Time Series Models to Forecast Barley Crop Production in The Kurdistan Region of Iraq: Time Series Models to Forecast Barley Crop Production

Lanja Assi  Hayder; Hezha Mohammed  Noor Mohammed; Jawher Jumaa Ali

doi:10.63841/iue22501

Authors

Lanja Assi Hayder Accounting Departement, College of Administration and Economics, Charmo University, Sulaimani, Kurdistan Region, IRAQ Author https://orcid.org/0009-0001-3277-3310
Hezha Mohammed Noor Mohammed Business Administration Department, college of Administration and Economics, Charmo University, Sulaimani, Kurdistan Region, IRAQ Author https://orcid.org/0009-0008-0372-4158
Jawher Jumaa Ali Business Administration Department, college of Administration and Economics, Charmo University, Sulaimani, Kurdistan Region, IRAQ Author https://orcid.org/0009-0009-9857-7679

DOI:

https://doi.org/10.63841/iue22501

Keywords:

ARIMA Model, Barley Production, Box-Jenkins, Time Series forecasting

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.

Author Biographies

Lanja Assi Hayder, Accounting Departement, College of Administration and Economics, Charmo University, Sulaimani, Kurdistan Region, IRAQ

Lanja A. Hayder is a Lecturer at the Department of Accounting, College of Economics and Administration, Charmo University. She got the B.Sc. degree in Statistics, the M.Sc. degree in Statistics. Her research interests are in [Probability], [Biostatistics] and [Applied Statistics].
Hezha Mohammed Noor Mohammed, Business Administration Department, college of Administration and Economics, Charmo University, Sulaimani, Kurdistan Region, IRAQ

Hezha Mohammed Noor Mohammed is a Lecturer at the Business Administration Department, College of Administration and Economics, Charmo University. He got the B.Sc. degree in Statistics, the M.Sc. degree in Applied Statistics. His research interests are in [Biostatistics] and [Applied Statistics].
Jawher Jumaa Ali, Business Administration Department, college of Administration and Economics, Charmo University, Sulaimani, Kurdistan Region, IRAQ

Jawhar Jumaa Ali is a Lecturer at the Business Administration Department, College of Administration and Economics, Charmo University. He got the B.Sc. degree in Statistics the M.Sc. degree in Statistics. His research interests are in [Probability], [Biostatistics] and [Applied Statistics].

References

N. A. Abdul Karem,"Estimating Function of Supply for Barley Crop in Iraq for the Period (1990- 2014)," Euphrates J. Agric. Sci., vol. 9, no. 2, pp. 236–243, 2017.

Z. H. Mahmood, "economical analysis of barley supply response in iraq, irrigated, and rained area during 1990-2007," Anbar J. Agric. Sci., vol. 8, no. 4, pp. 244–254, 2010.

Kurdistan Regional Statistical Office, ‘Summary of crop data 1969-2023’, Kurdistan Region Statistics Office. [Online]. Available: https://krso.gov.krd/content/upload/1/root/پوخته‌ى-داتاى-به‌روبوومه‌كانى-هاوينه‌-و-زستانه‌1969-2023.pdf

A. R. H. Al-Moola, "Forecasting of Wheat Production in Iraq Using Box- Jenkins Model for Period 2020-2024," Anbar J. Agric. Sci., vol. 18, no. 1, pp. 109–118, 2020, doi: 10.32649/ajas.2020.170516.

L. K. Hamza and I. M. Alwan, "Using Time Series Analysis to Predicting of the Amount of Solid Waste for Baghdad Governorate From 2008 - 2018," in Al-Rafidain University College For Sciences, 2020, pp. 270–284.

T. W. Mapuwei, J. Ndava, M. Kachaka, and B. Kusotera, "An Application of Time Series ARIMA Forecasting Model for Predicting Tobacco Production in Zimbabwe’" Am. J. Model. Optim., vol. 9, no. 1, pp. 15–22, 2022, doi: 10.12691/ajmo-9-1-3.

