On the statistical identification of DSGE models

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Title: On the statistical identification of DSGE models
Authors: Consolo, AgostinoFavero, Carlo A.Paccagnini, Alessia
Permanent link: http://hdl.handle.net/10197/7586
Date: May-2009
Online since: 2016-04-26T11:48:43Z
Abstract: Dynamic Stochastic General Equilibrium (DSGE) models are now considered attractive by the profession not only from the theoretical perspective but also from an empirical standpoint. As a consequence of this development, methods for diagnosing the fit of these models are being proposed and implemented. In this article we illustrate how the concept of statistical identification, that was introduced and used by Spanos [Spanos, Aris, 1990. The simultaneous-equations model revisited: Statistical adequacy and identification. Journal of Econometrics 44, 87–105] to criticize traditional evaluation methods of Cowles Commission models, could be relevant for DSGE models. We conclude that the recently proposed model evaluation method, based on the DSGE–VAR(λ), might not satisfy the condition for statistical identification. However, our application also shows that the adoption of a FAVAR as a statistically identified benchmark leaves unaltered the support of the data for the DSGE model and that a DSGE–FAVAR can be an optimal forecasting model.
Type of material: Journal Article
Publisher: Elsevier
Journal: Journal of Econometrics
Volume: 150
Issue: 1
Start page: 99
End page: 115
Copyright (published version): 2009 Elsevier
Keywords: Bayesian analysisDynamic stochastic general equilibrium modelModel evaluationStatistical identificationVector autoregressionFactor-augmented vector autoregression
DOI: 10.1016/j.jeconom.2009.02.012
Language: en
Status of Item: Peer reviewed
Appears in Collections:Economics Research Collection

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