Abstract

Do financial volatility shocks matter for WTI oil and stock markets? They should since world economic activity responds to volatility. To investigate this question, we revisit two empirical frameworks widely used in the literature. Our baseline involves the standard identification of oil shocks in structural vector autoregressions (SVAR) with (world) oil supply, demand, and real oil prices. We then propose a global vector autoregressive (GVAR) model integrating 14 major world economies. We introduce the volatility measure (VIX), various stock markets, and compare two oil demand proxies: real economic activity (REA) based on commodity prices and world industrial production (WIP). The results of the impulse response analysis do not indicate major differences across models. However, when measuring the share of oil price variance explained by shocks to VIX (or to U.S. high-bond corporate yield) SVAR overestimates the influence of VIX. We find (world) demand shocks explain a larger part of the variance of oil and stock markets compared to supply shocks. In SVAR, new information coming from a one standard deviation shock to VIX is incorporated negatively and instantaneously on real oil prices: −1.6 for REA and −1.4 for WIP. In GVAR these are reduced slightly to −1.2 from VIX and to −0.6 if coming from corporate bond yield shocks. Our study highlights the sensitivity of econometric results to distinct approaches: one that identifies shocks and another that captures spillover effects.

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