I. K. Mustafa and O. K. Jbara, "Forecasting the food gap and production of wheat crop in Iraq for the period (2016-2025)," Iraqi J. Agric. Sci., vol. 49, no. 4, pp. 560–568, 2018, doi: 10.36103/ijas.v49i4.63.

H. A. Drebee, N. A. A. Razak, and A. A. Mohsen, "Maize Production Forecasting in Iraq : A Box- Jenkins Approach for the Period of 2022-2026," in Earth and Environmental Science, 2023. doi: 10.1088/1755-1315/1259/1/012128.

S. N. Yaequb, A. A. Aziz, H. M. Saeed, and H. O. Faqe, "Forecasting For Silver Closing Price and Modifying Predictions by Using Wavelet Transformation," Polytech. J. Humanit. Soc. Sci., vol. 3, no. 1, pp. 129–142, 2022. doi: 10.25156/ptjhss.v3n1y2022.pp129-142.

H. A. H. Al Sarhan, "Using some statistical methods to predict the lost electrical energy (applied study)," University of Karbala, 2018.

M. M. Faqe and A. S. Hamad, "Use the time-series models to predict the numbers of children with Respiratory Infections Streams(RIS) in the governorate of Sulaymaniyah," Univ. Kirkuk J. Adm. Econ. Sci., vol. 5, no. 1, pp. 201–219, 2015.

B. S. Abdulhaq, "A statistical Model for Forecasting the Needs of Electrical Power in Erbil- Iraq," Mansoura University, 2014.

A. H. M. Albasri, "Using ARIMA models to forecast the volume of cargo handled in Iraqi ports An applied study in the general company of Iraqi ports," J. Econ. Adm. Sci., vol. 26, no. 120, pp. 452–474, 2020.

A. H. Farhan, "Using dickey _ fuller expanded test for testing variables of investment function in Iraq," J. Econ. Adm. Sci., vol. 25, no. 114, pp. 1–19, 2019. doi: 10.33095/jeas.v25i114.1752.

N. J. Mohammed and A. T. Jabbar, "Forecasting Air Pollution Using Time Series," J. Madenat Al-Elem, vol. 13, no. 1, pp. 303–318, 2021.

W. A. Hadba, "comparison method process capability indices for normal and non-normal data by use simulating," Kirkuk Univ. J. /Scientific Stud., vol. 11, no. 4, pp. 112–140, 2016.

B. K. Ahmed, S. A. Rahim, B. B. Maaroof, and H. A. Taher, "Comparison Between ARIMA And Fourier ARIMA Model To Forecast The Demand Of Electricity In Sulaimani Governorate," Qalaai Zanist Sci. J., vol. 5, no. 3, pp. 908–940, 2020. doi: 10.25212/lfu.qzj.5.3.36.

M. M. ELSayed, H. M. Mostafa, and Sanaa H.M. Sadek, "An Analytical Study of the Current and Future Status of Agricultural Land in Egypt," Alexandria Sci. Exch. J., vol. 44, no. 2, pp. 227–243, 2023, doi: 10.21608/asejaiqjsae.2023.296518.

D. H. Kadir, "Time Series Modeling to Forecast on Consuming Electricity : A case study Analysis of electrical consumption in Erbil City from 2014 to 2018," Journal of Al-Rafidain University College For Sciences, 2020, pp. 473–485.

A. A. Hamad, "The forecast quantities of electrical energy consumed per month in Anbar province , for the period 2013- 2014," AL-Anbar Univ. J. Econ. Adm. Sci., vol. 7, no. 14, pp. 343–356, 2015.

E. Y. Hamid and M. H. Osman Abushaba, "Use of Exponential Holt Model and the Box-Jenkins Methodology in Predicting the Time Series of Cement Production in Sudan," J. Al-Qadisiyah Comput. Sci. Math., vol. 12, no. 1, pp. 42–59, 2020, doi: 10.29304/jqcm.2020.12.1.666.

S. Hussein, "Using the ARIMA method in forecasting money supply in the Iraqi economy," Gulf Econ., vol. 34, no. 35, pp. 113–136, 2018.