Modeling for growth and forecasting of pulse production in Bangladesh

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 1st order homogenous stationary...

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Main Authors: Rahman, Niaz Md. Farhat, Rahman, Mohammad Mijanur, Baten, Md Azizul
Format: Article
Language:English
Published: MAXWELL Science Publication 2013
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Online Access:http://repo.uum.edu.my/12825/1/5587.pdf
http://repo.uum.edu.my/12825/
http://maxwellsci.com/jp/abstract.php?jid=RJASET&no=316&abs=14
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Institution: Universiti Utara Malaysia
Language: English
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spelling my.uum.repo.128252014-12-17T07:42:16Z http://repo.uum.edu.my/12825/ Modeling for growth and forecasting of pulse production in Bangladesh Rahman, Niaz Md. Farhat Rahman, Mohammad Mijanur Baten, Md Azizul QA76 Computer software 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 1st order 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. MAXWELL Science Publication 2013 Article PeerReviewed application/pdf en http://repo.uum.edu.my/12825/1/5587.pdf Rahman, Niaz Md. Farhat and Rahman, Mohammad Mijanur and Baten, Md Azizul (2013) Modeling for growth and forecasting of pulse production in Bangladesh. Research Journal of Applied Sciences, Engineering and Technology, 5 (24). pp. 5578-5587. ISSN 2040-7459 http://maxwellsci.com/jp/abstract.php?jid=RJASET&no=316&abs=14
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Rahman, Niaz Md. Farhat
Rahman, Mohammad Mijanur
Baten, Md Azizul
Modeling for growth and forecasting of pulse production in Bangladesh
description 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 1st order 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.
format Article
author Rahman, Niaz Md. Farhat
Rahman, Mohammad Mijanur
Baten, Md Azizul
author_facet Rahman, Niaz Md. Farhat
Rahman, Mohammad Mijanur
Baten, Md Azizul
author_sort Rahman, Niaz Md. Farhat
title Modeling for growth and forecasting of pulse production in Bangladesh
title_short Modeling for growth and forecasting of pulse production in Bangladesh
title_full Modeling for growth and forecasting of pulse production in Bangladesh
title_fullStr Modeling for growth and forecasting of pulse production in Bangladesh
title_full_unstemmed Modeling for growth and forecasting of pulse production in Bangladesh
title_sort modeling for growth and forecasting of pulse production in bangladesh
publisher MAXWELL Science Publication
publishDate 2013
url http://repo.uum.edu.my/12825/1/5587.pdf
http://repo.uum.edu.my/12825/
http://maxwellsci.com/jp/abstract.php?jid=RJASET&no=316&abs=14
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