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Time Series Modeling and Forecasting on GDP Data of Bangladesh: An Application of Arima Model

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  • Md Ariful Haque

    (Lecturer, Department of Management Information Systems. Khawaja Yunus Ali University, Bangladesh.)

  • Aziz Ahmed

    (Senior Manager (M&E Expert), Non-Government Organization, Bangladesh.)

Abstract

The basic economic condition of a country is measured and presented by Gross Domestic Product (GDP). Government’s high officials, Business owners or managers, rely on forecasting of GDP, to determine fiscal year monitory policy and operating activities. This paper has collected GDP data from 1971 to 2021 from an international website. Exploratory analysis has performed for trend, seasonality & outlier detection. Augmented Dickey-Fuller test, Phillip Peron and Kwiatkowski-Phillips-Schmidt-Shin test has performed to check seasonality and stationary. To determine the best fitted model for GDP, ARIMA models (Autoregressive integrated Moving Average) have constructed using Box-Jenkins technique. Considering all statistical criterions this paper has determined ARIMA (4, 2, 1) isthe best fitted model and forecasted for the next ten years. Finally, residual test has performed to determine reliable forecasting.

Suggested Citation

  • Md Ariful Haque & Aziz Ahmed, 2024. "Time Series Modeling and Forecasting on GDP Data of Bangladesh: An Application of Arima Model," International Journal of Latest Technology in Engineering, Management & Applied Science, International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS), vol. 13(4), pages 199-207, April.
    • Handle: RePEc:bjb:journl:v:13:y:2024:i:4:p:199-207
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    References listed on IDEAS

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    1. Abdullah Ghazo, 2021. "Applying the ARIMA Model to the Process of Forecasting GDP and CPI in the Jordanian Economy," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(3), pages 70-77, May.
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