Najlaa Salah Mdloul; Jadoa Shehab Ahmed; Ahmad Hussein Battal
Volume 22, Issue 1 , March 2022, , Pages 78-95
Abstract
The aim of the research is to predict the value of agricultural output and some fiscal policy variables using quarterly data from the first quarter of 2021 until the fourth quarter of 2025, through the application of different time series methods (random behavior, general trend, moving averages, simple ...
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The aim of the research is to predict the value of agricultural output and some fiscal policy variables using quarterly data from the first quarter of 2021 until the fourth quarter of 2025, through the application of different time series methods (random behavior, general trend, moving averages, simple exponential smoothing, Brown’s method In the exponential smoothing, ARIMA models) on each of the following variables (value of agricultural output, oil prices, government spending, GDP, agricultural investment, agricultural imports), and the results showed that ARIMA (1,0,1) model is the best A model for forecasting oil prices until the fourth quarter of 2025, and the results indicated that the general trend model is the best model for predicting the government spending variable until the fourth quarter of 2025, while the ARIMA (1,1,1) model was the model chosen to predict the variable GDP until the fourth quarter of 2025, as well as it became clear from the results that the best model used for prediction agricultural investment is the exponential smoothing model, while the ARIMA (2,0,4) model was the best model for forecasting agricultural imports until the fourth quarter of In 2025, the results also indicated that the best model that can be employed to predict the variable value of agricultural output is the quadratic trend model according to the predictive ability tests of different models..
