Inference in structural vector autoregressions when the identifying assumptions are not fully believed: Re-evaluating the role of monetary policy in economic fluctuations
Christiane Baumeister and
James D. Hamilton
Journal of Monetary Economics, 2018, vol. 100, issue C, 48-65
Abstract:
Point estimates and error bands for SVARs that are set identified are only justified if the researcher is persuaded that some parameter values are a priori more plausible than others. When such prior information exists, traditional approaches can be generalized to allow for doubts about the identifying assumptions. We use information about both structural coefficients and impacts of shocks and propose a new asymmetric t-distribution for incorporating information about signs in a nondogmatic way. We apply these methods to a three-variable macroeconomic model and conclude that monetary policy shocks are not the major driver of output, inflation, or interest rates.
Keywords: Structural vector autoregressions; Set identification; Monetary policy; Impulse-response functions; Historical decompositions; Model uncertainty; Informative priors (search for similar items in EconPapers)
JEL-codes: C11 C32 E52 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (87)
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Related works:
Working Paper: Inference in Structural Vector Autoregressions when the Identifying Assumptions are not Fully Believed: Re-evaluating the Role of Monetary Policy in Economic Fluctuations (2018) 
Working Paper: Inference in Structural Vector Autoregressions When the Identifying Assumptions are Not Fully Believed: Re-evaluating the Role of Monetary Policy in Economic Fluctuations (2018) 
Working Paper: Inference in structural vector auto regressions when the identifying assumptions are not fully believed: Re-evaluating the role of monetary policy in economic fluctuations (2018) 
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Persistent link: https://EconPapers.repec.org/RePEc:eee:moneco:v:100:y:2018:i:c:p:48-65
DOI: 10.1016/j.jmoneco.2018.06.005
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