Measuring energy resilience via risk absorption: High-frequency evidence from China

Energy markets face intensifying shocks, making a real-time measure of energy resilience essential. Conventional low-frequency metrics miss short-run dynamics and the risk-absorption capacity of the energy system. This study proposes a methodological framework to assess energy resilience through risk-absorption by (i) integrating mixed-frequency indicators into an energy system index (ESI) via a dynamic factor model, (ii) proxying systemic financial stress with marginal expected shortfall, and (iii) tracing the ESI's impulse response to risk shocks using a time-varying parameter VAR with stochastic volatility. This approach captures high-frequency dynamics, accommodates evolving transmission mechanisms, and yields two interpretable risk-absorption measures: energy resilience intensity (ERi) and energy resilience duration (ERd). For China during 2009–2022, the results show that energy resilience stabilized overall and was shaped mainly by risks stemming from external financing dependence (international financial markets) and capital-price transmission (stock markets). ERd and ERi display a clear dual-regime pattern, with both regimes exhibiting strong self-sustaining persistence. Four pronounced fluctuations—2010–2011, 2014–2015, 2017–2018, and 2020–2022—correspond to surges in geopolitical risk (GPR), trade policy uncertainty (TPU), and climate risks. Empirically, TPU exerts a dual effect on energy resilience by shortening ERd while reducing ERi, whereas geopolitical and climate risks mainly prolong recovery processes (increasing ERd) without significantly weakening systemic stability (ERi). In addition, domestic emergencies such as campaign-based decarbonization also exert an impact on ERd. This study provides a dynamic, high-frequency measurement framework and clarifies the differential roles of geopolitical, trade, and climate risks in shaping energy resilience across risk-absorption intensity and duration.