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Identifying an appropriate forecasting model for forecasting total import of Bangladesh

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  • TANVIR KHAN

Abstract

Forecasting future values of economic variables are some of the most critical tasks of a country. Especially the values related to foreign trade are to be forecasted efficiently as the need for planning is great in this sector. The main objective of this research paper is to select an appropriate model for time series forecasting of total import (in taka crore) of Bangladesh. The decision throughout this study is mainly concerned with seasonal autoregressive integrated moving average (SARIMA) model, Holt-Winters’ trend and seasonal model with seasonality modeled additively and vector autoregressive model with some other relevant variables. An attempt was made to derive a unique and suitable forecasting model of total import of Bangladesh that will help us to find forecasts with minimum forecasting error

Suggested Citation

  • Tanvir Khan, 2011. "Identifying an appropriate forecasting model for forecasting total import of Bangladesh," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 12(1), pages 179-192, August.
    • Handle: RePEc:csb:stintr:v:12:y:2011:i:1:p:179-192
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    Citations

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    Cited by:

    1. Sara Rafiq & Liu Hai Yun & Gulzar Ali, 2016. "Forecasting the Trend Analysis of Trade Balance of Pakistan: A Theoretical and Empirical Investigation," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 6(7), pages 188-214, July.
    2. Hussain, Anwar & Rahman, Muhammad & Memon, Junaid Alam, 2016. "Forecasting electricity consumption in Pakistan: the way forward," Energy Policy, Elsevier, vol. 90(C), pages 73-80.
    3. Nyoni, Thabani, 2019. "Exports and imports in Zimbabwe: recent insights from artificial neural networks," MPRA Paper 96906, University Library of Munich, Germany.

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