2023•Seikei ronsō/Review of economics and political scienceOpen access

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

Hanan Mahmoud Sayed Agbo

Open full text 31 citations

Abstract

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.

Open-access reader

About this research paper

What this paper is about

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.

Why it matters

OpenAlex reports 31 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

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.

Key concepts: Autoregressive integrated moving average, Autoregressive conditional heteroskedasticity, Volatility (finance), Economics, Econometrics, Agriculture, Autoregressive model, Box–Jenkins

Related papers

Back to paper searchBrowse research topicsOriginal source
Forecasting agricultural price volatility of some export crops in Egypt using ARIMA/GARCH model — Research Paper | ScholarLens