PL EN


2011 | 12 | 1 | 179-192
Article title

Identifying an Appropriate Forecasting Model for Forecasting Total Import of Bangladesh

Authors
Content
Title variants
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.
Year
Volume
12
Issue
1
Pages
179-192
Physical description
Contributors
author
  • University of Dhaka
References
  • AMISANO, G. AND GIANNINI, C. (1997). Topics in Structural VAR Econometrics, Springer-Verlag, Berlin, 2nd edition.
  • GUJRATI, D. N. AND SANGEETHA (2007). Basic Econometrics, McGraw-Hill Book Co, New York.
  • HAMILTON,J.D. (1994). Time Series Analysis, Princeton University Press, Princeton.
  • MAKRIDAKIS, S., WHEELWRITGHT, S. C. AND HYNDMAN, R. J. (1998). Forecasting Methods and Applications, John Wiley and Sons, Ink., New York.
  • PFAFF, B. (2008). VAR, SVAR and SVEC Models: Implementation within R Package vars, New York. URL: http://CRAN.R-project.org/package=vars.
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.desklight-16baa304-2a0d-4cfe-9610-881b7329b85f
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