Forecasting Cotton Production in Iraq during the years (1960-2022) using Markov Chain Approach and Holt-Winter Method

Cotton is a fibrous material derived from the seed pods of the cotton plant (Gossypium). It is a natural fiber extensively utilized in the textile industry for the manufacturing of items like clothing, linens, and other fabric-based products. Valued for its breathability, absorbency, and adaptabilit...

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Bibliographic Details
Published in:	Tikrit Journal of Administrative and Economic Sciences Vol. 20; no. 66, part 2
Main Authors:	Heshu Othman Faqe, Ayad Otham Hamdin, Mohammad Mahmood Faqe Hussein
Format:	Journal Article
Language:	Arabic English
Published:	Tikrit University 30-06-2024
Subjects:	Markov Chain, Holt-Winters, Dickey-Fuller test,Transition probability matrix, Randomnes test
Online Access:	Get full text
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Summary:	Cotton is a fibrous material derived from the seed pods of the cotton plant (Gossypium). It is a natural fiber extensively utilized in the textile industry for the manufacturing of items like clothing, linens, and other fabric-based products. Valued for its breathability, absorbency, and adaptability, cotton is a widely chosen material for diverse everyday goods. Two models are used in this study, such as the Markov chain approach and the Holt-Winter method, to forecast cotton production in Iraq over the years 1960–2022. A Markov chain approach model is a accurate framework describing a series of states in a system. The chance of moving from one state to another depends only on the present state, without consideration of the historical. This model adheres to the Markov property, exhibiting a memoryless characteristic. It encompasses a set of states, transition probabilities between these states, and a stochastic process evolving over discrete time intervals. The Holt-Winters method is a robust technique for forecasting time series data, particularly when the data exhibits both trend and seasonality. This method integrates three key components into its forecasting model: level , trend and seasonality . The data for this study was obtained from the website: https://www.indexmundi.com/agriculture. The study evaluates the performance of the two forecasting models. The results show that the Holt-Winter method is more accurate than the Markov chain dependent on RMSE, MAE, and MAPE, and cotton production in Iraq will decrease over the coming years.
ISSN:	1813-1719
DOI:	10.25130/tjaes.20.66.2.18