A weekly structural VAR model of the US crude oil market

Daniele Valenti, Andrea Bastianin and Matteo Manera ()

Energy Economics, 2023, vol. 121, issue C

Abstract: We present a weekly structural Vector Autoregressive model of the US crude oil market. Exploiting weekly data we can explain short-run crude oil price dynamics, including variations 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 elasticizes. 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 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: COVID-19; WTI price; Futures-spot price spread; Speculation; Structural VAR; Bayesian VAR (search for similar items in EconPapers)
JEL-codes: C32 Q02 Q41 Q43 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0140988323001548
Full text for ScienceDirect subscribers only

Related works:
Working Paper: A weekly structural VAR model of the US crude oil market (2022)
Working Paper: A weekly structural VAR model of the US crude oil market
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:121:y:2023:i:c:s0140988323001548

DOI: 10.1016/j.eneco.2023.106656

Access Statistics for this article

Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().