Forecasting agricultural price volatility of some export crops in Egypt using ARIMA/GARCH model

Hanan Mahmoud Sayed Agbo
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引用次数: 1

Abstract

PurposeThis study focuses on forecasting the price of the most important export crops of vegetables and fruits in Egypt from 2016 to 2030.Design/methodology/approachThe study applied generalized autoregressive conditional heteroskedasticity (GARCH) model and autoregressive integrated moving average (ARIMA) model.FindingsThe 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/valueThe 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.
利用ARIMA/GARCH模型预测埃及部分出口作物的农产品价格波动
本研究的重点是预测2016 - 2030年埃及最重要的出口作物蔬菜和水果的价格。本研究采用广义自回归条件异方差(GARCH)模型和自回归积分移动平均(ARIMA)模型。结果表明,ARIMA(1,1,1)、ARIMA(2.1,2)、ARIMA(1,1,0)、ARIMA(1,1,2)、ARIMA(0,1,0)、ARIMA(1,1,1)和ARIMA(1,1,1)分别是最适合评估青豆、西红柿、洋葱、橙子、葡萄和草莓价格波动的拟合模型。结果还显示,仅在马铃薯中存在ARCH效应,因此建议使用GARCH方法代替。GARCH(1,1)是预测马铃薯价格的较好模型。独创性/价值对发展中国家粮食价格波动的研究至关重要,因为在这些经济体中,家庭预算的很大一部分用于粮食,因此预测农产品价格是在农业生产、消费、销售和贸易领域制定许多经济计划的重要要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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