Hadeel Ghaleb Hassan Al-Douri; Bassem Fadel Latif Al Douri
Volume 22, Issue 1 , March 2022, , Pages 61-77
Abstract
The study aimed to predict Iraqi agricultural and food imports for the period (2021-2027) using the Box-Jenkins methodology. The autocorrelation and partial functions were used for the purpose of ensuring the stability of time series and testing the residual correlation, histogram and probabilistic distribution ...
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The study aimed to predict Iraqi agricultural and food imports for the period (2021-2027) using the Box-Jenkins methodology. The autocorrelation and partial functions were used for the purpose of ensuring the stability of time series and testing the residual correlation, histogram and probabilistic distribution of residuals of the estimated model for the purpose of ensuring the suitability of the chosen model The study found an increase in both Iraqi agricultural and food imports during the studied period, and in light of the results reached, the study recommends maintaining the growth of this sector at 1.5%, 1.2% for agricultural and food imports, respectively..
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..
