On the interdependence between biofuel, fossil fuel and agricultural food prices: Evidence from quantile tests

This study investigates the long-and short-run relationships between fossil fuel, biofuel and agricultural food commodity prices by applying the cointegration and causality analysis. This study employs a quantile approach to consider the non-linearity and asymmetry in the relationship of data. To reduce a possible noise contained in the data, this study uses weekly average data of biofuel (ethanol), fossil fuel (West Texas Intermediate [WTI] oil) and agricultural food commodity (corn) futures prices from April 18, 2005 to October 30, 2020. The main findings are summarised as follows. First, we discover no evidence of cointegration between the quantiles of WTI oil, ethanol and corn prices when all quantiles are considered, although the results of the linear cointegration test are inconclusive. Second, results of the Granger non-causality test in quantiles reveal a significant short-run bidirectional causality between the returns of WTI oil, ethanol and corn prices, for all or most quantiles of the distribution. This implies asymmetric and nonlinear causal linkage between these variables. Moreover, the re-sults of our analysis have several policy implications, including energy price stability, decrease in energy dependence on fossil fuels, promotion of agricultural industry, environmental sustainability, energy conversion and reduction of greenhouse gas emissions.

Automated summary

This study investigates the relationships between fossil fuel, biofuel, and agricultural food commodity prices by applying cointegration and causality analysis methods. The findings suggest that there is an asymmetric and nonlinear causal linkage between these variables. The study's results have important policy implications for energy price stability, reducing dependence on fossil fuels, promoting the agricultural industry, environmental sustainability, energy conversion, and greenhouse gas emissions reduction.