التنبؤ بالمساحة المزروعة من القمح في سورية باستخدام نموذج ARIMA

Abstract

This research aims to study and analyze the time series of wheat cultivated area as a percentage of arable land in Syria, from 1998 to 2022. The main objective is to develop a predictive model that assists policymakers in evaluating the effectiveness of current policies and formulating future strategies and policies related to wheat. This is achieved by employing the Box-Jenkins methodology to build Autoregressive Integrated Moving Average (ARIMA) model, utilizing the RStudio statistical programming language. Stationarity tests (Augmented Dickey-Fuller, ADF) were conducted, along with the use of Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) coefficients, in addition to AIC, BIC, and AICC criteria. The analysis results, based on several statistical criteria, indicated that the ARIMA (0,1,4) model is the most suitable for forecasting the percentage of wheat cultivated area relative to arable land. The forecast indicates that the cultivated wheat area in 2027 is expected to increase to 19.84%, compared to 19% in 2022.