This paper examines the application of the Autoregressive Integrated Moving Average (ARIMA) Model in modeling GDP. The paper critically reviews the empirical literature on the application of ARIMA models in modeling GDP in various economies with the objective of establishing the appropriateness and popularity of ARIMA model in studying GDP. The paper concludes that ARIMA (2, 2, 2) and ARIMA (3, 1, 1) are significantly applied in studies involving 182-days treasury bills and ARIMA (1, 1, 0) 91-days treasury bills respectively. This paper proposes the application of Q-statistic for autocorrelation, Jarque-Bera (JB) test for normality and Box-Jenkins analysis for model identification and estimation, diagnosis as well as forecasting. The paper further presents that the correlogram of real GDP rate series can be used for GDP modeling, specifically recommending the application of ARCH and GARCH family models in studies involving the analysis of treasury bills. Lastly, this paper recommends the adoption of the expenditure approach to measure GDP and proposes a model that can be adopted in GDP modeling.
Cite this paper
Muma, B. and Karoki, A. (2022). Modeling GDP Using Autoregressive Integrated Moving Average (ARIMA) Model: A Systematic Review. Open Access Library Journal, 9, e8355. doi: http://dx.doi.org/10.4236/oalib.1108355.
Abdul, N., Abdullah, Z. and Azhan, M. (2015) An Autoregressive Distributed Lag (ARDL) Analysis of the Nexus between Savings and Investment in the Three Asian Economies. The Journal of Developing Areas, 49, 323-334.
https://doi.org/10.1353/jda.2015.0154
Igbasan, S. and Olanrewaju, S. (2020) Comparison of Forecasting Models Using Nigeria Monthly Treasury Bill Rates Data. International Journal of Statistics and Applications, 10, 25-33.
United Nations (2015) As Developing Countries Strive to Enhance Economic Performance, Developed Partners Should Honour or Surpass Aid Pledges, Addis Conference Hears. https://www.un.org/press/en/2015/dev3187.doc.htm
United Nations (2020) Promote Inclusive and Sustainable Economic Growth, Employment and Decent Work for All.
https://www.un.org/sustainabledevelopment/economic-growth/
Karungu, R., Memba, F. and Muturi, W. (2020) Influence of Financial Contagion on Stock Performance of Firms Listed in the Nairobi Securities Exchange. Accounting, 6, 1-16. https://doi.org/10.5267/j.ac.2019.7.001
Aisen, A. and Veiga, F. (2011) How Does Political Instability Affect Economic Growth? IMF Working Paper No. 11/12, International Monetary Fund, Braga.
https://doi.org/10.2139/ssrn.1751422
Agrawal, V. (2018) GDP Modelling and Forecasting Using ARIMA: An Empirical Study from India. Doctoral Dissertation, Central European University, Budapest.
Caustisanu, C. and Hatmanu, M. (2019) Comparative Analysis of Economic Growth Determinants in Roman and Central and Eastern European Countries. Proceedings of the International Conference on Applied Statistics, 1, 162-170.
https://doi.org/10.2478/icas-2019-0014
Yang, B., Li, C.G., Li, M., Pan, K. and Wang, D. (2016) Application of ARIMA Model in the Prediction of the Gross Domestic Product. Advances in Intelligent Systems Research, 130, 1258-1262. https://doi.org/10.2991/mcei-16.2016.257
Wabomba, M.S., Mutwiri, M.P. and Fredrick, M. (2016) Modeling and Forecasting Kenyan GDP Using Autoregressive Integrated Moving Average (ARIMA) Models. Science Journal of Applied Mathematics and Statistics, 4, 64-73.
Verma, P., Dumka, A., Bhardwaj, A., et al. (2021) A Statistical Analysis of Impact of COVID19 on the Global Economy and Stock Index Returns. SN Computer Science, 2, Article No. 27. https://doi.org/10.1007/s42979-020-00410-w
Abonazel, M. and Abd-Elftah, A. (2019) Forecasting Egyptian GDP Using ARIMA Models. Reports on Economics and Finance, 5, 35-47.
https://doi.org/10.12988/ref.2019.81023
Omekara, C., Okereke, O. and Ehighibe, S. (2016) Time Series Analysis of Interest Rate in Nigeria: A Comparison of ARIMA and State Space Model. International Journal of Probability and Statistics, 5, 33-47.
Ondieki, I. (2014) Modelling Volatility of Interest and Treasury Bill Rates Using ARCH/GARCH Family and Their Effect on Pension Fund. University of Nairobi, Nairobi.
