Advances and Applications in Statistics
Volume 59, Issue 1, Pages 89 - 101
(November 2019) http://dx.doi.org/10.17654/AS059010089 |
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MODELING AND FORECASTING OF WHEAT PRODUCTION IN EGYPT
Essam Fawzy, Badrya Mahmoud and Aya Mongy
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Abstract: Based on a group of variables and data collected from 1990 to 2017, the paper intended to predict the wheat production in Egypt. The independent variables were: cultivated area of wheat, cost of production of wheat, wheat consumption, storage capacity of wheat, number of population, quantity of imports of wheat and the dependent variable was the wheat production (the quantity available for consumption of wheat production). The linear ridge regression model, the logarithmic ridge regression model and ARIMA model (1, 1, 2) were used. The results showed that the logarithmic ridge regression model and ARIMA model (1, 1, 2) were the best models to predict the wheat production in Egypt. |
Keywords and phrases: wheat production, ridge regression, variance inflation factor (VIF), ridge regression parameter, autoregressive integrated moving average (ARIMA).
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