On the identification of the oil-stock market relationship

Abstract

The alternative identification techniques for oil market shocks could be responsible for the mixed results in the oil-stock market literature. This study employs a Bayesian Structural Vector Autoregression (SVAR) to compare the implications of traditional identification approaches (SVAR with zero/sign restrictions) with those from the baseline model (Bayesian SVAR) for the case of the US. We find that the baseline model implies more plausible posterior price elasticities of oil supply and demand and a more profound effect of oil supply shocks on oil prices. Nonetheless, all models provide qualitatively similar conclusions for the effects of oil market shocks on the US stock market, with shocks coming from the demand side playing a more important role than oil supply shocks. Overall, this study reveals that traditional identification schemes remain a good approximation in practice for the oil-stock market relationship.