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Structural DSGE models are used for analyzing both policy and the sources ofbusiness cycles. Conclusions based on full structural models are, however, poten-tially affected by misspecification. A competing method is to use partially identi-fied SVARs based on narrative shocks. This paper asks whether both approachesagree. Specifically, I use narrative data in a DSGE-SVAR that partially identify pol-icy shocks in the VAR and assess the fit of the DSGE model relative to this nar-rative benchmark. In developing this narrative DSGE-SVAR, I develop a tractableBayesian approach to proxy VARs and show that such an approach is valid formodels with a certain class of Taylor rules. Estimating a DSGE-SVAR based on astandard DSGE model with fiscal rules and narrative data, I find that the DSGEmodel identification is at odds with the narrative information as measured by themarginal likelihood. I trace this discrepancy to differences in impulse responses,identified historical shocks and policy rules. The results indicate monetary ac-commodation of fiscal shocks