Identifying an Appropriate Forecasting Model for Forecasting Total Import of Bangladesh

• Authors: Khan Tanvir
• Languages of publication: EN

Abstracts

EN

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.

Keywords

EN

ARIMA model; Holt Winters’ trend and seasonality method; VAR model; Forecasting accuracy; Out-of-sample accuracy measurement

• Publisher: Główny Urząd Statystyczny
• Journal: Statistics in Transition new series
• Year: 2011
• Volume: 12
• Issue: 1
• Pages: 179-192

Contributors

author

Khan Tanvir

• University of Dhaka

References

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