| Summary: | Aim: Coronavirus disease 2019 (COVID-19) pandemic have included negative consequences both in health management and economic life at national and international level. The aim of this research is to examine the causal relationship between COVID-19 pandemic and agricultural commodity prices for the world.
Material and Methods: To this end, we employ Toda-Yamamoto and Fourier Toda-Yamamoto causality tests for the period of January 24, 2020 to January 22, 2021. Before testing the causal relationship between variables, we apply augmented Dickey Fuller (ADF) and Fourier ADF unit root tests to each series to determine maximum order of integration.
Results: The findings show that all variables are stationary in their first difference and the maximum order of integration is determined as 1. The results obtained from causality tests show that COVID-19 new cases Granger cause to coffee, sugar, cotton, corn, and soybean prices while COVID-19 new cases do not cause wheat and oats prices. It was also concluded that new deaths based on COVID-19 Granger cause to coffee, sugar, and cotton whereas COVID-19 new deaths do not cause to corn, soybean, wheat and oat prices.
Conclusion: In this study, time series analysis based on Toda-Yamamoto and Fourier Toda-Yamamoto causality tests highlight that the COVID-19 total new cases and total new deaths in the world has predictive power to predict further prices of agricultural commodities. Therefore, in terms of health management, policy makers should give substantial significance to the implementation of COVID-19 related health policies and agricultural policies together during the COVID-19 pandemic period.
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