Year: 2025
Type: article
Abstract: Time series are important methods in analyzing phenomena and events during specific time periods and predicting future values that contribute to giving an estimated picture of the phenomenon. Therefore, the study aimed to use the Box Jenkins methodology to forecasting barley production in the Kurdistan Region of Iraq for the period (2024-2030) based on the time series of barley production in Kurdistan for the period (1981-2023). It was found through studying the time series of barley production quantities for the period (1981-2023) that the time series is unstable in the mean and variance; after taking the second difference of the data to convert it to a stable series in the mean and then taking the natural logarithm transformation to convert it to a stable series around the variance, it was found that the appropriate model for predicting barley production in the Kurdistan Region is ARIMA (1,2,1) among the group of proposed models for having the lowest values for the criteria (BIC, SBC, H_Q). The study recommends using the models that have been developed to predict barley production in the Kurdistan Region and adopting the predictions resulting from these models in developing future plans. The study also recommends applying the Box-Jenkins methodology to deduce and develop models to predict other crops, based on the actual analysis of the time series as explained in the study.
DOI: 10.63841/iue22510
Authors: Hayder, Mohammed, Ali
Institution: Charmo University
Language: English
Field: Decision Sciences
Domain: Social Sciences
SDG: Zero hunger
Open Access status: hybrid
OpenAlex ID: W4411317255