USING A DYNAMIC TIME SERIES MODEL (ARIMA) FOR FORECASTING OF EGYPTIAN COTTON CROP VARIABLES - Mohamed. A. Elsamie; Tarek Ali; Deyi Zhou1 (Journal of Animal and Plant Sciences, 2020)
The Egyptian cotton crop is considered one of the important strategic crops, as it is one of the main pillars of the Egyptian national economic structure, and is used in many local industries, such as the textile industry, oil and soap industry, animal feed etc. Also, the cultivation of this crop employs more than one million workers and earns the Country a lot of foreign exchange from the export of this crop. In the past period, there has been a steady decline in the cultivation; in terms of land area and quantity produced of the crop. To achieve the Aims of this study Used ARIMA models because these models combine the method of Autoregression, the moving average of the time series to the forecasting of the cultivated area, Productivity, and Production of the cotton crop where these models are characterized by high accuracy in the analysis of Time series. We found from the results the cultivated area of that crop reached 230.30 thousand acres in 2018 then decreased to 27.85 thousand acres in 2024. After that the Production of the cotton crop in Egypt will cease because there is no area planted of cotton crop in Egypt after the year 2024. Also, the results of the productivity forecast were 7.06 quintals in 2018 then dropped to 6.61 quintals in 2025. Also, the results of the forecast of Production of the cotton crop reached 1173.61 thousand quintals in 2018 then reduced to 128.33 thousand quintals in 2024. Then after 2024, the Production of Egyptian cotton crop ceased permanently.
Keywords: forecasting; ARIMA model; Moving average model; Cotton crop. Auto-regressive model. Egypt; Auto-correlation function; Partial Auto-correlation Function