Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/279468 
Year of Publication: 
2023
Series/Report no.: 
Working Paper No. 2023-13
Publisher: 
Federal Reserve Bank of Atlanta, Atlanta, GA
Abstract: 
There has been a call for caution when using the conventional method for Bayesian inference in setidentified structural vector autoregressions on the grounds that the uniform prior over the set of orthogonal matrices could be nonuniform for individual impulse responses or other quantity of interest. This paper challenges this call by formally showing that, when the focus is on joint inference, the uniform prior over the set of orthogonal matrices is not only sufficient but also necessary for inference based on a uniform joint prior distribution over the identified set for the vector of impulse responses. In addition, we show how to use the conventional method to conduct inference based on a uniform joint prior distribution for the vector of impulse responses. We generalize our results to vectors of objects of interest beyond impulse responses.
Subjects: 
Bayesian
SVARs
uniform prior
sign restrictions
JEL: 
C11
C33
E47
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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