Modeling and Forecasting of Agricultural Products Export in Iran: Application of Artificial Neural Networks

Document Type : Research Article

Authors

• H. Mehrabi
• S. Koochakzadeh

Department of Agricultural Economics, Shahid Bahonar University of Kerman

10.22067/jead2.v1388i1.2067

Abstract

Abstract
To get ride of fragile and unsustainable single product export, a comprehensive knowledge of export potential and comparative advantage is required. Agricultural products can be considered as a suitable target for this purpose. For more efficient planning for agricultural products export, proper forecasting is necessary. To achieve this goal, two methods were used and compared. First, an autoregressive integrated moving average (ARIMA) and second, artificial neural networks. For this purpose, the data were received from customhouse from 1961-2006. The data from 1961- 2002 were used for modeling and the last 4 years, were used for examination of forecasting power. Results indicated that artificial neural networks radial basis was more efficient in comparison with other neural networks methods and ARIMA for forecasting the quantity of agricultural products export. Finally, the quantities of agricultural products export forecasted for 2007-2011 by artificial neural networks radial basis.

Key words: Agricultural Products Export, ARIMA, Artificial Neural Networks, Iran

20.1001.1.20084722.1388.23.1.6.2

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