Effect of Energy Price on Cereal Price Using Mixed Data Sampling Regression Models (Generalized OLS-based ARDL Approach)

Document Type : Research Article



The relationship between energy and agricultural products prices is an important and influential factor on food price surge. On the other hand, data availability in different frequencies is a dilemma facing time series econometricians, because by averaging of the data some valuable information in high frequency data will be lost. MIDAS regression models have recently been developed as an alternative dealing with mixed frequency data problem. This study applies generalized ARDL approach to estimate MIDAS regression for prediction of cereal prices using quarterly data on exchange rate and annual data on energy prices, interest rate, and inflation for the period 1982-2008. Prediction accuracy Statistics show that MIDAS model provides more accurate prediction of cereal price compared to simple averaging method.


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