A STATISTICAL MODEL TO PREDICT THE FOOD GAP OF THE WHEAT CROP IN EGYPT
Mamdouh Abdel Alim Saad Mowafy; Hanaa Hussein Ali Aboul Ela;
Abstract
Wheat is one of the most important strategic food commodities in
Egypt according to food security considerations. The Egyptian society
is facing a major challenge that the total production of wheat is still
not sufficient for the consumption needs resulting from the increase
in population, which lead to the rise of the food gap and increase of
wheat, which is reflected in the low self-sufficiency rate, which is
shown through the data of the Food and Agriculture Organization
of the United Nations FAO during the period (1961-2014), therefore
the research aims to predict the food gap and components of
wheat crop in Egypt during the period (2015-2025) to determine the
future of Egypt in terms of food security for this strategic crop. The
food gap, production and consumption functions of wheat were
estimated using autoregressive integrated moving average (ARIMA)
models, and generalized autoregressive conditional heteroscedasticity
(GARCH) models. The results of the study showed that the best
model for predicting the food gap is ARIMA(0, 1, 11) - GARCH(0, 1),
ARIMA(0, 1, 1) for the production and ARIMA(6, 1, 8) for the
consumption, and that the food gap is expected to increase in the
future, due to the increase in population.
Egypt according to food security considerations. The Egyptian society
is facing a major challenge that the total production of wheat is still
not sufficient for the consumption needs resulting from the increase
in population, which lead to the rise of the food gap and increase of
wheat, which is reflected in the low self-sufficiency rate, which is
shown through the data of the Food and Agriculture Organization
of the United Nations FAO during the period (1961-2014), therefore
the research aims to predict the food gap and components of
wheat crop in Egypt during the period (2015-2025) to determine the
future of Egypt in terms of food security for this strategic crop. The
food gap, production and consumption functions of wheat were
estimated using autoregressive integrated moving average (ARIMA)
models, and generalized autoregressive conditional heteroscedasticity
(GARCH) models. The results of the study showed that the best
model for predicting the food gap is ARIMA(0, 1, 11) - GARCH(0, 1),
ARIMA(0, 1, 1) for the production and ARIMA(6, 1, 8) for the
consumption, and that the food gap is expected to increase in the
future, due to the increase in population.
Other data
Title | A STATISTICAL MODEL TO PREDICT THE FOOD GAP OF THE WHEAT CROP IN EGYPT | Authors | Mamdouh Abdel Alim Saad Mowafy; Hanaa Hussein Ali Aboul Ela | Keywords | self-sufficiency (SS);ARIMA;ARCH;GARCH;TGARCH;EGARCH;volatility | Issue Date | 21-Aug-2017 | Publisher | Pushpa Publishing House, Allahabad, India | Journal | Advances and Applications in Statistics | Volume | 51 | Issue | 3 | Start page | 205 | End page | 230 | DOI | https://orcid.org/0000-0001-8856-9610 |
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