nigeria. CBN Journal of Applied Statistics, 4 (2), 1-29.
[7] Etuk, E. H. (2012): Predicting Inflation Rates of Nigeria Using a Seasonal Box-Jenkins Model. Journal of Statistical and Econometric Methods, 1 (3), 27-37.
[8] Etuk, E. H., Uchendu, B. and Victoredema, U. A. (2012): Forecasting Nigeria Inflation Rates by a Seasonal ARIMA Model. Canadian Journal of Pure and Applied Sciences, 6 (3), 2179-2185.
[9] Fakiyesi, O. M. (1996): Further Empirical Analysis of Inflation in Nigeria. Central Bank of Nigeria Economic and Financial Review, 34 (1), 489-499.
[10] Gary, G. M. (1995): The main determinants of Inflation in Nigeria. IMF Staff Papers. International Monetary Fund, 42 (2), 270-289.
[11] Hall, R. (1982): Inflation: Causes and Effects. University of Chicago Press, Chicago.
[12] Imimole, B. and Enoma, A. (2011): Exchange Rates Depreciation and Inflation in Nigeria (1986-2008). Business and Economics Journal, BEJ-28, 1-12.
[13] Johnson, H. G. (1973): Further Essay in Monetary Economy. George Wallen and Unwin. London.
[14] Junttila, J. (2001): Structural breaks, ARIMA models and finish Inflation forecasts. International Journal of Forecasting, 17, 203-230.
[15] Odusanya, I. A. and Atanda, A. A. M. (2010): Analysis of Inflation and its determinants in Nigeria: Pakistan Journal of Social Sciences, 7 (2), 97-100.
[16] Ojameruaye, E. O. (1998): Analysis of the determinants of general price level in Nigeria. Research and Development, 5 (1, 2), 80-96.
[17] Olajide, J. T., Ayansola, O. A., Odusina, M. T. and Oyenuga, I. F. (2012): Forecasting the Inflation Rates in Nigeria: Box-Jenkins Approach. IOSR Journal of Mathematics, 3 (5), 15-19.
[18] Onwioduokit, E. A. (2002): Fiscal Deficit and Inflation in Nigeria: An Empirical Investigation of Causal Relationships. CBN Economic and Financial Review, 37 (2), 1-1.
[19] Otu, A. O., Osuji, G. A., Opara, J., Mbachu, H. I. and Iheagwara, A. I. (2014): Application of SARIMA models in modeling and forecasting Nigeria’s Inflation Rates. American Journal of Applied Mathematics and Statistics, 2 (1), 16-28.
[20] Omekara, C. O., Ekpenyong, E. J. and Ekerete, M. P. (2013): Modeling the Nigeria Inflation Rates using Periodogram and Fourier Series Analysis. CBN Journal of Applied Statistics, 4 (2), 51-68.
[21] Pufnik, A. and Kunovac, D. (2006): Short-term Forecasting of Inflation in Croatia with Seasonal ARIMA processes. Working Paper, w-16, Croatia National Bank.
[22] Saz, G. (2011): The Efficacy of SARIMA Models for Forecasting Inflation Rates of Developing Countries: The Case for Turkey. International Research Journal and Finance and Economics, 62, 111-142.
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Cite This Article
  • 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

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    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

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    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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  • @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}
    }
    

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    T1  - Short-Term Forecasting of Nigeria Inflation Rates Using Seasonal ARIMA Model
    AU  - Ekpenyong Emmanuel John
    AU  - Udoudo Unyime Patrick
    Y1  - 2016/05/25
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    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
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Author Information
  • Department of Statistics, Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria

  • Department of Statistics, Akwa Ibom State Polytechnic, Ikot Osurua, Akwa Ibom State, Nigeria

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