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Bayesian Structural VAR Models: A New Approach for Prior Beliefs on Impulse Responses

Martin Bruns () and Michele Piffer

No 1796, Discussion Papers of DIW Berlin from DIW Berlin, German Institute for Economic Research

Abstract: Structural VAR models are frequently identified using sign restrictions on contemporaneous impulse responses. We develop a methodology that can handle a set of prior distributions that is much larger than the one currently allowed for by traditional methods. We then develop an importance sampler that explores the posterior distribution just as conveniently as with traditional approaches. This makes the existing trade-off between careful prior selection and tractable posterior sampling disappear. We use this framework to combine sign restrictions with information on the volatility of the variables in the model, and show that this sharpens posterior inference. Applying the methodology to the oil market, we find that supply shocks have a strong role in driving the dynamics of the price of oil and in explaining the drop in oil production during the Gulf war.

Keywords: Sign restrictions; Bayesian inference; oil market (search for similar items in EconPapers)
JEL-codes: C32 C11 E50 H62 (search for similar items in EconPapers)
Pages: 38, II, 92 p.
Date: 2019
New Economics Papers: this item is included in nep-ecm and nep-ets
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Working Paper: Bayesian Structural VAR models: a new approach for prior beliefs on impulse responses (2018) Downloads
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