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Application of ARIMAX Model on Forecasting Nigeria’s GDP

Received: 12 July 2021    Accepted: 21 July 2021    Published: 29 October 2021
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Abstract

This paper proposes an appropriate ARIMAX model that is used to forecast the Nigeria’s GDP. The data used for the study is sourced from the World Bank for a period of 1990-2019. The ARIMA model is fitted on the residuals using Box-Jenkins approach. The Bayesian Information Criterion (BIC) is adopted to assess the adequacy of the models. The raw data satisfy the assumption of multicollinearity when export is eliminated and the residual series is stationary after the first differencing. This study shows that import is a significant exogenous variable for the GDP dynamics. The ARIMA (0,1,1) with BIC value of 35.253 is considered the appropriate model to be combined with the exogenous variable. The results showed that the ARIMAX (0,1,1) is more ideal and adequate for forecasting Nigeria’s GDP based on the Theil’s U forecast accuracy measures.

Published in American Journal of Theoretical and Applied Statistics (Volume 10, Issue 5)
DOI 10.11648/j.ajtas.20211005.12
Page(s) 216-225
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), 2024. Published by Science Publishing Group

Keywords

GDP, Regression, BIC, ARIMA, ARIMAX, Theil’s U Statistic

References
[1] ABONAZEL, M. R., ABD-ELFTAH, A. J., Forecasting Egyptian GDP using ARIMA Models, Reports on Economics and Finance, 2019, Vol. 5, No. 1, 35-47.
[2] ARNEJA, R. S., KAUR N., SAIHHJPAL, Analyses and Forecasting Evaluation of GDP of India using ARIMA Model, International Journal of Advanced Science and Technology, 2020, vol. 29, No. 11s, 1102-1107.
[3] ATANU ENEBI Y., ETTE HARRISON E., NWUJU KINGDOM, NWAOHA WILLIAN C., ARIMA Model for Gross Domestic Product (GDP): Evidence from Nigeria, Archives of Current Research International, 2020, 20 (7), 49-61.
[4] AWEL, Y. M., Forecasting GDP Growth: Application of Autoregressive Integrated Moving Average Model, Empirical Economic Review, 2018, Vol. 1, No. 2, 1-16.
[5] CHIKUMBE, E. S., SIKOTA, S., Forecasting Zambia’s Gross Domestic Product using Time Series Autoregressive Integrated Moving Average (ARIMA) Model, International Journal of Innovation Science and Research Technology, 2020, Vol. 5, Issue 9.
[6] DURKA, P., PASTOREKOVA, S., ARIMA vs ARIMAX – which approach is better to analyze and forecast macroeconomic time series? Proceedings of 30th international conference on mathematical methods in economics, 2012, 136-140.
[7] EKHOSUEHI, V. U., OMOREGIE, D. E., Inspecting debt servicing mechanism in Nigeria using ARMAX model of the koyck-kind, Operations Research and Decisions, 2021, 31 (1), 5-20. DOI: 10.37190/ord210101.
[8] GHAZO ABDULLAH, Applying the ARIMA Model to the Process of Forecasting GDP and CPI in the Jordanian Economy, International Journal of Financial Research, 2020, Vol 12, No 3.
[9] LIU MEI, LI H., ZHOU Y., WANG W., XING F., Substructural damage detection in shear structures via ARMAX model and optimal subpattern assignment distance, Engineering Structures, 2019, 191, 625-639.
[10] MAITY, B., CHATTERJEE, B., Forecasting GDP growth rates of India: An empirical study, International Journal of Economics and Management Sciences, 2012, 1 (9), 52-58.
[11] MIAH, M. M., TABASSUM, M., RANA, M. S., Modeling and Forecasting of GDP in Bangladesh: An ARIMA Approach, Journal of Mechanics of Continua and Mathematical Science, 2019, 14 (3), 150-166.
[12] MUSUNDI SAMMY WABOMBA, M'MUKIIRA PETER MUTWIRI, MUNGAI FREDRICK, Modeling and forecasting Kenyan GDP using autoregressive integrated moving average (ARIMA) models, Science Journal of Applied Mathematics and Statistics, 2016, 4 (2), 64-73.
[13] NING, WEI, KUAN-JIANG, BIAN, ZHI-FA, YUAN, Analysis and Forecast of Shaanxi GDP Based on the ARIMA Model, Asian Agricultural Research, USA-China Science and Culture Media Corporation, 2010, 2 (01), 1-4.
[14] RANA, S. B., Forecasting GDP Movements in Nepal using Autoregressive Integrated Moving Average (ARIMA) Modelling Process, Journal of Business and Social Sciences Research, 2019, Vol. iv, No. 2.
[15] SALAH UDDIN, K. M, TANZIM, N., Forecasting GDP of Bangladesh using ARIMA Model, International Journal of Business and Management, 2021, Vol. 16, No. 6.
[16] TOUMA, H. Y., Application of the Statistical Analysis for Prediction of the Jordan GDP using ARIMA Time Series and Holt’s Linear Trend Models for the Period 2003-2013, Mathematical Theory and Modelling, 2014, 4 (14), 19-26.
[17] Ulyah, S. M., Mardianto, M. F., Sediono, F. (2019) Comparing the Performance of Seasonal ARIMAX Model and Nonparametric Regression Model in Predicting Claim Reserve of Education Insurance, Journal of Physics: Conference Series 1397 (2019) 012074 IOP Publishing doi: 10.1088/1742-6596/1397/1/012074.
[18] Wabomba, M. S., Mutwiri, M. P., Frederick, M., Modelling and Forecasting Kenyan GDP using ARIMA models, Science Journal of Applied Mathematics and Statistics, 2016, 4 (2), 64-73.
[19] ZAKAI, M., A time series modeling on GDP of Pakistan, Journal of Contemporary Issues in Business Research, 2014, 3 (4), 200-210.
[20] ZHENG W. X., On least-squares identification of ARMAX models, 15th Triennial World Congress, Barcelona, Spain, 2002, 391-296.
Cite This Article
  • APA Style

