Forecasting Coarse Rice Prices in Bangladesh

Authors

  • MF Hassan Department of Agricultural Statistics, Bangladesh Agricultural University Mymensingh-2202
  • MA Islam Professor, Department of Agricultural Statistics, Bangladesh Agricultural University, Mymensingh-2202
  • MF Imam Associate Professor, Department of Agricultural Statistics, Bangladesh Agricultural University, Mymensingh-2202
  • SM Sayem Lecturer, Department of Agricultural Statistics, Bangladesh Agricultural University, Mymensingh-2202,

DOI:

https://doi.org/10.3329/pa.v22i1-2.16480

Keywords:

Coarse rice, Forecasting, Price

Abstract

Bangladesh being a developing country, always tries to control the market prices of coarse rice for stable political and social condition. The main aim of this paper is to find out appropriate deterministic time series model using the latest selection criteria that could best describe the coarse rice price pattern in Bangladesh during the time period July 1975 to December 2011. A total of 438 secondary data on monthly wholesale prices of coarse rice from July 1975 to December 2011 have been used for time series analysis. In this study growth models of different types are fitted using the software package SPSS 20 for the selected time series. The study reveals that cubic model is the best fitted model for wholesale price of coarse rice on the basis of model selection criterion (R2, R2 , RMSE, AIC, BIC, MAE and MAPE). Cubic growth rates varied from 0.68% to 4.03%. After choosing the best growth model by the model selection criteria the coarse rice prices are forecasted for the time period January 2012 to December 2013.

DOI: http://dx.doi.org/10.3329/pa.v22i1-2.16480

Progress. Agric. 22(1 & 2): 193-201, 2011

Downloads

Download data is not yet available.
Abstract
881
PDF
1234

Downloads

Published

2013-09-26

How to Cite

Hassan, M., Islam, M., Imam, M., & Sayem, S. (2013). Forecasting Coarse Rice Prices in Bangladesh. Progressive Agriculture, 22(1-2), 193–201. https://doi.org/10.3329/pa.v22i1-2.16480

Issue

Section

Social Science