A Narrative Approach to a Fiscal DSGE Model

Abstract

Structural DSGE models are used both for analyzing 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 VARs based on narrative shocks.This paper asks whether both approaches agree.First, I show that, theoretically, the narrative VAR approach is valid in a class of DSGE models with Taylor-type policy rules.Second, I quantify whether the two approaches also agree empirically, that is, whether DSGE model restrictions on the VARs and the narrative variables are supported by the data.To that end, I first adapt the existing methods for shock identification with external instruments for Bayesian VARs in the SUR framework.I also extend the DSGE-VAR framework to incorporate these instruments.Based on a standard DSGE model with fiscal rules, my results indicate that the DSGE model identification is at odds with the narrative information as measured by the marginal likelihood.I trace this discrepancy to differences both in impulse responses and identified historical shocks.

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