Economic Forecast of the Wealthiest Gulf Countries Using ARIMA Model
Gulf Cooperation Council (GCC) members are considered one of the fastest growing economies. This paper aims to empirically forecast the economic activity of the biggest GCC countries: Qatar, Saudi Arabia, and the United Arab Emirates. An Auto-Regressive Integrated Moving Average (ARIMA) model of the Gross Domestic Product in the three countries is obtained using the Box-Jenkins methodology during the 1980-2020 period. The appropriate models for the three economies are of ARIMA (0,2,1), the forecasts are at a 95% confidence level and predicts a growth in the three understudy countries for the upcoming five years.
Youssef, J., Ishker, N., Fakhreddine, N. 2021. Economic Forecast of the Wealthiest Gulf Countries Using ARIMA Model. Journal of Applied Economic Sciences, Volume XVI, Summer, 2(72): 228– 237. https://doi.org/10.57017/jaes.v16.2(72).08
[1] Ab Rahman, A.B., and Abu-Hussin, M.F.B. 2009. GCC economic integration challenge and opportunity for Malaysian economy, Journal of International Social Research, 2(9). Available at: https://www.research gate.net/publication/38106794_GCC_Economic_Integration_Challenge_and_Opportunity_for_Malaysian_Economy
[2] Abonazel, M.R., and Abd-Elftah, A.I. 2019. Forecasting Egyptian GDP using ARIMA models, Reports on Economics and Finance, 5(1): 35-47. DOI: 10.12988/ref.2019.81023
[3] Agrawal, V. 2018. GDP modelling and forecasting using ARIMA: An empirical study from India, Working paper, Central European University, Austria, Hungary.
[4] Box, G.E.P., and Jenkins, G. 1970. Time series analysis, forecasting and control, Holden-Day, San Francisco. ISBN - 10: 0816210942, ISBN - 13: 978-0816210947.
[5] Dinh, D.V. 2020. Forecasting domestic credit growth based on ARIMA model: Evidence from Vietnam and China, Management Science Letters, 10(5): 1001-1010. DOI: 10.5267/j.msl.2019.11.010
[6] Dritsaki, C.2015. Forecasting real GDP rate through econometric models: An empirical study from Greece” Journal of International Business and Economics, 3(1): 13-19. DOI: 10.15640/jibe.v3n1a2
[7] Eissa, N. 2020. Forecasting the GDP per Capita for Egypt and Saudi Arabia using ARIMA Models, Working paper, Faculty of Economics and Political Science, Future University, Egypt. DOI:10.5430/rwe.v11n1p247
[8] Judi, Y. 2007. Forecasting the Non–Oil GDP in the United Arab Emirates by Using ARIMA Models, International Review of Business Research Papers, 3(2): 162-183.
[9] Leamer, E.E., and Leamer, E.E. 2009. Gross Domestic Product, Macroeconomic Patterns and Stories, ISBN: 978-3-540-46389-4. DOI:10.1007/978-3-540-46389-4
[10] Maity, B., and Chatterjee, B. 2012. Forecasting GDP growth rates of India: An empirical study, International Journal of Economics and Management Sciences, 1: 52-58.
[11] Ning, W., Kuan-jiang, B., and Zhi-fa, Y.2010. Analysis and forecast of Shaanxi GDP based on the ARIMA Model, Asian Agricultural Research, 2(1812-2016-143365): 34-41. DOI: 10.22004/ag.econ.93238
[12] Vohra, R. 2017. The impact of oil prices on GCC economies, International Journal of Business and Social Science, 8(2): 7 - 14.
[13] Voumik, L.C., and Smrity, D.Y. 2020. Forecasting GDP per capita in Bangladesh: Using ARIMA Model, European Journal of Business and Management Research, 5(5). DOI: 10.24018/ejbmr.2020.5.5.533
[14] 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(2): 64-73. DOI: 10.11648/j.sjams.20160402.18
[15] Zakai, M. 2014. A time series modeling on GDP of Pakistan, Journal of Contemporary Issues in Business Research, 3(4): 200-210.
[16] Zhang, H., and Rudholm, N. 2013. Modeling and forecasting regional GDP in Sweden using autoregressive models, Working paper, Dalarna University, Sweden, Stockholm. Available at: http://www.statistics.du.se/ essays/BI_D13_HaonanZhang.pdf
*** Gulf Cooperation Council (GCC). Available at: II. The GCC Customs Union – January 2003 (gcc-sg.org)