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

Md Ariful Haque and Aziz Ahmed
Additional contact information
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.

International Journal of Latest Technology in Engineering, Management & Applied Science, 2024, vol. 13, issue 4, 199-207

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.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.ijltemas.in/DigitalLibrary/Vol.13Issue4/199-207.pdf (application/pdf)
https://www.ijltemas.in/papers/volume-13-issue-4/199-207.html (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjb:journl:v:13:y:2024:i:4:p:199-207

Access Statistics for this article

International Journal of Latest Technology in Engineering, Management & Applied Science is currently edited by Dr. Pawan Verma

More articles in International Journal of Latest Technology in Engineering, Management & Applied Science from International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Bibliographic data for series maintained by Dr. Pawan Verma ().