    Christogonus Ifeanyichukwu Ugoh, Chinwendu Alice Uzuke, Dominic Obioma Ugoh. (2021). Application of ARIMAX Model on Forecasting Nigeria’s GDP. American Journal of Theoretical and Applied Statistics, 10(5), 216-225. https://doi.org/10.11648/j.ajtas.20211005.12

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    ACS Style

    Christogonus Ifeanyichukwu Ugoh; Chinwendu Alice Uzuke; Dominic Obioma Ugoh. Application of ARIMAX Model on Forecasting Nigeria’s GDP. Am. J. Theor. Appl. Stat. 2021, 10(5), 216-225. doi: 10.11648/j.ajtas.20211005.12

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    AMA Style

    Christogonus Ifeanyichukwu Ugoh, Chinwendu Alice Uzuke, Dominic Obioma Ugoh. Application of ARIMAX Model on Forecasting Nigeria’s GDP. Am J Theor Appl Stat. 2021;10(5):216-225. doi: 10.11648/j.ajtas.20211005.12

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  • @article{10.11648/j.ajtas.20211005.12,
      author = {Christogonus Ifeanyichukwu Ugoh and Chinwendu Alice Uzuke and Dominic Obioma Ugoh},
      title = {Application of ARIMAX Model on Forecasting Nigeria’s GDP},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {10},
      number = {5},
      pages = {216-225},
      doi = {10.11648/j.ajtas.20211005.12},
      url = {https://doi.org/10.11648/j.ajtas.20211005.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20211005.12},
      abstract = {This paper proposes an appropriate ARIMAX model that is used to forecast the Nigeria’s GDP. The data used for the study is sourced from the World Bank for a period of 1990-2019. The ARIMA model is fitted on the residuals using Box-Jenkins approach. The Bayesian Information Criterion (BIC) is adopted to assess the adequacy of the models. The raw data satisfy the assumption of multicollinearity when export is eliminated and the residual series is stationary after the first differencing. This study shows that import is a significant exogenous variable for the GDP dynamics. The ARIMA (0,1,1) with BIC value of 35.253 is considered the appropriate model to be combined with the exogenous variable. The results showed that the ARIMAX (0,1,1) is more ideal and adequate for forecasting Nigeria’s GDP based on the Theil’s U forecast accuracy measures.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - Application of ARIMAX Model on Forecasting Nigeria’s GDP
    AU  - Christogonus Ifeanyichukwu Ugoh
    AU  - Chinwendu Alice Uzuke
    AU  - Dominic Obioma Ugoh
    Y1  - 2021/10/29
    PY  - 2021
    N1  - https://doi.org/10.11648/j.ajtas.20211005.12
    DO  - 10.11648/j.ajtas.20211005.12
    T2  - American Journal of Theoretical and Applied Statistics
    JF  - American Journal of Theoretical and Applied Statistics
    JO  - American Journal of Theoretical and Applied Statistics
    SP  - 216
    EP  - 225
    PB  - Science Publishing Group
    SN  - 2326-9006
    UR  - https://doi.org/10.11648/j.ajtas.20211005.12
    AB  - This paper proposes an appropriate ARIMAX model that is used to forecast the Nigeria’s GDP. The data used for the study is sourced from the World Bank for a period of 1990-2019. The ARIMA model is fitted on the residuals using Box-Jenkins approach. The Bayesian Information Criterion (BIC) is adopted to assess the adequacy of the models. The raw data satisfy the assumption of multicollinearity when export is eliminated and the residual series is stationary after the first differencing. This study shows that import is a significant exogenous variable for the GDP dynamics. The ARIMA (0,1,1) with BIC value of 35.253 is considered the appropriate model to be combined with the exogenous variable. The results showed that the ARIMAX (0,1,1) is more ideal and adequate for forecasting Nigeria’s GDP based on the Theil’s U forecast accuracy measures.
    VL  - 10
    IS  - 5
    ER  - 

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Author Information
  • Department of Statistics, Faculty of Physical Sciences, Nnamdi Azikiwe University, Awka, Nigeria

  • Department of Statistics, Faculty of Physical Sciences, Nnamdi Azikiwe University, Awka, Nigeria

  • Department of Statistics, Faculty of Physical Sciences, Nnamdi Azikiwe University, Awka, Nigeria

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