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: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MAXWELL Science Publication
2013
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| Subjects: | |
| 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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| Summary: | 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. |
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