مؤسسة الشرق الأوسط للنشر العلمي

عادةً ما يتم الرد في غضون خمس دقائق

الإصدار الثامن عشر: 06 مارس 2023
من مجلة الشرق الأوسط للنشر العلمي

Modeling and Forecasting Food Gap in Syria: a Box-Jenkins ARIMA approach

Zein Hussain Sulieman
Abstract

This research aims to analyze the Syrian food gap, to determine its characteristics, development, and vulnerability, and then to create the appropriate predictive model, depending on the time series data of the commodity balance and of the food Gap between (1986-2019). ARIMA's models were used to formulate the best model for prediction, compared to other traditional models. During the study period, the value of the Food Gap was very changeful, as the coefficient of variation has risen to 344, 2 % . And most of the studied period years showed a positive value of the gap ( food deficit), its maximum was 3044 million in 1987, while the gap decreased , reaching negative values ( food surplus)during six years, its maximum (-3738) million dollars in 2006. For the prediction process, there was no general , statistically clear trend of the time series of the Syrian food Gap by using traditional models like "Ordinary least square" method , while the efficiency of "ARIMA" models was visible , where the best model for prediction was " ARIMA (0,1,1)" , which provided expectations of the continuous increasing of the Syrian Food Gap's value during 2020-2025 , which indicates the necessity of taking urgent measures by focusing on the agricultural sector, especially by increasing investments and reclaiming more land.

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