A weekly structural VAR model of the US crude oil market - Daniele Valenti; Andrea Bastianin; Matteo Manera (Fondazione Eni Enrico Mattei (FEEM), 2022)
We present a weekly structural Vector Autoregressive (VAR) model of the US crude oil market. Exploiting weekly data we can explain short-run crude oil price dynamics, including those related with the COVID-19 pandemic and with the Russia's invasion of Ukraine. The model is set identified with a Bayesian approach that allows to impose restrictions directly on structural parameters of interest, such as supply and demand elasticises. Our model incorporates both the futures-spot price spread to capture shocks to the real price of crude oil driven by changes in expectations and US inventories to describe price fluctuations due to unexpected of variations of above-ground stocks. Including the futures-spot price spread is key for accounting for feedback effects from the financial to the physical market for crude oil and for identifying a new structural shock that we label expectational shock. This shock plays a crucial role when describing the series of events that have led to the spike in the price of crude oil recorded in the aftermath of Russia's invasion of Ukraine.
Keywords: C32; Q02; Q41; Q43; 330; COVID-19; WTI price; futures-spot price spread; speculation; structural VAR; Bayesian VAR