Salwa Almohammad(1) Ibtessam Jasem*(2) and Mai Lubboss(1)
(1). Agriculture Economy Department, Faculty of Agriculture, Aleppo University, Aleppo, Syria.
(2). Cotton Crop Administration, General Commission for Scientific Agricultural Research (GCSAR), Damascus, Syria.
(*Correspoding author: Dr. Ibtessam Jasem. E-Mail: firstname.lastname@example.org).
Received: 31/12/2016 Accepted: 25/01/2017
Prediction acquired a great importance in economic studies, that made the decision-makers draw economic and social policies for future, depending on the available data of the phenomenon history. Many economic prediction methods were used as Autoregressive Integrated Moving Averages (ARIMA). This model is a mixture of autoregressive technique and moving averages. The objective of this research is to use ARIMA models for predicting production area and productivity of cotton crop in Syria, and at the level of the major producing provinces (Al Hasakah, Aleppo, Rakka and Al-Ghab), because of their high accuracy in time series analysis and prediction. Annual data of the production area and productivity of irrigated cotton crop during the period (1985-2012) was used. The results revealed that ARIMA model (1.0.0) is the most appropriate one for predicting the production area and productivity of cotton in Syria up till 2020 according to the statistical tests of the accuracy of predictive models. The results suggested an increase in area and productivity for the next eight years with an annual growth rate higher than the annual growth rate for the studied period (1985-2012), where the annual growth rates of the area and production were (0.48% and 0.30%), respectively.
Keywords: ARIMA models, Cotton , Syria.
Full paper in Arabic: PDF