Journal of Agricultural Economics & Development
Iranian Agricultural Economics Society (IAES)

Selection the Suitable Model for Forecasting land, Production and Price of Sugar Beet in Iran

Document Type : Research Article

Authors

M. Rafati 1
Y. Azarinfar 2
R. Mohammadzadeh 3

1 Faculty of ARDPERI

2 MS in ARDPER

3 MS in Agriculture Economic (Shiraz Un.)

https://doi.org/10.22067/jead2.v1390i2.9705
Abstract
Abstract
The aim of this study was to selecting the suitable model for forecast land, production and Price of sugar beet in Iran. For this purpose, Models applied to forecast are ARIMA, Single and Double Exponential Smoothing, Harmonic, Artificial Neural Network and ARCH for period 1993-2008. Results of Durbin-Watson tests, land, production and price of sugar beet series were found non stochastic and predictable. Based on the lowest forecasting error criterion, ARIMA is the best model for forecast production and price of sugar beet series. But in orther to forecast land of sugar beet, Neural Network model is the best. Hence, using the forecast method can affect on different policy about production via forecasting the fluctuation variables.
Jel Classification: Q11 – D12 – C32 – C22

Keywords

ARCH
ARIMA
Artificial Neural Network
Exponential Smoothing
Forecasting
Harmonic
Iran
Land
Production
Price
Sugar beet
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  • Receive Date 11 September 2011
  • First Publish Date 11 September 2011

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