Energy Markets and Macroeconomic Tail Risks: A Mixed-Frequency Quantile VAR Connectedness Approach

Abstract

Against the backdrop of rising uncertainty in global energy markets, the tail directional connectedness between energy-price fluctuations and macroeconomic conditions has become an important issue for macroprudential monitoring. Drawing on the mixed-frequency information stacking idea of the MF-VAR-DY model, this paper constructs an MF-QVAR-DY model that embeds high-frequency energy prices and low-frequency macroeconomic variables within a unified conditional quantile system, and examines the directional connectedness structure among fossil energy, clean energy, and U.S. macroeconomic variables. The results show that: first, total connectedness between energy markets and macroeconomic variables exhibits a pronounced high-at-both-ends, low-in-the-middle pattern; second, from a mixed-frequency perspective, crude oil is a stable outward risk transmitter, whereas clean energy plays a stronger outward spillover role at extreme quantiles; third, during the COVID-19 pandemic, fossil and clean energy jointly transmitted risk, whereas during the Russia-Ukraine conflict, the crude oil market dominated risk spillovers. This paper provides empirical evidence for using high-frequency energy information in macroeconomic tail-risk monitoring.