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     Research Journal of Applied Sciences, Engineering and Technology


Modeling for Growth and Forecasting of Pulse Production in Bangladesh

1Niaz Md. FarhatRahman, 2Mohammad MijanurRahman and 3Md. AzizulBaten
1Scientific Officer, Agricultural Statistics Division Bangladesh Rice Research Institute (BRRI), Gazipur-1701
2Department of Business Administration, Faculty of Business, Bangladesh University Mohammadpur, Dhaka, Bangladesh
3Department of Decision Science, School of Quantitative Sciences University Utara Malaysia, 01600, Sintok, Kedah DarulAman, Malaysia
Research Journal of Applied Sciences, Engineering and Technology  2013  24:5578-5587
http://dx.doi.org/10.19026/rjaset.5.4239  |  © The Author(s) 2013
Received: October 12, 2012  |  Accepted: December 06, 2012  |  Published: May 30, 2013

Abstract

The present study was carried out to estimate growth pattern and examine the best ARIMA model to efficiently forecasting pigeon pea, chickpea and field pea pulse production in Bangladesh. It appeared that the time series data for pigeon pea, chickpea and field pea were 1storder homogenous stationary. Two types of models namely Box-Jenkins type Autoregressive Integrated Moving Average (ARIMA) and deterministic type growth models, are examined to identify the best forecasting models for pigeon pea, chickpea and field pea pulse production in Bangladesh. The study revealed that the best models were ARIMA (1, 1 and 1), ARIMA (0, 1 and 0) and ARIMA (1, 1 and 3) for pigeon pea, chickpea and field pea pulse production, respectively. Among the deterministic type growth models, the cubic model is best for pigeon pea, chickpea and field pea pulse production. The analysis indicated that short-term forecasts were more efficient for ARIMA models compared to the deterministic models. The production uncertainty of pulse could be minimized if production were forecasted well and necessary steps were taken against losses. The findings of this study would be more useful for policy makers, researchers as well as producers in order to forecast future national pulse production more accurately in the short run.

Keywords:

ARIMA model, chickpea, field pea, forecasting, growth model, pigeon pea,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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