Document Type : Research Paper
M.Sc. Student, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
Associate Professor, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
Professor, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
Assistant Professor, Department of Agriculture Economics, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
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.
- Ayyub, R. M., Bilal, M. & Ahmed, M. (2011). Meat price hikes and its forecasting in Pakistan. The Journal of Animal and Plant Science, 21(2), 256-259.
- Azizi, J. & Torkamani, J. (2000). Estimate of different kinds of meat demand functions in Iran. (2000). Agriculture Economics and Development, 9(34), 217-237. (in Farsi)
- Dashty, E. & Mohammadi, H. (2009). Chick meat and table-egg prices forecasting by artificial neural network in Iran. Quarterly Journal of Economic Research and Policies, 18(55), 87-106. (in Farsi)
- Enders, W. (2004). Applied Econometrics Time Series. Wiley University publication(3ed Edition).
- Ghahremanzadeh, M. & Rashidghalam, M. (2014). Develop of forecasting season kinds of meat prices model in Iran: Application of Periodic Auto-Regressive Model (PAR). Quarterly Journal of Economic Research and Policies, 46(3), 469-480. (in Farsi)
- Jahangard, H. (2008). Demand projection for major food commodities in Iran. M.Sc. thesis, Faculty of Agricultures Economics and Development, Tehran University. Iran. (in Farsi)
- Koopahi, M. (2009). Principles of Agricultures Economics. Tehran University Publication(13th Ed). (in Farsi)
- Moghaddasi, R. & Feizabadi, Y. (2006). Estimate of forecasting chicken meat price model by Box-Jenkins Method. Iranian Journal of Agriculture Science, 13(1), 1-10. (in Farsi)
- Nelson, C. R. & Plosser, C. I. (1982). Trend and random walk in macroeconomic time series: some evidence and implication. Journal of Monetary, 10, 139-162.
- TŁUCZAK, A. (2016). The forecast of pig meat prices in the EU-The use of adaptive Winter's model. Scientific Papers Series Management, Economic Engineering in Agriculture and Rural Development, 16(2), 307-311.
- Tsay, R. S. (2002). Analysis of financial time series. A Wiley-Interscience Publication. (3rd Ed).
- Wang, Z. & Bessler, D. A. (2003). Forecast Evaluations in Meat Demand Analysis. Journal of Forecasting, 21, 191-206.
- Wolters, J. & Kirchgässner, G. (2007). Introduction to modern time series analysis. Springer. 271.