Moment connectedness and driving factors in the energy-food nexus: A time-frequency perspective

2025-10-28

AI Summary

Against the backdrop of escalating macroeconomic uncertainty, risk interlinkages between energy and food markets have grown increasingly complex, threatening global energy and food security. This study develops a multiscale moment connectivity framework integrating the GJRSK model, time–frequency spillover indices, and random forest regression to systematically characterize heterogeneous spillovers of mean, volatility, skewness, and kurtosis across time–frequency domains—marking the first such comprehensive analysis. Key findings reveal crude oil as the central hub for cross-market risk transmission; spillovers exhibit pronounced time-variation, crisis sensitivity, and cyclical heterogeneity; and macrofinancial conditions, supply–demand fundamentals, policy uncertainty, and climate shocks constitute primary drivers. The results provide both theoretical foundations and empirical evidence for coordinated governance of the energy–food nexus.

Technology Category

• Game Theory and Economic Paradigms: Coordination and Collaboration
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Humanities & Computational Social Science

Application Category

• Economics, Online Markets and Human Computation: The sharing economy
• Security and Privacy: Large-scale security measurements
• Social Networks and Social Media: Social media analysis through the lenses of networks

Abstract

With escalating macroeconomic uncertainty, the risk interlinkages between energy and food markets have become increasingly complex, posing serious challenges to global energy and food security. This paper proposes an integrated framework combining the GJRSK model, the time-frequency connectedness analysis, and the random forest method to systematically investigate the moment connectedness within the energy-food nexus and explore the key drivers of various spillover effects. The results reveal significant multidimensional risk spillovers with pronounced time variation, heterogeneity, and crisis sensitivity. Return and skewness connectedness are primarily driven by short-term spillovers, kurtosis connectedness is more prominent over the medium term, while volatility connectedness is dominated by long-term dynamics. Notably, crude oil consistently serves as a central transmitter in diverse connectedness networks. Furthermore, the spillover effects are influenced by multiple factors, including macro-financial conditions, oil supply-demand fundamentals, policy uncertainties, and climate-related shocks, with the core drivers of connectedness varying considerably across different moments and timescales. These findings provide valuable insights for the coordinated governance of energy and food markets, the improvement of multilayered risk early-warning systems, and the optimization of investment strategies.

Problem

• Analyzing multidimensional risk spillovers in energy-food markets
• Identifying key drivers of moment connectedness across timescales
• Investigating crude oil's central role in interconnectedness networks

Innovation

• Combining GJRSK model with time-frequency connectedness analysis
• Using random forest method to identify key spillover drivers
• Analyzing multidimensional moment connectedness across different timescales