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

مجله اقتصاد و توسعه کشاورزی

Article 2, Volume 25, Issue 2, July 2011   

Document Type: Research Article

DOI: 10.22067/jead2.v1390i2.9705

Authors

M. Rafati^{* 1}; Y. Azarinfar²; R. Mohammadzadeh³

¹Faculty of ARDPERI

²MS in ARDPER

³MS in Agriculture Economic (Shiraz Un.)

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

References