Agricultural Research Management Information System

Home
Research Summary
Search
About Us
- ARMIS
- Brochure
Contact Us
Report
User Request
Data Input
Help
- Operation Manual
  - PDF
  - Video
- Program Area & Commodity
We have reached 37600 number of research entries at this moment.

- Logout

Research Detail

Home
Research
Detail

An Analysis of Rice Price in Mymensing Town Market: Pattern and Forecasting

S.A. Sabur
Associate Professor
Associate Professor, Department of Cooperation and MarketingBangladesh Agricultural University, Mymensingh

Md. Ershadul Haque
Assistant Professor
Assistant Professor, Department of Agricultural Statistics, Bangladesh Agricultural University, Mymensingh

Abstract/ Executive Summary:

The paper investigates the trend, seasonal and cyclic al variations of retail and wholesale prices of price in Mymensingh town market and forecasts the future prices based on ARIMA model. Compound growth rates of real prices indicate that consumers seem to he better off with respect to rice price since independence, particularly during 80's. Seasonal price variation of fine rice is found to be higher compared with coarse rice because of continuous flow of coarse rice in the market. Peak price month has changed to April from September and seasonal price variation has reduced markedly due to higher production of Boro paddy. Apart from seasonal cycles, there exist a five year cycle in rice price as revealed by the harmonic analysis. As the structure of rice price has changed since independence, the forecasting of prices based on ARIMA model for the whole period provides poor performance. However, the forecasting of prices improves considerably when the study period is reduced. Thus, it may be concluded that ARIMA model can be used to forecast short term rice price in Bangladesh.

Keywords: Analysis, Rice price, Market.Pattern and forecasting

Location:

Start Date:

End Date:

Program Area: Socio-economic and Policy

Commodity: Rice

Objectives:

To investigate the pattern of retail and wholesale prices of rice of Mymensingh town and to forecast their future movement using ARIMA model.

Methodology:

Compound growth rates (C.G.R.) of price were calculated by fitting exponential functions of the type bt Y=ae or lo- Y =log a+bt Where Y = price of rice in tea and t = time. Seasonal variations were estimated by ratio to moving average method considering multiplicative model. Trends were estimated by a simple 12 months moving average method and seasonal indices were worked out by averaging the detrended series. To analyze nature of cycles influencing the behavior of various agricultural commodities, harmonic and spectral analysis are commonly used. hartnonic analysis is simple as it involves an easy procedure ol calculation while spectral analysis involves a somewhat difficult and tedious procedure. Some studies using harmonic analysis include Abel's (1962) study on cattle and hog cycles in U.S.A., Kulsreshta and Wilson's (1973) study on same subjects in Canada, Waugh and Miller's (1970) study on fish cycles and george and Ciovinda's t1975) study on potato cycles in India. Hartnonic analysis is a technique in which a continuous function is represented by a sine and cosine functions. In this study, the following function was estimated.

Source of Information: Bangladesh J. Agric.Econs. XVI, 2(December 1993): 61-75

Article Link (Online Journal):

Funding Source:

Total Budget (Tk.) :

Achievement/Findings:

Compound growth rates of real prices indicate that consumers seem to he better off with respect to rice price since independence, particularly during 80's. Seasonal price variation of fine rice is found to be higher compared with coarse rice because of continuous flow of coarse rice in the market. Peak price month has changed to April from September and seasonal price variation has reduced markedly due to higher production of Boro paddy. Apart from seasonal cycles, there exist a five year cycle in rice price as revealed by the harmonic analysis. As the structure of rice price has changed since independence, the forecasting of prices based on ARIMA model for the whole period provides poor performance. However, the forecasting of prices improves considerably when the study period is reduced. Thus, it may be concluded that ARIMA model can be used to forecast short term rice price in Bangladesh.

Knowledge Management: Journal