Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/217202 
Year of Publication: 
2020
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 11 [Issue:] 2 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2020 [Pages:] 801-837
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
Structural DSGE models are used for analyzing both policy and the sources of business cycles. Conclusions based on full structural models are, however, potentially affected by misspecification. A competing method is to use partially identified SVARs based on narrative shocks. This paper asks whether both approaches agree. Specifically, I use narrative data in a DSGE-SVAR that partially identify policy shocks in the VAR and assess the fit of the DSGE model relative to this narrative benchmark. In developing this narrative DSGE-SVAR, I develop a tractable Bayesian approach to proxy VARs and show that such an approach is valid for models with a certain class of Taylor rules. Estimating a DSGE-SVAR based on a standard DSGE model with fiscal rules and narrative data, I find that the DSGE model identification is at odds with the narrative information as measured by the marginal likelihood. I trace this discrepancy to differences in impulse responses, identified historical shocks and policy rules. The results indicate monetary accommodation of fiscal shocks.
Subjects: 
Fiscal policy
monetary policy
DSGE model
Bayesian estimation
narrative shocks
Bayesian VAR
JEL: 
C32
E32
E52
E62
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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