Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We analyze the relationship between US energy (i.e., crude oil, diesel, gasoline, and ethanol) and soybean prices using monthly data from 2005 to 2024. Using a quantile VAR connectedness model, we examine the interplay between energy and food prices across different quantiles. Our findings show that 96 % of the volatility in the network of fossil fuel, biofuel, and food prices is driven by changes in this network. Crude oil and ethanol prices primarily transmit shocks that influence soybean prices, whereas soybean price changes impact ethanol prices, creating feedback mechanisms. Soybean and gasoline prices showed the most significant shocks in the nexus. Our study reveals the dynamic feedback between prices and their interaction within the network, contributing to the understanding of the consequences of biofuels as a clean energy source. Rigorous robustness tests using cross-quantilogram and wavelet quantile correlation validate our findings, offering insights for policymakers managing energy and food price fluctuations.