Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/316076 
Erscheinungsjahr: 
2023
Quellenangabe: 
[Journal:] Review of Economics and Political Science (REPS) [ISSN:] 2631-3561 [Volume:] 8 [Issue:] 2 [Year:] 2023 [Pages:] 123-133
Verlag: 
Emerald, Bingley
Zusammenfassung: 
Purpose: This study focuses on forecasting the price of the most important export crops of vegetables and fruits in Egypt from 2016 to 2030. Design/methodology/approach: The study applied generalized autoregressive conditional heteroskedasticity (GARCH) model and autoregressive integrated moving average (ARIMA) model. Findings: The results show that ARIMA (1,1,1), ARIMA (2.1,2), ARIMA (1,1,0), ARIMA (1,1,2), ARIMA (0,1,0) and ARIMA (1,1,1) are the most appropriate fitted models to evaluate the volatility of price of green beans, tomatoes, onions, oranges, grapes and strawberries, respectively. The results also revealed the presence of ARCH effect only in the case of Potatoes, hence it is suggested that the GARCH approach be used instead. The GARCH (1,1) is found to be a better model in forecasting price of potatoes. Originality/value: The study of food price volatility in developing countries is essential, since a significant share of household budgets is spent on food in these economies, so forecasting agricultural prices is a substantial requirement for drawing up many economic plans in the fields of agricultural production, consumption, marketing and trade.
Schlagwörter: 
Agricultural price
ARIMA
Export crops
Forecasting
GARCH model
Volatility
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