Time-Frequency Dynamics of Biofuels-Fuels-Food System

TL;DR

This study uses wavelet coherence to analyze the time-frequency correlation dynamics between biofuels and related commodities, revealing how these relationships change during food crises and stable periods.

Contribution

It introduces a model-free wavelet coherence approach to examine the evolving correlations between biofuels and commodities across time and frequencies.

Findings

Correlations vary over time and across frequencies.

Ethanol and corn, biodiesel and German diesel are highly correlated at low frequencies.

Food crises increase the importance of higher frequency correlations.

Abstract

For the first time, we apply the wavelet coherence methodology on biofuels (ethanol and biodiesel) and a wide range of related commodities (gasoline, diesel, crude oil, corn, wheat, soybeans, sugarcane and rapeseed oil). This way, we are able to investigate dynamics of correlations in time and across scales (frequencies) with a model-free approach. We show that correlations indeed vary in time and across frequencies. We find two highly correlated pairs which are strongly connected at low frequencies - ethanol with corn and biodiesel with German diesel - during almost the whole analyzed period (2003-2011). Structure of correlations remarkably changes during the food crisis - higher frequencies become important for both mentioned pairs. This implies that during stable periods, ethanol is correlated with corn and biodiesel is correlated with German diesel mainly at low frequencies so that they follow a common long-term trend. However, in the crisis periods, ethanol (biodiesel) is lead by corn (German diesel) even at high frequencies (low scales), which implies that the biofuels prices react more rapidly to the changes in their producing factors.