The sensitivity of oil price shocks to preexisting market conditions: A GVAR analysis

Jennifer Considine (Lead / Corresponding author), Emre Hatipoglu, Abdullah Aldayel

    Research output: Contribution to journalArticlepeer-review

    4 Citations (Scopus)
    12 Downloads (Pure)


    This study develops a Global Vector Autoregression (GVAR) model to simulate various types of shocks to oil markets and to see whether such shocks are time-sensitive in oil markets. Our model extends the canonical Mohaddes and Pesaran (2016) model temporally (to 2018Q3), spatially (including Russia, Iran, and Venezuela), and by adding oil inventories as an additional country-specific variable. Two of its characteristics make GVAR particularly suited to this analysis. First, the GVAR framework is specifically designed to account for the interaction between many countries. Second, world oil supplies and inventories are modeled jointly with key global and country-level macroeconomic variables. The results indicate conditions existing in the markets prior to the disturbance determine the global economic implications of an oil price shock. To cite only one example, a negative price shock in markets characterized by loose inventories will have significant negative implications for real GDP in the consuming nations, specifically Europe Latin America, and the Asia Pacific. In tight markets, on the other hand a negative price shock has the potential to increase real GDP for the world as a whole.
    Original languageEnglish
    Article number100225
    Number of pages30
    JournalJournal of Commodity Markets
    Early online date11 Nov 2021
    Publication statusPublished - Sept 2022


    • GVAR
    • Oil inventories
    • Oil markets
    • Oil price
    • Shock
    • Simulation

    ASJC Scopus subject areas

    • Finance
    • Economics and Econometrics


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