Identifying daily oil market shocks: evidence from the Hormuz crisis

This paper develops a daily Bayesian structural VAR model of the global crude oil market that decomposes the real price of oil into three fundamental drivers: shocks to global real economic activity, shocks to oil price expectations and shocks to physical oil supply. We combine a daily sign-restriction identification strategy with a posterior filtering step based on monthly physical oil market data, which sharpens the economic interpretation of the estimated daily shocks. We apply the model to provide a real-time interpretation of the main drivers behind the 2026 Strait of Hormuz crisis, one of the largest and most abrupt oil price shocks of recent years. Our results show that oil supply shocks account for the bulk of the initial price surge following the closure of the Strait, aggregate demand shocks become increasingly important in sustaining elevated prices over the following weeks and expectational shocks act in the direction of mitigating the oil price surge. We further validate the model against four major historical episodes – the 2003-08 oil price boom, the Global Financial Crisis, the 2014-15 oil price collapse, and the COVID-19 pandemic – showing that the daily decomposition is consistent with the prevailing narrative of these events. The framework offers policymakers a timely tool for monitoring the structural sources of oil price fluctuations as they unfold.