Comparison of NNARX, ANN and ARIMA Techniques to Poultry Retail Price Forecasting

Ali Reza Karbasi, Somayeh Shirzadi Laskukalayeh and Seiad Mohammad Fahimifard

No 50321, 2009 Conference, August 16-22, 2009, Beijing, China from International Association of Agricultural Economists

Abstract: The lack of study among the economic forecasting literature that can empirically proves the hypothesis of being more powerfulness of dynamic neural networks in comparison with the static neural networks models for forecasting, is the most important motivation of this study. In this paper, the utilization of NNARX as a nonlinear dynamic neural network model, ANN as a nonlinear static neural network model and ARIMA as a linear model were compared to forecast poultry retail price. As a case study on Iranian poultry retail price, we compare forecast performance of these models for three forecasts (1, 2 and 4 week ahead). Results show that NNARX and ANN models outperform ARIMA model, and also NNARX model outperforms ANN model for all three forecasts.

Keywords: Demand and Price Analysis; Marketing (search for similar items in EconPapers)
Pages: 12
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:ags:iaae09:50321

DOI: 10.22004/ag.econ.50321

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