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

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  • Karbasi, Ali Reza
  • Laskukalayeh, Somayeh Shirzadi
  • Fahimifard, Seiad Mohammad

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.

Suggested Citation

  • Karbasi, Ali Reza & Laskukalayeh, Somayeh Shirzadi & Fahimifard, Seiad Mohammad, 2009. "Comparison of NNARX, ANN and ARIMA Techniques to Poultry Retail Price Forecasting," 2009 Conference, August 16-22, 2009, Beijing, China 50321, International Association of Agricultural Economists.
    • Handle: RePEc:ags:iaae09:50321
    DOI: 10.22004/ag.econ.50321
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    Keywords

    Demand and Price Analysis; Marketing;

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