Traditional approaches to structural vector autoregressions (VARs) can be viewed as special cases of Bayesian inference arising from very strong prior beliefs. These methods can be generalized with a less restrictive formulation that incorporates uncertainty about the identifying assumptions themselves. We use this approach to revisit the importance of shocks to oil supply and demand. Supply disruptions turn out to be a bigger factor in historical oil price movements and inventory accumulation a smaller factor than implied by earlier estimates. Supply shocks lead to a reduction in global economic activity after a significant lag, whereas shocks to oil demand do not. (JEL C32, L71, Q35, Q43)
The views expressed in this paper are those of the authors and do not necessarily reflect those of the Bank of Canada. We thank Luc Bauwens, Fabio Canova, Gary Chamberlain, Drew Creal, Lutz Kilian, Adrian Pagan, Elie Tamer, Harald Uhlig, and anonymous referees for helpful comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
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