Predicting chicken meat price in Iranian poultry industry and comparing it with global outlook

Document Type : Research Paper

Authors

1 M.Sc. Student, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

2 Associate Professor, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

3 Professor, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

4 Assistant Professor, Department of Agriculture Economics, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

Abstract

At this study, with using from univariate and multivariate Econometrics Models of time series techniques, the annual prices from 2015 to 2020 for Iran and from 2014 to 2020 for world was predicted. The Iran data related to the chicken price, corn price, soybean meal price and chicken production rate from 1990 to 2014 were provided from Ministry of Agriculture Iran, State Livestock Affairs Logistics (S.L.A.L) Inc. and Central Bank of the Islamic Republic of Iran and the world data were provided from FAO STAT for the year 1961-2013. The most appropriate model for fitness and prediction of chicken meat in Iran is the autoregressive moving average model (ARMAX (3,5)), with the in-sample and out of sample of predicting error are 2.12 and 4.7 percent and in world, autoregressive moving average model (ARMA (1,13)) with the in-sample and out of sample of predicting error are 4.34 and 3.91 percent, according to mean absolute percent error criterion. Also the results of vector error correction models (VECM) estimation have shown one unit increasing in the ratio of the price of corn to soy and the amount of meat production in Iran, can increase 7.59 and 3.29 percent in Iran chicken meat and one unit increasing in world price of corn and the amount of world production of chicken meat can cause increase equal 0.31, 0.46 and 0.64 percent in chicken meat world price.

Keywords

References

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History

  • Receive Date: 03 October 2017
  • Revise Date: 27 January 2018
  • Accept Date: 28 January 2018

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