Price Forecasting Edible Oil: Case Study Sunflower Oil

Document Type : Scientific-research

Authors

1 Assistant Professor, Institute for Trade Studies and Research

2 ITSR

10.30465/ce.2024.48871.1968

Abstract

The present study aims to identify the influencing variables and ‎investigate their effect on the price of sunflower oil in Iran and out-of-sample forecast (2023:10-2024:09) using the vector autoregression ‎method. First, due to the cointegration of the research variables, we used ‎the Johansen-Juselius cointegration test to confirm the long-term ‎relationship between the variables. long-term and short-term ‎models were estimated, and the error correction coefficient was obtained‏ ‏‎at -0.3147. Next, we investigated impulse response functions. According ‎to the results of impulse response functions, shocks in the price of the ‎substitute product, the government exchange rate, and the global oil ‎price index (with 16, 10, and 9.6 percent in standard form, respectively) ‎have been more effective than other variables on the fluctuations of the ‎sunflower oil price. Also, the variance decomposition showed the global ‎oil price index variable explains the changes in the dependent variable ‎more than. Finally, we estimated out-of-sample forecasts. ‎Based on the forecast evaluation criteria, the model can accurately ‎forecast the price trend of sunflower oil. Also, according to our findings ‎, obstacles to production, formulating and ‎implementing incentive packages for producers, and reviewing the ‎regulations for importing goods into the country to control the price of ‎sunflower oil‎

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History

  • Receive Date: 30 April 2024
  • Revise Date: 07 July 2024
  • Accept Date: 19 July 2024

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