Determining an optimal pattern for the Prediction of potato and onion consumption in Iran

1.334 443


Abstract. Given the importance of agriculture in the economy and the increasing role of potato and onion in the diet, this paper predicts the consumption of these products using a statistical model. Therefore, based on single and multi-variable models, data from 1970-2013 was applied to predict potato consumption using double exponential adjustment model and ARIMA (2, 1, 3) model was applied to predict onion consumption in 2015-2018. The results not only show a suitable prediction based on  error criteria for the above mentioned models, but also reveals the fact that the application of an annual series using appropriate and valid models can provide acceptable results. The comparison of these Predictions with actual values is a sign for the high prediction power of these models and confirm this claim. According to our study, it is anticipated that per capita consumption of potato and onion will reach to 31.4 and 18.9 kg at the end of the year 2018.


Prediction, Dual power adjustment, ARIMA, VAR ،٬ ARDL, Potato and onion

Full Text:



Adhikari.M. at all (2003). Water Demand Forecasting for Poultry Production Selected Paper Prepared for AAEA

Campo, I.S. and J.C. Beghin.(2005). Dairy Food Consumption, Production, and Policy in Japan. Working Paper 05-WP 401. Center for Agricultural and Rural Development

Chorng.s.(2005). Model identification of arima family using genetic algorithms. Applied mathematics and computation pp 164

-Deaton, A. S. & G. Laroque. 1992. On the behavior of commodity prices, Review of Economic Studies, 59:1-23

Halicioglu, F. (2004). An ARDL Model of International Tourist Flows to Turkey. Global Business and Economics Review.

Houston. & at all.(2003). Forecasting Broiler Water Demand Econometric & Times Series Analysis Selected Paper Prepared For Western Ag. Econ

Joy.H. and Barry. r (2001). Principles of operations management. Prentice Hall Inc. new jersey

Levin.R. (1989). Quantitative approaches to management. Mac grow hill

Monroe . k.(1990) : Pricing’ making profitable decision Mac grow hill international ‘ Editions

Mello, M.D. and K. S. Nell.( 2001). The Forecasting Ability of a Co integrated VAR Demand System With Endogenous vs. Exogenous Expenditure Variable: An Application to the UK Imports of Tourism From Neighboring Countries”

Sabur.r.(1993). Analysis of rice price of in immensity town market. Pattern and forecasting Bangladesh. G . of. Ag. Eco (16)

Soares, L and M.C. Medeiros. (1999). Modeling and forecasting short-term electric load demand: a two step methodology.

Roger.k.(1984). Forecasting future price trends in the u.s. fresh and processed potato market (g.of food distribution research )

Volkan.s.(2006). Forecasting production of fossil fuel sources in turkey using a comparative regression and arima model. Energy policy 3 4

winter.a.(1996). Expectations’ supply response and marketing boards: an example from Kenya: Ag. Eco (14).