IDEAS home Printed from https://ideas.repec.org/a/ibn/ijbmjn/v16y2023i6p56.html
   My bibliography  Save this article

Forecasting GDP of Bangladesh Using ARIMA Model

Author

Listed:
  • K. M. Salah Uddin
  • Nishat Tanzim

Abstract

Gross Domestic Product (GDP) is an important indicators of a country’s economic growth. To assist in decision making process, this study intends to forecast the GDP for seven years and identify the factors affecting the GDP in context of Bangladesh using the data from World Bank. The Autoregressive Integrated Moving Average (ARIMA) model is adopted to predict the GDP from 2019 to 2025 and multiple linear regression has been used to explore the factors affecting GDP. Different types of ARIMA (P, I, Q) tested and applied the ARIMA (1, 2, 1) model are found as best appropriate for forecasting. Q-Q plot, residuals plot, PACF and ACF graphs of the residuals are drawn for checking model adequacy. From this study, it is observed that GDP trend is steadily improving over years in Bangladesh that will remain expanding in the forthcoming.

Suggested Citation

  • K. M. Salah Uddin & Nishat Tanzim, 2023. "Forecasting GDP of Bangladesh Using ARIMA Model," International Journal of Business and Management, Canadian Center of Science and Education, vol. 16(6), pages 1-56, February.
    • Handle: RePEc:ibn:ijbmjn:v:16:y:2023:i:6:p:56
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/ijbm/article/download/0/0/45220/47952
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/ijbm/article/view/0/45220
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rudrani Bhattacharya & Parma Chakravartti & Sudipto Mundle, 2019. "Forecasting India’s economic growth: a time-varying parameter regression approach," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 12(3), pages 205-228, September.
    2. Taoxiong Liu & Xiaofei Xu & Fangda Fan, 2018. "Forecasting Chinese GDP Using Online Data," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(4), pages 733-746, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bhattacharya, Rudrani & Mundle, Sudipto, 2021. "A nowcast of 2021-22 GDP growth and forecast for 2022-23 based on a Factor Augmented Time Varying Coefficients Regression Model," Working Papers 21/361, National Institute of Public Finance and Policy.
    2. Shikha Gupta & Nand Kumar, 2023. "Time varying dynamics of globalization effect in India," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 22(1), pages 81-97, January.
    3. Benedikt Maas, 2020. "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 394-411, April.
    4. Stotsky, Janet G. & Chakraborty, Lekha & Gandhi, Piyush, 2018. "Impact of Intergovernmental Fiscal Transfers on Gender Equality in India: An Empirical Analysis," Working Papers 18/240, National Institute of Public Finance and Policy.
    5. Barker, Jamie & Herrala, Risto, 2021. "Assessing the mid-term growth outlook for the Indian economy," BOFIT Policy Briefs 8/2021, Bank of Finland Institute for Emerging Economies (BOFIT).
    6. Shikha Gupta & Nand Kumar, 2021. "Dynamics of globalization effect in India," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(6), pages 1394-1406, September.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:ijbmjn:v:16:y:2023:i:6:p:56. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.