On the statistical identification of DSGE models

Agostino Consolo, Carlo Favero () and Alessia Paccagnini

Journal of Econometrics, 2009, vol. 150, issue 1, 99-115

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([lambda]), might not satisfy the condition for statistical identification. However, our application also shows that the adoption of a FAVARÂ 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.

Keywords: Bayesian; analysis; Dynamic; stochastic; general; equilibrium; model; Model; evaluation; Statistical; identification; Vector; autoregression; Factor-augmented; vector; autoregression (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304-4076(09)00048-7
Full text for ScienceDirect subscribers only

Related works:
Working Paper: On the Statistical Identification of DSGE Models (2009)
Working Paper: On the statistical identification of DSGE models (2009)
Working Paper: On the Statistical Identification of DSGE Models (2007)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:150:y:2009:i:1:p:99-115

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().